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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Online RNN network to predict first names of us babies"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import tensorflow as tf\n",
"from tensorflow import keras\n",
"from tensorflow.keras import layers\n",
"from tensorflow.keras import activations\n",
"import matplotlib.pyplot as plt\n",
"from sklearn.model_selection import train_test_split\n",
"import random"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Dataset"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import csv\n",
"\n",
"with open('database/StateNames.csv', newline='') as csvfile:\n",
" data = list(csv.reader(csvfile))\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Id', 'Name', 'Year', 'Gender', 'State', 'Count']\n",
"1910\n",
"['Mary', 'Annie', 'Anna', 'Margaret', 'Helen', 'Elsie', 'Lucy', 'Dorothy', 'Mary', 'Margaret', 'Ruth', 'Annie', 'Elizabeth', 'Helen', 'Mary', 'Elsie', 'Agnes', 'Anna', 'Helen', 'Louise', 'Jean', 'Ruth', 'Alice', 'Esther', 'Ethel', 'Margaret', 'Marie', 'Mary', 'Elizabeth', 'Margaret', 'Helen', 'Alice', 'Annie', 'Louise', 'Mary', 'Margaret', 'Alice', 'Annie', 'Elizabeth', 'Helen', 'Clara', 'Dorothy', 'Martha', 'Agnes', 'Esther', 'Frances', 'Julia', 'Lillian', 'Mildred', 'Pauline', 'Mary', 'Alice', 'Helen', 'Anna', 'Dorothy', 'Margaret', 'Ruth', 'Elizabeth', 'Frances', 'Katherine', 'Martha', 'Annie', 'Clara', 'Emma', 'Hazel', 'Julia', 'Marie', 'Minnie', 'Pauline', 'Mary', 'Helen', 'Dorothy', 'Frances', 'Ruth', 'Alice', 'Anna', 'Agnes', 'Annie', 'Julia', 'Lillian', 'Margaret', 'Daisy', 'Edna', 'Esther', 'Evelyn', 'Florence', 'Katherine', 'Louise', 'Lucy', 'Marie', 'Sally', 'Mary', 'Margaret', 'Helen', 'Frances', 'Alice', 'Olga', 'Ruth', 'Clara']\n",
"['14', '12', '10', '8', '7', '6', '6', '5', '12', '7', '7', '6', '6', '6', '9', '8', '7', '7', '7', '7', '6', '6', '5', '5', '5', '5', '5', '21', '9', '8', '7', '5', '5', '5', '22', '10', '8', '8', '7', '7', '6', '6', '6', '5', '5', '5', '5', '5', '5', '5', '23', '13', '12', '10', '10', '9', '9', '7', '6', '6', '6', '5', '5', '5', '5', '5', '5', '5', '5', '18', '12', '8', '8', '8', '7', '7', '6', '6', '6', '6', '6', '5', '5', '5', '5', '5', '5', '5', '5', '5', '5', '21', '11', '10', '9', '7', '7', '7', '6']\n"
]
}
],
"source": [
"print(data[0])\n",
"print(data[2][2])\n",
"# data starts in the year 1910\n",
"print([entry[1] for entry in data[1:100] if int(entry[2]) < 1940])\n",
"print([entry[5] for entry in data[1:100] if int(entry[2]) < 1940])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
]
}
],
"source": [
"# use one hot encoding of the alphabetical letters (using just lower case)\n",
"\n",
"from keras.utils import to_categorical\n",
"\n",
"# define universe of possible input values\n",
"alphabet = ' abcdefghijklmnopqrstuvwxyz'\n",
"char_to_int = dict((c, i) for i, c in enumerate(alphabet))\n",
"int_to_char = dict((i, c) for i, c in enumerate(alphabet))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"def get_names(data, nb=1000, id0=0):\n",
" # take square of number of occurances, so we should learn also the special names\n",
" names = [entry[1] for entry in data[1+id0:] if int(entry[0]) < id0+nb for _ in range(int(np.sqrt(int(entry[5]))))]\n",
" start_year = data[1+id0][2]\n",
" end_year = data[1+id0+nb][2]\n",
" \n",
" return names, start_year, end_year, len(names) "
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"def split_and_shuffle(names, train_size=0.5):\n",
" names_train, names_test = train_test_split(names, train_size=train_size, random_state=42, shuffle=True)\n",
" return names_train, names_test"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"def to_one_hot_single(names, max_len_names):\n",
" num_names = np.zeros((len(names), max_len_names))\n",
" for i, name in enumerate(names):\n",
" for j in range(max_len_names):\n",
" if j < len(name):\n",
" num_names[i,j] = char_to_int[name[j].lower()]\n",
" else:\n",
" num_names[i,j] = 0\n",
"\n",
" one_hot_names = to_categorical(num_names, num_classes=27)\n",
" \n",
" return one_hot_names\n",
"\n",
"def to_one_hot(*names_set, max_len_names=5):\n",
" one_hot_sets = []\n",
" for _set in names_set:\n",
" one_hot_sets.append(to_one_hot_single(_set, max_len_names))\n",
" \n",
" if len(one_hot_sets) == 1:\n",
" return one_hot_sets[0]\n",
" \n",
" return tuple(one_hot_sets)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"def to_sequence_single(one_hot):\n",
" # generate sequences and apply padding with white space\n",
" max_len_names = one_hot.shape[1]\n",
" x_data = np.zeros((one_hot.shape[0]*max_len_names, max_len_names-1, 27))\n",
" y_data = np.zeros((one_hot.shape[0]*max_len_names, 27))\n",
" for i in range(one_hot.shape[0]):\n",
" for j in range(max_len_names):\n",
" #print(str(i) + \", \" + str(j))\n",
" tmp = np.zeros((max_len_names*3, 27))\n",
" # set everything equal to a space\n",
" tmp[:, 0] = 1\n",
" # insert actual word\n",
" tmp[max_len_names:2*max_len_names] = one_hot[i]\n",
" x_data[i*max_len_names+j] = tmp[j+1:max_len_names+j]\n",
" y_data[i*max_len_names+j] = tmp[max_len_names+j]\n",
" # print(y_data[i*max_len_names+j])\n",
"\n",
" return x_data, y_data\n",
"\n",
"def to_sequence(*one_hot_set):\n",
" split_sets = []\n",
" for _set in one_hot_set:\n",
" split_sets += to_sequence_single(_set)\n",
" \n",
" return tuple(split_sets)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"names, s_year, e_year, count = get_names(data)\n",
"names_train, names_test = split_and_shuffle(names)\n",
"\n",
"one_hot_names_train, one_hot_names_test = to_one_hot(names_train, names_test)\n",
"\n",
"x_train, y_train, x_test, y_test = to_sequence(one_hot_names_train, one_hot_names_test)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2392\n",
"1196\n",
"(5980, 4, 27)\n",
"(5980, 27)\n"
]
}
],
"source": [
"print(len(names))\n",
"print(len(names_train))\n",
"print(x_train.shape)\n",
"print(y_train.shape)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Model"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Model: \"sequential\"\n",
"_________________________________________________________________\n",
"Layer (type) Output Shape Param # \n",
"=================================================================\n",
"simple_rnn (SimpleRNN) (None, 128) 19968 \n",
"_________________________________________________________________\n",
"dense (Dense) (None, 27) 3483 \n",
"=================================================================\n",
"Total params: 23,451\n",
"Trainable params: 23,451\n",
"Non-trainable params: 0\n",
"_________________________________________________________________\n"
]
}
],
"source": [
"model = keras.Sequential()\n",
"# Add an Embedding layer expecting input vocab of size 1000, and\n",
"# output embedding dimension of size 64.\n",
"#model.add(layers.Embedding(input_dim=1000, output_dim=64))\n",
"\n",
"model.add(layers.InputLayer(input_shape=(x_train.shape[1], len(alphabet))))\n",
"\n",
"# Add a LSTM layer with 128 internal units.\n",
"model.add(layers.SimpleRNN(128))\n",
"\n",
"# Add a Dense layer with 10 units.\n",
"model.add(layers.Dense(27, activation=activations.sigmoid))\n",
"\n",
"model.summary()\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"model.compile(\n",
" loss='categorical_crossentropy',\n",
" #loss=keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n",
" optimizer=\"sgd\",\n",
" metrics=[\"accuracy\"],\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Train on 5980 samples, validate on 5980 samples\n",
"Epoch 1/500\n",
"5980/5980 [==============================] - 1s 120us/sample - loss: 3.2994 - accuracy: 0.0485 - val_loss: 3.2947 - val_accuracy: 0.0517\n",
"Epoch 2/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.2890 - accuracy: 0.0562 - val_loss: 3.2844 - val_accuracy: 0.0594\n",
"Epoch 3/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.2792 - accuracy: 0.0612 - val_loss: 3.2746 - val_accuracy: 0.0640\n",
"Epoch 4/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 3.2699 - accuracy: 0.0625 - val_loss: 3.2652 - val_accuracy: 0.0651\n",
"Epoch 5/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.2610 - accuracy: 0.0649 - val_loss: 3.2563 - val_accuracy: 0.0681\n",
"Epoch 6/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.2525 - accuracy: 0.0687 - val_loss: 3.2477 - val_accuracy: 0.0766\n",
"Epoch 7/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 3.2443 - accuracy: 0.0729 - val_loss: 3.2394 - val_accuracy: 0.0734\n",
"Epoch 8/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.2363 - accuracy: 0.0706 - val_loss: 3.2314 - val_accuracy: 0.0746\n",
"Epoch 9/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.2287 - accuracy: 0.0727 - val_loss: 3.2237 - val_accuracy: 0.0758\n",
"Epoch 10/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.2212 - accuracy: 0.0734 - val_loss: 3.2161 - val_accuracy: 0.0758\n",
"Epoch 11/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.2140 - accuracy: 0.0737 - val_loss: 3.2088 - val_accuracy: 0.0764\n",
"Epoch 12/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.2069 - accuracy: 0.0747 - val_loss: 3.2016 - val_accuracy: 0.0769\n",
"Epoch 13/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 3.2000 - accuracy: 0.0749 - val_loss: 3.1946 - val_accuracy: 0.0697\n",
"Epoch 14/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 3.1932 - accuracy: 0.0684 - val_loss: 3.1877 - val_accuracy: 0.0671\n",
"Epoch 15/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.1866 - accuracy: 0.0689 - val_loss: 3.1810 - val_accuracy: 0.0691\n",
"Epoch 16/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.1801 - accuracy: 0.0697 - val_loss: 3.1744 - val_accuracy: 0.0702\n",
"Epoch 17/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.1737 - accuracy: 0.0721 - val_loss: 3.1679 - val_accuracy: 0.0771\n",
"Epoch 18/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 3.1674 - accuracy: 0.0764 - val_loss: 3.1615 - val_accuracy: 0.0774\n",
"Epoch 19/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.1613 - accuracy: 0.0747 - val_loss: 3.1552 - val_accuracy: 0.0732\n",
"Epoch 20/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 3.1552 - accuracy: 0.0744 - val_loss: 3.1490 - val_accuracy: 0.0732\n",
"Epoch 21/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 3.1491 - accuracy: 0.0747 - val_loss: 3.1429 - val_accuracy: 0.0732\n",
"Epoch 22/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.1432 - accuracy: 0.0819 - val_loss: 3.1369 - val_accuracy: 0.0903\n",
"Epoch 23/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.1373 - accuracy: 0.0866 - val_loss: 3.1309 - val_accuracy: 0.0903\n",
"Epoch 24/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 3.1315 - accuracy: 0.0938 - val_loss: 3.1250 - val_accuracy: 0.0998\n",
"Epoch 25/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.1258 - accuracy: 0.1002 - val_loss: 3.1192 - val_accuracy: 0.1002\n",
"Epoch 26/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.1201 - accuracy: 0.1000 - val_loss: 3.1134 - val_accuracy: 0.1018\n",
"Epoch 27/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 3.1145 - accuracy: 0.1023 - val_loss: 3.1077 - val_accuracy: 0.1018\n",
"Epoch 28/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.1090 - accuracy: 0.0985 - val_loss: 3.1021 - val_accuracy: 0.0918\n",
"Epoch 29/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 3.1035 - accuracy: 0.0935 - val_loss: 3.0965 - val_accuracy: 0.0948\n",
"Epoch 30/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 3.0981 - accuracy: 0.0952 - val_loss: 3.0910 - val_accuracy: 0.0948\n",
"Epoch 31/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.0927 - accuracy: 0.0952 - val_loss: 3.0855 - val_accuracy: 0.0948\n",
"Epoch 32/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.0873 - accuracy: 0.0957 - val_loss: 3.0801 - val_accuracy: 0.0953\n",
"Epoch 33/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.0820 - accuracy: 0.0957 - val_loss: 3.0747 - val_accuracy: 0.0953\n",
"Epoch 34/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.0768 - accuracy: 0.0957 - val_loss: 3.0694 - val_accuracy: 0.0953\n",
"Epoch 35/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.0716 - accuracy: 0.0957 - val_loss: 3.0641 - val_accuracy: 0.0953\n",
"Epoch 36/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 3.0664 - accuracy: 0.1010 - val_loss: 3.0588 - val_accuracy: 0.1378\n",
"Epoch 37/500\n",
"5980/5980 [==============================] - 0s 13us/sample - loss: 3.0613 - accuracy: 0.1309 - val_loss: 3.0537 - val_accuracy: 0.1378\n",
"Epoch 38/500\n",
"5980/5980 [==============================] - 0s 13us/sample - loss: 3.0562 - accuracy: 0.1309 - val_loss: 3.0485 - val_accuracy: 0.1378\n",
"Epoch 39/500\n",
"5980/5980 [==============================] - 0s 13us/sample - loss: 3.0512 - accuracy: 0.1309 - val_loss: 3.0434 - val_accuracy: 0.1371\n",
"Epoch 40/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 3.0463 - accuracy: 0.1306 - val_loss: 3.0384 - val_accuracy: 0.1371\n",
"Epoch 41/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 3.0413 - accuracy: 0.1306 - val_loss: 3.0334 - val_accuracy: 0.1371\n",
"Epoch 42/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 3.0364 - accuracy: 0.1303 - val_loss: 3.0284 - val_accuracy: 0.1410\n",
"Epoch 43/500\n",
"5980/5980 [==============================] - 0s 14us/sample - loss: 3.0316 - accuracy: 0.1319 - val_loss: 3.0235 - val_accuracy: 0.1410\n",
"Epoch 44/500\n",
"5980/5980 [==============================] - 0s 21us/sample - loss: 3.0268 - accuracy: 0.1353 - val_loss: 3.0186 - val_accuracy: 0.1446\n",
"Epoch 45/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 3.0220 - accuracy: 0.1361 - val_loss: 3.0138 - val_accuracy: 0.1446\n",
"Epoch 46/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 3.0173 - accuracy: 0.1361 - val_loss: 3.0091 - val_accuracy: 0.1446\n",
"Epoch 47/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 3.0127 - accuracy: 0.1361 - val_loss: 3.0043 - val_accuracy: 0.1446\n",
"Epoch 48/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 3.0081 - accuracy: 0.1361 - val_loss: 2.9997 - val_accuracy: 0.1446\n",
"Epoch 49/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 3.0035 - accuracy: 0.1361 - val_loss: 2.9950 - val_accuracy: 0.1446\n",
"Epoch 50/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.9990 - accuracy: 0.1361 - val_loss: 2.9905 - val_accuracy: 0.1505\n",
"Epoch 51/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.9945 - accuracy: 0.1431 - val_loss: 2.9859 - val_accuracy: 0.1500\n",
"Epoch 52/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.9901 - accuracy: 0.1428 - val_loss: 2.9815 - val_accuracy: 0.1485\n",
"Epoch 53/500\n",
"5980/5980 [==============================] - 0s 22us/sample - loss: 2.9857 - accuracy: 0.1418 - val_loss: 2.9770 - val_accuracy: 0.1485\n",
"Epoch 54/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.9814 - accuracy: 0.1416 - val_loss: 2.9727 - val_accuracy: 0.1485\n",
"Epoch 55/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.9771 - accuracy: 0.1415 - val_loss: 2.9684 - val_accuracy: 0.1485\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 56/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.9729 - accuracy: 0.1423 - val_loss: 2.9641 - val_accuracy: 0.1495\n",
"Epoch 57/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9688 - accuracy: 0.1445 - val_loss: 2.9599 - val_accuracy: 0.1495\n",
"Epoch 58/500\n",
"5980/5980 [==============================] - 0s 13us/sample - loss: 2.9647 - accuracy: 0.1445 - val_loss: 2.9558 - val_accuracy: 0.1495\n",
"Epoch 59/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9606 - accuracy: 0.1445 - val_loss: 2.9517 - val_accuracy: 0.1495\n",
"Epoch 60/500\n",
"5980/5980 [==============================] - 0s 14us/sample - loss: 2.9566 - accuracy: 0.1453 - val_loss: 2.9476 - val_accuracy: 0.1533\n",
"Epoch 61/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9527 - accuracy: 0.1488 - val_loss: 2.9437 - val_accuracy: 0.1552\n",
"Epoch 62/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9488 - accuracy: 0.1508 - val_loss: 2.9398 - val_accuracy: 0.1552\n",
"Epoch 63/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9450 - accuracy: 0.1517 - val_loss: 2.9359 - val_accuracy: 0.1569\n",
"Epoch 64/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9412 - accuracy: 0.1525 - val_loss: 2.9321 - val_accuracy: 0.1569\n",
"Epoch 65/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9375 - accuracy: 0.1525 - val_loss: 2.9284 - val_accuracy: 0.1569\n",
"Epoch 66/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9339 - accuracy: 0.1525 - val_loss: 2.9247 - val_accuracy: 0.1569\n",
"Epoch 67/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9303 - accuracy: 0.1525 - val_loss: 2.9211 - val_accuracy: 0.1569\n",
"Epoch 68/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9268 - accuracy: 0.1522 - val_loss: 2.9175 - val_accuracy: 0.1569\n",
"Epoch 69/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9233 - accuracy: 0.1507 - val_loss: 2.9140 - val_accuracy: 0.1569\n",
"Epoch 70/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9199 - accuracy: 0.1512 - val_loss: 2.9106 - val_accuracy: 0.1569\n",
"Epoch 71/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.9166 - accuracy: 0.1512 - val_loss: 2.9072 - val_accuracy: 0.1569\n",
"Epoch 72/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.9133 - accuracy: 0.1512 - val_loss: 2.9039 - val_accuracy: 0.1569\n",
"Epoch 73/500\n",
"5980/5980 [==============================] - 0s 23us/sample - loss: 2.9100 - accuracy: 0.1512 - val_loss: 2.9007 - val_accuracy: 0.1569\n",
"Epoch 74/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.9069 - accuracy: 0.1512 - val_loss: 2.8975 - val_accuracy: 0.1569\n",
"Epoch 75/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.9038 - accuracy: 0.1512 - val_loss: 2.8943 - val_accuracy: 0.1569\n",
"Epoch 76/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.9007 - accuracy: 0.1512 - val_loss: 2.8912 - val_accuracy: 0.1569\n",
"Epoch 77/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8977 - accuracy: 0.1512 - val_loss: 2.8882 - val_accuracy: 0.1569\n",
"Epoch 78/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.8948 - accuracy: 0.1512 - val_loss: 2.8853 - val_accuracy: 0.1569\n",
"Epoch 79/500\n",
"5980/5980 [==============================] - 0s 23us/sample - loss: 2.8919 - accuracy: 0.1512 - val_loss: 2.8824 - val_accuracy: 0.1569\n",
"Epoch 80/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.8890 - accuracy: 0.1512 - val_loss: 2.8795 - val_accuracy: 0.1569\n",
"Epoch 81/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.8863 - accuracy: 0.1512 - val_loss: 2.8767 - val_accuracy: 0.1569\n",
"Epoch 82/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8836 - accuracy: 0.1512 - val_loss: 2.8740 - val_accuracy: 0.1569\n",
"Epoch 83/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8809 - accuracy: 0.1512 - val_loss: 2.8713 - val_accuracy: 0.1569\n",
"Epoch 84/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8783 - accuracy: 0.1512 - val_loss: 2.8686 - val_accuracy: 0.1569\n",
"Epoch 85/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8757 - accuracy: 0.1512 - val_loss: 2.8660 - val_accuracy: 0.1569\n",
"Epoch 86/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8732 - accuracy: 0.1512 - val_loss: 2.8635 - val_accuracy: 0.1569\n",
"Epoch 87/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8707 - accuracy: 0.1512 - val_loss: 2.8610 - val_accuracy: 0.1569\n",
"Epoch 88/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8683 - accuracy: 0.1512 - val_loss: 2.8586 - val_accuracy: 0.1569\n",
"Epoch 89/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8659 - accuracy: 0.1512 - val_loss: 2.8562 - val_accuracy: 0.1569\n",
"Epoch 90/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8636 - accuracy: 0.1512 - val_loss: 2.8538 - val_accuracy: 0.1569\n",
"Epoch 91/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8613 - accuracy: 0.1512 - val_loss: 2.8515 - val_accuracy: 0.1569\n",
"Epoch 92/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8590 - accuracy: 0.1512 - val_loss: 2.8492 - val_accuracy: 0.1569\n",
"Epoch 93/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8568 - accuracy: 0.1512 - val_loss: 2.8470 - val_accuracy: 0.1575\n",
"Epoch 94/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8546 - accuracy: 0.1515 - val_loss: 2.8448 - val_accuracy: 0.1575\n",
"Epoch 95/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8525 - accuracy: 0.1515 - val_loss: 2.8426 - val_accuracy: 0.1570\n",
"Epoch 96/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.8504 - accuracy: 0.1503 - val_loss: 2.8405 - val_accuracy: 0.1559\n",
"Epoch 97/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8484 - accuracy: 0.1502 - val_loss: 2.8384 - val_accuracy: 0.1559\n",
"Epoch 98/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8463 - accuracy: 0.1502 - val_loss: 2.8364 - val_accuracy: 0.1559\n",
"Epoch 99/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8444 - accuracy: 0.1502 - val_loss: 2.8344 - val_accuracy: 0.1559\n",
"Epoch 100/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8424 - accuracy: 0.1502 - val_loss: 2.8324 - val_accuracy: 0.1559\n",
"Epoch 101/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8405 - accuracy: 0.1502 - val_loss: 2.8305 - val_accuracy: 0.1559\n",
"Epoch 102/500\n",
"5980/5980 [==============================] - 0s 14us/sample - loss: 2.8386 - accuracy: 0.1502 - val_loss: 2.8286 - val_accuracy: 0.1559\n",
"Epoch 103/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8367 - accuracy: 0.1502 - val_loss: 2.8267 - val_accuracy: 0.1559\n",
"Epoch 104/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8349 - accuracy: 0.1502 - val_loss: 2.8248 - val_accuracy: 0.1559\n",
"Epoch 105/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8331 - accuracy: 0.1502 - val_loss: 2.8230 - val_accuracy: 0.1559\n",
"Epoch 106/500\n",
"5980/5980 [==============================] - 0s 16us/sample - loss: 2.8313 - accuracy: 0.1502 - val_loss: 2.8212 - val_accuracy: 0.1559\n",
"Epoch 107/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8296 - accuracy: 0.1502 - val_loss: 2.8194 - val_accuracy: 0.1559\n",
"Epoch 108/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8279 - accuracy: 0.1502 - val_loss: 2.8176 - val_accuracy: 0.1559\n",
"Epoch 109/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8261 - accuracy: 0.1502 - val_loss: 2.8159 - val_accuracy: 0.1559\n",
"Epoch 110/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8245 - accuracy: 0.1502 - val_loss: 2.8142 - val_accuracy: 0.1559\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 111/500\n",
"5980/5980 [==============================] - 0s 13us/sample - loss: 2.8228 - accuracy: 0.1502 - val_loss: 2.8125 - val_accuracy: 0.1559\n",
"Epoch 112/500\n",
"5980/5980 [==============================] - 0s 13us/sample - loss: 2.8212 - accuracy: 0.1502 - val_loss: 2.8108 - val_accuracy: 0.1559\n",
"Epoch 113/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8195 - accuracy: 0.1502 - val_loss: 2.8092 - val_accuracy: 0.1559\n",
"Epoch 114/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8180 - accuracy: 0.1502 - val_loss: 2.8076 - val_accuracy: 0.1559\n",
"Epoch 115/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8164 - accuracy: 0.1502 - val_loss: 2.8060 - val_accuracy: 0.1559\n",
"Epoch 116/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8148 - accuracy: 0.1502 - val_loss: 2.8044 - val_accuracy: 0.1559\n",
"Epoch 117/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8133 - accuracy: 0.1502 - val_loss: 2.8028 - val_accuracy: 0.1559\n",
"Epoch 118/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8117 - accuracy: 0.1502 - val_loss: 2.8012 - val_accuracy: 0.1559\n",
"Epoch 119/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8102 - accuracy: 0.1502 - val_loss: 2.7997 - val_accuracy: 0.1559\n",
"Epoch 120/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8087 - accuracy: 0.1502 - val_loss: 2.7981 - val_accuracy: 0.1559\n",
"Epoch 121/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8072 - accuracy: 0.1502 - val_loss: 2.7966 - val_accuracy: 0.1559\n",
"Epoch 122/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.8058 - accuracy: 0.1502 - val_loss: 2.7951 - val_accuracy: 0.1559\n",
"Epoch 123/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8043 - accuracy: 0.1502 - val_loss: 2.7936 - val_accuracy: 0.1559\n",
"Epoch 124/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8028 - accuracy: 0.1502 - val_loss: 2.7921 - val_accuracy: 0.1559\n",
"Epoch 125/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8014 - accuracy: 0.1502 - val_loss: 2.7907 - val_accuracy: 0.1559\n",
"Epoch 126/500\n",
"5980/5980 [==============================] - 0s 15us/sample - loss: 2.8000 - accuracy: 0.1493 - val_loss: 2.7892 - val_accuracy: 0.1555\n",
"Epoch 127/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7986 - accuracy: 0.1488 - val_loss: 2.7878 - val_accuracy: 0.1555\n",
"Epoch 128/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7972 - accuracy: 0.1488 - val_loss: 2.7863 - val_accuracy: 0.1555\n",
"Epoch 129/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7957 - accuracy: 0.1488 - val_loss: 2.7849 - val_accuracy: 0.1555\n",
"Epoch 130/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7944 - accuracy: 0.1488 - val_loss: 2.7834 - val_accuracy: 0.1555\n",
"Epoch 131/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7930 - accuracy: 0.1488 - val_loss: 2.7820 - val_accuracy: 0.1555\n",
"Epoch 132/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7916 - accuracy: 0.1488 - val_loss: 2.7806 - val_accuracy: 0.1555\n",
"Epoch 133/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7902 - accuracy: 0.1488 - val_loss: 2.7792 - val_accuracy: 0.1555\n",
"Epoch 134/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7888 - accuracy: 0.1488 - val_loss: 2.7778 - val_accuracy: 0.1555\n",
"Epoch 135/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7875 - accuracy: 0.1488 - val_loss: 2.7764 - val_accuracy: 0.1555\n",
"Epoch 136/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7861 - accuracy: 0.1488 - val_loss: 2.7750 - val_accuracy: 0.1555\n",
"Epoch 137/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7847 - accuracy: 0.1488 - val_loss: 2.7736 - val_accuracy: 0.1555\n",
"Epoch 138/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7834 - accuracy: 0.1488 - val_loss: 2.7722 - val_accuracy: 0.1555\n",
"Epoch 139/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7821 - accuracy: 0.1488 - val_loss: 2.7709 - val_accuracy: 0.1555\n",
"Epoch 140/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7807 - accuracy: 0.1488 - val_loss: 2.7695 - val_accuracy: 0.1555\n",
"Epoch 141/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7794 - accuracy: 0.1488 - val_loss: 2.7681 - val_accuracy: 0.1555\n",
"Epoch 142/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7780 - accuracy: 0.1488 - val_loss: 2.7667 - val_accuracy: 0.1555\n",
"Epoch 143/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7767 - accuracy: 0.1488 - val_loss: 2.7654 - val_accuracy: 0.1555\n",
"Epoch 144/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7754 - accuracy: 0.1488 - val_loss: 2.7640 - val_accuracy: 0.1555\n",
"Epoch 145/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7740 - accuracy: 0.1488 - val_loss: 2.7626 - val_accuracy: 0.1555\n",
"Epoch 146/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7727 - accuracy: 0.1488 - val_loss: 2.7613 - val_accuracy: 0.1555\n",
"Epoch 147/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7714 - accuracy: 0.1488 - val_loss: 2.7599 - val_accuracy: 0.1555\n",
"Epoch 148/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.7700 - accuracy: 0.1488 - val_loss: 2.7585 - val_accuracy: 0.1555\n",
"Epoch 149/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7687 - accuracy: 0.1488 - val_loss: 2.7572 - val_accuracy: 0.1555\n",
"Epoch 150/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7674 - accuracy: 0.1488 - val_loss: 2.7558 - val_accuracy: 0.1555\n",
"Epoch 151/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7660 - accuracy: 0.1488 - val_loss: 2.7545 - val_accuracy: 0.1555\n",
"Epoch 152/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7647 - accuracy: 0.1488 - val_loss: 2.7531 - val_accuracy: 0.1555\n",
"Epoch 153/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7634 - accuracy: 0.1488 - val_loss: 2.7518 - val_accuracy: 0.1555\n",
"Epoch 154/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7621 - accuracy: 0.1488 - val_loss: 2.7504 - val_accuracy: 0.1555\n",
"Epoch 155/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7607 - accuracy: 0.1488 - val_loss: 2.7490 - val_accuracy: 0.1555\n",
"Epoch 156/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7594 - accuracy: 0.1488 - val_loss: 2.7477 - val_accuracy: 0.1555\n",
"Epoch 157/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7581 - accuracy: 0.1488 - val_loss: 2.7463 - val_accuracy: 0.1555\n",
"Epoch 158/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7567 - accuracy: 0.1488 - val_loss: 2.7450 - val_accuracy: 0.1555\n",
"Epoch 159/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7554 - accuracy: 0.1488 - val_loss: 2.7436 - val_accuracy: 0.1555\n",
"Epoch 160/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7541 - accuracy: 0.1488 - val_loss: 2.7423 - val_accuracy: 0.1555\n",
"Epoch 161/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7527 - accuracy: 0.1488 - val_loss: 2.7409 - val_accuracy: 0.1555\n",
"Epoch 162/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7514 - accuracy: 0.1488 - val_loss: 2.7396 - val_accuracy: 0.1555\n",
"Epoch 163/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7501 - accuracy: 0.1488 - val_loss: 2.7382 - val_accuracy: 0.1555\n",
"Epoch 164/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7487 - accuracy: 0.1488 - val_loss: 2.7368 - val_accuracy: 0.1555\n",
"Epoch 165/500\n"
]
},
{
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"text": [
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.7474 - accuracy: 0.1488 - val_loss: 2.7355 - val_accuracy: 0.1555\n",
"Epoch 166/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7461 - accuracy: 0.1488 - val_loss: 2.7341 - val_accuracy: 0.1555\n",
"Epoch 167/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7447 - accuracy: 0.1488 - val_loss: 2.7328 - val_accuracy: 0.1555\n",
"Epoch 168/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7434 - accuracy: 0.1488 - val_loss: 2.7314 - val_accuracy: 0.1555\n",
"Epoch 169/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7421 - accuracy: 0.1488 - val_loss: 2.7301 - val_accuracy: 0.1555\n",
"Epoch 170/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7407 - accuracy: 0.1488 - val_loss: 2.7287 - val_accuracy: 0.1555\n",
"Epoch 171/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7394 - accuracy: 0.1488 - val_loss: 2.7274 - val_accuracy: 0.1555\n",
"Epoch 172/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7381 - accuracy: 0.1488 - val_loss: 2.7260 - val_accuracy: 0.1555\n",
"Epoch 173/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7367 - accuracy: 0.1488 - val_loss: 2.7247 - val_accuracy: 0.1555\n",
"Epoch 174/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7354 - accuracy: 0.1488 - val_loss: 2.7233 - val_accuracy: 0.1555\n",
"Epoch 175/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7341 - accuracy: 0.1488 - val_loss: 2.7219 - val_accuracy: 0.1555\n",
"Epoch 176/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7327 - accuracy: 0.1488 - val_loss: 2.7206 - val_accuracy: 0.1555\n",
"Epoch 177/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7314 - accuracy: 0.1488 - val_loss: 2.7192 - val_accuracy: 0.1555\n",
"Epoch 178/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7301 - accuracy: 0.1488 - val_loss: 2.7179 - val_accuracy: 0.1555\n",
"Epoch 179/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7287 - accuracy: 0.1488 - val_loss: 2.7165 - val_accuracy: 0.1555\n",
"Epoch 180/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7274 - accuracy: 0.1488 - val_loss: 2.7152 - val_accuracy: 0.1555\n",
"Epoch 181/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7261 - accuracy: 0.1488 - val_loss: 2.7138 - val_accuracy: 0.1555\n",
"Epoch 182/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7248 - accuracy: 0.1488 - val_loss: 2.7125 - val_accuracy: 0.1555\n",
"Epoch 183/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7234 - accuracy: 0.1488 - val_loss: 2.7111 - val_accuracy: 0.1555\n",
"Epoch 184/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.7221 - accuracy: 0.1488 - val_loss: 2.7098 - val_accuracy: 0.1555\n",
"Epoch 185/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7208 - accuracy: 0.1488 - val_loss: 2.7084 - val_accuracy: 0.1555\n",
"Epoch 186/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7194 - accuracy: 0.1488 - val_loss: 2.7071 - val_accuracy: 0.1555\n",
"Epoch 187/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7181 - accuracy: 0.1488 - val_loss: 2.7057 - val_accuracy: 0.1555\n",
"Epoch 188/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7168 - accuracy: 0.1488 - val_loss: 2.7044 - val_accuracy: 0.1555\n",
"Epoch 189/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7155 - accuracy: 0.1488 - val_loss: 2.7031 - val_accuracy: 0.1555\n",
"Epoch 190/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7142 - accuracy: 0.1488 - val_loss: 2.7017 - val_accuracy: 0.1555\n",
"Epoch 191/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7129 - accuracy: 0.1488 - val_loss: 2.7004 - val_accuracy: 0.1555\n",
"Epoch 192/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7115 - accuracy: 0.1488 - val_loss: 2.6991 - val_accuracy: 0.1555\n",
"Epoch 193/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7102 - accuracy: 0.1488 - val_loss: 2.6977 - val_accuracy: 0.1555\n",
"Epoch 194/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7089 - accuracy: 0.1488 - val_loss: 2.6964 - val_accuracy: 0.1555\n",
"Epoch 195/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7076 - accuracy: 0.1488 - val_loss: 2.6951 - val_accuracy: 0.1555\n",
"Epoch 196/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7063 - accuracy: 0.1488 - val_loss: 2.6938 - val_accuracy: 0.1555\n",
"Epoch 197/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7050 - accuracy: 0.1488 - val_loss: 2.6924 - val_accuracy: 0.1555\n",
"Epoch 198/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.7037 - accuracy: 0.1488 - val_loss: 2.6911 - val_accuracy: 0.1555\n",
"Epoch 199/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7024 - accuracy: 0.1488 - val_loss: 2.6898 - val_accuracy: 0.1555\n",
"Epoch 200/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.7011 - accuracy: 0.1488 - val_loss: 2.6885 - val_accuracy: 0.1555\n",
"Epoch 201/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.6998 - accuracy: 0.1488 - val_loss: 2.6872 - val_accuracy: 0.1555\n",
"Epoch 202/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6985 - accuracy: 0.1488 - val_loss: 2.6859 - val_accuracy: 0.1555\n",
"Epoch 203/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6973 - accuracy: 0.1488 - val_loss: 2.6846 - val_accuracy: 0.1555\n",
"Epoch 204/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.6960 - accuracy: 0.1488 - val_loss: 2.6833 - val_accuracy: 0.1555\n",
"Epoch 205/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6947 - accuracy: 0.1488 - val_loss: 2.6820 - val_accuracy: 0.1555\n",
"Epoch 206/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6934 - accuracy: 0.1488 - val_loss: 2.6807 - val_accuracy: 0.1555\n",
"Epoch 207/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6921 - accuracy: 0.1488 - val_loss: 2.6794 - val_accuracy: 0.1555\n",
"Epoch 208/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6908 - accuracy: 0.1488 - val_loss: 2.6781 - val_accuracy: 0.1555\n",
"Epoch 209/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6896 - accuracy: 0.1488 - val_loss: 2.6768 - val_accuracy: 0.1555\n",
"Epoch 210/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6883 - accuracy: 0.1488 - val_loss: 2.6755 - val_accuracy: 0.1555\n",
"Epoch 211/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6871 - accuracy: 0.1488 - val_loss: 2.6742 - val_accuracy: 0.1555\n",
"Epoch 212/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6858 - accuracy: 0.1488 - val_loss: 2.6730 - val_accuracy: 0.1555\n",
"Epoch 213/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.6846 - accuracy: 0.1488 - val_loss: 2.6717 - val_accuracy: 0.1555\n",
"Epoch 214/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6833 - accuracy: 0.1488 - val_loss: 2.6704 - val_accuracy: 0.1555\n",
"Epoch 215/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6821 - accuracy: 0.1488 - val_loss: 2.6691 - val_accuracy: 0.1555\n",
"Epoch 216/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6808 - accuracy: 0.1488 - val_loss: 2.6679 - val_accuracy: 0.1555\n",
"Epoch 217/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6796 - accuracy: 0.1488 - val_loss: 2.6666 - val_accuracy: 0.1555\n",
"Epoch 218/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6783 - accuracy: 0.1488 - val_loss: 2.6654 - val_accuracy: 0.1555\n",
"Epoch 219/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.6771 - accuracy: 0.1488 - val_loss: 2.6641 - val_accuracy: 0.1555\n"
]
},
{
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"text": [
"Epoch 220/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6759 - accuracy: 0.1488 - val_loss: 2.6629 - val_accuracy: 0.1555\n",
"Epoch 221/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6746 - accuracy: 0.1488 - val_loss: 2.6616 - val_accuracy: 0.1555\n",
"Epoch 222/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6734 - accuracy: 0.1488 - val_loss: 2.6604 - val_accuracy: 0.1555\n",
"Epoch 223/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6722 - accuracy: 0.1488 - val_loss: 2.6591 - val_accuracy: 0.1555\n",
"Epoch 224/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6710 - accuracy: 0.1488 - val_loss: 2.6579 - val_accuracy: 0.1555\n",
"Epoch 225/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.6698 - accuracy: 0.1488 - val_loss: 2.6567 - val_accuracy: 0.1555\n",
"Epoch 226/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.6686 - accuracy: 0.1488 - val_loss: 2.6554 - val_accuracy: 0.1555\n",
"Epoch 227/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.6674 - accuracy: 0.1488 - val_loss: 2.6542 - val_accuracy: 0.1555\n",
"Epoch 228/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6662 - accuracy: 0.1488 - val_loss: 2.6530 - val_accuracy: 0.1555\n",
"Epoch 229/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.6650 - accuracy: 0.1488 - val_loss: 2.6517 - val_accuracy: 0.1555\n",
"Epoch 230/500\n",
"5980/5980 [==============================] - 0s 22us/sample - loss: 2.6638 - accuracy: 0.1488 - val_loss: 2.6505 - val_accuracy: 0.1555\n",
"Epoch 231/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.6625 - accuracy: 0.1488 - val_loss: 2.6493 - val_accuracy: 0.1555\n",
"Epoch 232/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6614 - accuracy: 0.1488 - val_loss: 2.6481 - val_accuracy: 0.1555\n",
"Epoch 233/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6601 - accuracy: 0.1488 - val_loss: 2.6469 - val_accuracy: 0.1555\n",
"Epoch 234/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6590 - accuracy: 0.1488 - val_loss: 2.6457 - val_accuracy: 0.1555\n",
"Epoch 235/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.6578 - accuracy: 0.1488 - val_loss: 2.6445 - val_accuracy: 0.1555\n",
"Epoch 236/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6566 - accuracy: 0.1488 - val_loss: 2.6433 - val_accuracy: 0.1555\n",
"Epoch 237/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6554 - accuracy: 0.1488 - val_loss: 2.6421 - val_accuracy: 0.1555\n",
"Epoch 238/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6543 - accuracy: 0.1488 - val_loss: 2.6409 - val_accuracy: 0.1555\n",
"Epoch 239/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.6531 - accuracy: 0.1488 - val_loss: 2.6397 - val_accuracy: 0.1555\n",
"Epoch 240/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6519 - accuracy: 0.1488 - val_loss: 2.6385 - val_accuracy: 0.1555\n",
"Epoch 241/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6507 - accuracy: 0.1488 - val_loss: 2.6373 - val_accuracy: 0.1555\n",
"Epoch 242/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6496 - accuracy: 0.1488 - val_loss: 2.6361 - val_accuracy: 0.1555\n",
"Epoch 243/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6484 - accuracy: 0.1488 - val_loss: 2.6349 - val_accuracy: 0.1555\n",
"Epoch 244/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6472 - accuracy: 0.1488 - val_loss: 2.6337 - val_accuracy: 0.1555\n",
"Epoch 245/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6461 - accuracy: 0.1488 - val_loss: 2.6325 - val_accuracy: 0.1555\n",
"Epoch 246/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6449 - accuracy: 0.1488 - val_loss: 2.6313 - val_accuracy: 0.1555\n",
"Epoch 247/500\n",
"5980/5980 [==============================] - 0s 16us/sample - loss: 2.6437 - accuracy: 0.1488 - val_loss: 2.6302 - val_accuracy: 0.1555\n",
"Epoch 248/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6426 - accuracy: 0.1488 - val_loss: 2.6290 - val_accuracy: 0.1555\n",
"Epoch 249/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6414 - accuracy: 0.1488 - val_loss: 2.6278 - val_accuracy: 0.1555\n",
"Epoch 250/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6403 - accuracy: 0.1488 - val_loss: 2.6266 - val_accuracy: 0.1555\n",
"Epoch 251/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6391 - accuracy: 0.1488 - val_loss: 2.6254 - val_accuracy: 0.1555\n",
"Epoch 252/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6379 - accuracy: 0.1488 - val_loss: 2.6243 - val_accuracy: 0.1555\n",
"Epoch 253/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6368 - accuracy: 0.1488 - val_loss: 2.6231 - val_accuracy: 0.1555\n",
"Epoch 254/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6357 - accuracy: 0.1488 - val_loss: 2.6219 - val_accuracy: 0.1555\n",
"Epoch 255/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.6345 - accuracy: 0.1488 - val_loss: 2.6207 - val_accuracy: 0.1555\n",
"Epoch 256/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6333 - accuracy: 0.1488 - val_loss: 2.6195 - val_accuracy: 0.1555\n",
"Epoch 257/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6322 - accuracy: 0.1488 - val_loss: 2.6184 - val_accuracy: 0.1555\n",
"Epoch 258/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6310 - accuracy: 0.1488 - val_loss: 2.6172 - val_accuracy: 0.1555\n",
"Epoch 259/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6299 - accuracy: 0.1488 - val_loss: 2.6160 - val_accuracy: 0.1555\n",
"Epoch 260/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6287 - accuracy: 0.1488 - val_loss: 2.6148 - val_accuracy: 0.1555\n",
"Epoch 261/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6275 - accuracy: 0.1488 - val_loss: 2.6136 - val_accuracy: 0.1555\n",
"Epoch 262/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6264 - accuracy: 0.1488 - val_loss: 2.6124 - val_accuracy: 0.1555\n",
"Epoch 263/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6252 - accuracy: 0.1488 - val_loss: 2.6113 - val_accuracy: 0.1555\n",
"Epoch 264/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6241 - accuracy: 0.1488 - val_loss: 2.6101 - val_accuracy: 0.1555\n",
"Epoch 265/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6229 - accuracy: 0.1488 - val_loss: 2.6089 - val_accuracy: 0.1555\n",
"Epoch 266/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6218 - accuracy: 0.1488 - val_loss: 2.6077 - val_accuracy: 0.1555\n",
"Epoch 267/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6206 - accuracy: 0.1488 - val_loss: 2.6065 - val_accuracy: 0.1555\n",
"Epoch 268/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.6194 - accuracy: 0.1488 - val_loss: 2.6053 - val_accuracy: 0.1555\n",
"Epoch 269/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.6183 - accuracy: 0.1488 - val_loss: 2.6042 - val_accuracy: 0.1555\n",
"Epoch 270/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6171 - accuracy: 0.1488 - val_loss: 2.6030 - val_accuracy: 0.1555\n",
"Epoch 271/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6160 - accuracy: 0.1488 - val_loss: 2.6018 - val_accuracy: 0.1555\n",
"Epoch 272/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6148 - accuracy: 0.1488 - val_loss: 2.6006 - val_accuracy: 0.1555\n",
"Epoch 273/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6136 - accuracy: 0.1488 - val_loss: 2.5994 - val_accuracy: 0.1555\n",
"Epoch 274/500\n"
]
},
{
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"output_type": "stream",
"text": [
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6124 - accuracy: 0.1488 - val_loss: 2.5981 - val_accuracy: 0.1555\n",
"Epoch 275/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6113 - accuracy: 0.1488 - val_loss: 2.5969 - val_accuracy: 0.1555\n",
"Epoch 276/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.6101 - accuracy: 0.1488 - val_loss: 2.5957 - val_accuracy: 0.1555\n",
"Epoch 277/500\n",
"5980/5980 [==============================] - 0s 22us/sample - loss: 2.6089 - accuracy: 0.1488 - val_loss: 2.5945 - val_accuracy: 0.1555\n",
"Epoch 278/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.6077 - accuracy: 0.1488 - val_loss: 2.5933 - val_accuracy: 0.1555\n",
"Epoch 279/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6065 - accuracy: 0.1488 - val_loss: 2.5921 - val_accuracy: 0.1555\n",
"Epoch 280/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6053 - accuracy: 0.1488 - val_loss: 2.5909 - val_accuracy: 0.1555\n",
"Epoch 281/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6042 - accuracy: 0.1488 - val_loss: 2.5897 - val_accuracy: 0.1555\n",
"Epoch 282/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.6030 - accuracy: 0.1488 - val_loss: 2.5884 - val_accuracy: 0.1555\n",
"Epoch 283/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.6018 - accuracy: 0.1488 - val_loss: 2.5872 - val_accuracy: 0.1555\n",
"Epoch 284/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.6006 - accuracy: 0.1488 - val_loss: 2.5860 - val_accuracy: 0.1555\n",
"Epoch 285/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.5994 - accuracy: 0.1488 - val_loss: 2.5847 - val_accuracy: 0.1555\n",
"Epoch 286/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5982 - accuracy: 0.1488 - val_loss: 2.5835 - val_accuracy: 0.1555\n",
"Epoch 287/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5970 - accuracy: 0.1488 - val_loss: 2.5823 - val_accuracy: 0.1555\n",
"Epoch 288/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5958 - accuracy: 0.1488 - val_loss: 2.5810 - val_accuracy: 0.1555\n",
"Epoch 289/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5945 - accuracy: 0.1488 - val_loss: 2.5798 - val_accuracy: 0.1555\n",
"Epoch 290/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5934 - accuracy: 0.1488 - val_loss: 2.5785 - val_accuracy: 0.1555\n",
"Epoch 291/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5921 - accuracy: 0.1488 - val_loss: 2.5773 - val_accuracy: 0.1555\n",
"Epoch 292/500\n",
"5980/5980 [==============================] - 0s 25us/sample - loss: 2.5909 - accuracy: 0.1488 - val_loss: 2.5760 - val_accuracy: 0.1555\n",
"Epoch 293/500\n",
"5980/5980 [==============================] - 0s 26us/sample - loss: 2.5897 - accuracy: 0.1488 - val_loss: 2.5747 - val_accuracy: 0.1555\n",
"Epoch 294/500\n",
"5980/5980 [==============================] - 0s 24us/sample - loss: 2.5885 - accuracy: 0.1488 - val_loss: 2.5735 - val_accuracy: 0.1555\n",
"Epoch 295/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5873 - accuracy: 0.1488 - val_loss: 2.5722 - val_accuracy: 0.1555\n",
"Epoch 296/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.5860 - accuracy: 0.1488 - val_loss: 2.5710 - val_accuracy: 0.1555\n",
"Epoch 297/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.5848 - accuracy: 0.1488 - val_loss: 2.5697 - val_accuracy: 0.1555\n",
"Epoch 298/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5836 - accuracy: 0.1488 - val_loss: 2.5685 - val_accuracy: 0.1555\n",
"Epoch 299/500\n",
"5980/5980 [==============================] - 0s 27us/sample - loss: 2.5824 - accuracy: 0.1488 - val_loss: 2.5672 - val_accuracy: 0.1555\n",
"Epoch 300/500\n",
"5980/5980 [==============================] - 0s 23us/sample - loss: 2.5811 - accuracy: 0.1488 - val_loss: 2.5659 - val_accuracy: 0.1555\n",
"Epoch 301/500\n",
"5980/5980 [==============================] - 0s 26us/sample - loss: 2.5799 - accuracy: 0.1488 - val_loss: 2.5647 - val_accuracy: 0.1555\n",
"Epoch 302/500\n",
"5980/5980 [==============================] - 0s 24us/sample - loss: 2.5787 - accuracy: 0.1488 - val_loss: 2.5634 - val_accuracy: 0.1555\n",
"Epoch 303/500\n",
"5980/5980 [==============================] - 0s 23us/sample - loss: 2.5775 - accuracy: 0.1488 - val_loss: 2.5622 - val_accuracy: 0.1555\n",
"Epoch 304/500\n",
"5980/5980 [==============================] - 0s 26us/sample - loss: 2.5762 - accuracy: 0.1488 - val_loss: 2.5609 - val_accuracy: 0.1555\n",
"Epoch 305/500\n",
"5980/5980 [==============================] - 0s 21us/sample - loss: 2.5750 - accuracy: 0.1488 - val_loss: 2.5597 - val_accuracy: 0.1555\n",
"Epoch 306/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5738 - accuracy: 0.1488 - val_loss: 2.5584 - val_accuracy: 0.1555\n",
"Epoch 307/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5726 - accuracy: 0.1488 - val_loss: 2.5571 - val_accuracy: 0.1555\n",
"Epoch 308/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5714 - accuracy: 0.1488 - val_loss: 2.5559 - val_accuracy: 0.1555\n",
"Epoch 309/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5702 - accuracy: 0.1488 - val_loss: 2.5546 - val_accuracy: 0.1555\n",
"Epoch 310/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.5689 - accuracy: 0.1488 - val_loss: 2.5534 - val_accuracy: 0.1555\n",
"Epoch 311/500\n",
"5980/5980 [==============================] - 0s 25us/sample - loss: 2.5677 - accuracy: 0.1488 - val_loss: 2.5521 - val_accuracy: 0.1555\n",
"Epoch 312/500\n",
"5980/5980 [==============================] - 0s 22us/sample - loss: 2.5665 - accuracy: 0.1488 - val_loss: 2.5509 - val_accuracy: 0.1555\n",
"Epoch 313/500\n",
"5980/5980 [==============================] - 0s 25us/sample - loss: 2.5653 - accuracy: 0.1488 - val_loss: 2.5496 - val_accuracy: 0.1555\n",
"Epoch 314/500\n",
"5980/5980 [==============================] - 0s 23us/sample - loss: 2.5641 - accuracy: 0.1488 - val_loss: 2.5484 - val_accuracy: 0.1555\n",
"Epoch 315/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5629 - accuracy: 0.1488 - val_loss: 2.5471 - val_accuracy: 0.1555\n",
"Epoch 316/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5617 - accuracy: 0.1488 - val_loss: 2.5459 - val_accuracy: 0.1555\n",
"Epoch 317/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.5604 - accuracy: 0.1488 - val_loss: 2.5446 - val_accuracy: 0.1555\n",
"Epoch 318/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5592 - accuracy: 0.1488 - val_loss: 2.5434 - val_accuracy: 0.1555\n",
"Epoch 319/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5580 - accuracy: 0.1488 - val_loss: 2.5422 - val_accuracy: 0.1555\n",
"Epoch 320/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5568 - accuracy: 0.1488 - val_loss: 2.5409 - val_accuracy: 0.1555\n",
"Epoch 321/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5556 - accuracy: 0.1488 - val_loss: 2.5397 - val_accuracy: 0.1555\n",
"Epoch 322/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5544 - accuracy: 0.1488 - val_loss: 2.5385 - val_accuracy: 0.1555\n",
"Epoch 323/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5532 - accuracy: 0.1488 - val_loss: 2.5372 - val_accuracy: 0.1555\n",
"Epoch 324/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.5520 - accuracy: 0.1488 - val_loss: 2.5360 - val_accuracy: 0.1555\n",
"Epoch 325/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5508 - accuracy: 0.1488 - val_loss: 2.5348 - val_accuracy: 0.1555\n",
"Epoch 326/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5496 - accuracy: 0.1488 - val_loss: 2.5335 - val_accuracy: 0.1555\n",
"Epoch 327/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5484 - accuracy: 0.1554 - val_loss: 2.5323 - val_accuracy: 0.1721\n",
"Epoch 328/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5472 - accuracy: 0.1634 - val_loss: 2.5311 - val_accuracy: 0.1721\n"
]
},
{
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"text": [
"Epoch 329/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5461 - accuracy: 0.1634 - val_loss: 2.5298 - val_accuracy: 0.1721\n",
"Epoch 330/500\n",
"5980/5980 [==============================] - 0s 22us/sample - loss: 2.5448 - accuracy: 0.1634 - val_loss: 2.5286 - val_accuracy: 0.1721\n",
"Epoch 331/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.5436 - accuracy: 0.1634 - val_loss: 2.5274 - val_accuracy: 0.1721\n",
"Epoch 332/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5424 - accuracy: 0.1634 - val_loss: 2.5261 - val_accuracy: 0.1721\n",
"Epoch 333/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5413 - accuracy: 0.1634 - val_loss: 2.5249 - val_accuracy: 0.1721\n",
"Epoch 334/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5400 - accuracy: 0.1634 - val_loss: 2.5237 - val_accuracy: 0.1721\n",
"Epoch 335/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5388 - accuracy: 0.1634 - val_loss: 2.5224 - val_accuracy: 0.1721\n",
"Epoch 336/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5376 - accuracy: 0.1634 - val_loss: 2.5212 - val_accuracy: 0.1721\n",
"Epoch 337/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5364 - accuracy: 0.1634 - val_loss: 2.5200 - val_accuracy: 0.1721\n",
"Epoch 338/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5352 - accuracy: 0.1634 - val_loss: 2.5187 - val_accuracy: 0.1721\n",
"Epoch 339/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5340 - accuracy: 0.1634 - val_loss: 2.5175 - val_accuracy: 0.1721\n",
"Epoch 340/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5327 - accuracy: 0.1634 - val_loss: 2.5162 - val_accuracy: 0.1721\n",
"Epoch 341/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5315 - accuracy: 0.1634 - val_loss: 2.5150 - val_accuracy: 0.1721\n",
"Epoch 342/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5303 - accuracy: 0.1634 - val_loss: 2.5137 - val_accuracy: 0.1721\n",
"Epoch 343/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5291 - accuracy: 0.1634 - val_loss: 2.5124 - val_accuracy: 0.1721\n",
"Epoch 344/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5278 - accuracy: 0.1634 - val_loss: 2.5112 - val_accuracy: 0.1721\n",
"Epoch 345/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5266 - accuracy: 0.1634 - val_loss: 2.5099 - val_accuracy: 0.1716\n",
"Epoch 346/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5253 - accuracy: 0.1629 - val_loss: 2.5086 - val_accuracy: 0.1716\n",
"Epoch 347/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5241 - accuracy: 0.1629 - val_loss: 2.5073 - val_accuracy: 0.1716\n",
"Epoch 348/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5228 - accuracy: 0.1629 - val_loss: 2.5060 - val_accuracy: 0.1716\n",
"Epoch 349/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5215 - accuracy: 0.1629 - val_loss: 2.5047 - val_accuracy: 0.1716\n",
"Epoch 350/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5202 - accuracy: 0.1629 - val_loss: 2.5034 - val_accuracy: 0.1716\n",
"Epoch 351/500\n",
"5980/5980 [==============================] - 0s 23us/sample - loss: 2.5190 - accuracy: 0.1629 - val_loss: 2.5021 - val_accuracy: 0.1716\n",
"Epoch 352/500\n",
"5980/5980 [==============================] - 0s 23us/sample - loss: 2.5177 - accuracy: 0.1629 - val_loss: 2.5008 - val_accuracy: 0.1716\n",
"Epoch 353/500\n",
"5980/5980 [==============================] - 0s 23us/sample - loss: 2.5164 - accuracy: 0.1629 - val_loss: 2.4995 - val_accuracy: 0.1716\n",
"Epoch 354/500\n",
"5980/5980 [==============================] - 0s 22us/sample - loss: 2.5150 - accuracy: 0.1615 - val_loss: 2.4981 - val_accuracy: 0.1716\n",
"Epoch 355/500\n",
"5980/5980 [==============================] - 0s 23us/sample - loss: 2.5137 - accuracy: 0.1584 - val_loss: 2.4968 - val_accuracy: 0.1667\n",
"Epoch 356/500\n",
"5980/5980 [==============================] - 0s 22us/sample - loss: 2.5124 - accuracy: 0.1607 - val_loss: 2.4954 - val_accuracy: 0.1667\n",
"Epoch 357/500\n",
"5980/5980 [==============================] - 0s 22us/sample - loss: 2.5110 - accuracy: 0.1607 - val_loss: 2.4940 - val_accuracy: 0.1667\n",
"Epoch 358/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5097 - accuracy: 0.1607 - val_loss: 2.4927 - val_accuracy: 0.1667\n",
"Epoch 359/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5083 - accuracy: 0.1607 - val_loss: 2.4913 - val_accuracy: 0.1667\n",
"Epoch 360/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5069 - accuracy: 0.1717 - val_loss: 2.4899 - val_accuracy: 0.2079\n",
"Epoch 361/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5056 - accuracy: 0.1950 - val_loss: 2.4884 - val_accuracy: 0.2079\n",
"Epoch 362/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5041 - accuracy: 0.1987 - val_loss: 2.4870 - val_accuracy: 0.2152\n",
"Epoch 363/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.5027 - accuracy: 0.1997 - val_loss: 2.4856 - val_accuracy: 0.2152\n",
"Epoch 364/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.5013 - accuracy: 0.2007 - val_loss: 2.4841 - val_accuracy: 0.2162\n",
"Epoch 365/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4998 - accuracy: 0.2020 - val_loss: 2.4826 - val_accuracy: 0.2162\n",
"Epoch 366/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.4983 - accuracy: 0.2020 - val_loss: 2.4811 - val_accuracy: 0.2162\n",
"Epoch 367/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.4969 - accuracy: 0.2020 - val_loss: 2.4796 - val_accuracy: 0.2164\n",
"Epoch 368/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.4954 - accuracy: 0.2022 - val_loss: 2.4781 - val_accuracy: 0.2164\n",
"Epoch 369/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.4939 - accuracy: 0.2022 - val_loss: 2.4765 - val_accuracy: 0.2167\n",
"Epoch 370/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.4924 - accuracy: 0.2022 - val_loss: 2.4750 - val_accuracy: 0.2167\n",
"Epoch 371/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4908 - accuracy: 0.2035 - val_loss: 2.4734 - val_accuracy: 0.2177\n",
"Epoch 372/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4893 - accuracy: 0.2038 - val_loss: 2.4718 - val_accuracy: 0.2177\n",
"Epoch 373/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.4877 - accuracy: 0.2038 - val_loss: 2.4702 - val_accuracy: 0.2182\n",
"Epoch 374/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4861 - accuracy: 0.2043 - val_loss: 2.4686 - val_accuracy: 0.2194\n",
"Epoch 375/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4845 - accuracy: 0.2055 - val_loss: 2.4670 - val_accuracy: 0.2194\n",
"Epoch 376/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4828 - accuracy: 0.2055 - val_loss: 2.4653 - val_accuracy: 0.2194\n",
"Epoch 377/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4812 - accuracy: 0.2070 - val_loss: 2.4637 - val_accuracy: 0.2204\n",
"Epoch 378/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4797 - accuracy: 0.2082 - val_loss: 2.4620 - val_accuracy: 0.2204\n",
"Epoch 379/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4779 - accuracy: 0.2196 - val_loss: 2.4603 - val_accuracy: 0.2339\n",
"Epoch 380/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4763 - accuracy: 0.2201 - val_loss: 2.4586 - val_accuracy: 0.2411\n",
"Epoch 381/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4746 - accuracy: 0.2301 - val_loss: 2.4569 - val_accuracy: 0.2448\n",
"Epoch 382/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4729 - accuracy: 0.2375 - val_loss: 2.4552 - val_accuracy: 0.2520\n",
"Epoch 383/500\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4712 - accuracy: 0.2410 - val_loss: 2.4535 - val_accuracy: 0.2525\n",
"Epoch 384/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4696 - accuracy: 0.2430 - val_loss: 2.4518 - val_accuracy: 0.2585\n",
"Epoch 385/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4678 - accuracy: 0.2468 - val_loss: 2.4501 - val_accuracy: 0.2587\n",
"Epoch 386/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4661 - accuracy: 0.2497 - val_loss: 2.4484 - val_accuracy: 0.2632\n",
"Epoch 387/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4645 - accuracy: 0.2537 - val_loss: 2.4466 - val_accuracy: 0.2632\n",
"Epoch 388/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4627 - accuracy: 0.2545 - val_loss: 2.4449 - val_accuracy: 0.2666\n",
"Epoch 389/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4610 - accuracy: 0.2599 - val_loss: 2.4431 - val_accuracy: 0.2717\n",
"Epoch 390/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4593 - accuracy: 0.2640 - val_loss: 2.4414 - val_accuracy: 0.2702\n",
"Epoch 391/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4576 - accuracy: 0.2640 - val_loss: 2.4396 - val_accuracy: 0.2732\n",
"Epoch 392/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4559 - accuracy: 0.2652 - val_loss: 2.4379 - val_accuracy: 0.2736\n",
"Epoch 393/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4541 - accuracy: 0.2659 - val_loss: 2.4362 - val_accuracy: 0.2747\n",
"Epoch 394/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4524 - accuracy: 0.2674 - val_loss: 2.4344 - val_accuracy: 0.2771\n",
"Epoch 395/500\n",
"5980/5980 [==============================] - 0s 16us/sample - loss: 2.4506 - accuracy: 0.2701 - val_loss: 2.4327 - val_accuracy: 0.2774\n",
"Epoch 396/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4489 - accuracy: 0.2737 - val_loss: 2.4309 - val_accuracy: 0.2798\n",
"Epoch 397/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4472 - accuracy: 0.2747 - val_loss: 2.4292 - val_accuracy: 0.2831\n",
"Epoch 398/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4455 - accuracy: 0.2766 - val_loss: 2.4274 - val_accuracy: 0.2843\n",
"Epoch 399/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4438 - accuracy: 0.2779 - val_loss: 2.4257 - val_accuracy: 0.2843\n",
"Epoch 400/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4420 - accuracy: 0.2778 - val_loss: 2.4240 - val_accuracy: 0.2801\n",
"Epoch 401/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4404 - accuracy: 0.2764 - val_loss: 2.4222 - val_accuracy: 0.2804\n",
"Epoch 402/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4386 - accuracy: 0.2771 - val_loss: 2.4205 - val_accuracy: 0.2804\n",
"Epoch 403/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.4369 - accuracy: 0.2791 - val_loss: 2.4187 - val_accuracy: 0.2813\n",
"Epoch 404/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4352 - accuracy: 0.2791 - val_loss: 2.4170 - val_accuracy: 0.2791\n",
"Epoch 405/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4336 - accuracy: 0.2768 - val_loss: 2.4153 - val_accuracy: 0.2778\n",
"Epoch 406/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.4318 - accuracy: 0.2768 - val_loss: 2.4135 - val_accuracy: 0.2778\n",
"Epoch 407/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.4301 - accuracy: 0.2769 - val_loss: 2.4118 - val_accuracy: 0.2778\n",
"Epoch 408/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.4284 - accuracy: 0.2764 - val_loss: 2.4101 - val_accuracy: 0.2768\n",
"Epoch 409/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.4267 - accuracy: 0.2758 - val_loss: 2.4083 - val_accuracy: 0.2853\n",
"Epoch 410/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4250 - accuracy: 0.2798 - val_loss: 2.4066 - val_accuracy: 0.2834\n",
"Epoch 411/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4233 - accuracy: 0.2781 - val_loss: 2.4049 - val_accuracy: 0.2834\n",
"Epoch 412/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4216 - accuracy: 0.2786 - val_loss: 2.4032 - val_accuracy: 0.2838\n",
"Epoch 413/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4200 - accuracy: 0.2779 - val_loss: 2.4015 - val_accuracy: 0.2838\n",
"Epoch 414/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4183 - accuracy: 0.2783 - val_loss: 2.3997 - val_accuracy: 0.2836\n",
"Epoch 415/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.4166 - accuracy: 0.2776 - val_loss: 2.3980 - val_accuracy: 0.2836\n",
"Epoch 416/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4149 - accuracy: 0.2763 - val_loss: 2.3963 - val_accuracy: 0.2811\n",
"Epoch 417/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4132 - accuracy: 0.2754 - val_loss: 2.3946 - val_accuracy: 0.2811\n",
"Epoch 418/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4116 - accuracy: 0.2761 - val_loss: 2.3929 - val_accuracy: 0.2868\n",
"Epoch 419/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4099 - accuracy: 0.2788 - val_loss: 2.3912 - val_accuracy: 0.2873\n",
"Epoch 420/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4082 - accuracy: 0.2798 - val_loss: 2.3896 - val_accuracy: 0.2804\n",
"Epoch 421/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4066 - accuracy: 0.2749 - val_loss: 2.3879 - val_accuracy: 0.2799\n",
"Epoch 422/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.4049 - accuracy: 0.2747 - val_loss: 2.3862 - val_accuracy: 0.2799\n",
"Epoch 423/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.4032 - accuracy: 0.2746 - val_loss: 2.3845 - val_accuracy: 0.2799\n",
"Epoch 424/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.4016 - accuracy: 0.2746 - val_loss: 2.3828 - val_accuracy: 0.2788\n",
"Epoch 425/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3999 - accuracy: 0.2741 - val_loss: 2.3811 - val_accuracy: 0.2788\n",
"Epoch 426/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3983 - accuracy: 0.2741 - val_loss: 2.3795 - val_accuracy: 0.2788\n",
"Epoch 427/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3967 - accuracy: 0.2741 - val_loss: 2.3778 - val_accuracy: 0.2788\n",
"Epoch 428/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3951 - accuracy: 0.2741 - val_loss: 2.3761 - val_accuracy: 0.2831\n",
"Epoch 429/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3934 - accuracy: 0.2791 - val_loss: 2.3745 - val_accuracy: 0.2831\n",
"Epoch 430/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3918 - accuracy: 0.2788 - val_loss: 2.3728 - val_accuracy: 0.2811\n",
"Epoch 431/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.3901 - accuracy: 0.2814 - val_loss: 2.3711 - val_accuracy: 0.2888\n",
"Epoch 432/500\n",
"5980/5980 [==============================] - 0s 19us/sample - loss: 2.3885 - accuracy: 0.2846 - val_loss: 2.3695 - val_accuracy: 0.2888\n",
"Epoch 433/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3869 - accuracy: 0.2844 - val_loss: 2.3678 - val_accuracy: 0.2871\n",
"Epoch 434/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.3853 - accuracy: 0.2844 - val_loss: 2.3662 - val_accuracy: 0.2871\n",
"Epoch 435/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3836 - accuracy: 0.2838 - val_loss: 2.3646 - val_accuracy: 0.2871\n",
"Epoch 436/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3820 - accuracy: 0.2838 - val_loss: 2.3629 - val_accuracy: 0.2871\n",
"Epoch 437/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3804 - accuracy: 0.2838 - val_loss: 2.3613 - val_accuracy: 0.2871\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 438/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3788 - accuracy: 0.2860 - val_loss: 2.3597 - val_accuracy: 0.2871\n",
"Epoch 439/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3772 - accuracy: 0.2875 - val_loss: 2.3580 - val_accuracy: 0.2916\n",
"Epoch 440/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3757 - accuracy: 0.2886 - val_loss: 2.3564 - val_accuracy: 0.2928\n",
"Epoch 441/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3740 - accuracy: 0.2888 - val_loss: 2.3548 - val_accuracy: 0.2928\n",
"Epoch 442/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3724 - accuracy: 0.2888 - val_loss: 2.3532 - val_accuracy: 0.2928\n",
"Epoch 443/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3708 - accuracy: 0.2888 - val_loss: 2.3516 - val_accuracy: 0.2928\n",
"Epoch 444/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3693 - accuracy: 0.2891 - val_loss: 2.3500 - val_accuracy: 0.2928\n",
"Epoch 445/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3677 - accuracy: 0.2893 - val_loss: 2.3483 - val_accuracy: 0.2935\n",
"Epoch 446/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3661 - accuracy: 0.2895 - val_loss: 2.3467 - val_accuracy: 0.2935\n",
"Epoch 447/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3645 - accuracy: 0.2913 - val_loss: 2.3451 - val_accuracy: 0.2962\n",
"Epoch 448/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3630 - accuracy: 0.2905 - val_loss: 2.3435 - val_accuracy: 0.2962\n",
"Epoch 449/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3614 - accuracy: 0.2965 - val_loss: 2.3419 - val_accuracy: 0.2962\n",
"Epoch 450/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3598 - accuracy: 0.2920 - val_loss: 2.3404 - val_accuracy: 0.3038\n",
"Epoch 451/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3582 - accuracy: 0.3003 - val_loss: 2.3388 - val_accuracy: 0.3042\n",
"Epoch 452/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3567 - accuracy: 0.3003 - val_loss: 2.3372 - val_accuracy: 0.3042\n",
"Epoch 453/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3551 - accuracy: 0.3030 - val_loss: 2.3356 - val_accuracy: 0.3042\n",
"Epoch 454/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3535 - accuracy: 0.3082 - val_loss: 2.3341 - val_accuracy: 0.3050\n",
"Epoch 455/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3520 - accuracy: 0.3047 - val_loss: 2.3325 - val_accuracy: 0.3227\n",
"Epoch 456/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3505 - accuracy: 0.3159 - val_loss: 2.3309 - val_accuracy: 0.3227\n",
"Epoch 457/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3488 - accuracy: 0.3135 - val_loss: 2.3293 - val_accuracy: 0.3227\n",
"Epoch 458/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3473 - accuracy: 0.3156 - val_loss: 2.3278 - val_accuracy: 0.3216\n",
"Epoch 459/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3458 - accuracy: 0.3177 - val_loss: 2.3262 - val_accuracy: 0.3216\n",
"Epoch 460/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3442 - accuracy: 0.3176 - val_loss: 2.3247 - val_accuracy: 0.3216\n",
"Epoch 461/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3427 - accuracy: 0.3177 - val_loss: 2.3231 - val_accuracy: 0.3216\n",
"Epoch 462/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3412 - accuracy: 0.3177 - val_loss: 2.3215 - val_accuracy: 0.3216\n",
"Epoch 463/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3396 - accuracy: 0.3169 - val_loss: 2.3200 - val_accuracy: 0.3216\n",
"Epoch 464/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3381 - accuracy: 0.3184 - val_loss: 2.3184 - val_accuracy: 0.3216\n",
"Epoch 465/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3365 - accuracy: 0.3176 - val_loss: 2.3168 - val_accuracy: 0.3216\n",
"Epoch 466/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3350 - accuracy: 0.3179 - val_loss: 2.3153 - val_accuracy: 0.3217\n",
"Epoch 467/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3336 - accuracy: 0.3179 - val_loss: 2.3138 - val_accuracy: 0.3201\n",
"Epoch 468/500\n",
"5980/5980 [==============================] - 0s 20us/sample - loss: 2.3319 - accuracy: 0.3164 - val_loss: 2.3122 - val_accuracy: 0.3201\n",
"Epoch 469/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3304 - accuracy: 0.3174 - val_loss: 2.3107 - val_accuracy: 0.3201\n",
"Epoch 470/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3289 - accuracy: 0.3167 - val_loss: 2.3092 - val_accuracy: 0.3201\n",
"Epoch 471/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3274 - accuracy: 0.3166 - val_loss: 2.3077 - val_accuracy: 0.3201\n",
"Epoch 472/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3259 - accuracy: 0.3171 - val_loss: 2.3061 - val_accuracy: 0.3201\n",
"Epoch 473/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3244 - accuracy: 0.3164 - val_loss: 2.3046 - val_accuracy: 0.3201\n",
"Epoch 474/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3228 - accuracy: 0.3167 - val_loss: 2.3030 - val_accuracy: 0.3201\n",
"Epoch 475/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3213 - accuracy: 0.3239 - val_loss: 2.3015 - val_accuracy: 0.3283\n",
"Epoch 476/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3198 - accuracy: 0.3263 - val_loss: 2.3000 - val_accuracy: 0.3283\n",
"Epoch 477/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3183 - accuracy: 0.3269 - val_loss: 2.2985 - val_accuracy: 0.3283\n",
"Epoch 478/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3168 - accuracy: 0.3268 - val_loss: 2.2970 - val_accuracy: 0.3283\n",
"Epoch 479/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3153 - accuracy: 0.3268 - val_loss: 2.2955 - val_accuracy: 0.3283\n",
"Epoch 480/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3138 - accuracy: 0.3268 - val_loss: 2.2940 - val_accuracy: 0.3283\n",
"Epoch 481/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3123 - accuracy: 0.3268 - val_loss: 2.2924 - val_accuracy: 0.3283\n",
"Epoch 482/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3107 - accuracy: 0.3268 - val_loss: 2.2909 - val_accuracy: 0.3283\n",
"Epoch 483/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3092 - accuracy: 0.3268 - val_loss: 2.2894 - val_accuracy: 0.3283\n",
"Epoch 484/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3077 - accuracy: 0.3268 - val_loss: 2.2879 - val_accuracy: 0.3283\n",
"Epoch 485/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3063 - accuracy: 0.3263 - val_loss: 2.2864 - val_accuracy: 0.3283\n",
"Epoch 486/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.3047 - accuracy: 0.3251 - val_loss: 2.2849 - val_accuracy: 0.3273\n",
"Epoch 487/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3034 - accuracy: 0.3261 - val_loss: 2.2835 - val_accuracy: 0.3273\n",
"Epoch 488/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3017 - accuracy: 0.3249 - val_loss: 2.2820 - val_accuracy: 0.3273\n",
"Epoch 489/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.3003 - accuracy: 0.3274 - val_loss: 2.2805 - val_accuracy: 0.3247\n",
"Epoch 490/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.2988 - accuracy: 0.3247 - val_loss: 2.2790 - val_accuracy: 0.3273\n",
"Epoch 491/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.2972 - accuracy: 0.3279 - val_loss: 2.2775 - val_accuracy: 0.3247\n",
"Epoch 492/500\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.2958 - accuracy: 0.3234 - val_loss: 2.2760 - val_accuracy: 0.3247\n",
"Epoch 493/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.2943 - accuracy: 0.3242 - val_loss: 2.2745 - val_accuracy: 0.3247\n",
"Epoch 494/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.2929 - accuracy: 0.3256 - val_loss: 2.2730 - val_accuracy: 0.3329\n",
"Epoch 495/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.2914 - accuracy: 0.3301 - val_loss: 2.2716 - val_accuracy: 0.3329\n",
"Epoch 496/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.2899 - accuracy: 0.3314 - val_loss: 2.2701 - val_accuracy: 0.3329\n",
"Epoch 497/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.2884 - accuracy: 0.3284 - val_loss: 2.2686 - val_accuracy: 0.3329\n",
"Epoch 498/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.2869 - accuracy: 0.3323 - val_loss: 2.2671 - val_accuracy: 0.3334\n",
"Epoch 499/500\n",
"5980/5980 [==============================] - 0s 18us/sample - loss: 2.2854 - accuracy: 0.3326 - val_loss: 2.2657 - val_accuracy: 0.3348\n",
"Epoch 500/500\n",
"5980/5980 [==============================] - 0s 17us/sample - loss: 2.2840 - accuracy: 0.3331 - val_loss: 2.2642 - val_accuracy: 0.3360\n"
]
}
],
"source": [
"history = model.fit(\n",
" x_train, y_train, validation_data=(x_test, y_test), batch_size=1000, epochs=500, verbose=1\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"dict_keys(['loss', 'accuracy', 'val_loss', 'val_accuracy'])\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# list all data in history\n",
"print(history.history.keys())\n",
"# summarize history for accuracy\n",
"plt.plot(history.history['accuracy'])\n",
"plt.plot(history.history['val_accuracy'])\n",
"plt.title('model accuracy')\n",
"plt.ylabel('accuracy')\n",
"plt.xlabel('epoch')\n",
"plt.legend(['train', 'test'], loc='upper left')\n",
"plt.show()\n",
"\n",
"plt.plot(history.history['loss'])\n",
"plt.plot(history.history['val_loss'])\n",
"plt.title('model loss')\n",
"plt.ylabel('loss')\n",
"plt.xlabel('epoch')\n",
"plt.legend(['train', 'test'], loc='upper left')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"id 0, from year 1910 to 1946\n",
"id 1410756, from year 1984 to 1986\n",
"id 2822613, from year 1924 to 1927\n",
"id 4234470, from year 2002 to 2004\n",
"id 5646327, from year 2008 to 2014\n",
"start index for training is 0\n",
"Train on 5980 samples, validate on 5980 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5980/5980 [==============================] - 0s 28us/sample - loss: 2.2682 - accuracy: 0.3351\n",
"5980/5980 [==============================] - 0s 29us/sample - loss: 2.2496 - accuracy: 0.3361\n",
"5980/5980 [==============================] - 0s 29us/sample - loss: 2.2496 - accuracy: 0.3361\n",
"12255/12255 [==============================] - 0s 29us/sample - loss: 2.7235 - accuracy: 0.1850\n",
"14070/14070 [==============================] - 0s 31us/sample - loss: 2.9346 - accuracy: 0.1485\n",
"11565/11565 [==============================] - 0s 29us/sample - loss: 2.9184 - accuracy: 0.1547\n",
"7000/7000 [==============================] - 0s 31us/sample - loss: 2.9625 - accuracy: 0.1636\n",
"start index for training is 1000\n",
"Train on 7625 samples, validate on 7630 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7625/7625 [==============================] - 0s 33us/sample - loss: 2.5056 - accuracy: 0.2400\n",
"7630/7630 [==============================] - 0s 34us/sample - loss: 2.5258 - accuracy: 0.2316\n",
"5980/5980 [==============================] - 0s 31us/sample - loss: 2.2548 - accuracy: 0.3401\n",
"12255/12255 [==============================] - 0s 30us/sample - loss: 2.7051 - accuracy: 0.1840\n",
"14070/14070 [==============================] - 0s 29us/sample - loss: 2.9218 - accuracy: 0.1517\n",
"11565/11565 [==============================] - 0s 29us/sample - loss: 2.8931 - accuracy: 0.1540\n",
"7000/7000 [==============================] - 0s 29us/sample - loss: 2.9336 - accuracy: 0.1647\n",
"start index for training is 2000\n",
"Train on 7795 samples, validate on 7795 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7795/7795 [==============================] - 0s 33us/sample - loss: 2.5943 - accuracy: 0.1932\n",
"7795/7795 [==============================] - 0s 36us/sample - loss: 2.6002 - accuracy: 0.1918\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.2579 - accuracy: 0.3343\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.6894 - accuracy: 0.1854\n",
"14070/14070 [==============================] - 0s 30us/sample - loss: 2.9069 - accuracy: 0.1484\n",
"11565/11565 [==============================] - 0s 30us/sample - loss: 2.8834 - accuracy: 0.1577\n",
"7000/7000 [==============================] - 0s 30us/sample - loss: 2.9230 - accuracy: 0.1709\n",
"start index for training is 3000\n",
"Train on 7560 samples, validate on 7560 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7560/7560 [==============================] - 0s 34us/sample - loss: 2.5722 - accuracy: 0.2090\n",
"7560/7560 [==============================] - 0s 33us/sample - loss: 2.5795 - accuracy: 0.2041\n",
"5980/5980 [==============================] - 0s 32us/sample - loss: 2.2567 - accuracy: 0.3457\n",
"12255/12255 [==============================] - 0s 29us/sample - loss: 2.6681 - accuracy: 0.1927\n",
"14070/14070 [==============================] - 0s 30us/sample - loss: 2.9031 - accuracy: 0.1511\n",
"11565/11565 [==============================] - 0s 30us/sample - loss: 2.8780 - accuracy: 0.1569\n",
"7000/7000 [==============================] - 0s 31us/sample - loss: 2.9163 - accuracy: 0.1616\n",
"start index for training is 4000\n",
"Train on 7555 samples, validate on 7560 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7555/7555 [==============================] - 0s 33us/sample - loss: 2.6017 - accuracy: 0.2029\n",
"7560/7560 [==============================] - 0s 32us/sample - loss: 2.5989 - accuracy: 0.2045\n",
"5980/5980 [==============================] - 0s 31us/sample - loss: 2.2588 - accuracy: 0.3645\n",
"12255/12255 [==============================] - 0s 30us/sample - loss: 2.6383 - accuracy: 0.2037\n",
"14070/14070 [==============================] - 0s 32us/sample - loss: 2.9140 - accuracy: 0.1554\n",
"11565/11565 [==============================] - 0s 30us/sample - loss: 2.8746 - accuracy: 0.1657\n",
"7000/7000 [==============================] - 0s 31us/sample - loss: 2.9107 - accuracy: 0.1777\n",
"start index for training is 5000\n",
"Train on 7385 samples, validate on 7390 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7385/7385 [==============================] - 0s 33us/sample - loss: 2.5839 - accuracy: 0.2041\n",
"7390/7390 [==============================] - 0s 31us/sample - loss: 2.5765 - accuracy: 0.2084\n",
"5980/5980 [==============================] - 0s 30us/sample - loss: 2.2632 - accuracy: 0.3647\n",
"12255/12255 [==============================] - 0s 29us/sample - loss: 2.6111 - accuracy: 0.2051\n",
"14070/14070 [==============================] - 0s 34us/sample - loss: 2.9242 - accuracy: 0.1598\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.8740 - accuracy: 0.1746\n",
"7000/7000 [==============================] - 0s 33us/sample - loss: 2.9090 - accuracy: 0.1901\n",
"start index for training is 6000\n",
"Train on 7835 samples, validate on 7840 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7835/7835 [==============================] - 0s 34us/sample - loss: 2.5694 - accuracy: 0.2063\n",
"7840/7840 [==============================] - 0s 43us/sample - loss: 2.5834 - accuracy: 0.2037\n",
"5980/5980 [==============================] - 0s 31us/sample - loss: 2.2681 - accuracy: 0.3508\n",
"12255/12255 [==============================] - 0s 29us/sample - loss: 2.5864 - accuracy: 0.2022\n",
"14070/14070 [==============================] - 0s 31us/sample - loss: 2.9319 - accuracy: 0.1451\n",
"11565/11565 [==============================] - 0s 30us/sample - loss: 2.8734 - accuracy: 0.1684\n",
"7000/7000 [==============================] - 0s 31us/sample - loss: 2.9062 - accuracy: 0.1779\n",
"start index for training is 7000\n",
"Train on 7810 samples, validate on 7810 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7810/7810 [==============================] - 0s 34us/sample - loss: 2.5561 - accuracy: 0.2095\n",
"7810/7810 [==============================] - 0s 40us/sample - loss: 2.5736 - accuracy: 0.2087\n",
"5980/5980 [==============================] - 0s 33us/sample - loss: 2.2730 - accuracy: 0.3624\n",
"12255/12255 [==============================] - 0s 31us/sample - loss: 2.5693 - accuracy: 0.2078\n",
"14070/14070 [==============================] - 0s 31us/sample - loss: 2.9309 - accuracy: 0.1541\n",
"11565/11565 [==============================] - 0s 31us/sample - loss: 2.8672 - accuracy: 0.1717\n",
"7000/7000 [==============================] - 0s 30us/sample - loss: 2.8964 - accuracy: 0.1816\n",
"start index for training is 8000\n",
"Train on 8035 samples, validate on 8035 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8035/8035 [==============================] - 0s 34us/sample - loss: 2.5569 - accuracy: 0.2171\n",
"8035/8035 [==============================] - 0s 32us/sample - loss: 2.5331 - accuracy: 0.2148\n",
"5980/5980 [==============================] - 0s 30us/sample - loss: 2.2765 - accuracy: 0.3590\n",
"12255/12255 [==============================] - 0s 31us/sample - loss: 2.5554 - accuracy: 0.2114\n",
"14070/14070 [==============================] - 0s 31us/sample - loss: 2.9245 - accuracy: 0.1407\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.8613 - accuracy: 0.1692\n",
"7000/7000 [==============================] - 0s 33us/sample - loss: 2.8853 - accuracy: 0.1751\n",
"start index for training is 9000\n",
"Train on 7590 samples, validate on 7590 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7590/7590 [==============================] - 0s 34us/sample - loss: 2.5436 - accuracy: 0.2360\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"7590/7590 [==============================] - 0s 33us/sample - loss: 2.5713 - accuracy: 0.2219\n",
"5980/5980 [==============================] - 0s 32us/sample - loss: 2.2784 - accuracy: 0.3431\n",
"12255/12255 [==============================] - 0s 31us/sample - loss: 2.5493 - accuracy: 0.2162\n",
"14070/14070 [==============================] - 0s 31us/sample - loss: 2.9280 - accuracy: 0.1416\n",
"11565/11565 [==============================] - 0s 30us/sample - loss: 2.8588 - accuracy: 0.1709\n",
"7000/7000 [==============================] - ETA: 0s - loss: 2.8748 - accuracy: 0.18 - 0s 30us/sample - loss: 2.8777 - accuracy: 0.1787\n",
"start index for training is 10000\n",
"Train on 7105 samples, validate on 7110 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7105/7105 [==============================] - 0s 34us/sample - loss: 2.5685 - accuracy: 0.2227\n",
"7110/7110 [==============================] - 0s 31us/sample - loss: 2.5702 - accuracy: 0.2232\n",
"5980/5980 [==============================] - 0s 31us/sample - loss: 2.2775 - accuracy: 0.3284\n",
"12255/12255 [==============================] - 0s 30us/sample - loss: 2.5454 - accuracy: 0.2136\n",
"14070/14070 [==============================] - 0s 30us/sample - loss: 2.9149 - accuracy: 0.1368\n",
"11565/11565 [==============================] - 0s 30us/sample - loss: 2.8407 - accuracy: 0.1680\n",
"7000/7000 [==============================] - 0s 31us/sample - loss: 2.8602 - accuracy: 0.1764\n",
"start index for training is 11000\n",
"Train on 6730 samples, validate on 6735 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6730/6730 [==============================] - 0s 34us/sample - loss: 2.5793 - accuracy: 0.2282\n",
"6735/6735 [==============================] - 0s 33us/sample - loss: 2.5639 - accuracy: 0.2270\n",
"5980/5980 [==============================] - 0s 31us/sample - loss: 2.2805 - accuracy: 0.3386\n",
"12255/12255 [==============================] - 0s 30us/sample - loss: 2.5511 - accuracy: 0.2099\n",
"14070/14070 [==============================] - 0s 31us/sample - loss: 2.9021 - accuracy: 0.1406\n",
"11565/11565 [==============================] - 0s 30us/sample - loss: 2.8327 - accuracy: 0.1650\n",
"7000/7000 [==============================] - 0s 31us/sample - loss: 2.8505 - accuracy: 0.1743\n",
"start index for training is 12000\n",
"Train on 6865 samples, validate on 6870 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6865/6865 [==============================] - 0s 34us/sample - loss: 2.5938 - accuracy: 0.2320\n",
"6870/6870 [==============================] - 0s 34us/sample - loss: 2.5761 - accuracy: 0.2360\n",
"5980/5980 [==============================] - 0s 32us/sample - loss: 2.2991 - accuracy: 0.3438\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.5715 - accuracy: 0.2168\n",
"14070/14070 [==============================] - 0s 31us/sample - loss: 2.8896 - accuracy: 0.1432\n",
"11565/11565 [==============================] - 0s 31us/sample - loss: 2.8360 - accuracy: 0.1663\n",
"7000/7000 [==============================] - 0s 30us/sample - loss: 2.8506 - accuracy: 0.1821\n",
"start index for training is 13000\n",
"Train on 6505 samples, validate on 6505 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6505/6505 [==============================] - 0s 34us/sample - loss: 2.6344 - accuracy: 0.2220\n",
"6505/6505 [==============================] - 0s 36us/sample - loss: 2.6470 - accuracy: 0.2232\n",
"5980/5980 [==============================] - 0s 32us/sample - loss: 2.2761 - accuracy: 0.3554\n",
"12255/12255 [==============================] - 0s 31us/sample - loss: 2.5724 - accuracy: 0.2188\n",
"14070/14070 [==============================] - 0s 31us/sample - loss: 2.8236 - accuracy: 0.1598\n",
"11565/11565 [==============================] - 0s 32us/sample - loss: 2.8061 - accuracy: 0.1748\n",
"7000/7000 [==============================] - 0s 33us/sample - loss: 2.8268 - accuracy: 0.1923\n",
"start index for training is 14000\n",
"Train on 6815 samples, validate on 6815 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6815/6815 [==============================] - 0s 36us/sample - loss: 2.6898 - accuracy: 0.1834\n",
"6815/6815 [==============================] - 0s 34us/sample - loss: 2.6748 - accuracy: 0.1865\n",
"5980/5980 [==============================] - 0s 32us/sample - loss: 2.2986 - accuracy: 0.3254\n",
"12255/12255 [==============================] - 0s 32us/sample - loss: 2.6205 - accuracy: 0.1964\n",
"14070/14070 [==============================] - 0s 32us/sample - loss: 2.7559 - accuracy: 0.1692\n",
"11565/11565 [==============================] - 0s 33us/sample - loss: 2.7948 - accuracy: 0.1756\n",
"7000/7000 [==============================] - 0s 33us/sample - loss: 2.8197 - accuracy: 0.1850\n",
"start index for training is 15000\n",
"Train on 8880 samples, validate on 8880 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8880/8880 [==============================] - 0s 35us/sample - loss: 2.6885 - accuracy: 0.1720\n",
"8880/8880 [==============================] - 0s 32us/sample - loss: 2.6849 - accuracy: 0.1724\n",
"5980/5980 [==============================] - 0s 33us/sample - loss: 2.2920 - accuracy: 0.3341\n",
"12255/12255 [==============================] - 0s 32us/sample - loss: 2.6098 - accuracy: 0.2017\n",
"14070/14070 [==============================] - 0s 32us/sample - loss: 2.7294 - accuracy: 0.1689\n",
"11565/11565 [==============================] - 0s 32us/sample - loss: 2.7788 - accuracy: 0.1734\n",
"7000/7000 [==============================] - 0s 31us/sample - loss: 2.8068 - accuracy: 0.1823\n",
"start index for training is 16000\n",
"Train on 8955 samples, validate on 8955 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8955/8955 [==============================] - 0s 35us/sample - loss: 2.6822 - accuracy: 0.1755\n",
"8955/8955 [==============================] - 0s 33us/sample - loss: 2.6645 - accuracy: 0.1764\n",
"5980/5980 [==============================] - 0s 32us/sample - loss: 2.3080 - accuracy: 0.3395\n",
"12255/12255 [==============================] - 0s 32us/sample - loss: 2.6090 - accuracy: 0.2034\n",
"14070/14070 [==============================] - 0s 31us/sample - loss: 2.7139 - accuracy: 0.1709\n",
"11565/11565 [==============================] - 0s 32us/sample - loss: 2.7688 - accuracy: 0.1862\n",
"7000/7000 [==============================] - 0s 33us/sample - loss: 2.7978 - accuracy: 0.1919\n",
"start index for training is 17000\n",
"Train on 8505 samples, validate on 8510 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8505/8505 [==============================] - 0s 35us/sample - loss: 2.6486 - accuracy: 0.1835\n",
"8510/8510 [==============================] - 0s 33us/sample - loss: 2.6350 - accuracy: 0.1851\n",
"5980/5980 [==============================] - 0s 32us/sample - loss: 2.3078 - accuracy: 0.3431\n",
"12255/12255 [==============================] - 0s 32us/sample - loss: 2.5918 - accuracy: 0.2051\n",
"14070/14070 [==============================] - 0s 32us/sample - loss: 2.7078 - accuracy: 0.1832\n",
"11565/11565 [==============================] - 0s 32us/sample - loss: 2.7533 - accuracy: 0.1843\n",
"7000/7000 [==============================] - 0s 33us/sample - loss: 2.7832 - accuracy: 0.1886\n",
"start index for training is 18000\n",
"Train on 8855 samples, validate on 8860 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8855/8855 [==============================] - 0s 35us/sample - loss: 2.6262 - accuracy: 0.2261\n",
"8860/8860 [==============================] - 0s 32us/sample - loss: 2.6283 - accuracy: 0.2169\n",
"5980/5980 [==============================] - 0s 33us/sample - loss: 2.3186 - accuracy: 0.3333\n",
"12255/12255 [==============================] - 0s 32us/sample - loss: 2.5686 - accuracy: 0.2059\n",
"14070/14070 [==============================] - 0s 33us/sample - loss: 2.7128 - accuracy: 0.2055\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11565/11565 [==============================] - 0s 31us/sample - loss: 2.7291 - accuracy: 0.2044\n",
"7000/7000 [==============================] - 0s 31us/sample - loss: 2.7554 - accuracy: 0.2121\n",
"start index for training is 19000\n",
"Train on 9545 samples, validate on 9545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9545/9545 [==============================] - 0s 36us/sample - loss: 2.6128 - accuracy: 0.2264\n",
"9545/9545 [==============================] - 0s 34us/sample - loss: 2.6184 - accuracy: 0.2213\n",
"5980/5980 [==============================] - 0s 31us/sample - loss: 2.3192 - accuracy: 0.3274\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.5588 - accuracy: 0.2037\n",
"14070/14070 [==============================] - 0s 31us/sample - loss: 2.7077 - accuracy: 0.2062\n",
"11565/11565 [==============================] - 0s 33us/sample - loss: 2.7123 - accuracy: 0.2072\n",
"7000/7000 [==============================] - 0s 35us/sample - loss: 2.7360 - accuracy: 0.2137\n",
"start index for training is 20000\n",
"Train on 9625 samples, validate on 9630 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9625/9625 [==============================] - 0s 35us/sample - loss: 2.6254 - accuracy: 0.2189\n",
"9630/9630 [==============================] - 0s 34us/sample - loss: 2.6249 - accuracy: 0.2223\n",
"5980/5980 [==============================] - 0s 33us/sample - loss: 2.3124 - accuracy: 0.3104\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.5469 - accuracy: 0.2046\n",
"14070/14070 [==============================] - 0s 32us/sample - loss: 2.6971 - accuracy: 0.1955\n",
"11565/11565 [==============================] - 0s 32us/sample - loss: 2.6928 - accuracy: 0.2104\n",
"7000/7000 [==============================] - 0s 33us/sample - loss: 2.7131 - accuracy: 0.2160\n",
"start index for training is 21000\n",
"Train on 9205 samples, validate on 9210 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9205/9205 [==============================] - 0s 36us/sample - loss: 2.6132 - accuracy: 0.2280\n",
"9210/9210 [==============================] - 0s 34us/sample - loss: 2.6147 - accuracy: 0.2229\n",
"5980/5980 [==============================] - 0s 33us/sample - loss: 2.3100 - accuracy: 0.3236\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.5424 - accuracy: 0.2110\n",
"14070/14070 [==============================] - 0s 34us/sample - loss: 2.6890 - accuracy: 0.2000\n",
"11565/11565 [==============================] - 0s 32us/sample - loss: 2.6750 - accuracy: 0.2179\n",
"7000/7000 [==============================] - 0s 32us/sample - loss: 2.6892 - accuracy: 0.2251\n",
"start index for training is 22000\n",
"Train on 8490 samples, validate on 8490 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8490/8490 [==============================] - 0s 35us/sample - loss: 2.6143 - accuracy: 0.2214\n",
"8490/8490 [==============================] - 0s 34us/sample - loss: 2.6103 - accuracy: 0.2240\n",
"5980/5980 [==============================] - 0s 33us/sample - loss: 2.3162 - accuracy: 0.3343\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 2.5317 - accuracy: 0.2098\n",
"14070/14070 [==============================] - 0s 33us/sample - loss: 2.6958 - accuracy: 0.1922\n",
"11565/11565 [==============================] - 0s 33us/sample - loss: 2.6556 - accuracy: 0.2225\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6656 - accuracy: 0.2331\n",
"start index for training is 23000\n",
"Train on 8305 samples, validate on 8310 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8305/8305 [==============================] - 0s 36us/sample - loss: 2.5899 - accuracy: 0.2450\n",
"8310/8310 [==============================] - 0s 34us/sample - loss: 2.5956 - accuracy: 0.2378\n",
"5980/5980 [==============================] - 0s 33us/sample - loss: 2.3232 - accuracy: 0.3256\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.5243 - accuracy: 0.2104\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.6995 - accuracy: 0.1901\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.6400 - accuracy: 0.2318\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.6433 - accuracy: 0.2469\n",
"start index for training is 24000\n",
"Train on 8180 samples, validate on 8180 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8180/8180 [==============================] - 0s 35us/sample - loss: 2.5813 - accuracy: 0.2434\n",
"8180/8180 [==============================] - 0s 34us/sample - loss: 2.5955 - accuracy: 0.2335\n",
"5980/5980 [==============================] - 0s 34us/sample - loss: 2.3352 - accuracy: 0.3356\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.5263 - accuracy: 0.2268\n",
"14070/14070 [==============================] - 0s 33us/sample - loss: 2.7016 - accuracy: 0.1802\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.6263 - accuracy: 0.2287\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.6221 - accuracy: 0.2380\n",
"start index for training is 25000\n",
"Train on 7820 samples, validate on 7820 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7820/7820 [==============================] - 0s 38us/sample - loss: 2.5977 - accuracy: 0.2304\n",
"7820/7820 [==============================] - 0s 35us/sample - loss: 2.5850 - accuracy: 0.2332\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.3329 - accuracy: 0.3381\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.5243 - accuracy: 0.2265\n",
"14070/14070 [==============================] - 0s 32us/sample - loss: 2.6954 - accuracy: 0.1845\n",
"11565/11565 [==============================] - 0s 33us/sample - loss: 2.6150 - accuracy: 0.2276\n",
"7000/7000 [==============================] - 0s 33us/sample - loss: 2.6047 - accuracy: 0.2356\n",
"start index for training is 26000\n",
"Train on 8735 samples, validate on 8735 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8735/8735 [==============================] - 0s 36us/sample - loss: 2.5631 - accuracy: 0.2213\n",
"8735/8735 [==============================] - 0s 35us/sample - loss: 2.5823 - accuracy: 0.2182\n",
"5980/5980 [==============================] - 0s 33us/sample - loss: 2.2906 - accuracy: 0.3288\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.5166 - accuracy: 0.2364\n",
"14070/14070 [==============================] - 0s 34us/sample - loss: 2.6621 - accuracy: 0.1882\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.6310 - accuracy: 0.2170\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.6281 - accuracy: 0.2240\n",
"start index for training is 27000\n",
"Train on 12550 samples, validate on 12550 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12550/12550 [==============================] - 0s 37us/sample - loss: 2.4217 - accuracy: 0.2487\n",
"12550/12550 [==============================] - 0s 35us/sample - loss: 2.4328 - accuracy: 0.2471\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.2558 - accuracy: 0.3326\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 2.5314 - accuracy: 0.2233\n",
"14070/14070 [==============================] - 0s 33us/sample - loss: 2.6640 - accuracy: 0.1906\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.6844 - accuracy: 0.1994\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.6967 - accuracy: 0.2194\n",
"start index for training is 28000\n",
"Train on 12205 samples, validate on 12205 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12205/12205 [==============================] - 0s 37us/sample - loss: 2.4168 - accuracy: 0.2544\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12205/12205 [==============================] - 0s 35us/sample - loss: 2.4269 - accuracy: 0.2498\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.2399 - accuracy: 0.3268\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 2.5443 - accuracy: 0.2169\n",
"14070/14070 [==============================] - 0s 33us/sample - loss: 2.6567 - accuracy: 0.1883\n",
"11565/11565 [==============================] - 0s 33us/sample - loss: 2.6997 - accuracy: 0.1852\n",
"7000/7000 [==============================] - 0s 33us/sample - loss: 2.7182 - accuracy: 0.1996\n",
"start index for training is 29000\n",
"Train on 12580 samples, validate on 12580 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12580/12580 [==============================] - 0s 37us/sample - loss: 2.3901 - accuracy: 0.2673\n",
"12580/12580 [==============================] - 0s 36us/sample - loss: 2.4126 - accuracy: 0.2624\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2213 - accuracy: 0.3251\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.5449 - accuracy: 0.2243\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.6509 - accuracy: 0.1942\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.7063 - accuracy: 0.1890\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.7262 - accuracy: 0.2071\n",
"start index for training is 30000\n",
"Train on 12380 samples, validate on 12380 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12380/12380 [==============================] - 0s 37us/sample - loss: 2.3969 - accuracy: 0.2658\n",
"12380/12380 [==============================] - 0s 35us/sample - loss: 2.3981 - accuracy: 0.2737\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 2.2083 - accuracy: 0.3522\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.5488 - accuracy: 0.2312\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.6522 - accuracy: 0.1896\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.7160 - accuracy: 0.1904\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.7357 - accuracy: 0.1956\n",
"start index for training is 31000\n",
"Train on 11685 samples, validate on 11690 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11685/11685 [==============================] - 0s 41us/sample - loss: 2.4121 - accuracy: 0.2679\n",
"11690/11690 [==============================] - 0s 43us/sample - loss: 2.4139 - accuracy: 0.2621\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1966 - accuracy: 0.3801\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.5411 - accuracy: 0.2369\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.6359 - accuracy: 0.2019\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.7039 - accuracy: 0.1959\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.7218 - accuracy: 0.2041\n",
"start index for training is 32000\n",
"Train on 13870 samples, validate on 13870 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13870/13870 [==============================] - 1s 37us/sample - loss: 2.3670 - accuracy: 0.2854\n",
"13870/13870 [==============================] - 0s 36us/sample - loss: 2.3701 - accuracy: 0.2929\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 2.1724 - accuracy: 0.3826\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.5362 - accuracy: 0.2297\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.6297 - accuracy: 0.2030\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.7088 - accuracy: 0.1859\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.7275 - accuracy: 0.1949\n",
"start index for training is 33000\n",
"Train on 12110 samples, validate on 12115 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12110/12110 [==============================] - 0s 38us/sample - loss: 2.3472 - accuracy: 0.2888\n",
"12115/12115 [==============================] - 0s 36us/sample - loss: 2.3508 - accuracy: 0.2965\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.1587 - accuracy: 0.3791\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.5378 - accuracy: 0.2360\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.6331 - accuracy: 0.2075\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.7207 - accuracy: 0.1860\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.7390 - accuracy: 0.1943\n",
"start index for training is 34000\n",
"Train on 12625 samples, validate on 12625 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12625/12625 [==============================] - 0s 38us/sample - loss: 2.3726 - accuracy: 0.2832\n",
"12625/12625 [==============================] - 0s 36us/sample - loss: 2.3770 - accuracy: 0.2822\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.1504 - accuracy: 0.3880\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.5372 - accuracy: 0.2406\n",
"14070/14070 [==============================] - 0s 36us/sample - loss: 2.6158 - accuracy: 0.2090\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.7073 - accuracy: 0.1933\n",
"7000/7000 [==============================] - 0s 35us/sample - loss: 2.7249 - accuracy: 0.2026\n",
"start index for training is 35000\n",
"Train on 14105 samples, validate on 14105 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14105/14105 [==============================] - 1s 38us/sample - loss: 2.3314 - accuracy: 0.3109\n",
"14105/14105 [==============================] - 1s 35us/sample - loss: 2.3377 - accuracy: 0.3032\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 2.1307 - accuracy: 0.3985\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 2.5237 - accuracy: 0.2499\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.6152 - accuracy: 0.2083\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.7057 - accuracy: 0.1927\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.7212 - accuracy: 0.1996\n",
"start index for training is 36000\n",
"Train on 11775 samples, validate on 11780 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11775/11775 [==============================] - 0s 37us/sample - loss: 2.3164 - accuracy: 0.3079\n",
"11780/11780 [==============================] - 0s 37us/sample - loss: 2.3290 - accuracy: 0.2979\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.1134 - accuracy: 0.4028\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.5209 - accuracy: 0.2405\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.6068 - accuracy: 0.2076\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.7028 - accuracy: 0.1805\n",
"7000/7000 [==============================] - 0s 66us/sample - loss: 2.7170 - accuracy: 0.1924\n",
"start index for training is 37000\n",
"Train on 12475 samples, validate on 12475 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12475/12475 [==============================] - 1s 47us/sample - loss: 2.3487 - accuracy: 0.2805\n",
"12475/12475 [==============================] - 1s 55us/sample - loss: 2.3351 - accuracy: 0.2959\n",
"5980/5980 [==============================] - 0s 64us/sample - loss: 2.1172 - accuracy: 0.3915\n",
"12255/12255 [==============================] - 1s 65us/sample - loss: 2.5342 - accuracy: 0.2410\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.5965 - accuracy: 0.2127\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11565/11565 [==============================] - 1s 55us/sample - loss: 2.7079 - accuracy: 0.1891\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.7231 - accuracy: 0.1987\n",
"start index for training is 38000\n",
"Train on 13880 samples, validate on 13880 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13880/13880 [==============================] - 1s 40us/sample - loss: 2.3139 - accuracy: 0.3074\n",
"13880/13880 [==============================] - 1s 37us/sample - loss: 2.3001 - accuracy: 0.3065\n",
"5980/5980 [==============================] - 0s 62us/sample - loss: 2.0965 - accuracy: 0.3960\n",
"12255/12255 [==============================] - 1s 52us/sample - loss: 2.5202 - accuracy: 0.2389\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.5897 - accuracy: 0.2063\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.7010 - accuracy: 0.1819\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.7150 - accuracy: 0.1936\n",
"start index for training is 39000\n",
"Train on 13505 samples, validate on 13505 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13505/13505 [==============================] - 1s 47us/sample - loss: 2.2986 - accuracy: 0.3037\n",
"13505/13505 [==============================] - 1s 42us/sample - loss: 2.2963 - accuracy: 0.3140\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0815 - accuracy: 0.4085\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.5175 - accuracy: 0.2384\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.5848 - accuracy: 0.2089\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.7018 - accuracy: 0.1851\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.7150 - accuracy: 0.1980\n",
"start index for training is 40000\n",
"Train on 13445 samples, validate on 13445 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13445/13445 [==============================] - 1s 40us/sample - loss: 2.2943 - accuracy: 0.3124\n",
"13445/13445 [==============================] - 1s 42us/sample - loss: 2.2928 - accuracy: 0.3170\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.0591 - accuracy: 0.4216\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.5073 - accuracy: 0.2386\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.5859 - accuracy: 0.2104\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.7008 - accuracy: 0.1880\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.7145 - accuracy: 0.2036\n",
"start index for training is 41000\n",
"Train on 13260 samples, validate on 13265 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13260/13260 [==============================] - 1s 43us/sample - loss: 2.2686 - accuracy: 0.3193\n",
"13265/13265 [==============================] - 0s 38us/sample - loss: 2.2908 - accuracy: 0.3094\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 2.0414 - accuracy: 0.4263\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.4983 - accuracy: 0.2378\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.5859 - accuracy: 0.2072\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.6993 - accuracy: 0.1833\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.7125 - accuracy: 0.1971\n",
"start index for training is 42000\n",
"Train on 12825 samples, validate on 12830 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12825/12825 [==============================] - 1s 57us/sample - loss: 2.2854 - accuracy: 0.3137\n",
"12830/12830 [==============================] - 1s 46us/sample - loss: 2.2937 - accuracy: 0.3099\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0311 - accuracy: 0.4254\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.4959 - accuracy: 0.2377\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.5779 - accuracy: 0.2096\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.6938 - accuracy: 0.1869\n",
"7000/7000 [==============================] - 0s 35us/sample - loss: 2.7071 - accuracy: 0.2013\n",
"start index for training is 43000\n",
"Train on 11690 samples, validate on 11695 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11690/11690 [==============================] - 0s 39us/sample - loss: 2.2985 - accuracy: 0.3068\n",
"11695/11695 [==============================] - 0s 38us/sample - loss: 2.3129 - accuracy: 0.2875\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 2.0219 - accuracy: 0.4301\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 2.4938 - accuracy: 0.2365\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.5694 - accuracy: 0.2116\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.6882 - accuracy: 0.1834\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.7009 - accuracy: 0.1983\n",
"start index for training is 44000\n",
"Train on 14545 samples, validate on 14550 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14545/14545 [==============================] - 1s 37us/sample - loss: 2.2600 - accuracy: 0.3062\n",
"14550/14550 [==============================] - 1s 36us/sample - loss: 2.2899 - accuracy: 0.2903\n",
"5980/5980 [==============================] - 0s 34us/sample - loss: 2.0099 - accuracy: 0.4226\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 2.4825 - accuracy: 0.2321\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.5663 - accuracy: 0.2060\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.6803 - accuracy: 0.1807\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6926 - accuracy: 0.1914\n",
"start index for training is 45000\n",
"Train on 14110 samples, validate on 14110 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14110/14110 [==============================] - 1s 42us/sample - loss: 2.2391 - accuracy: 0.3228\n",
"14110/14110 [==============================] - 1s 51us/sample - loss: 2.2604 - accuracy: 0.3104\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.9916 - accuracy: 0.4512\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.4756 - accuracy: 0.2377\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.5716 - accuracy: 0.2069\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.6787 - accuracy: 0.1883\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.6899 - accuracy: 0.2020\n",
"start index for training is 46000\n",
"Train on 14945 samples, validate on 14945 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14945/14945 [==============================] - 1s 42us/sample - loss: 2.2410 - accuracy: 0.3111\n",
"14945/14945 [==============================] - 1s 37us/sample - loss: 2.2582 - accuracy: 0.2974\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.9742 - accuracy: 0.4552\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.4615 - accuracy: 0.2325\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.5695 - accuracy: 0.2082\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.6713 - accuracy: 0.1873\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.6800 - accuracy: 0.2000\n",
"start index for training is 47000\n",
"Train on 12550 samples, validate on 12555 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12550/12550 [==============================] - 0s 39us/sample - loss: 2.2555 - accuracy: 0.3024\n",
"12555/12555 [==============================] - 1s 40us/sample - loss: 2.2518 - accuracy: 0.3010\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 1.9706 - accuracy: 0.4537\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.4646 - accuracy: 0.2265\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.5676 - accuracy: 0.2109\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.6727 - accuracy: 0.1863\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.6834 - accuracy: 0.1980\n",
"start index for training is 48000\n",
"Train on 13880 samples, validate on 13885 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13880/13880 [==============================] - 1s 42us/sample - loss: 2.2835 - accuracy: 0.3010\n",
"13885/13885 [==============================] - 1s 37us/sample - loss: 2.2776 - accuracy: 0.2976\n",
"5980/5980 [==============================] - ETA: 0s - loss: 1.9706 - accuracy: 0.42 - 0s 33us/sample - loss: 1.9645 - accuracy: 0.4244\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.4527 - accuracy: 0.2324\n",
"14070/14070 [==============================] - 0s 34us/sample - loss: 2.5605 - accuracy: 0.2245\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.6695 - accuracy: 0.2040\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.6822 - accuracy: 0.2197\n",
"start index for training is 49000\n",
"Train on 14790 samples, validate on 14795 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14790/14790 [==============================] - 1s 40us/sample - loss: 2.2249 - accuracy: 0.3174\n",
"14795/14795 [==============================] - 1s 36us/sample - loss: 2.2455 - accuracy: 0.3059\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 1.9509 - accuracy: 0.4809\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.4394 - accuracy: 0.2271\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.5659 - accuracy: 0.2145\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.6588 - accuracy: 0.1849\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.6695 - accuracy: 0.1977\n",
"start index for training is 50000\n",
"Train on 13185 samples, validate on 13185 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13185/13185 [==============================] - 1s 47us/sample - loss: 2.2406 - accuracy: 0.3012\n",
"13185/13185 [==============================] - 1s 43us/sample - loss: 2.2405 - accuracy: 0.3048\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.9482 - accuracy: 0.4816\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.4424 - accuracy: 0.2273\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.5665 - accuracy: 0.2173\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.6615 - accuracy: 0.1901\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.6722 - accuracy: 0.2053\n",
"start index for training is 51000\n",
"Train on 13135 samples, validate on 13140 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13135/13135 [==============================] - 1s 62us/sample - loss: 2.2662 - accuracy: 0.2901\n",
"13140/13140 [==============================] - 1s 53us/sample - loss: 2.2702 - accuracy: 0.2926\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9417 - accuracy: 0.4378\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.4261 - accuracy: 0.2310\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.5614 - accuracy: 0.2268\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.6596 - accuracy: 0.2086\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.6715 - accuracy: 0.2307\n",
"start index for training is 52000\n",
"Train on 13840 samples, validate on 13840 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13840/13840 [==============================] - 1s 49us/sample - loss: 2.2329 - accuracy: 0.2944\n",
"13840/13840 [==============================] - 1s 47us/sample - loss: 2.2349 - accuracy: 0.2910\n",
"5980/5980 [==============================] - 0s 75us/sample - loss: 1.9409 - accuracy: 0.4841\n",
"12255/12255 [==============================] - 1s 73us/sample - loss: 2.4167 - accuracy: 0.2344\n",
"14070/14070 [==============================] - 1s 73us/sample - loss: 2.5723 - accuracy: 0.2105\n",
"11565/11565 [==============================] - 1s 52us/sample - loss: 2.6567 - accuracy: 0.1901\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.6689 - accuracy: 0.2020\n",
"start index for training is 53000\n",
"Train on 12220 samples, validate on 12225 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12220/12220 [==============================] - 1s 73us/sample - loss: 2.2590 - accuracy: 0.2942\n",
"12225/12225 [==============================] - 1s 81us/sample - loss: 2.2816 - accuracy: 0.2756\n",
"5980/5980 [==============================] - 0s 56us/sample - loss: 1.9332 - accuracy: 0.4926\n",
"12255/12255 [==============================] - 1s 53us/sample - loss: 2.4019 - accuracy: 0.2442\n",
"14070/14070 [==============================] - 1s 51us/sample - loss: 2.5684 - accuracy: 0.2123\n",
"11565/11565 [==============================] - 1s 55us/sample - loss: 2.6499 - accuracy: 0.1957\n",
"7000/7000 [==============================] - 1s 90us/sample - loss: 2.6621 - accuracy: 0.2109\n",
"start index for training is 54000\n",
"Train on 13540 samples, validate on 13545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13540/13540 [==============================] - 1s 48us/sample - loss: 2.2254 - accuracy: 0.3016\n",
"13545/13545 [==============================] - 1s 44us/sample - loss: 2.2412 - accuracy: 0.3034\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.9301 - accuracy: 0.4928\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.3926 - accuracy: 0.2450\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.5766 - accuracy: 0.2090\n",
"11565/11565 [==============================] - 1s 54us/sample - loss: 2.6512 - accuracy: 0.1991\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.6630 - accuracy: 0.2069\n",
"start index for training is 55000\n",
"Train on 12195 samples, validate on 12200 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12195/12195 [==============================] - 1s 60us/sample - loss: 2.2619 - accuracy: 0.2848\n",
"12200/12200 [==============================] - 1s 56us/sample - loss: 2.2726 - accuracy: 0.2807\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 1.9236 - accuracy: 0.5002\n",
"12255/12255 [==============================] - 1s 53us/sample - loss: 2.3801 - accuracy: 0.2392\n",
"14070/14070 [==============================] - 1s 55us/sample - loss: 2.5649 - accuracy: 0.2153\n",
"11565/11565 [==============================] - 1s 51us/sample - loss: 2.6494 - accuracy: 0.1984\n",
"7000/7000 [==============================] - 0s 57us/sample - loss: 2.6638 - accuracy: 0.2090\n",
"start index for training is 56000\n",
"Train on 12200 samples, validate on 12205 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12200/12200 [==============================] - 1s 53us/sample - loss: 2.2423 - accuracy: 0.2928\n",
"12205/12205 [==============================] - 1s 54us/sample - loss: 2.2316 - accuracy: 0.2964\n",
"5980/5980 [==============================] - 0s 51us/sample - loss: 1.9298 - accuracy: 0.4943\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.3751 - accuracy: 0.2462\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.5806 - accuracy: 0.1986\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.6511 - accuracy: 0.1988\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.6668 - accuracy: 0.2070\n",
"start index for training is 57000\n",
"Train on 12910 samples, validate on 12910 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12910/12910 [==============================] - 1s 42us/sample - loss: 2.2543 - accuracy: 0.2768\n",
"12910/12910 [==============================] - 0s 39us/sample - loss: 2.2564 - accuracy: 0.2771\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9266 - accuracy: 0.4774\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.3519 - accuracy: 0.2444s - loss: 2.3589 - ac\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.5750 - accuracy: 0.1993\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.6409 - accuracy: 0.1980\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.6547 - accuracy: 0.2077\n",
"start index for training is 58000\n",
"Train on 10395 samples, validate on 10400 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10395/10395 [==============================] - 0s 43us/sample - loss: 2.2593 - accuracy: 0.2856\n",
"10400/10400 [==============================] - 0s 43us/sample - loss: 2.2600 - accuracy: 0.2763\n",
"5980/5980 [==============================] - 0s 56us/sample - loss: 1.9250 - accuracy: 0.4839\n",
"12255/12255 [==============================] - 1s 53us/sample - loss: 2.3425 - accuracy: 0.2562\n",
"14070/14070 [==============================] - 1s 52us/sample - loss: 2.5802 - accuracy: 0.2038\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.6399 - accuracy: 0.2020\n",
"7000/7000 [==============================] - 0s 56us/sample - loss: 2.6538 - accuracy: 0.2120\n",
"start index for training is 59000\n",
"Train on 13145 samples, validate on 13145 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13145/13145 [==============================] - 1s 45us/sample - loss: 2.2143 - accuracy: 0.2886\n",
"13145/13145 [==============================] - 1s 41us/sample - loss: 2.2175 - accuracy: 0.2891\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.9327 - accuracy: 0.4836\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.3292 - accuracy: 0.2550\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.5918 - accuracy: 0.2007\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.6433 - accuracy: 0.1960\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.6576 - accuracy: 0.2057\n",
"start index for training is 60000\n",
"Train on 11765 samples, validate on 11765 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11765/11765 [==============================] - 1s 50us/sample - loss: 2.2185 - accuracy: 0.2835\n",
"11765/11765 [==============================] - 1s 47us/sample - loss: 2.2277 - accuracy: 0.2744\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.9338 - accuracy: 0.4729\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.3090 - accuracy: 0.2638\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.5965 - accuracy: 0.1967\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.6416 - accuracy: 0.2020\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.6562 - accuracy: 0.2100\n",
"start index for training is 61000\n",
"Train on 11500 samples, validate on 11500 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11500/11500 [==============================] - 0s 42us/sample - loss: 2.2410 - accuracy: 0.2855\n",
"11500/11500 [==============================] - 0s 38us/sample - loss: 2.2217 - accuracy: 0.2797\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.9402 - accuracy: 0.4309\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.2907 - accuracy: 0.2650\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.5982 - accuracy: 0.1933\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.6362 - accuracy: 0.1923\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.6495 - accuracy: 0.2064\n",
"start index for training is 62000\n",
"Train on 11500 samples, validate on 11505 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11500/11500 [==============================] - 1s 46us/sample - loss: 2.2213 - accuracy: 0.2840\n",
"11505/11505 [==============================] - 0s 43us/sample - loss: 2.2167 - accuracy: 0.2845\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9476 - accuracy: 0.4314\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.2792 - accuracy: 0.2629\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.6148 - accuracy: 0.1864\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.6424 - accuracy: 0.1931\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6567 - accuracy: 0.2009\n",
"start index for training is 63000\n",
"Train on 10810 samples, validate on 10815 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10810/10810 [==============================] - 1s 60us/sample - loss: 2.2167 - accuracy: 0.2939\n",
"10815/10815 [==============================] - 1s 65us/sample - loss: 2.2313 - accuracy: 0.2805\n",
"5980/5980 [==============================] - 0s 80us/sample - loss: 1.9580 - accuracy: 0.4157\n",
"12255/12255 [==============================] - 1s 84us/sample - loss: 2.2629 - accuracy: 0.2646\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 2.6224 - accuracy: 0.1820\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.6374 - accuracy: 0.1886\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.6499 - accuracy: 0.1933\n",
"start index for training is 64000\n",
"Train on 11370 samples, validate on 11375 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11370/11370 [==============================] - 0s 40us/sample - loss: 2.2152 - accuracy: 0.2786\n",
"11375/11375 [==============================] - 0s 40us/sample - loss: 2.1952 - accuracy: 0.2848\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.9567 - accuracy: 0.4492\n",
"12255/12255 [==============================] - 1s 60us/sample - loss: 2.2483 - accuracy: 0.2731\n",
"14070/14070 [==============================] - 1s 54us/sample - loss: 2.6265 - accuracy: 0.1965\n",
"11565/11565 [==============================] - 1s 54us/sample - loss: 2.6441 - accuracy: 0.1979\n",
"7000/7000 [==============================] - 0s 53us/sample - loss: 2.6550 - accuracy: 0.2044\n",
"start index for training is 65000\n",
"Train on 9855 samples, validate on 9860 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9855/9855 [==============================] - 0s 47us/sample - loss: 2.2482 - accuracy: 0.2807\n",
"9860/9860 [==============================] - 0s 46us/sample - loss: 2.2495 - accuracy: 0.2819\n",
"5980/5980 [==============================] - 0s 46us/sample - loss: 1.9740 - accuracy: 0.4139\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.2387 - accuracy: 0.2758\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.6382 - accuracy: 0.1942\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.6382 - accuracy: 0.1893\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.6475 - accuracy: 0.1999\n",
"start index for training is 66000\n",
"Train on 11545 samples, validate on 11545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11545/11545 [==============================] - 1s 55us/sample - loss: 2.1968 - accuracy: 0.2845\n",
"11545/11545 [==============================] - 1s 50us/sample - loss: 2.1999 - accuracy: 0.2925\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.9753 - accuracy: 0.4094\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.2200 - accuracy: 0.2765\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.6475 - accuracy: 0.1915\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.6465 - accuracy: 0.1949\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.6549 - accuracy: 0.2047\n",
"start index for training is 67000\n",
"Train on 9825 samples, validate on 9830 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9825/9825 [==============================] - 0s 49us/sample - loss: 2.2225 - accuracy: 0.2719\n",
"9830/9830 [==============================] - 0s 43us/sample - loss: 2.2394 - accuracy: 0.2720\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9817 - accuracy: 0.4092\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.2150 - accuracy: 0.2802\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.6495 - accuracy: 0.1891\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.6480 - accuracy: 0.1924\n",
"7000/7000 [==============================] - 0s 52us/sample - loss: 2.6564 - accuracy: 0.2037\n",
"start index for training is 68000\n",
"Train on 11170 samples, validate on 11170 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11170/11170 [==============================] - 1s 47us/sample - loss: 2.2006 - accuracy: 0.2959\n",
"11170/11170 [==============================] - 0s 38us/sample - loss: 2.2079 - accuracy: 0.2970\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9908 - accuracy: 0.3905\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.2023 - accuracy: 0.2955\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.6662 - accuracy: 0.1793\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.6466 - accuracy: 0.1888\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.6559 - accuracy: 0.1953\n",
"start index for training is 69000\n",
"Train on 9895 samples, validate on 9900 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9895/9895 [==============================] - 0s 49us/sample - loss: 2.2161 - accuracy: 0.2937\n",
"9900/9900 [==============================] - 0s 42us/sample - loss: 2.2171 - accuracy: 0.2837\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9850 - accuracy: 0.4087\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.1919 - accuracy: 0.3042\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.6429 - accuracy: 0.1938\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.6371 - accuracy: 0.2076\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.6443 - accuracy: 0.2147\n",
"start index for training is 70000\n",
"Train on 10740 samples, validate on 10745 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10740/10740 [==============================] - 0s 47us/sample - loss: 2.1874 - accuracy: 0.2991\n",
"10745/10745 [==============================] - 0s 42us/sample - loss: 2.1985 - accuracy: 0.2945\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.9888 - accuracy: 0.4003\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.1774 - accuracy: 0.2957\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.6593 - accuracy: 0.1879\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.6449 - accuracy: 0.1932\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.6528 - accuracy: 0.1997\n",
"start index for training is 71000\n",
"Train on 9780 samples, validate on 9785 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9780/9780 [==============================] - 0s 41us/sample - loss: 2.2121 - accuracy: 0.2954\n",
"9785/9785 [==============================] - 0s 39us/sample - loss: 2.2203 - accuracy: 0.2880\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.9919 - accuracy: 0.3888\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1719 - accuracy: 0.3017\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.6573 - accuracy: 0.1826\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.6434 - accuracy: 0.1900\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.6517 - accuracy: 0.1971\n",
"start index for training is 72000\n",
"Train on 11175 samples, validate on 11180 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11175/11175 [==============================] - 0s 41us/sample - loss: 2.1855 - accuracy: 0.3100\n",
"11180/11180 [==============================] - 0s 37us/sample - loss: 2.1982 - accuracy: 0.3042\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9935 - accuracy: 0.3928\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.1586 - accuracy: 0.3118\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.6695 - accuracy: 0.1918\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.6401 - accuracy: 0.2035\n",
"7000/7000 [==============================] - 0s 35us/sample - loss: 2.6501 - accuracy: 0.2090\n",
"start index for training is 73000\n",
"Train on 9165 samples, validate on 9170 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9165/9165 [==============================] - 0s 40us/sample - loss: 2.1976 - accuracy: 0.2968\n",
"9170/9170 [==============================] - 0s 37us/sample - loss: 2.2231 - accuracy: 0.2887\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.0000 - accuracy: 0.3901\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.1514 - accuracy: 0.3075\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.6704 - accuracy: 0.1907\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.6403 - accuracy: 0.2060\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.6454 - accuracy: 0.2097\n",
"start index for training is 74000\n",
"Train on 11365 samples, validate on 11370 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11365/11365 [==============================] - 0s 40us/sample - loss: 2.1952 - accuracy: 0.3022\n",
"11370/11370 [==============================] - 0s 39us/sample - loss: 2.2030 - accuracy: 0.3057\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9994 - accuracy: 0.3980\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1389 - accuracy: 0.3148\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.6720 - accuracy: 0.1973\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.6466 - accuracy: 0.2060\n",
"7000/7000 [==============================] - 0s 35us/sample - loss: 2.6529 - accuracy: 0.2127\n",
"start index for training is 75000\n",
"Train on 9365 samples, validate on 9365 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9365/9365 [==============================] - 0s 41us/sample - loss: 2.2224 - accuracy: 0.2878\n",
"9365/9365 [==============================] - 0s 36us/sample - loss: 2.2365 - accuracy: 0.2847\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.0103 - accuracy: 0.3779\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1359 - accuracy: 0.3094\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.6810 - accuracy: 0.1861\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.6397 - accuracy: 0.2001\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.6447 - accuracy: 0.2074\n",
"start index for training is 76000\n",
"Train on 9975 samples, validate on 9975 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9975/9975 [==============================] - 0s 41us/sample - loss: 2.2062 - accuracy: 0.2982\n",
"9975/9975 [==============================] - 0s 37us/sample - loss: 2.2100 - accuracy: 0.2954\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0178 - accuracy: 0.3836\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1326 - accuracy: 0.3057\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.6844 - accuracy: 0.1898\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.6349 - accuracy: 0.2021\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6351 - accuracy: 0.2056\n",
"start index for training is 77000\n",
"Train on 10385 samples, validate on 10390 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10385/10385 [==============================] - 0s 39us/sample - loss: 2.2269 - accuracy: 0.2941\n",
"10390/10390 [==============================] - 0s 37us/sample - loss: 2.2374 - accuracy: 0.2851\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.0232 - accuracy: 0.3590\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 2.1275 - accuracy: 0.3063\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.6820 - accuracy: 0.1836\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.6271 - accuracy: 0.1898\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6281 - accuracy: 0.1994\n",
"start index for training is 78000\n",
"Train on 8665 samples, validate on 8665 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8665/8665 [==============================] - 0s 41us/sample - loss: 2.2525 - accuracy: 0.2922\n",
"8665/8665 [==============================] - 0s 42us/sample - loss: 2.2554 - accuracy: 0.2821\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0413 - accuracy: 0.3712\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1309 - accuracy: 0.3067\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.7005 - accuracy: 0.1878\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.6298 - accuracy: 0.2057\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.6287 - accuracy: 0.2124\n",
"start index for training is 79000\n",
"Train on 11235 samples, validate on 11240 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11235/11235 [==============================] - 0s 39us/sample - loss: 2.2343 - accuracy: 0.2968\n",
"11240/11240 [==============================] - 0s 36us/sample - loss: 2.2253 - accuracy: 0.2952\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.0392 - accuracy: 0.3635\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.1250 - accuracy: 0.3083\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.6961 - accuracy: 0.1886\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.6228 - accuracy: 0.2072\n",
"7000/7000 [==============================] - 0s 35us/sample - loss: 2.6232 - accuracy: 0.2140\n",
"start index for training is 80000\n",
"Train on 9395 samples, validate on 9395 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9395/9395 [==============================] - 0s 39us/sample - loss: 2.2187 - accuracy: 0.2973\n",
"9395/9395 [==============================] - 0s 38us/sample - loss: 2.2470 - accuracy: 0.2911\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 2.0555 - accuracy: 0.3594\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.1293 - accuracy: 0.3098\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.7119 - accuracy: 0.1807\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.6238 - accuracy: 0.2034\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.6247 - accuracy: 0.2116\n",
"start index for training is 81000\n",
"Train on 8640 samples, validate on 8640 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8640/8640 [==============================] - 0s 41us/sample - loss: 2.2578 - accuracy: 0.2978\n",
"8640/8640 [==============================] - 0s 47us/sample - loss: 2.2639 - accuracy: 0.2977\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 2.0436 - accuracy: 0.3671\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1279 - accuracy: 0.3188\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.7022 - accuracy: 0.1843\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.6212 - accuracy: 0.2037\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.6193 - accuracy: 0.2114\n",
"start index for training is 82000\n",
"Train on 10980 samples, validate on 10980 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10980/10980 [==============================] - 0s 41us/sample - loss: 2.2400 - accuracy: 0.3075\n",
"10980/10980 [==============================] - 0s 37us/sample - loss: 2.2394 - accuracy: 0.3080\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0580 - accuracy: 0.3674\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.1330 - accuracy: 0.3229\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.7152 - accuracy: 0.1830\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.6294 - accuracy: 0.2034\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.6255 - accuracy: 0.2077\n",
"start index for training is 83000\n",
"Train on 9485 samples, validate on 9485 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9485/9485 [==============================] - 0s 40us/sample - loss: 2.2241 - accuracy: 0.3071\n",
"9485/9485 [==============================] - 0s 35us/sample - loss: 2.2258 - accuracy: 0.3068\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.0772 - accuracy: 0.3577\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 2.1431 - accuracy: 0.3117\n",
"14070/14070 [==============================] - 0s 34us/sample - loss: 2.7404 - accuracy: 0.1800\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.6439 - accuracy: 0.2005\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.6398 - accuracy: 0.2071\n",
"start index for training is 84000\n",
"Train on 8800 samples, validate on 8800 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8800/8800 [==============================] - 0s 37us/sample - loss: 2.2392 - accuracy: 0.3017\n",
"8800/8800 [==============================] - 0s 38us/sample - loss: 2.2546 - accuracy: 0.3041\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0702 - accuracy: 0.3686s - loss: 2.0677 - accuracy: 0.\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1383 - accuracy: 0.3214\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.7314 - accuracy: 0.1780\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.6302 - accuracy: 0.2031\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.6252 - accuracy: 0.2084\n",
"start index for training is 85000\n",
"Train on 8500 samples, validate on 8505 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8500/8500 [==============================] - 0s 41us/sample - loss: 2.2258 - accuracy: 0.2991\n",
"8505/8505 [==============================] - 0s 36us/sample - loss: 2.2663 - accuracy: 0.3019\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.0718 - accuracy: 0.3651\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.1401 - accuracy: 0.3091\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.7391 - accuracy: 0.1790\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.6370 - accuracy: 0.2007\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6341 - accuracy: 0.2067\n",
"start index for training is 86000\n",
"Train on 10125 samples, validate on 10125 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10125/10125 [==============================] - 0s 43us/sample - loss: 2.2276 - accuracy: 0.3168\n",
"10125/10125 [==============================] - 0s 37us/sample - loss: 2.2194 - accuracy: 0.3174\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.0595 - accuracy: 0.3676\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 2.1335 - accuracy: 0.3191\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.7212 - accuracy: 0.1826\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.6224 - accuracy: 0.2013\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6183 - accuracy: 0.2054\n",
"start index for training is 87000\n",
"Train on 9690 samples, validate on 9695 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9690/9690 [==============================] - 0s 38us/sample - loss: 2.2293 - accuracy: 0.2991\n",
"9695/9695 [==============================] - 0s 38us/sample - loss: 2.2392 - accuracy: 0.2992\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.0605 - accuracy: 0.3572\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1405 - accuracy: 0.3106\n",
"14070/14070 [==============================] - 0s 36us/sample - loss: 2.7211 - accuracy: 0.1842\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.6245 - accuracy: 0.2011s - loss: 2.6565 - accura\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6212 - accuracy: 0.2056\n",
"start index for training is 88000\n",
"Train on 9220 samples, validate on 9225 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9220/9220 [==============================] - 0s 38us/sample - loss: 2.2361 - accuracy: 0.2956\n",
"9225/9225 [==============================] - 0s 40us/sample - loss: 2.2507 - accuracy: 0.2993\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0706 - accuracy: 0.3669\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1453 - accuracy: 0.3139\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.7213 - accuracy: 0.1884\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.6253 - accuracy: 0.2064\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.6217 - accuracy: 0.2114\n",
"start index for training is 89000\n",
"Train on 9020 samples, validate on 9025 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9020/9020 [==============================] - 0s 41us/sample - loss: 2.2495 - accuracy: 0.2946\n",
"9025/9025 [==============================] - 0s 38us/sample - loss: 2.2357 - accuracy: 0.3034\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.0698 - accuracy: 0.3664\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1461 - accuracy: 0.3120\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.7187 - accuracy: 0.1856\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.6209 - accuracy: 0.2067\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6156 - accuracy: 0.2109\n",
"start index for training is 90000\n",
"Train on 8790 samples, validate on 8790 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8790/8790 [==============================] - 0s 41us/sample - loss: 2.2490 - accuracy: 0.2995\n",
"8790/8790 [==============================] - 0s 38us/sample - loss: 2.2381 - accuracy: 0.3039\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.0719 - accuracy: 0.3702\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1531 - accuracy: 0.3126\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.7152 - accuracy: 0.1881\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.6219 - accuracy: 0.2100\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6161 - accuracy: 0.2147\n",
"start index for training is 91000\n",
"Train on 8675 samples, validate on 8680 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8675/8675 [==============================] - 0s 38us/sample - loss: 2.2490 - accuracy: 0.3021\n",
"8680/8680 [==============================] - 0s 37us/sample - loss: 2.2645 - accuracy: 0.2922\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.0753 - accuracy: 0.3669\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1565 - accuracy: 0.3073\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.7232 - accuracy: 0.1861\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.6305 - accuracy: 0.2110\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.6246 - accuracy: 0.2167\n",
"start index for training is 92000\n",
"Train on 8635 samples, validate on 8635 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8635/8635 [==============================] - 0s 43us/sample - loss: 2.2592 - accuracy: 0.2888\n",
"8635/8635 [==============================] - 0s 38us/sample - loss: 2.2522 - accuracy: 0.2948\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.0636 - accuracy: 0.3662\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 2.1629 - accuracy: 0.3084\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.7017 - accuracy: 0.1940\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.6269 - accuracy: 0.2116\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6234 - accuracy: 0.2196\n",
"start index for training is 93000\n",
"Train on 8485 samples, validate on 8490 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8485/8485 [==============================] - 0s 40us/sample - loss: 2.2610 - accuracy: 0.2968\n",
"8490/8490 [==============================] - 0s 36us/sample - loss: 2.2453 - accuracy: 0.2896\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 2.0521 - accuracy: 0.3605\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1557 - accuracy: 0.3014\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.6965 - accuracy: 0.1857\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.6200 - accuracy: 0.2092\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.6172 - accuracy: 0.2153\n",
"start index for training is 94000\n",
"Train on 8555 samples, validate on 8560 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8555/8555 [==============================] - 0s 40us/sample - loss: 2.2688 - accuracy: 0.2876\n",
"8560/8560 [==============================] - 0s 37us/sample - loss: 2.2562 - accuracy: 0.2918\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.0591 - accuracy: 0.3612\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1610 - accuracy: 0.3041\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.6912 - accuracy: 0.1887\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.6180 - accuracy: 0.2101\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.6137 - accuracy: 0.2170\n",
"start index for training is 95000\n",
"Train on 10360 samples, validate on 10365 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10360/10360 [==============================] - 0s 40us/sample - loss: 2.4585 - accuracy: 0.2445\n",
"10365/10365 [==============================] - 0s 38us/sample - loss: 2.4738 - accuracy: 0.2378\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0469 - accuracy: 0.3535\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.2166 - accuracy: 0.2732\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.4723 - accuracy: 0.2334\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.5643 - accuracy: 0.2175\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5630 - accuracy: 0.2267\n",
"start index for training is 96000\n",
"Train on 10945 samples, validate on 10945 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10945/10945 [==============================] - 0s 42us/sample - loss: 2.4663 - accuracy: 0.2397\n",
"10945/10945 [==============================] - 0s 41us/sample - loss: 2.4722 - accuracy: 0.2288\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0692 - accuracy: 0.3579\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.2478 - accuracy: 0.2777\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4237 - accuracy: 0.2405\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.5588 - accuracy: 0.2155\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.5565 - accuracy: 0.2239\n",
"start index for training is 97000\n",
"Train on 11125 samples, validate on 11125 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11125/11125 [==============================] - 0s 40us/sample - loss: 2.4265 - accuracy: 0.2418\n",
"11125/11125 [==============================] - 0s 40us/sample - loss: 2.4372 - accuracy: 0.2468\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0862 - accuracy: 0.3487\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.2701 - accuracy: 0.2681\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3900 - accuracy: 0.2542\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.5541 - accuracy: 0.2241\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5515 - accuracy: 0.2346\n",
"start index for training is 98000\n",
"Train on 11725 samples, validate on 11730 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11725/11725 [==============================] - 0s 42us/sample - loss: 2.4201 - accuracy: 0.2516\n",
"11730/11730 [==============================] - 0s 39us/sample - loss: 2.3954 - accuracy: 0.2512\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0942 - accuracy: 0.3431\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.2826 - accuracy: 0.2660\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.3643 - accuracy: 0.2635\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.5505 - accuracy: 0.2213\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5511 - accuracy: 0.2266\n",
"start index for training is 99000\n",
"Train on 11765 samples, validate on 11770 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11765/11765 [==============================] - 1s 43us/sample - loss: 2.3675 - accuracy: 0.2591\n",
"11770/11770 [==============================] - 0s 39us/sample - loss: 2.3822 - accuracy: 0.2526\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1002 - accuracy: 0.3413\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.2911 - accuracy: 0.2619\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3414 - accuracy: 0.2723\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.5427 - accuracy: 0.2310\n",
"7000/7000 [==============================] - 0s 35us/sample - loss: 2.5419 - accuracy: 0.2337\n",
"start index for training is 100000\n",
"Train on 10495 samples, validate on 10500 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10495/10495 [==============================] - 0s 44us/sample - loss: 2.3729 - accuracy: 0.2595\n",
"10500/10500 [==============================] - 0s 40us/sample - loss: 2.3775 - accuracy: 0.2657\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1098 - accuracy: 0.3363\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.3064 - accuracy: 0.2557\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.3255 - accuracy: 0.2740\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.5453 - accuracy: 0.2257\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5443 - accuracy: 0.2336\n",
"start index for training is 101000\n",
"Train on 11025 samples, validate on 11025 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11025/11025 [==============================] - 0s 39us/sample - loss: 2.4388 - accuracy: 0.2383\n",
"11025/11025 [==============================] - 0s 38us/sample - loss: 2.4419 - accuracy: 0.2399\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1525 - accuracy: 0.3401\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3669 - accuracy: 0.2305\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3448 - accuracy: 0.2600\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.6225 - accuracy: 0.1919\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.6224 - accuracy: 0.1960\n",
"start index for training is 102000\n",
"Train on 12490 samples, validate on 12490 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12490/12490 [==============================] - 1s 45us/sample - loss: 2.3326 - accuracy: 0.2695\n",
"12490/12490 [==============================] - 1s 42us/sample - loss: 2.3305 - accuracy: 0.2725\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1147 - accuracy: 0.3273\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3148 - accuracy: 0.2546\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.2904 - accuracy: 0.2877\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.5389 - accuracy: 0.2383\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.5391 - accuracy: 0.2409\n",
"start index for training is 103000\n",
"Train on 12560 samples, validate on 12560 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12560/12560 [==============================] - 1s 40us/sample - loss: 2.3171 - accuracy: 0.2806\n",
"12560/12560 [==============================] - 0s 40us/sample - loss: 2.3172 - accuracy: 0.2732\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1271 - accuracy: 0.3222\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.3299 - accuracy: 0.2461\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2729 - accuracy: 0.2950\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.5389 - accuracy: 0.2402\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5399 - accuracy: 0.2447\n",
"start index for training is 104000\n",
"Train on 12245 samples, validate on 12250 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12245/12245 [==============================] - 0s 40us/sample - loss: 2.2938 - accuracy: 0.2777\n",
"12250/12250 [==============================] - 0s 41us/sample - loss: 2.3012 - accuracy: 0.2750\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1286 - accuracy: 0.3231\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.3344 - accuracy: 0.2451\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2573 - accuracy: 0.2916\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.5372 - accuracy: 0.2377\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.5370 - accuracy: 0.2420\n",
"start index for training is 105000\n",
"Train on 12275 samples, validate on 12275 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12275/12275 [==============================] - 1s 42us/sample - loss: 2.2822 - accuracy: 0.2914\n",
"12275/12275 [==============================] - 0s 37us/sample - loss: 2.2972 - accuracy: 0.2866\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1318 - accuracy: 0.3258\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3389 - accuracy: 0.2410\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2433 - accuracy: 0.3038\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.5381 - accuracy: 0.2424\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5381 - accuracy: 0.2464\n",
"start index for training is 106000\n",
"Train on 12240 samples, validate on 12240 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12240/12240 [==============================] - 0s 40us/sample - loss: 2.2698 - accuracy: 0.3001\n",
"12240/12240 [==============================] - 0s 37us/sample - loss: 2.2746 - accuracy: 0.2895\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 2.1358 - accuracy: 0.3281\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3459 - accuracy: 0.2366\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2295 - accuracy: 0.3086\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.5434 - accuracy: 0.2369\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.5434 - accuracy: 0.2381\n",
"start index for training is 107000\n",
"Train on 12275 samples, validate on 12275 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12275/12275 [==============================] - 1s 42us/sample - loss: 2.2602 - accuracy: 0.2990\n",
"12275/12275 [==============================] - 1s 41us/sample - loss: 2.2570 - accuracy: 0.2969\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1405 - accuracy: 0.3242\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3587 - accuracy: 0.2298\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2162 - accuracy: 0.3123\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.5377 - accuracy: 0.2307\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.5396 - accuracy: 0.2296\n",
"start index for training is 108000\n",
"Train on 12190 samples, validate on 12195 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12190/12190 [==============================] - 0s 41us/sample - loss: 2.2542 - accuracy: 0.2975\n",
"12195/12195 [==============================] - 0s 39us/sample - loss: 2.2488 - accuracy: 0.2967\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.1430 - accuracy: 0.3353\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3579 - accuracy: 0.2359\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2066 - accuracy: 0.3154\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.5326 - accuracy: 0.2380\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.5306 - accuracy: 0.2389\n",
"start index for training is 109000\n",
"Train on 12625 samples, validate on 12630 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12625/12625 [==============================] - 1s 41us/sample - loss: 2.2313 - accuracy: 0.3083\n",
"12630/12630 [==============================] - 0s 37us/sample - loss: 2.2283 - accuracy: 0.3039\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1483 - accuracy: 0.3273\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3692 - accuracy: 0.2337\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1958 - accuracy: 0.3217\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.5384 - accuracy: 0.2396\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.5378 - accuracy: 0.2431\n",
"start index for training is 110000\n",
"Train on 12625 samples, validate on 12625 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12625/12625 [==============================] - 0s 40us/sample - loss: 2.2284 - accuracy: 0.3164\n",
"12625/12625 [==============================] - 0s 36us/sample - loss: 2.2087 - accuracy: 0.3153\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1465 - accuracy: 0.3273\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3642 - accuracy: 0.2355\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1848 - accuracy: 0.3277\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.5341 - accuracy: 0.2364\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.5341 - accuracy: 0.2407\n",
"start index for training is 111000\n",
"Train on 12985 samples, validate on 12990 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12985/12985 [==============================] - 1s 40us/sample - loss: 2.2153 - accuracy: 0.3083\n",
"12990/12990 [==============================] - 0s 36us/sample - loss: 2.2308 - accuracy: 0.3131\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.1541 - accuracy: 0.3274\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.3712 - accuracy: 0.2326\n",
"14070/14070 [==============================] - 0s 36us/sample - loss: 2.1782 - accuracy: 0.3257\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.5321 - accuracy: 0.2371\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.5316 - accuracy: 0.2399\n",
"start index for training is 112000\n",
"Train on 12850 samples, validate on 12855 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12850/12850 [==============================] - 1s 44us/sample - loss: 2.1940 - accuracy: 0.3261\n",
"12855/12855 [==============================] - 1s 44us/sample - loss: 2.2289 - accuracy: 0.3173\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 2.1530 - accuracy: 0.3207\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.3700 - accuracy: 0.2415\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.1695 - accuracy: 0.3345\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.5333 - accuracy: 0.2395\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.5352 - accuracy: 0.2409\n",
"start index for training is 113000\n",
"Train on 13375 samples, validate on 13375 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13375/13375 [==============================] - 1s 40us/sample - loss: 2.2414 - accuracy: 0.3015\n",
"13375/13375 [==============================] - 1s 37us/sample - loss: 2.2250 - accuracy: 0.3028\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1462 - accuracy: 0.3268\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.3648 - accuracy: 0.2440\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.1627 - accuracy: 0.3279\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.5195 - accuracy: 0.2380\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.5224 - accuracy: 0.2437\n",
"start index for training is 114000\n",
"Train on 14795 samples, validate on 14795 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14795/14795 [==============================] - 1s 44us/sample - loss: 2.1891 - accuracy: 0.3159\n",
"14795/14795 [==============================] - 1s 41us/sample - loss: 2.1849 - accuracy: 0.3268\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1550 - accuracy: 0.3077\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.3691 - accuracy: 0.2478\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.1539 - accuracy: 0.3259\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.5233 - accuracy: 0.2348\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.5278 - accuracy: 0.2309\n",
"start index for training is 115000\n",
"Train on 14740 samples, validate on 14745 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14740/14740 [==============================] - 1s 41us/sample - loss: 2.1793 - accuracy: 0.3256\n",
"14745/14745 [==============================] - 1s 41us/sample - loss: 2.1745 - accuracy: 0.3268\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1564 - accuracy: 0.3222\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3708 - accuracy: 0.2441\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1475 - accuracy: 0.3332\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.5217 - accuracy: 0.2332\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5256 - accuracy: 0.2333\n",
"start index for training is 116000\n",
"Train on 14740 samples, validate on 14745 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14740/14740 [==============================] - 1s 41us/sample - loss: 2.1656 - accuracy: 0.3292\n",
"14745/14745 [==============================] - 1s 38us/sample - loss: 2.1723 - accuracy: 0.3316\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1643 - accuracy: 0.3102\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3807 - accuracy: 0.2418\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.1420 - accuracy: 0.3354\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.5322 - accuracy: 0.2366\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.5389 - accuracy: 0.2301\n",
"start index for training is 117000\n",
"Train on 14765 samples, validate on 14765 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14765/14765 [==============================] - 1s 41us/sample - loss: 2.1465 - accuracy: 0.3285\n",
"14765/14765 [==============================] - 1s 37us/sample - loss: 2.1823 - accuracy: 0.3201\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1606 - accuracy: 0.2958\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.3639 - accuracy: 0.2452\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.1400 - accuracy: 0.3329\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.5147 - accuracy: 0.2371\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.5217 - accuracy: 0.2396\n",
"start index for training is 118000\n",
"Train on 14625 samples, validate on 14625 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14625/14625 [==============================] - 1s 42us/sample - loss: 2.1454 - accuracy: 0.3172\n",
"14625/14625 [==============================] - 1s 39us/sample - loss: 2.1595 - accuracy: 0.3149\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.1720 - accuracy: 0.3035\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3744 - accuracy: 0.2382\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1390 - accuracy: 0.3281\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.5232 - accuracy: 0.2360\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5311 - accuracy: 0.2367\n",
"start index for training is 119000\n",
"Train on 13765 samples, validate on 13770 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13765/13765 [==============================] - 1s 40us/sample - loss: 2.1627 - accuracy: 0.3242\n",
"13770/13770 [==============================] - 1s 44us/sample - loss: 2.1582 - accuracy: 0.3229\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.1749 - accuracy: 0.2997\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3758 - accuracy: 0.2263\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1395 - accuracy: 0.3383\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.5207 - accuracy: 0.2401\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.5313 - accuracy: 0.2333\n",
"start index for training is 120000\n",
"Train on 13185 samples, validate on 13185 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13185/13185 [==============================] - 1s 40us/sample - loss: 2.2044 - accuracy: 0.3025\n",
"13185/13185 [==============================] - 1s 39us/sample - loss: 2.2059 - accuracy: 0.3053\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1609 - accuracy: 0.2972\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3659 - accuracy: 0.2233\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.1299 - accuracy: 0.3328\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.5080 - accuracy: 0.2236\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5180 - accuracy: 0.2203\n",
"start index for training is 121000\n",
"Train on 15200 samples, validate on 15205 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15200/15200 [==============================] - 1s 39us/sample - loss: 2.1532 - accuracy: 0.3185\n",
"15205/15205 [==============================] - 1s 42us/sample - loss: 2.1470 - accuracy: 0.3215\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1725 - accuracy: 0.2855\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3672 - accuracy: 0.2326\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1311 - accuracy: 0.3337\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.5030 - accuracy: 0.2463\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5154 - accuracy: 0.2454\n",
"start index for training is 122000\n",
"Train on 14725 samples, validate on 14725 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14725/14725 [==============================] - 1s 40us/sample - loss: 2.1361 - accuracy: 0.3196\n",
"14725/14725 [==============================] - 1s 37us/sample - loss: 2.1439 - accuracy: 0.3176\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1752 - accuracy: 0.3043\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3694 - accuracy: 0.2286\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1271 - accuracy: 0.3358\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.5095 - accuracy: 0.2423\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5243 - accuracy: 0.2413\n",
"start index for training is 123000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Train on 14025 samples, validate on 14025 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14025/14025 [==============================] - 1s 39us/sample - loss: 2.1466 - accuracy: 0.3161\n",
"14025/14025 [==============================] - 1s 37us/sample - loss: 2.1304 - accuracy: 0.3176\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.1892 - accuracy: 0.2794\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.3813 - accuracy: 0.2272\n",
"14070/14070 [==============================] - 0s 36us/sample - loss: 2.1387 - accuracy: 0.3370\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.5334 - accuracy: 0.2195\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.5483 - accuracy: 0.2146\n",
"start index for training is 124000\n",
"Train on 13510 samples, validate on 13515 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13510/13510 [==============================] - 1s 40us/sample - loss: 2.1172 - accuracy: 0.3404\n",
"13515/13515 [==============================] - 1s 38us/sample - loss: 2.1403 - accuracy: 0.3296\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1738 - accuracy: 0.2875\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.3559 - accuracy: 0.2341\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.1276 - accuracy: 0.3488\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.4892 - accuracy: 0.2553\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.5069 - accuracy: 0.2527\n",
"start index for training is 125000\n",
"Train on 13700 samples, validate on 13700 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13700/13700 [==============================] - 1s 39us/sample - loss: 2.1084 - accuracy: 0.3422\n",
"13700/13700 [==============================] - 0s 36us/sample - loss: 2.1168 - accuracy: 0.3406\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 2.1753 - accuracy: 0.2819\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.3507 - accuracy: 0.2370\n",
"14070/14070 [==============================] - 0s 36us/sample - loss: 2.1289 - accuracy: 0.3421\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.4810 - accuracy: 0.2522\n",
"7000/7000 [==============================] - 0s 35us/sample - loss: 2.4997 - accuracy: 0.2521\n",
"start index for training is 126000\n",
"Train on 13370 samples, validate on 13375 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13370/13370 [==============================] - 1s 40us/sample - loss: 2.1105 - accuracy: 0.3517\n",
"13375/13375 [==============================] - 1s 38us/sample - loss: 2.1180 - accuracy: 0.3376\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.1772 - accuracy: 0.2858\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3415 - accuracy: 0.2386\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.1349 - accuracy: 0.3412\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.4716 - accuracy: 0.2491\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4909 - accuracy: 0.2460\n",
"start index for training is 127000\n",
"Train on 12925 samples, validate on 12930 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12925/12925 [==============================] - 1s 39us/sample - loss: 2.1106 - accuracy: 0.3488\n",
"12930/12930 [==============================] - 0s 36us/sample - loss: 2.1189 - accuracy: 0.3415\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.1843 - accuracy: 0.2915\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.3400 - accuracy: 0.2432\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.1372 - accuracy: 0.3427\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.4600 - accuracy: 0.2524s - loss: 2.4866 - accura\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4819 - accuracy: 0.2491\n",
"start index for training is 128000\n",
"Train on 12580 samples, validate on 12585 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12580/12580 [==============================] - 1s 41us/sample - loss: 2.1041 - accuracy: 0.3541\n",
"12585/12585 [==============================] - 0s 37us/sample - loss: 2.1255 - accuracy: 0.3416\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1824 - accuracy: 0.2826\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3347 - accuracy: 0.2486\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1401 - accuracy: 0.3456\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.4500 - accuracy: 0.2540\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4722 - accuracy: 0.2499\n",
"start index for training is 129000\n",
"Train on 12680 samples, validate on 12680 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12680/12680 [==============================] - 1s 40us/sample - loss: 2.1161 - accuracy: 0.3368\n",
"12680/12680 [==============================] - 0s 37us/sample - loss: 2.1059 - accuracy: 0.3394\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1888 - accuracy: 0.2878\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.3329 - accuracy: 0.2538\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.1439 - accuracy: 0.3420\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.4363 - accuracy: 0.2545\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4567 - accuracy: 0.2523\n",
"start index for training is 130000\n",
"Train on 12795 samples, validate on 12795 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12795/12795 [==============================] - 1s 40us/sample - loss: 2.1015 - accuracy: 0.3524\n",
"12795/12795 [==============================] - 0s 38us/sample - loss: 2.1180 - accuracy: 0.3427\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1919 - accuracy: 0.2834\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3384 - accuracy: 0.2473\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.1486 - accuracy: 0.3419\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.4327 - accuracy: 0.2557\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4560 - accuracy: 0.2564\n",
"start index for training is 131000\n",
"Train on 12505 samples, validate on 12505 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12505/12505 [==============================] - 1s 48us/sample - loss: 2.1034 - accuracy: 0.3521\n",
"12505/12505 [==============================] - 1s 44us/sample - loss: 2.1294 - accuracy: 0.3375\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1915 - accuracy: 0.2833\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.3278 - accuracy: 0.2497\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.1446 - accuracy: 0.3435\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.4164 - accuracy: 0.2599\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.4378 - accuracy: 0.2576\n",
"start index for training is 132000\n",
"Train on 12320 samples, validate on 12325 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12320/12320 [==============================] - 0s 40us/sample - loss: 2.1012 - accuracy: 0.3511\n",
"12325/12325 [==============================] - 0s 40us/sample - loss: 2.1110 - accuracy: 0.3532\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1961 - accuracy: 0.2858\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3278 - accuracy: 0.2513\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1480 - accuracy: 0.3425\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.4081 - accuracy: 0.2633\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4268 - accuracy: 0.2611\n",
"start index for training is 133000\n",
"Train on 12380 samples, validate on 12380 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12380/12380 [==============================] - 1s 41us/sample - loss: 2.1043 - accuracy: 0.3424\n",
"12380/12380 [==============================] - 0s 37us/sample - loss: 2.1004 - accuracy: 0.3453\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1943 - accuracy: 0.2828\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3226 - accuracy: 0.2565\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1460 - accuracy: 0.3381\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3933 - accuracy: 0.2636\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4102 - accuracy: 0.2614\n",
"start index for training is 134000\n",
"Train on 12205 samples, validate on 12205 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12205/12205 [==============================] - 0s 40us/sample - loss: 2.1162 - accuracy: 0.3372\n",
"12205/12205 [==============================] - 0s 39us/sample - loss: 2.1054 - accuracy: 0.3422\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2081 - accuracy: 0.2844\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3284 - accuracy: 0.2503\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.1555 - accuracy: 0.3334\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3820 - accuracy: 0.2628\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3970 - accuracy: 0.2621\n",
"start index for training is 135000\n",
"Train on 11500 samples, validate on 11500 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11500/11500 [==============================] - 0s 43us/sample - loss: 2.1092 - accuracy: 0.3513\n",
"11500/11500 [==============================] - 0s 41us/sample - loss: 2.1185 - accuracy: 0.3447\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.2005 - accuracy: 0.2819\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.3206 - accuracy: 0.2425\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.1537 - accuracy: 0.3410\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3711 - accuracy: 0.2734\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.3868 - accuracy: 0.2717\n",
"start index for training is 136000\n",
"Train on 11650 samples, validate on 11655 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11650/11650 [==============================] - 1s 45us/sample - loss: 2.1465 - accuracy: 0.3221\n",
"11655/11655 [==============================] - 0s 39us/sample - loss: 2.1559 - accuracy: 0.3276\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.1974 - accuracy: 0.2898\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3130 - accuracy: 0.2455\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1584 - accuracy: 0.3395\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3492 - accuracy: 0.2839\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.3621 - accuracy: 0.2850\n",
"start index for training is 137000\n",
"Train on 12710 samples, validate on 12715 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12710/12710 [==============================] - 1s 46us/sample - loss: 2.1109 - accuracy: 0.3366\n",
"12715/12715 [==============================] - 0s 38us/sample - loss: 2.1327 - accuracy: 0.3298\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.2111 - accuracy: 0.2849\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3149 - accuracy: 0.2471\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.1697 - accuracy: 0.3404\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3344 - accuracy: 0.2779\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.3469 - accuracy: 0.2797\n",
"start index for training is 138000\n",
"Train on 10385 samples, validate on 10385 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10385/10385 [==============================] - 0s 43us/sample - loss: 2.1424 - accuracy: 0.3317\n",
"10385/10385 [==============================] - 0s 39us/sample - loss: 2.1382 - accuracy: 0.3353\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 2.2189 - accuracy: 0.2808\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3225 - accuracy: 0.2440\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.1713 - accuracy: 0.3390\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.3318 - accuracy: 0.2751\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3427 - accuracy: 0.2724\n",
"start index for training is 139000\n",
"Train on 11700 samples, validate on 11700 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11700/11700 [==============================] - 0s 42us/sample - loss: 2.1448 - accuracy: 0.3263\n",
"11700/11700 [==============================] - 1s 43us/sample - loss: 2.1712 - accuracy: 0.3208\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.2150 - accuracy: 0.2778\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3113 - accuracy: 0.2501\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.1757 - accuracy: 0.3443\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.3135 - accuracy: 0.2896\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3212 - accuracy: 0.2890\n",
"start index for training is 140000\n",
"Train on 11280 samples, validate on 11285 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11280/11280 [==============================] - 1s 48us/sample - loss: 2.1423 - accuracy: 0.3419\n",
"11285/11285 [==============================] - 0s 41us/sample - loss: 2.1349 - accuracy: 0.3426\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.2226 - accuracy: 0.3027\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.2995 - accuracy: 0.2618\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1935 - accuracy: 0.3372\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.2898 - accuracy: 0.2994\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2941 - accuracy: 0.2951\n",
"start index for training is 141000\n",
"Train on 10740 samples, validate on 10745 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10740/10740 [==============================] - 0s 42us/sample - loss: 2.1818 - accuracy: 0.3209\n",
"10745/10745 [==============================] - 0s 39us/sample - loss: 2.1755 - accuracy: 0.3228\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2213 - accuracy: 0.2773\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3054 - accuracy: 0.2521\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.1818 - accuracy: 0.3365\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.2838 - accuracy: 0.2963\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2862 - accuracy: 0.2946\n",
"start index for training is 142000\n",
"Train on 10360 samples, validate on 10365 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10360/10360 [==============================] - 0s 43us/sample - loss: 2.1386 - accuracy: 0.3456\n",
"10365/10365 [==============================] - 0s 40us/sample - loss: 2.1743 - accuracy: 0.3408\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.2394 - accuracy: 0.2843\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3071 - accuracy: 0.2694\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2107 - accuracy: 0.3259\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.2709 - accuracy: 0.3118\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.2705 - accuracy: 0.3150\n",
"start index for training is 143000\n",
"Train on 11485 samples, validate on 11485 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11485/11485 [==============================] - 1s 44us/sample - loss: 2.1822 - accuracy: 0.3311\n",
"11485/11485 [==============================] - 0s 39us/sample - loss: 2.1680 - accuracy: 0.3359\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.2447 - accuracy: 0.2766\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3011 - accuracy: 0.2761\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2042 - accuracy: 0.3268\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.2545 - accuracy: 0.3122\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.2485 - accuracy: 0.3074\n",
"start index for training is 144000\n",
"Train on 9140 samples, validate on 9140 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9140/9140 [==============================] - 0s 41us/sample - loss: 2.1964 - accuracy: 0.3305\n",
"9140/9140 [==============================] - 0s 38us/sample - loss: 2.1983 - accuracy: 0.3303\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.2473 - accuracy: 0.2747\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3137 - accuracy: 0.2641\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2130 - accuracy: 0.3236\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2484 - accuracy: 0.3136\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2430 - accuracy: 0.3190\n",
"start index for training is 145000\n",
"Train on 12405 samples, validate on 12405 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12405/12405 [==============================] - 1s 42us/sample - loss: 2.1392 - accuracy: 0.3562\n",
"12405/12405 [==============================] - 0s 37us/sample - loss: 2.1405 - accuracy: 0.3590\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.2494 - accuracy: 0.2853\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3031 - accuracy: 0.2750\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2135 - accuracy: 0.3163\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.2339 - accuracy: 0.3262\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.2163 - accuracy: 0.3301\n",
"start index for training is 146000\n",
"Train on 9950 samples, validate on 9950 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9950/9950 [==============================] - 0s 41us/sample - loss: 2.2181 - accuracy: 0.3204\n",
"9950/9950 [==============================] - 0s 38us/sample - loss: 2.1961 - accuracy: 0.3266\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2487 - accuracy: 0.2741\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.3014 - accuracy: 0.2649\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.2208 - accuracy: 0.3192\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2253 - accuracy: 0.3188\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.2085 - accuracy: 0.3267\n",
"start index for training is 147000\n",
"Train on 9500 samples, validate on 9500 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9500/9500 [==============================] - 0s 42us/sample - loss: 2.1900 - accuracy: 0.3337\n",
"9500/9500 [==============================] - 0s 39us/sample - loss: 2.1960 - accuracy: 0.3365\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2474 - accuracy: 0.2834\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.2978 - accuracy: 0.2685\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2182 - accuracy: 0.3087\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.2173 - accuracy: 0.3200\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1993 - accuracy: 0.3283\n",
"start index for training is 148000\n",
"Train on 12450 samples, validate on 12450 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12450/12450 [==============================] - 1s 74us/sample - loss: 2.1458 - accuracy: 0.3408\n",
"12450/12450 [==============================] - 1s 54us/sample - loss: 2.1489 - accuracy: 0.3445\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 2.2554 - accuracy: 0.2622\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.3008 - accuracy: 0.2703\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2382 - accuracy: 0.3116\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.2066 - accuracy: 0.3211\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.1784 - accuracy: 0.3237\n",
"start index for training is 149000\n",
"Train on 9830 samples, validate on 9830 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9830/9830 [==============================] - 0s 48us/sample - loss: 2.2083 - accuracy: 0.3208\n",
"9830/9830 [==============================] - 0s 44us/sample - loss: 2.2198 - accuracy: 0.3184\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.2471 - accuracy: 0.2736\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.2965 - accuracy: 0.2722\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.2284 - accuracy: 0.3071\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.2017 - accuracy: 0.3185\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.1726 - accuracy: 0.3236\n",
"start index for training is 150000\n",
"Train on 9245 samples, validate on 9245 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9245/9245 [==============================] - 0s 48us/sample - loss: 2.2186 - accuracy: 0.3120\n",
"9245/9245 [==============================] - 0s 45us/sample - loss: 2.2049 - accuracy: 0.3224\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.2511 - accuracy: 0.2567\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.3020 - accuracy: 0.2589\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2266 - accuracy: 0.3042\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.2015 - accuracy: 0.3189\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.1687 - accuracy: 0.3247\n",
"start index for training is 151000\n",
"Train on 11000 samples, validate on 11000 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11000/11000 [==============================] - 1s 51us/sample - loss: 2.1775 - accuracy: 0.3292\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11000/11000 [==============================] - 0s 45us/sample - loss: 2.1673 - accuracy: 0.3356\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.2665 - accuracy: 0.2721\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.3074 - accuracy: 0.2663\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.2349 - accuracy: 0.3089\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1906 - accuracy: 0.3279\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.1456 - accuracy: 0.3337\n",
"start index for training is 152000\n",
"Train on 10730 samples, validate on 10730 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10730/10730 [==============================] - 0s 46us/sample - loss: 2.2219 - accuracy: 0.3116\n",
"10730/10730 [==============================] - 0s 44us/sample - loss: 2.2188 - accuracy: 0.3198\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.2610 - accuracy: 0.2640\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 2.3042 - accuracy: 0.2634\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2308 - accuracy: 0.3129\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.1876 - accuracy: 0.3262\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.1411 - accuracy: 0.3369\n",
"start index for training is 153000\n",
"Train on 8370 samples, validate on 8375 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8370/8370 [==============================] - 0s 44us/sample - loss: 2.3152 - accuracy: 0.2683\n",
"8375/8375 [==============================] - 0s 42us/sample - loss: 2.3040 - accuracy: 0.2726\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1547 - accuracy: 0.3358\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.2917 - accuracy: 0.2723\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2019 - accuracy: 0.2918\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.2384 - accuracy: 0.3065\n",
"7000/7000 [==============================] - 0s 48us/sample - loss: 2.2173 - accuracy: 0.3080\n",
"start index for training is 154000\n",
"Train on 11070 samples, validate on 11075 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11070/11070 [==============================] - 1s 46us/sample - loss: 2.2189 - accuracy: 0.2863\n",
"11075/11075 [==============================] - 0s 42us/sample - loss: 2.2249 - accuracy: 0.2833\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 2.0891 - accuracy: 0.3075\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 2.3250 - accuracy: 0.2481\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2185 - accuracy: 0.2967\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3153 - accuracy: 0.2879\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.3066 - accuracy: 0.2914\n",
"start index for training is 155000\n",
"Train on 10755 samples, validate on 10760 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10755/10755 [==============================] - 0s 41us/sample - loss: 2.1972 - accuracy: 0.3048\n",
"10760/10760 [==============================] - 0s 39us/sample - loss: 2.2136 - accuracy: 0.2993\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0415 - accuracy: 0.3619\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3239 - accuracy: 0.2362\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2199 - accuracy: 0.2883\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3256 - accuracy: 0.2751\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3246 - accuracy: 0.2566\n",
"start index for training is 156000\n",
"Train on 11530 samples, validate on 11530 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11530/11530 [==============================] - 0s 43us/sample - loss: 2.1703 - accuracy: 0.3166\n",
"11530/11530 [==============================] - 0s 39us/sample - loss: 2.1764 - accuracy: 0.3136\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.0057 - accuracy: 0.3729\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3271 - accuracy: 0.2463\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2301 - accuracy: 0.2982\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3424 - accuracy: 0.2749\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3467 - accuracy: 0.2530\n",
"start index for training is 157000\n",
"Train on 12030 samples, validate on 12030 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12030/12030 [==============================] - 1s 43us/sample - loss: 2.1449 - accuracy: 0.3241\n",
"12030/12030 [==============================] - 1s 43us/sample - loss: 2.1569 - accuracy: 0.3219\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9766 - accuracy: 0.3881\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3166 - accuracy: 0.2412\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2357 - accuracy: 0.2891\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3417 - accuracy: 0.2708\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3457 - accuracy: 0.2516\n",
"start index for training is 158000\n",
"Train on 11840 samples, validate on 11845 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11840/11840 [==============================] - 0s 42us/sample - loss: 2.1224 - accuracy: 0.3389\n",
"11845/11845 [==============================] - 0s 41us/sample - loss: 2.1216 - accuracy: 0.3354\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9466 - accuracy: 0.4132\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.3272 - accuracy: 0.2440\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2366 - accuracy: 0.2921\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3688 - accuracy: 0.2621\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3745 - accuracy: 0.2357\n",
"start index for training is 159000\n",
"Train on 11550 samples, validate on 11550 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11550/11550 [==============================] - 0s 40us/sample - loss: 2.0970 - accuracy: 0.3433\n",
"11550/11550 [==============================] - 0s 40us/sample - loss: 2.1294 - accuracy: 0.3301\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9162 - accuracy: 0.4164\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.3216 - accuracy: 0.2445\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.2387 - accuracy: 0.2914\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3700 - accuracy: 0.2550\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3778 - accuracy: 0.2329\n",
"start index for training is 160000\n",
"Train on 10985 samples, validate on 10985 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10985/10985 [==============================] - 0s 41us/sample - loss: 2.0844 - accuracy: 0.3440\n",
"10985/10985 [==============================] - 0s 39us/sample - loss: 2.0951 - accuracy: 0.3417\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8982 - accuracy: 0.4151\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3225 - accuracy: 0.2458\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.2332 - accuracy: 0.2826\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3797 - accuracy: 0.2583\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3848 - accuracy: 0.2380\n",
"start index for training is 161000\n",
"Train on 10495 samples, validate on 10495 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10495/10495 [==============================] - 0s 43us/sample - loss: 2.1130 - accuracy: 0.3408\n",
"10495/10495 [==============================] - 0s 41us/sample - loss: 2.1052 - accuracy: 0.3324\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8991 - accuracy: 0.4258\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.3318 - accuracy: 0.2412\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.2341 - accuracy: 0.2925\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3879 - accuracy: 0.2555\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3931 - accuracy: 0.2350\n",
"start index for training is 162000\n",
"Train on 11845 samples, validate on 11850 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11845/11845 [==============================] - 1s 44us/sample - loss: 2.0287 - accuracy: 0.3664\n",
"11850/11850 [==============================] - 0s 40us/sample - loss: 2.0299 - accuracy: 0.3594\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8731 - accuracy: 0.4274\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3373 - accuracy: 0.2432\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2335 - accuracy: 0.2928\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.4034 - accuracy: 0.2572\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4092 - accuracy: 0.2389\n",
"start index for training is 163000\n",
"Train on 11900 samples, validate on 11905 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11900/11900 [==============================] - 1s 46us/sample - loss: 2.0367 - accuracy: 0.3628\n",
"11905/11905 [==============================] - 1s 43us/sample - loss: 2.0441 - accuracy: 0.3593\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.8601 - accuracy: 0.4341\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 2.3324 - accuracy: 0.2503\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2396 - accuracy: 0.2965\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.4023 - accuracy: 0.2487\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4065 - accuracy: 0.2323\n",
"start index for training is 164000\n",
"Train on 11880 samples, validate on 11885 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11880/11880 [==============================] - 1s 48us/sample - loss: 2.0120 - accuracy: 0.3720\n",
"11885/11885 [==============================] - 1s 43us/sample - loss: 2.0245 - accuracy: 0.3704\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 1.8487 - accuracy: 0.4326\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.3303 - accuracy: 0.2481\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2319 - accuracy: 0.2870\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.4118 - accuracy: 0.2447\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4181 - accuracy: 0.2289\n",
"start index for training is 165000\n",
"Train on 11435 samples, validate on 11435 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11435/11435 [==============================] - 1s 45us/sample - loss: 2.0239 - accuracy: 0.3543\n",
"11435/11435 [==============================] - 0s 39us/sample - loss: 2.0210 - accuracy: 0.3532\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8294 - accuracy: 0.4391\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.3326 - accuracy: 0.2483\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.2387 - accuracy: 0.2767\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.4208 - accuracy: 0.2440\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4268 - accuracy: 0.2286\n",
"start index for training is 166000\n",
"Train on 11770 samples, validate on 11775 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11770/11770 [==============================] - 1s 44us/sample - loss: 2.0064 - accuracy: 0.3634\n",
"11775/11775 [==============================] - 0s 39us/sample - loss: 2.0134 - accuracy: 0.3603\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8129 - accuracy: 0.4513\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.3237 - accuracy: 0.2476\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.2401 - accuracy: 0.2790\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.4218 - accuracy: 0.2516\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.4258 - accuracy: 0.2399\n",
"start index for training is 167000\n",
"Train on 11555 samples, validate on 11555 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11555/11555 [==============================] - 0s 42us/sample - loss: 2.0076 - accuracy: 0.3617\n",
"11555/11555 [==============================] - 0s 38us/sample - loss: 2.0225 - accuracy: 0.3532\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7991 - accuracy: 0.4654\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.3178 - accuracy: 0.2491\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2457 - accuracy: 0.2738\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.4263 - accuracy: 0.2508\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4313 - accuracy: 0.2394\n",
"start index for training is 168000\n",
"Train on 11715 samples, validate on 11715 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11715/11715 [==============================] - 1s 47us/sample - loss: 1.9862 - accuracy: 0.3611\n",
"11715/11715 [==============================] - 0s 41us/sample - loss: 2.0113 - accuracy: 0.3507\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7776 - accuracy: 0.4635\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.3126 - accuracy: 0.2557\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2463 - accuracy: 0.2763\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.4361 - accuracy: 0.2461\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4401 - accuracy: 0.2370\n",
"start index for training is 169000\n",
"Train on 11700 samples, validate on 11700 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11700/11700 [==============================] - 0s 41us/sample - loss: 1.9832 - accuracy: 0.3697\n",
"11700/11700 [==============================] - 0s 37us/sample - loss: 1.9944 - accuracy: 0.3619\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.7649 - accuracy: 0.4457\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.2983 - accuracy: 0.2564\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2541 - accuracy: 0.2740\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.4253 - accuracy: 0.2596\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4269 - accuracy: 0.2583\n",
"start index for training is 170000\n",
"Train on 11415 samples, validate on 11420 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11415/11415 [==============================] - 1s 56us/sample - loss: 1.9602 - accuracy: 0.3747\n",
"11420/11420 [==============================] - 1s 51us/sample - loss: 2.0038 - accuracy: 0.3641\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7494 - accuracy: 0.4550\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.2931 - accuracy: 0.2571\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2520 - accuracy: 0.2709\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.4327 - accuracy: 0.2565\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4346 - accuracy: 0.2573\n",
"start index for training is 171000\n",
"Train on 12060 samples, validate on 12060 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12060/12060 [==============================] - 1s 54us/sample - loss: 1.9798 - accuracy: 0.3631\n",
"12060/12060 [==============================] - 1s 48us/sample - loss: 1.9902 - accuracy: 0.3590\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.7526 - accuracy: 0.4590\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.2899 - accuracy: 0.2571\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2650 - accuracy: 0.2733\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.4297 - accuracy: 0.2589\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4307 - accuracy: 0.2626\n",
"start index for training is 172000\n",
"Train on 11855 samples, validate on 11855 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11855/11855 [==============================] - 1s 48us/sample - loss: 1.9850 - accuracy: 0.3557\n",
"11855/11855 [==============================] - 1s 50us/sample - loss: 1.9865 - accuracy: 0.3631\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 1.7390 - accuracy: 0.4617\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 2.2756 - accuracy: 0.2654\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2741 - accuracy: 0.2662\n",
"11565/11565 [==============================] - 1s 54us/sample - loss: 2.4328 - accuracy: 0.2624\n",
"7000/7000 [==============================] - 0s 66us/sample - loss: 2.4356 - accuracy: 0.2687\n",
"start index for training is 173000\n",
"Train on 13005 samples, validate on 13010 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13005/13005 [==============================] - 1s 58us/sample - loss: 1.9565 - accuracy: 0.3667\n",
"13010/13010 [==============================] - 1s 51us/sample - loss: 1.9549 - accuracy: 0.3666\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 1.7495 - accuracy: 0.4697\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 2.2683 - accuracy: 0.2574\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2959 - accuracy: 0.2783\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.4532 - accuracy: 0.2475\n",
"7000/7000 [==============================] - 0s 52us/sample - loss: 2.4494 - accuracy: 0.2507\n",
"start index for training is 174000\n",
"Train on 12040 samples, validate on 12045 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12040/12040 [==============================] - 1s 53us/sample - loss: 1.9797 - accuracy: 0.3587\n",
"12045/12045 [==============================] - 1s 45us/sample - loss: 1.9802 - accuracy: 0.3592\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.7306 - accuracy: 0.4711\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.2541 - accuracy: 0.2621\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2872 - accuracy: 0.2704\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.4412 - accuracy: 0.2581\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4481 - accuracy: 0.2617\n",
"start index for training is 175000\n",
"Train on 11540 samples, validate on 11545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11540/11540 [==============================] - 1s 59us/sample - loss: 1.9858 - accuracy: 0.3480\n",
"11545/11545 [==============================] - 0s 43us/sample - loss: 1.9933 - accuracy: 0.3515\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7313 - accuracy: 0.4667\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.2408 - accuracy: 0.2732\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.2971 - accuracy: 0.2704\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.4424 - accuracy: 0.2600\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4511 - accuracy: 0.2664\n",
"start index for training is 176000\n",
"Train on 11215 samples, validate on 11215 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11215/11215 [==============================] - 1s 47us/sample - loss: 1.9888 - accuracy: 0.3530\n",
"11215/11215 [==============================] - 1s 45us/sample - loss: 1.9955 - accuracy: 0.3497\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.7385 - accuracy: 0.4796\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.2280 - accuracy: 0.2726\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.3113 - accuracy: 0.2615\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.4456 - accuracy: 0.2553\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4533 - accuracy: 0.2686\n",
"start index for training is 177000\n",
"Train on 11140 samples, validate on 11140 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11140/11140 [==============================] - 0s 44us/sample - loss: 1.9898 - accuracy: 0.3436\n",
"11140/11140 [==============================] - 0s 40us/sample - loss: 1.9813 - accuracy: 0.3410\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.7466 - accuracy: 0.4584\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.2119 - accuracy: 0.2641\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.3092 - accuracy: 0.2616\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.4386 - accuracy: 0.2512\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.4453 - accuracy: 0.2584\n",
"start index for training is 178000\n",
"Train on 11195 samples, validate on 11200 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11195/11195 [==============================] - 0s 42us/sample - loss: 1.9701 - accuracy: 0.3496\n",
"11200/11200 [==============================] - 0s 37us/sample - loss: 1.9976 - accuracy: 0.3313\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7433 - accuracy: 0.4612\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1963 - accuracy: 0.2842\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3182 - accuracy: 0.2636\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.4467 - accuracy: 0.2559\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4598 - accuracy: 0.2683\n",
"start index for training is 179000\n",
"Train on 10715 samples, validate on 10720 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10715/10715 [==============================] - 1s 49us/sample - loss: 1.9727 - accuracy: 0.3434\n",
"10720/10720 [==============================] - 0s 40us/sample - loss: 1.9867 - accuracy: 0.3353\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7553 - accuracy: 0.4493\n",
"12255/12255 [==============================] - 1s 58us/sample - loss: 2.1853 - accuracy: 0.2819\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 63us/sample - loss: 2.3321 - accuracy: 0.2480\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.4544 - accuracy: 0.2415\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4665 - accuracy: 0.2466\n",
"start index for training is 180000\n",
"Train on 9935 samples, validate on 9935 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9935/9935 [==============================] - 0s 42us/sample - loss: 1.9895 - accuracy: 0.3344\n",
"9935/9935 [==============================] - 0s 37us/sample - loss: 1.9845 - accuracy: 0.3425\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7582 - accuracy: 0.4545\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1647 - accuracy: 0.2848\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3430 - accuracy: 0.2501\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.4567 - accuracy: 0.2425\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4727 - accuracy: 0.2453\n",
"start index for training is 181000\n",
"Train on 11355 samples, validate on 11360 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11355/11355 [==============================] - 1s 46us/sample - loss: 1.9529 - accuracy: 0.3450\n",
"11360/11360 [==============================] - 0s 40us/sample - loss: 1.9561 - accuracy: 0.3438\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.7775 - accuracy: 0.4565\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1344 - accuracy: 0.2891\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3734 - accuracy: 0.2494\n",
"11565/11565 [==============================] - 1s 60us/sample - loss: 2.4577 - accuracy: 0.2436\n",
"7000/7000 [==============================] - 1s 81us/sample - loss: 2.4718 - accuracy: 0.2464\n",
"start index for training is 182000\n",
"Train on 10640 samples, validate on 10640 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10640/10640 [==============================] - 1s 48us/sample - loss: 1.9812 - accuracy: 0.3488\n",
"10640/10640 [==============================] - 0s 43us/sample - loss: 1.9685 - accuracy: 0.3557\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7808 - accuracy: 0.4609\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1124 - accuracy: 0.3033\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.3741 - accuracy: 0.2527\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.4640 - accuracy: 0.2430\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4803 - accuracy: 0.2427\n",
"start index for training is 183000\n",
"Train on 9855 samples, validate on 9855 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9855/9855 [==============================] - 1s 62us/sample - loss: 1.9904 - accuracy: 0.3426\n",
"9855/9855 [==============================] - 0s 51us/sample - loss: 1.9935 - accuracy: 0.3514\n",
"5980/5980 [==============================] - 0s 61us/sample - loss: 1.7932 - accuracy: 0.4502\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 2.0901 - accuracy: 0.2937\n",
"14070/14070 [==============================] - 1s 59us/sample - loss: 2.3909 - accuracy: 0.2493\n",
"11565/11565 [==============================] - 1s 56us/sample - loss: 2.4629 - accuracy: 0.2366\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4781 - accuracy: 0.2384\n",
"start index for training is 184000\n",
"Train on 9540 samples, validate on 9540 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9540/9540 [==============================] - 0s 46us/sample - loss: 2.0118 - accuracy: 0.3357\n",
"9540/9540 [==============================] - 0s 47us/sample - loss: 1.9929 - accuracy: 0.3322\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.8043 - accuracy: 0.4435\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0741 - accuracy: 0.2921\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.3998 - accuracy: 0.2479\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.4669 - accuracy: 0.2380\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4811 - accuracy: 0.2400\n",
"start index for training is 185000\n",
"Train on 9575 samples, validate on 9580 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9575/9575 [==============================] - 0s 47us/sample - loss: 2.0123 - accuracy: 0.3366\n",
"9580/9580 [==============================] - 0s 41us/sample - loss: 1.9973 - accuracy: 0.3324\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8147 - accuracy: 0.4428\n",
"12255/12255 [==============================] - 1s 54us/sample - loss: 2.0541 - accuracy: 0.3109\n",
"14070/14070 [==============================] - 1s 58us/sample - loss: 2.4077 - accuracy: 0.2490\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.4648 - accuracy: 0.2377\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4795 - accuracy: 0.2364\n",
"start index for training is 186000\n",
"Train on 10735 samples, validate on 10735 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10735/10735 [==============================] - 1s 47us/sample - loss: 1.9732 - accuracy: 0.3576\n",
"10735/10735 [==============================] - 0s 45us/sample - loss: 1.9827 - accuracy: 0.3456\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8232 - accuracy: 0.4463\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0311 - accuracy: 0.3177\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4212 - accuracy: 0.2472\n",
"11565/11565 [==============================] - 1s 63us/sample - loss: 2.4740 - accuracy: 0.2366\n",
"7000/7000 [==============================] - 0s 69us/sample - loss: 2.4883 - accuracy: 0.2351\n",
"start index for training is 187000\n",
"Train on 10195 samples, validate on 10200 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10195/10195 [==============================] - 0s 44us/sample - loss: 1.9817 - accuracy: 0.3587\n",
"10200/10200 [==============================] - 0s 43us/sample - loss: 2.0091 - accuracy: 0.3486\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.8434 - accuracy: 0.4224\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.0093 - accuracy: 0.3262\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.4400 - accuracy: 0.2531\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.4708 - accuracy: 0.2446\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4800 - accuracy: 0.2494\n",
"start index for training is 188000\n",
"Train on 9685 samples, validate on 9685 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9685/9685 [==============================] - 0s 43us/sample - loss: 2.0076 - accuracy: 0.3389\n",
"9685/9685 [==============================] - 0s 41us/sample - loss: 2.0128 - accuracy: 0.3409\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.8546 - accuracy: 0.4274s - loss: 1.8593 - accuracy: \n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.9940 - accuracy: 0.3325\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.4387 - accuracy: 0.2416\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.4689 - accuracy: 0.2386\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4771 - accuracy: 0.2377\n",
"start index for training is 189000\n",
"Train on 9200 samples, validate on 9205 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9200/9200 [==============================] - 0s 42us/sample - loss: 2.0209 - accuracy: 0.3387\n",
"9205/9205 [==============================] - 0s 46us/sample - loss: 2.0122 - accuracy: 0.3420\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8558 - accuracy: 0.4159\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9788 - accuracy: 0.3410\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4392 - accuracy: 0.2418\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.4678 - accuracy: 0.2415\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.4755 - accuracy: 0.2426\n",
"start index for training is 190000\n",
"Train on 9230 samples, validate on 9230 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9230/9230 [==============================] - 0s 43us/sample - loss: 2.0017 - accuracy: 0.3476\n",
"9230/9230 [==============================] - 0s 42us/sample - loss: 2.0351 - accuracy: 0.3449\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.8780 - accuracy: 0.4052\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.9628 - accuracy: 0.3582\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.4642 - accuracy: 0.2306\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.4646 - accuracy: 0.2383\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4681 - accuracy: 0.2361\n",
"start index for training is 191000\n",
"Train on 10635 samples, validate on 10640 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10635/10635 [==============================] - 0s 45us/sample - loss: 2.0196 - accuracy: 0.3529\n",
"10640/10640 [==============================] - 0s 45us/sample - loss: 2.0007 - accuracy: 0.3643\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.8711 - accuracy: 0.4197\n",
"12255/12255 [==============================] - 1s 52us/sample - loss: 1.9518 - accuracy: 0.3661\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.4471 - accuracy: 0.2461\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.4600 - accuracy: 0.2509\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4653 - accuracy: 0.2467\n",
"start index for training is 192000\n",
"Train on 9540 samples, validate on 9545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9540/9540 [==============================] - 0s 49us/sample - loss: 2.0428 - accuracy: 0.3556\n",
"9545/9545 [==============================] - 0s 47us/sample - loss: 2.0534 - accuracy: 0.3514\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.8899 - accuracy: 0.4013\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9465 - accuracy: 0.3717\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.4708 - accuracy: 0.2399\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.4621 - accuracy: 0.2575\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4658 - accuracy: 0.2479\n",
"start index for training is 193000\n",
"Train on 9440 samples, validate on 9440 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9440/9440 [==============================] - 0s 53us/sample - loss: 2.0685 - accuracy: 0.3553\n",
"9440/9440 [==============================] - 0s 39us/sample - loss: 2.0653 - accuracy: 0.3495\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8996 - accuracy: 0.3844\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.9485 - accuracy: 0.3795\n",
"14070/14070 [==============================] - 1s 53us/sample - loss: 2.4739 - accuracy: 0.2326\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.4569 - accuracy: 0.2467\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4585 - accuracy: 0.2361\n",
"start index for training is 194000\n",
"Train on 9375 samples, validate on 9375 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9375/9375 [==============================] - 0s 45us/sample - loss: 2.0792 - accuracy: 0.3466\n",
"9375/9375 [==============================] - 0s 50us/sample - loss: 2.0829 - accuracy: 0.3461\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.9245 - accuracy: 0.4013\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.9522 - accuracy: 0.3754\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4916 - accuracy: 0.2331\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.4557 - accuracy: 0.2475\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4604 - accuracy: 0.2349\n",
"start index for training is 195000\n",
"Train on 9110 samples, validate on 9115 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9110/9110 [==============================] - 0s 44us/sample - loss: 2.1011 - accuracy: 0.3344\n",
"9115/9115 [==============================] - 0s 41us/sample - loss: 2.1045 - accuracy: 0.3348\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9165 - accuracy: 0.3739\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9496 - accuracy: 0.3772\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.4798 - accuracy: 0.2274\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.4467 - accuracy: 0.2502\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4493 - accuracy: 0.2386\n",
"start index for training is 196000\n",
"Train on 8295 samples, validate on 8300 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8295/8295 [==============================] - 0s 43us/sample - loss: 2.1300 - accuracy: 0.3355\n",
"8300/8300 [==============================] - 0s 42us/sample - loss: 2.0990 - accuracy: 0.3445\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9306 - accuracy: 0.4020\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9626 - accuracy: 0.3772\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.4947 - accuracy: 0.2380\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.4538 - accuracy: 0.2588\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4565 - accuracy: 0.2490\n",
"start index for training is 197000\n",
"Train on 8860 samples, validate on 8860 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8860/8860 [==============================] - 1s 74us/sample - loss: 2.1327 - accuracy: 0.3344\n",
"8860/8860 [==============================] - 0s 43us/sample - loss: 2.1410 - accuracy: 0.3359\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.9408 - accuracy: 0.3903\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9648 - accuracy: 0.3745\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.5041 - accuracy: 0.2338\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.4556 - accuracy: 0.2621\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4574 - accuracy: 0.2546\n",
"start index for training is 198000\n",
"Train on 9285 samples, validate on 9285 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9285/9285 [==============================] - 1s 74us/sample - loss: 2.1154 - accuracy: 0.3459\n",
"9285/9285 [==============================] - 1s 76us/sample - loss: 2.1225 - accuracy: 0.3440\n",
"5980/5980 [==============================] - 0s 77us/sample - loss: 1.9582 - accuracy: 0.3938\n",
"12255/12255 [==============================] - 1s 74us/sample - loss: 1.9763 - accuracy: 0.3684\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.5194 - accuracy: 0.2200\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.4547 - accuracy: 0.2573\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4553 - accuracy: 0.2490\n",
"start index for training is 199000\n",
"Train on 7605 samples, validate on 7605 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7605/7605 [==============================] - 0s 41us/sample - loss: 2.1572 - accuracy: 0.3265\n",
"7605/7605 [==============================] - 0s 38us/sample - loss: 2.1481 - accuracy: 0.3266\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9494 - accuracy: 0.3963\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9747 - accuracy: 0.3657s - loss: 1.9833 - accu\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.5149 - accuracy: 0.2225\n",
"11565/11565 [==============================] - 1s 57us/sample - loss: 2.4599 - accuracy: 0.2572\n",
"7000/7000 [==============================] - 1s 89us/sample - loss: 2.4623 - accuracy: 0.2524\n",
"start index for training is 200000\n",
"Train on 9480 samples, validate on 9480 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9480/9480 [==============================] - 1s 104us/sample - loss: 2.1276 - accuracy: 0.3388\n",
"9480/9480 [==============================] - 1s 80us/sample - loss: 2.1434 - accuracy: 0.3334\n",
"5980/5980 [==============================] - 0s 62us/sample - loss: 1.9509 - accuracy: 0.3936\n",
"12255/12255 [==============================] - 1s 53us/sample - loss: 1.9951 - accuracy: 0.3696\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.5112 - accuracy: 0.2231\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.4601 - accuracy: 0.2550\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4632 - accuracy: 0.2507\n",
"start index for training is 201000\n",
"Train on 7355 samples, validate on 7355 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7355/7355 [==============================] - 0s 46us/sample - loss: 2.1511 - accuracy: 0.3296\n",
"7355/7355 [==============================] - 0s 42us/sample - loss: 2.1698 - accuracy: 0.3263\n",
"5980/5980 [==============================] - 0s 56us/sample - loss: 1.9573 - accuracy: 0.4002\n",
"12255/12255 [==============================] - 1s 64us/sample - loss: 1.9987 - accuracy: 0.3647\n",
"14070/14070 [==============================] - 1s 57us/sample - loss: 2.5259 - accuracy: 0.2197\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 2.4746 - accuracy: 0.2470\n",
"7000/7000 [==============================] - 0s 55us/sample - loss: 2.4772 - accuracy: 0.2407\n",
"start index for training is 202000\n",
"Train on 9125 samples, validate on 9130 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9125/9125 [==============================] - 0s 44us/sample - loss: 2.1483 - accuracy: 0.3341\n",
"9130/9130 [==============================] - 0s 42us/sample - loss: 2.1617 - accuracy: 0.3310\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.9401 - accuracy: 0.3953\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0002 - accuracy: 0.3536\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4925 - accuracy: 0.2342\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.4584 - accuracy: 0.2535\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4577 - accuracy: 0.2494\n",
"start index for training is 203000\n",
"Train on 7470 samples, validate on 7470 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7470/7470 [==============================] - 0s 57us/sample - loss: 2.1764 - accuracy: 0.3229\n",
"7470/7470 [==============================] - ETA: 0s - loss: 2.1915 - accuracy: 0.32 - 1s 127us/sample - loss: 2.1933 - accuracy: 0.3258\n",
"5980/5980 [==============================] - 1s 135us/sample - loss: 1.9584 - accuracy: 0.3895\n",
"12255/12255 [==============================] - 1s 113us/sample - loss: 2.0149 - accuracy: 0.3506\n",
"14070/14070 [==============================] - 1s 87us/sample - loss: 2.5021 - accuracy: 0.2291\n",
"11565/11565 [==============================] - 1s 85us/sample - loss: 2.4672 - accuracy: 0.2542\n",
"7000/7000 [==============================] - 0s 57us/sample - loss: 2.4706 - accuracy: 0.2530\n",
"start index for training is 204000\n",
"Train on 9015 samples, validate on 9015 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9015/9015 [==============================] - 0s 50us/sample - loss: 2.1532 - accuracy: 0.3334\n",
"9015/9015 [==============================] - 1s 73us/sample - loss: 2.1487 - accuracy: 0.3310\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.9597 - accuracy: 0.3962\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0366 - accuracy: 0.3457\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4980 - accuracy: 0.2272\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.4747 - accuracy: 0.2524\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4756 - accuracy: 0.2486\n",
"start index for training is 205000\n",
"Train on 8610 samples, validate on 8610 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8610/8610 [==============================] - 1s 110us/sample - loss: 2.2149 - accuracy: 0.3086\n",
"8610/8610 [==============================] - 1s 85us/sample - loss: 2.2402 - accuracy: 0.2993\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 1.9255 - accuracy: 0.3774\n",
"12255/12255 [==============================] - 1s 59us/sample - loss: 2.0640 - accuracy: 0.3208\n",
"14070/14070 [==============================] - 1s 58us/sample - loss: 2.2493 - accuracy: 0.3014\n",
"11565/11565 [==============================] - 1s 61us/sample - loss: 2.4004 - accuracy: 0.2713\n",
"7000/7000 [==============================] - 0s 66us/sample - loss: 2.4011 - accuracy: 0.2660\n",
"start index for training is 206000\n",
"Train on 10375 samples, validate on 10380 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10375/10375 [==============================] - 1s 56us/sample - loss: 2.1918 - accuracy: 0.3050\n",
"10380/10380 [==============================] - 1s 60us/sample - loss: 2.1934 - accuracy: 0.3081\n",
"5980/5980 [==============================] - 0s 55us/sample - loss: 1.9652 - accuracy: 0.3495\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 2.1368 - accuracy: 0.2922\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.1724 - accuracy: 0.3211\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.4138 - accuracy: 0.2621\n",
"7000/7000 [==============================] - 0s 48us/sample - loss: 2.4176 - accuracy: 0.2544\n",
"start index for training is 207000\n",
"Train on 11010 samples, validate on 11015 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11010/11010 [==============================] - 1s 69us/sample - loss: 2.2171 - accuracy: 0.3010\n",
"11015/11015 [==============================] - 1s 73us/sample - loss: 2.2373 - accuracy: 0.2913\n",
"5980/5980 [==============================] - 1s 94us/sample - loss: 2.0269 - accuracy: 0.3510\n",
"12255/12255 [==============================] - 1s 65us/sample - loss: 2.1614 - accuracy: 0.2893\n",
"14070/14070 [==============================] - 1s 67us/sample - loss: 2.1802 - accuracy: 0.3104\n",
"11565/11565 [==============================] - 1s 75us/sample - loss: 2.3846 - accuracy: 0.2614\n",
"7000/7000 [==============================] - 0s 67us/sample - loss: 2.3787 - accuracy: 0.2671\n",
"start index for training is 208000\n",
"Train on 10735 samples, validate on 10735 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10735/10735 [==============================] - 1s 61us/sample - loss: 2.1622 - accuracy: 0.3412\n",
"10735/10735 [==============================] - 1s 56us/sample - loss: 2.1822 - accuracy: 0.3286\n",
"5980/5980 [==============================] - 0s 53us/sample - loss: 1.9959 - accuracy: 0.3627\n",
"12255/12255 [==============================] - 1s 56us/sample - loss: 2.1868 - accuracy: 0.2800\n",
"14070/14070 [==============================] - 1s 67us/sample - loss: 2.1003 - accuracy: 0.3613\n",
"11565/11565 [==============================] - 1s 62us/sample - loss: 2.4011 - accuracy: 0.2589\n",
"7000/7000 [==============================] - 0s 63us/sample - loss: 2.4072 - accuracy: 0.2511\n",
"start index for training is 209000\n",
"Train on 10680 samples, validate on 10685 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10680/10680 [==============================] - 1s 70us/sample - loss: 2.1454 - accuracy: 0.3328\n",
"10685/10685 [==============================] - 1s 61us/sample - loss: 2.1407 - accuracy: 0.3409\n",
"5980/5980 [==============================] - 0s 60us/sample - loss: 2.0056 - accuracy: 0.3520\n",
"12255/12255 [==============================] - 1s 68us/sample - loss: 2.2040 - accuracy: 0.2736\n",
"14070/14070 [==============================] - 1s 65us/sample - loss: 2.0752 - accuracy: 0.3610\n",
"11565/11565 [==============================] - 1s 65us/sample - loss: 2.3969 - accuracy: 0.2588\n",
"7000/7000 [==============================] - 0s 70us/sample - loss: 2.4022 - accuracy: 0.2481\n",
"start index for training is 210000\n",
"Train on 10700 samples, validate on 10700 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10700/10700 [==============================] - 1s 86us/sample - loss: 2.1230 - accuracy: 0.3461\n",
"10700/10700 [==============================] - 1s 87us/sample - loss: 2.1267 - accuracy: 0.3466\n",
"5980/5980 [==============================] - 0s 74us/sample - loss: 2.0198 - accuracy: 0.3478\n",
"12255/12255 [==============================] - 1s 72us/sample - loss: 2.2135 - accuracy: 0.2698\n",
"14070/14070 [==============================] - 1s 73us/sample - loss: 2.0556 - accuracy: 0.3687\n",
"11565/11565 [==============================] - 1s 65us/sample - loss: 2.3918 - accuracy: 0.2611\n",
"7000/7000 [==============================] - 0s 59us/sample - loss: 2.3954 - accuracy: 0.2510\n",
"start index for training is 211000\n",
"Train on 11685 samples, validate on 11685 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11685/11685 [==============================] - 1s 72us/sample - loss: 2.0645 - accuracy: 0.3638\n",
"11685/11685 [==============================] - 1s 69us/sample - loss: 2.0406 - accuracy: 0.3774\n",
"5980/5980 [==============================] - 0s 79us/sample - loss: 2.0213 - accuracy: 0.3440\n",
"12255/12255 [==============================] - 1s 72us/sample - loss: 2.2230 - accuracy: 0.2614\n",
"14070/14070 [==============================] - 1s 57us/sample - loss: 2.0362 - accuracy: 0.3735\n",
"11565/11565 [==============================] - 1s 57us/sample - loss: 2.4022 - accuracy: 0.2651\n",
"7000/7000 [==============================] - 0s 54us/sample - loss: 2.4088 - accuracy: 0.2543\n",
"start index for training is 212000\n",
"Train on 12010 samples, validate on 12015 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12010/12010 [==============================] - 1s 60us/sample - loss: 2.0760 - accuracy: 0.3520\n",
"12015/12015 [==============================] - 1s 56us/sample - loss: 2.0689 - accuracy: 0.3508\n",
"5980/5980 [==============================] - 0s 55us/sample - loss: 2.0620 - accuracy: 0.3467\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 2.2643 - accuracy: 0.2611\n",
"14070/14070 [==============================] - 1s 54us/sample - loss: 2.0316 - accuracy: 0.3669\n",
"11565/11565 [==============================] - 1s 51us/sample - loss: 2.4333 - accuracy: 0.2540\n",
"7000/7000 [==============================] - 0s 53us/sample - loss: 2.4351 - accuracy: 0.2440\n",
"start index for training is 213000\n",
"Train on 10510 samples, validate on 10515 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10510/10510 [==============================] - 1s 77us/sample - loss: 2.0523 - accuracy: 0.3614\n",
"10515/10515 [==============================] - 1s 69us/sample - loss: 2.0589 - accuracy: 0.3640\n",
"5980/5980 [==============================] - 0s 65us/sample - loss: 2.0402 - accuracy: 0.3418\n",
"12255/12255 [==============================] - 1s 58us/sample - loss: 2.2437 - accuracy: 0.2585\n",
"14070/14070 [==============================] - 1s 51us/sample - loss: 2.0103 - accuracy: 0.3794\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.4011 - accuracy: 0.2638\n",
"7000/7000 [==============================] - 0s 60us/sample - loss: 2.4061 - accuracy: 0.2547\n",
"start index for training is 214000\n",
"Train on 12390 samples, validate on 12395 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12390/12390 [==============================] - 1s 55us/sample - loss: 1.9820 - accuracy: 0.3906\n",
"12395/12395 [==============================] - 1s 61us/sample - loss: 1.9788 - accuracy: 0.3913\n",
"5980/5980 [==============================] - 0s 59us/sample - loss: 2.0567 - accuracy: 0.3341\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 2.2634 - accuracy: 0.2528\n",
"14070/14070 [==============================] - 1s 51us/sample - loss: 1.9940 - accuracy: 0.3871\n",
"11565/11565 [==============================] - 1s 51us/sample - loss: 2.4143 - accuracy: 0.2628\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.4208 - accuracy: 0.2554\n",
"start index for training is 215000\n",
"Train on 11185 samples, validate on 11185 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11185/11185 [==============================] - 1s 54us/sample - loss: 2.0069 - accuracy: 0.3720\n",
"11185/11185 [==============================] - 1s 52us/sample - loss: 2.0241 - accuracy: 0.3669\n",
"5980/5980 [==============================] - 0s 55us/sample - loss: 2.0627 - accuracy: 0.3418\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 2.2724 - accuracy: 0.2592\n",
"14070/14070 [==============================] - 1s 66us/sample - loss: 1.9849 - accuracy: 0.3861\n",
"11565/11565 [==============================] - 1s 85us/sample - loss: 2.4150 - accuracy: 0.2614\n",
"7000/7000 [==============================] - 0s 51us/sample - loss: 2.4222 - accuracy: 0.2537\n",
"start index for training is 216000\n",
"Train on 11815 samples, validate on 11820 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11815/11815 [==============================] - 1s 59us/sample - loss: 1.9510 - accuracy: 0.3870\n",
"11820/11820 [==============================] - 1s 57us/sample - loss: 1.9484 - accuracy: 0.3928\n",
"5980/5980 [==============================] - 0s 59us/sample - loss: 2.0757 - accuracy: 0.3395\n",
"12255/12255 [==============================] - 1s 54us/sample - loss: 2.2792 - accuracy: 0.2616\n",
"14070/14070 [==============================] - 1s 53us/sample - loss: 1.9759 - accuracy: 0.3828\n",
"11565/11565 [==============================] - 1s 58us/sample - loss: 2.4186 - accuracy: 0.2568\n",
"7000/7000 [==============================] - 0s 60us/sample - loss: 2.4245 - accuracy: 0.2490\n",
"start index for training is 217000\n",
"Train on 12280 samples, validate on 12280 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12280/12280 [==============================] - 1s 100us/sample - loss: 1.9759 - accuracy: 0.3867\n",
"12280/12280 [==============================] - 1s 81us/sample - loss: 1.9633 - accuracy: 0.3844\n",
"5980/5980 [==============================] - 0s 65us/sample - loss: 2.0644 - accuracy: 0.3125\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 1s 84us/sample - loss: 2.2871 - accuracy: 0.2501\n",
"14070/14070 [==============================] - 1s 74us/sample - loss: 1.9661 - accuracy: 0.3977\n",
"11565/11565 [==============================] - 1s 67us/sample - loss: 2.4231 - accuracy: 0.2593\n",
"7000/7000 [==============================] - 0s 63us/sample - loss: 2.4319 - accuracy: 0.2503\n",
"start index for training is 218000\n",
"Train on 11295 samples, validate on 11295 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11295/11295 [==============================] - 1s 65us/sample - loss: 1.9580 - accuracy: 0.3896\n",
"11295/11295 [==============================] - 1s 96us/sample - loss: 1.9884 - accuracy: 0.3916\n",
"5980/5980 [==============================] - 0s 81us/sample - loss: 2.0744 - accuracy: 0.3201\n",
"12255/12255 [==============================] - 1s 75us/sample - loss: 2.3008 - accuracy: 0.2450\n",
"14070/14070 [==============================] - 1s 61us/sample - loss: 1.9609 - accuracy: 0.4029\n",
"11565/11565 [==============================] - 1s 74us/sample - loss: 2.4327 - accuracy: 0.2503\n",
"7000/7000 [==============================] - 1s 84us/sample - loss: 2.4417 - accuracy: 0.2406\n",
"start index for training is 219000\n",
"Train on 13870 samples, validate on 13875 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13870/13870 [==============================] - 1s 101us/sample - loss: 1.8891 - accuracy: 0.4205\n",
"13875/13875 [==============================] - 1s 92us/sample - loss: 1.8948 - accuracy: 0.4135\n",
"5980/5980 [==============================] - 1s 94us/sample - loss: 2.0850 - accuracy: 0.3259\n",
"12255/12255 [==============================] - 1s 82us/sample - loss: 2.3011 - accuracy: 0.2498\n",
"14070/14070 [==============================] - 1s 60us/sample - loss: 1.9587 - accuracy: 0.4008\n",
"11565/11565 [==============================] - 1s 60us/sample - loss: 2.4352 - accuracy: 0.2593\n",
"7000/7000 [==============================] - 0s 51us/sample - loss: 2.4456 - accuracy: 0.2493\n",
"start index for training is 220000\n",
"Train on 11840 samples, validate on 11845 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11840/11840 [==============================] - 1s 90us/sample - loss: 1.9421 - accuracy: 0.4011\n",
"11845/11845 [==============================] - 1s 69us/sample - loss: 1.9492 - accuracy: 0.3893\n",
"5980/5980 [==============================] - 1s 97us/sample - loss: 2.0809 - accuracy: 0.3313\n",
"12255/12255 [==============================] - 1s 56us/sample - loss: 2.2947 - accuracy: 0.2596\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 1.9548 - accuracy: 0.3957\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 2.4243 - accuracy: 0.2583\n",
"7000/7000 [==============================] - 0s 54us/sample - loss: 2.4376 - accuracy: 0.2430\n",
"start index for training is 221000\n",
"Train on 14450 samples, validate on 14455 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14450/14450 [==============================] - 1s 68us/sample - loss: 1.8745 - accuracy: 0.4244\n",
"14455/14455 [==============================] - 1s 65us/sample - loss: 1.8713 - accuracy: 0.4254\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 2.0928 - accuracy: 0.3227\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 2.3057 - accuracy: 0.2470\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.9548 - accuracy: 0.4010\n",
"11565/11565 [==============================] - 1s 52us/sample - loss: 2.4389 - accuracy: 0.2547\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.4514 - accuracy: 0.2387\n",
"start index for training is 222000\n",
"Train on 11575 samples, validate on 11580 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11575/11575 [==============================] - 1s 76us/sample - loss: 1.9332 - accuracy: 0.3939\n",
"11580/11580 [==============================] - 1s 53us/sample - loss: 1.9623 - accuracy: 0.3909\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 2.0887 - accuracy: 0.3278\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 2.2976 - accuracy: 0.2539\n",
"14070/14070 [==============================] - 1s 58us/sample - loss: 1.9497 - accuracy: 0.4043\n",
"11565/11565 [==============================] - 1s 60us/sample - loss: 2.4210 - accuracy: 0.2604\n",
"7000/7000 [==============================] - 0s 64us/sample - loss: 2.4344 - accuracy: 0.2474\n",
"start index for training is 223000\n",
"Train on 14065 samples, validate on 14065 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14065/14065 [==============================] - 1s 57us/sample - loss: 1.8753 - accuracy: 0.4318\n",
"14065/14065 [==============================] - 1s 55us/sample - loss: 1.8573 - accuracy: 0.4279\n",
"5980/5980 [==============================] - 0s 63us/sample - loss: 2.0902 - accuracy: 0.3059\n",
"12255/12255 [==============================] - 1s 61us/sample - loss: 2.3038 - accuracy: 0.2454\n",
"14070/14070 [==============================] - 1s 51us/sample - loss: 1.9535 - accuracy: 0.4077\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.4324 - accuracy: 0.2642\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.4507 - accuracy: 0.2539\n",
"start index for training is 224000\n",
"Train on 11435 samples, validate on 11435 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11435/11435 [==============================] - 1s 51us/sample - loss: 1.9119 - accuracy: 0.3985\n",
"11435/11435 [==============================] - 1s 49us/sample - loss: 1.9415 - accuracy: 0.3844\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.1042 - accuracy: 0.3095\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.3095 - accuracy: 0.2301\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.9565 - accuracy: 0.3959\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.4320 - accuracy: 0.2359\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.4520 - accuracy: 0.2183\n",
"start index for training is 225000\n",
"Train on 13950 samples, validate on 13955 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13950/13950 [==============================] - 1s 53us/sample - loss: 1.8666 - accuracy: 0.4178\n",
"13955/13955 [==============================] - 1s 52us/sample - loss: 1.8618 - accuracy: 0.4212\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1223 - accuracy: 0.3042\n",
"12255/12255 [==============================] - 1s 50us/sample - loss: 2.3117 - accuracy: 0.2445\n",
"14070/14070 [==============================] - 1s 51us/sample - loss: 1.9610 - accuracy: 0.4069\n",
"11565/11565 [==============================] - 1s 49us/sample - loss: 2.4328 - accuracy: 0.2657\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.4514 - accuracy: 0.2549\n",
"start index for training is 226000\n",
"Train on 11765 samples, validate on 11765 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11765/11765 [==============================] - 1s 48us/sample - loss: 1.9068 - accuracy: 0.4071\n",
"11765/11765 [==============================] - 1s 44us/sample - loss: 1.9237 - accuracy: 0.4109\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1214 - accuracy: 0.2960\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3035 - accuracy: 0.2437\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9605 - accuracy: 0.4045\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.4170 - accuracy: 0.2638\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4359 - accuracy: 0.2527\n",
"start index for training is 227000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Train on 13025 samples, validate on 13025 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13025/13025 [==============================] - 1s 43us/sample - loss: 1.8910 - accuracy: 0.4185\n",
"13025/13025 [==============================] - 1s 40us/sample - loss: 1.8876 - accuracy: 0.4191\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1658 - accuracy: 0.2860\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.3494 - accuracy: 0.2281\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.9965 - accuracy: 0.3965\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.4771 - accuracy: 0.2450\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4982 - accuracy: 0.2289\n",
"start index for training is 228000\n",
"Train on 12215 samples, validate on 12215 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12215/12215 [==============================] - 1s 52us/sample - loss: 1.8593 - accuracy: 0.4173\n",
"12215/12215 [==============================] - 1s 48us/sample - loss: 1.8543 - accuracy: 0.4135\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 2.1363 - accuracy: 0.2940\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 2.2990 - accuracy: 0.2477\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.9713 - accuracy: 0.3999\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.4157 - accuracy: 0.2701\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4366 - accuracy: 0.2581\n",
"start index for training is 229000\n",
"Train on 11585 samples, validate on 11585 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11585/11585 [==============================] - 1s 46us/sample - loss: 1.8725 - accuracy: 0.4114\n",
"11585/11585 [==============================] - 1s 46us/sample - loss: 1.8911 - accuracy: 0.4076\n",
"5980/5980 [==============================] - 0s 66us/sample - loss: 2.1308 - accuracy: 0.2926\n",
"12255/12255 [==============================] - 1s 79us/sample - loss: 2.2845 - accuracy: 0.2406\n",
"14070/14070 [==============================] - 1s 72us/sample - loss: 1.9729 - accuracy: 0.3978\n",
"11565/11565 [==============================] - 1s 71us/sample - loss: 2.3993 - accuracy: 0.2648\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.4213 - accuracy: 0.2554\n",
"start index for training is 230000\n",
"Train on 11565 samples, validate on 11570 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 1.8904 - accuracy: 0.4087\n",
"11570/11570 [==============================] - 1s 54us/sample - loss: 1.9064 - accuracy: 0.4001\n",
"5980/5980 [==============================] - 0s 69us/sample - loss: 2.1386 - accuracy: 0.2794\n",
"12255/12255 [==============================] - 1s 64us/sample - loss: 2.2823 - accuracy: 0.2525\n",
"14070/14070 [==============================] - 1s 65us/sample - loss: 1.9854 - accuracy: 0.3867\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 2.3872 - accuracy: 0.2805\n",
"7000/7000 [==============================] - 0s 59us/sample - loss: 2.4082 - accuracy: 0.2780\n",
"start index for training is 231000\n",
"Train on 12275 samples, validate on 12280 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12275/12275 [==============================] - 1s 59us/sample - loss: 1.8713 - accuracy: 0.4152\n",
"12280/12280 [==============================] - 1s 60us/sample - loss: 1.8653 - accuracy: 0.4227\n",
"5980/5980 [==============================] - 0s 63us/sample - loss: 2.1318 - accuracy: 0.2865\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 2.2657 - accuracy: 0.2589\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.9906 - accuracy: 0.3844\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3628 - accuracy: 0.2853\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.3839 - accuracy: 0.2864\n",
"start index for training is 232000\n",
"Train on 11665 samples, validate on 11665 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11665/11665 [==============================] - 1s 74us/sample - loss: 1.8996 - accuracy: 0.4077\n",
"11665/11665 [==============================] - 1s 63us/sample - loss: 1.8975 - accuracy: 0.4054\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.1386 - accuracy: 0.2861\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.2726 - accuracy: 0.2477\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.9907 - accuracy: 0.3893\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.3549 - accuracy: 0.2795\n",
"7000/7000 [==============================] - 0s 53us/sample - loss: 2.3821 - accuracy: 0.2707\n",
"start index for training is 233000\n",
"Train on 10930 samples, validate on 10935 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10930/10930 [==============================] - 1s 48us/sample - loss: 1.9192 - accuracy: 0.3998\n",
"10935/10935 [==============================] - 0s 41us/sample - loss: 1.9476 - accuracy: 0.3844\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1315 - accuracy: 0.2982\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.2587 - accuracy: 0.2599\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.9899 - accuracy: 0.3941\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3296 - accuracy: 0.2902\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.3529 - accuracy: 0.2856\n",
"start index for training is 234000\n",
"Train on 12260 samples, validate on 12260 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12260/12260 [==============================] - 1s 45us/sample - loss: 1.8810 - accuracy: 0.4202\n",
"12260/12260 [==============================] - 0s 39us/sample - loss: 1.8776 - accuracy: 0.4219\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1448 - accuracy: 0.3032\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.2606 - accuracy: 0.2693\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.0019 - accuracy: 0.3780\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3091 - accuracy: 0.2969\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3302 - accuracy: 0.2919\n",
"start index for training is 235000\n",
"Train on 11470 samples, validate on 11470 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11470/11470 [==============================] - 1s 45us/sample - loss: 1.8936 - accuracy: 0.4269\n",
"11470/11470 [==============================] - 0s 43us/sample - loss: 1.9180 - accuracy: 0.4174\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1582 - accuracy: 0.2900\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.2649 - accuracy: 0.2623\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0124 - accuracy: 0.3777\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3004 - accuracy: 0.3036\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.3211 - accuracy: 0.2966\n",
"start index for training is 236000\n",
"Train on 11080 samples, validate on 11085 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11080/11080 [==============================] - 1s 67us/sample - loss: 1.9697 - accuracy: 0.3839\n",
"11085/11085 [==============================] - 1s 82us/sample - loss: 1.9768 - accuracy: 0.3778\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"5980/5980 [==============================] - 1s 92us/sample - loss: 2.1677 - accuracy: 0.3008\n",
"12255/12255 [==============================] - 1s 61us/sample - loss: 2.2475 - accuracy: 0.2662\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.0272 - accuracy: 0.3771\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2608 - accuracy: 0.3064\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2753 - accuracy: 0.2943\n",
"start index for training is 237000\n",
"Train on 11170 samples, validate on 11175 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11170/11170 [==============================] - 1s 46us/sample - loss: 1.9560 - accuracy: 0.3959\n",
"11175/11175 [==============================] - 1s 48us/sample - loss: 1.9282 - accuracy: 0.4055\n",
"5980/5980 [==============================] - 0s 53us/sample - loss: 2.1625 - accuracy: 0.3102\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 2.2483 - accuracy: 0.2738\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.0340 - accuracy: 0.3798\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2489 - accuracy: 0.3120\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2597 - accuracy: 0.3073\n",
"start index for training is 238000\n",
"Train on 10895 samples, validate on 10895 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10895/10895 [==============================] - 1s 50us/sample - loss: 2.0072 - accuracy: 0.3630\n",
"10895/10895 [==============================] - 1s 48us/sample - loss: 1.9660 - accuracy: 0.3764\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1634 - accuracy: 0.2925\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.2444 - accuracy: 0.2698\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.0359 - accuracy: 0.3760\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.2108 - accuracy: 0.3224\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.2186 - accuracy: 0.3150\n",
"start index for training is 239000\n",
"Train on 10280 samples, validate on 10280 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10280/10280 [==============================] - 0s 47us/sample - loss: 2.0156 - accuracy: 0.3676\n",
"10280/10280 [==============================] - 0s 46us/sample - loss: 2.0137 - accuracy: 0.3627\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 2.1742 - accuracy: 0.3100\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 2.2353 - accuracy: 0.2758\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.0580 - accuracy: 0.3721\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1969 - accuracy: 0.3202\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.1940 - accuracy: 0.3200\n",
"start index for training is 240000\n",
"Train on 10200 samples, validate on 10205 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10200/10200 [==============================] - 1s 54us/sample - loss: 2.0144 - accuracy: 0.3670\n",
"10205/10205 [==============================] - 1s 57us/sample - loss: 2.0477 - accuracy: 0.3567\n",
"5980/5980 [==============================] - 0s 77us/sample - loss: 2.1799 - accuracy: 0.3022\n",
"12255/12255 [==============================] - 1s 60us/sample - loss: 2.2414 - accuracy: 0.2796\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.0652 - accuracy: 0.3664\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1701 - accuracy: 0.3313\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1699 - accuracy: 0.3280\n",
"start index for training is 241000\n",
"Train on 10325 samples, validate on 10325 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10325/10325 [==============================] - 1s 51us/sample - loss: 2.0363 - accuracy: 0.3615\n",
"10325/10325 [==============================] - 0s 44us/sample - loss: 2.0503 - accuracy: 0.3611\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 2.1833 - accuracy: 0.3012\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.2374 - accuracy: 0.2846\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.0760 - accuracy: 0.3566\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1548 - accuracy: 0.3365\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.1463 - accuracy: 0.3347\n",
"start index for training is 242000\n",
"Train on 10320 samples, validate on 10325 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10320/10320 [==============================] - 0s 45us/sample - loss: 2.0286 - accuracy: 0.3683\n",
"10325/10325 [==============================] - 0s 44us/sample - loss: 2.0755 - accuracy: 0.3526\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.1863 - accuracy: 0.2933\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.2385 - accuracy: 0.2857\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0913 - accuracy: 0.3384\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.1324 - accuracy: 0.3394\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1208 - accuracy: 0.3341\n",
"start index for training is 243000\n",
"Train on 10445 samples, validate on 10450 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10445/10445 [==============================] - 0s 44us/sample - loss: 2.0319 - accuracy: 0.3727\n",
"10450/10450 [==============================] - 0s 48us/sample - loss: 2.0909 - accuracy: 0.3631\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1903 - accuracy: 0.2839\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.2370 - accuracy: 0.2844\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.1017 - accuracy: 0.3430\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1251 - accuracy: 0.3482\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.1021 - accuracy: 0.3451\n",
"start index for training is 244000\n",
"Train on 9920 samples, validate on 9925 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9920/9920 [==============================] - 0s 40us/sample - loss: 2.0652 - accuracy: 0.3607\n",
"9925/9925 [==============================] - 0s 43us/sample - loss: 2.0725 - accuracy: 0.3649\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 2.1950 - accuracy: 0.3018\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.2348 - accuracy: 0.2850\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.0999 - accuracy: 0.3408\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.1100 - accuracy: 0.3490\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.0827 - accuracy: 0.3479\n",
"start index for training is 245000\n",
"Train on 8980 samples, validate on 8980 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8980/8980 [==============================] - 0s 52us/sample - loss: 2.1302 - accuracy: 0.3308\n",
"8980/8980 [==============================] - 0s 46us/sample - loss: 2.1516 - accuracy: 0.3340\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 2.1939 - accuracy: 0.3042\n",
"12255/12255 [==============================] - 1s 57us/sample - loss: 2.2395 - accuracy: 0.2840\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.1060 - accuracy: 0.3456\n",
"11565/11565 [==============================] - 1s 54us/sample - loss: 2.1035 - accuracy: 0.3503\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"7000/7000 [==============================] - 1s 76us/sample - loss: 2.0757 - accuracy: 0.3499\n",
"start index for training is 246000\n",
"Train on 10430 samples, validate on 10435 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10430/10430 [==============================] - 1s 56us/sample - loss: 2.0809 - accuracy: 0.3577\n",
"10435/10435 [==============================] - 0s 45us/sample - loss: 2.1027 - accuracy: 0.3591\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.2152 - accuracy: 0.3054\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.2506 - accuracy: 0.2780\n",
"14070/14070 [==============================] - 1s 55us/sample - loss: 2.1164 - accuracy: 0.3440\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.0981 - accuracy: 0.3575\n",
"7000/7000 [==============================] - 0s 58us/sample - loss: 2.0530 - accuracy: 0.3646\n",
"start index for training is 247000\n",
"Train on 9430 samples, validate on 9435 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9430/9430 [==============================] - 0s 53us/sample - loss: 2.1375 - accuracy: 0.3389\n",
"9435/9435 [==============================] - 1s 60us/sample - loss: 2.1089 - accuracy: 0.3436\n",
"5980/5980 [==============================] - 0s 53us/sample - loss: 2.2067 - accuracy: 0.3030\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.2502 - accuracy: 0.2766\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.1177 - accuracy: 0.3443\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.0916 - accuracy: 0.3580\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.0394 - accuracy: 0.3620\n",
"start index for training is 248000\n",
"Train on 8965 samples, validate on 8965 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8965/8965 [==============================] - 1s 63us/sample - loss: 2.1965 - accuracy: 0.3256\n",
"8965/8965 [==============================] - 0s 48us/sample - loss: 2.1603 - accuracy: 0.3404\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 2.2113 - accuracy: 0.2980\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.2504 - accuracy: 0.2777\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.1164 - accuracy: 0.3453\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.0878 - accuracy: 0.3605\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.0330 - accuracy: 0.3603\n",
"start index for training is 249000\n",
"Train on 8290 samples, validate on 8295 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8290/8290 [==============================] - 0s 49us/sample - loss: 2.1870 - accuracy: 0.3146\n",
"8295/8295 [==============================] - 0s 43us/sample - loss: 2.1716 - accuracy: 0.3212\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 2.1215 - accuracy: 0.3055\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.2196 - accuracy: 0.2779\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.0991 - accuracy: 0.3478\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.0858 - accuracy: 0.3588\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.0391 - accuracy: 0.3650\n",
"start index for training is 250000\n",
"Train on 7725 samples, validate on 7730 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7725/7725 [==============================] - 0s 45us/sample - loss: 2.1281 - accuracy: 0.3182\n",
"7730/7730 [==============================] - 0s 43us/sample - loss: 2.1610 - accuracy: 0.3058\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9726 - accuracy: 0.3816\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.2342 - accuracy: 0.2678\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.1044 - accuracy: 0.3395\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1747 - accuracy: 0.3241\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.1646 - accuracy: 0.3153\n",
"start index for training is 251000\n",
"Train on 8360 samples, validate on 8365 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8360/8360 [==============================] - 0s 44us/sample - loss: 2.0843 - accuracy: 0.3390\n",
"8365/8365 [==============================] - 0s 42us/sample - loss: 2.1159 - accuracy: 0.3333\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.9037 - accuracy: 0.4217\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.2301 - accuracy: 0.2576\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.1184 - accuracy: 0.3276\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.2071 - accuracy: 0.3026\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2053 - accuracy: 0.2847\n",
"start index for training is 252000\n",
"Train on 8175 samples, validate on 8175 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8175/8175 [==============================] - 0s 45us/sample - loss: 2.0719 - accuracy: 0.3465\n",
"8175/8175 [==============================] - 0s 39us/sample - loss: 2.0635 - accuracy: 0.3464\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8614 - accuracy: 0.4247\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.2312 - accuracy: 0.2629\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1364 - accuracy: 0.3163\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.2337 - accuracy: 0.2932\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2342 - accuracy: 0.2730\n",
"start index for training is 253000\n",
"Train on 8345 samples, validate on 8345 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8345/8345 [==============================] - 0s 43us/sample - loss: 2.0408 - accuracy: 0.3599\n",
"8345/8345 [==============================] - 0s 40us/sample - loss: 2.0247 - accuracy: 0.3612\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8159 - accuracy: 0.4620\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.2269 - accuracy: 0.2657\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.1253 - accuracy: 0.3127\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.2470 - accuracy: 0.2908\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2524 - accuracy: 0.2754\n",
"start index for training is 254000\n",
"Train on 8285 samples, validate on 8285 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8285/8285 [==============================] - 0s 48us/sample - loss: 1.9876 - accuracy: 0.3704\n",
"8285/8285 [==============================] - 0s 43us/sample - loss: 1.9965 - accuracy: 0.3669\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7818 - accuracy: 0.4679\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 2.2196 - accuracy: 0.2744\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.1361 - accuracy: 0.3043\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.2594 - accuracy: 0.2857\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2608 - accuracy: 0.2750\n",
"start index for training is 255000\n",
"Train on 8725 samples, validate on 8730 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8725/8725 [==============================] - 0s 45us/sample - loss: 1.9700 - accuracy: 0.3687\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"8730/8730 [==============================] - 0s 41us/sample - loss: 1.9649 - accuracy: 0.3623\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7498 - accuracy: 0.4923\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.2091 - accuracy: 0.2705\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.1358 - accuracy: 0.2996\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.2532 - accuracy: 0.2863\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2516 - accuracy: 0.2764\n",
"start index for training is 256000\n",
"Train on 9330 samples, validate on 9335 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9330/9330 [==============================] - 1s 55us/sample - loss: 1.9575 - accuracy: 0.3746\n",
"9335/9335 [==============================] - 0s 48us/sample - loss: 1.9599 - accuracy: 0.3717\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7304 - accuracy: 0.4895\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.2068 - accuracy: 0.2667\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.1476 - accuracy: 0.3091\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.2594 - accuracy: 0.2864\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.2614 - accuracy: 0.2764\n",
"start index for training is 257000\n",
"Train on 9960 samples, validate on 9960 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9960/9960 [==============================] - 1s 50us/sample - loss: 1.9332 - accuracy: 0.3815\n",
"9960/9960 [==============================] - 0s 46us/sample - loss: 1.9508 - accuracy: 0.3723\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 1.7190 - accuracy: 0.4612\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 2.1909 - accuracy: 0.2781\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.1635 - accuracy: 0.3076\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2680 - accuracy: 0.3053\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2713 - accuracy: 0.2983\n",
"start index for training is 258000\n",
"Train on 10065 samples, validate on 10070 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10065/10065 [==============================] - 0s 43us/sample - loss: 1.9584 - accuracy: 0.3722\n",
"10070/10070 [==============================] - 0s 46us/sample - loss: 1.9390 - accuracy: 0.3763\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.7159 - accuracy: 0.4756\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.1789 - accuracy: 0.2836\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.1752 - accuracy: 0.3058\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.2784 - accuracy: 0.2959\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2835 - accuracy: 0.2884\n",
"start index for training is 259000\n",
"Train on 9610 samples, validate on 9610 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9610/9610 [==============================] - 0s 45us/sample - loss: 1.9552 - accuracy: 0.3556\n",
"9610/9610 [==============================] - 0s 40us/sample - loss: 1.9615 - accuracy: 0.3508\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7037 - accuracy: 0.4972\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1624 - accuracy: 0.2837\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.1680 - accuracy: 0.3071\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.2871 - accuracy: 0.2776\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2932 - accuracy: 0.2590\n",
"start index for training is 260000\n",
"Train on 11310 samples, validate on 11310 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11310/11310 [==============================] - 1s 60us/sample - loss: 1.9314 - accuracy: 0.3722\n",
"11310/11310 [==============================] - 0s 42us/sample - loss: 1.9409 - accuracy: 0.3660\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7033 - accuracy: 0.4652\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.1515 - accuracy: 0.2830\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.1785 - accuracy: 0.2959\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.2880 - accuracy: 0.2823\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2916 - accuracy: 0.2727\n",
"start index for training is 261000\n",
"Train on 10370 samples, validate on 10370 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10370/10370 [==============================] - 0s 43us/sample - loss: 1.9492 - accuracy: 0.3630\n",
"10370/10370 [==============================] - 0s 44us/sample - loss: 1.9379 - accuracy: 0.3688\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7048 - accuracy: 0.4595\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1466 - accuracy: 0.2796\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1863 - accuracy: 0.3160\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3088 - accuracy: 0.2870\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3202 - accuracy: 0.2803\n",
"start index for training is 262000\n",
"Train on 10600 samples, validate on 10600 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10600/10600 [==============================] - 1s 50us/sample - loss: 1.9330 - accuracy: 0.3533\n",
"10600/10600 [==============================] - 0s 45us/sample - loss: 1.9525 - accuracy: 0.3565\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.7098 - accuracy: 0.4620\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.1220 - accuracy: 0.2876\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.1946 - accuracy: 0.3161\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 2.3134 - accuracy: 0.2901\n",
"7000/7000 [==============================] - 0s 61us/sample - loss: 2.3256 - accuracy: 0.2830\n",
"start index for training is 263000\n",
"Train on 10720 samples, validate on 10725 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10720/10720 [==============================] - 0s 44us/sample - loss: 1.9345 - accuracy: 0.3623\n",
"10725/10725 [==============================] - 0s 41us/sample - loss: 1.9347 - accuracy: 0.3556\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.7054 - accuracy: 0.4952\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.1012 - accuracy: 0.2886\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.2015 - accuracy: 0.2986\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3155 - accuracy: 0.2675\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3270 - accuracy: 0.2570\n",
"start index for training is 264000\n",
"Train on 10520 samples, validate on 10520 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10520/10520 [==============================] - 0s 47us/sample - loss: 1.9099 - accuracy: 0.3680\n",
"10520/10520 [==============================] - 0s 46us/sample - loss: 1.9314 - accuracy: 0.3605\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7104 - accuracy: 0.4717\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0932 - accuracy: 0.2926\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2069 - accuracy: 0.2966\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3286 - accuracy: 0.2658\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.3428 - accuracy: 0.2619\n",
"start index for training is 265000\n",
"Train on 10030 samples, validate on 10035 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10030/10030 [==============================] - 0s 46us/sample - loss: 1.9196 - accuracy: 0.3740\n",
"10035/10035 [==============================] - 0s 42us/sample - loss: 1.9482 - accuracy: 0.3627\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7305 - accuracy: 0.4513\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0817 - accuracy: 0.3162\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2200 - accuracy: 0.2844\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3261 - accuracy: 0.2923\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3378 - accuracy: 0.2937\n",
"start index for training is 266000\n",
"Train on 9885 samples, validate on 9890 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9885/9885 [==============================] - 0s 44us/sample - loss: 1.9166 - accuracy: 0.3669\n",
"9890/9890 [==============================] - 0s 38us/sample - loss: 1.9182 - accuracy: 0.3656\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.7251 - accuracy: 0.4527\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0649 - accuracy: 0.3106\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2268 - accuracy: 0.2770\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3393 - accuracy: 0.2688\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.3559 - accuracy: 0.2643\n",
"start index for training is 267000\n",
"Train on 10220 samples, validate on 10220 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10220/10220 [==============================] - 0s 46us/sample - loss: 1.8971 - accuracy: 0.3880\n",
"10220/10220 [==============================] - 0s 40us/sample - loss: 1.8976 - accuracy: 0.3824\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7398 - accuracy: 0.4500\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0434 - accuracy: 0.3382\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2471 - accuracy: 0.2770\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3477 - accuracy: 0.2682\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3607 - accuracy: 0.2654\n",
"start index for training is 268000\n",
"Train on 10050 samples, validate on 10050 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10050/10050 [==============================] - 0s 43us/sample - loss: 1.9136 - accuracy: 0.3652\n",
"10050/10050 [==============================] - 0s 40us/sample - loss: 1.9126 - accuracy: 0.3684\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7535 - accuracy: 0.4527\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0330 - accuracy: 0.3190\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2548 - accuracy: 0.2865\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3404 - accuracy: 0.2727\n",
"7000/7000 [==============================] - 0s 56us/sample - loss: 2.3585 - accuracy: 0.2684\n",
"start index for training is 269000\n",
"Train on 9225 samples, validate on 9225 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9225/9225 [==============================] - 0s 43us/sample - loss: 1.9142 - accuracy: 0.3618\n",
"9225/9225 [==============================] - 0s 39us/sample - loss: 1.9223 - accuracy: 0.3548\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7502 - accuracy: 0.4629\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0068 - accuracy: 0.3197\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2576 - accuracy: 0.2759\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3499 - accuracy: 0.2705\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.3676 - accuracy: 0.2614\n",
"start index for training is 270000\n",
"Train on 9730 samples, validate on 9730 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9730/9730 [==============================] - 0s 44us/sample - loss: 1.9115 - accuracy: 0.3666\n",
"9730/9730 [==============================] - 0s 46us/sample - loss: 1.9460 - accuracy: 0.3507\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.7628 - accuracy: 0.4360\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9985 - accuracy: 0.3201\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2591 - accuracy: 0.2837\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3402 - accuracy: 0.2783\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3591 - accuracy: 0.2769\n",
"start index for training is 271000\n",
"Train on 10380 samples, validate on 10380 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10380/10380 [==============================] - 1s 58us/sample - loss: 1.8915 - accuracy: 0.3670\n",
"10380/10380 [==============================] - 0s 42us/sample - loss: 1.9260 - accuracy: 0.3604\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7658 - accuracy: 0.4249\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9740 - accuracy: 0.3275\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2744 - accuracy: 0.2755\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3544 - accuracy: 0.2648\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3746 - accuracy: 0.2539\n",
"start index for training is 272000\n",
"Train on 9855 samples, validate on 9860 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9855/9855 [==============================] - 0s 42us/sample - loss: 1.9029 - accuracy: 0.3620\n",
"9860/9860 [==============================] - 0s 39us/sample - loss: 1.9363 - accuracy: 0.3658\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7705 - accuracy: 0.4742\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9600 - accuracy: 0.3357\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2821 - accuracy: 0.2757\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3547 - accuracy: 0.2694\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.3776 - accuracy: 0.2581\n",
"start index for training is 273000\n",
"Train on 9785 samples, validate on 9785 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9785/9785 [==============================] - 0s 46us/sample - loss: 1.9416 - accuracy: 0.3556\n",
"9785/9785 [==============================] - 0s 45us/sample - loss: 1.9551 - accuracy: 0.3501\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.7884 - accuracy: 0.4431\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.9455 - accuracy: 0.3490\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2862 - accuracy: 0.2706\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3410 - accuracy: 0.2779\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.3630 - accuracy: 0.2704\n",
"start index for training is 274000\n",
"Train on 10365 samples, validate on 10365 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"10365/10365 [==============================] - 0s 43us/sample - loss: 1.9082 - accuracy: 0.3765\n",
"10365/10365 [==============================] - 0s 42us/sample - loss: 1.9215 - accuracy: 0.3658\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7851 - accuracy: 0.4400\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9260 - accuracy: 0.3670\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2949 - accuracy: 0.2710\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3524 - accuracy: 0.2789\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3762 - accuracy: 0.2729s - loss: 2.3810 - accuracy\n",
"start index for training is 275000\n",
"Train on 9925 samples, validate on 9930 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9925/9925 [==============================] - 0s 47us/sample - loss: 1.9398 - accuracy: 0.3596\n",
"9930/9930 [==============================] - 0s 40us/sample - loss: 1.9576 - accuracy: 0.3559\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7899 - accuracy: 0.4316\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.9148 - accuracy: 0.3669\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2943 - accuracy: 0.2694\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3461 - accuracy: 0.2781\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3695 - accuracy: 0.2691\n",
"start index for training is 276000\n",
"Train on 10580 samples, validate on 10585 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10580/10580 [==============================] - 0s 44us/sample - loss: 1.8999 - accuracy: 0.3804\n",
"10585/10585 [==============================] - 0s 40us/sample - loss: 1.9044 - accuracy: 0.3820\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8107 - accuracy: 0.4430\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.8944 - accuracy: 0.3825\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.3127 - accuracy: 0.2602\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3459 - accuracy: 0.2794\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3664 - accuracy: 0.2700\n",
"start index for training is 277000\n",
"Train on 10355 samples, validate on 10355 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10355/10355 [==============================] - 0s 43us/sample - loss: 1.9573 - accuracy: 0.3680\n",
"10355/10355 [==============================] - 0s 39us/sample - loss: 1.9546 - accuracy: 0.3676\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8060 - accuracy: 0.4316\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8867 - accuracy: 0.3859\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.3178 - accuracy: 0.2546\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3508 - accuracy: 0.2789\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3723 - accuracy: 0.2677\n",
"start index for training is 278000\n",
"Train on 9330 samples, validate on 9330 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9330/9330 [==============================] - 0s 45us/sample - loss: 1.9497 - accuracy: 0.3639\n",
"9330/9330 [==============================] - 0s 41us/sample - loss: 1.9641 - accuracy: 0.3633\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8255 - accuracy: 0.4324\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.8797 - accuracy: 0.3817\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.3286 - accuracy: 0.2675\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3451 - accuracy: 0.2852\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3658 - accuracy: 0.2766\n",
"start index for training is 279000\n",
"Train on 9170 samples, validate on 9175 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9170/9170 [==============================] - 0s 47us/sample - loss: 1.9672 - accuracy: 0.3714\n",
"9175/9175 [==============================] - 0s 44us/sample - loss: 1.9622 - accuracy: 0.3690\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.8246 - accuracy: 0.4425\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8748 - accuracy: 0.3851\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.3341 - accuracy: 0.2665\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3592 - accuracy: 0.2809\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3812 - accuracy: 0.2723\n",
"start index for training is 280000\n",
"Train on 12230 samples, validate on 12235 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12230/12230 [==============================] - 1s 44us/sample - loss: 1.9121 - accuracy: 0.3918\n",
"12235/12235 [==============================] - 0s 39us/sample - loss: 1.9054 - accuracy: 0.3908\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.8330 - accuracy: 0.4339\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.8640 - accuracy: 0.3885\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3464 - accuracy: 0.2634\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3565 - accuracy: 0.2809\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3745 - accuracy: 0.2721\n",
"start index for training is 281000\n",
"Train on 10230 samples, validate on 10235 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10230/10230 [==============================] - 0s 45us/sample - loss: 1.9679 - accuracy: 0.3714\n",
"10235/10235 [==============================] - ETA: 0s - loss: 1.9848 - accuracy: 0.37 - 0s 47us/sample - loss: 1.9926 - accuracy: 0.3721\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8270 - accuracy: 0.4221\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.8588 - accuracy: 0.3965\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.3455 - accuracy: 0.2637\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3578 - accuracy: 0.2811\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.3804 - accuracy: 0.2746\n",
"start index for training is 282000\n",
"Train on 9705 samples, validate on 9710 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9705/9705 [==============================] - 0s 44us/sample - loss: 1.9753 - accuracy: 0.3720\n",
"9710/9710 [==============================] - 0s 40us/sample - loss: 1.9928 - accuracy: 0.3722\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8363 - accuracy: 0.4085\n",
"12255/12255 [==============================] - 1s 56us/sample - loss: 1.8603 - accuracy: 0.3968\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3533 - accuracy: 0.2627\n",
"11565/11565 [==============================] - 1s 58us/sample - loss: 2.3559 - accuracy: 0.2770\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.3814 - accuracy: 0.2714\n",
"start index for training is 283000\n",
"Train on 9750 samples, validate on 9750 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9750/9750 [==============================] - 0s 50us/sample - loss: 1.9883 - accuracy: 0.3704\n",
"9750/9750 [==============================] - 0s 47us/sample - loss: 1.9980 - accuracy: 0.3643\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.8461 - accuracy: 0.4037\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.8579 - accuracy: 0.3954\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.3537 - accuracy: 0.2663\n",
"11565/11565 [==============================] - 1s 57us/sample - loss: 2.3517 - accuracy: 0.2759\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.3749 - accuracy: 0.2676\n",
"start index for training is 284000\n",
"Train on 9825 samples, validate on 9830 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9825/9825 [==============================] - 0s 51us/sample - loss: 2.0206 - accuracy: 0.3653\n",
"9830/9830 [==============================] - 0s 43us/sample - loss: 2.0275 - accuracy: 0.3630\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.8428 - accuracy: 0.4254\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.8591 - accuracy: 0.3953s - loss: 1.8539 - \n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.3569 - accuracy: 0.2682\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3541 - accuracy: 0.2736\n",
"7000/7000 [==============================] - 0s 68us/sample - loss: 2.3766 - accuracy: 0.2640\n",
"start index for training is 285000\n",
"Train on 9825 samples, validate on 9825 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9825/9825 [==============================] - 1s 51us/sample - loss: 2.0143 - accuracy: 0.3699\n",
"9825/9825 [==============================] - 1s 67us/sample - loss: 2.0231 - accuracy: 0.3603\n",
"5980/5980 [==============================] - 0s 59us/sample - loss: 1.8538 - accuracy: 0.4217\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.8597 - accuracy: 0.3961\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.3696 - accuracy: 0.2604\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3541 - accuracy: 0.2753\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.3758 - accuracy: 0.2659\n",
"start index for training is 286000\n",
"Train on 10010 samples, validate on 10010 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10010/10010 [==============================] - 0s 47us/sample - loss: 2.0699 - accuracy: 0.3338\n",
"10010/10010 [==============================] - 0s 41us/sample - loss: 2.0875 - accuracy: 0.3298\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.8909 - accuracy: 0.4022\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.9194 - accuracy: 0.3640\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.4070 - accuracy: 0.2601\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.4400 - accuracy: 0.2588\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4618 - accuracy: 0.2577\n",
"start index for training is 287000\n",
"Train on 9925 samples, validate on 9930 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9925/9925 [==============================] - 0s 45us/sample - loss: 2.0564 - accuracy: 0.3610\n",
"9930/9930 [==============================] - 0s 42us/sample - loss: 2.0425 - accuracy: 0.3602\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8589 - accuracy: 0.4219\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.8672 - accuracy: 0.3977\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.3893 - accuracy: 0.2639\n",
"11565/11565 [==============================] - 1s 49us/sample - loss: 2.3646 - accuracy: 0.2730\n",
"7000/7000 [==============================] - 0s 61us/sample - loss: 2.3895 - accuracy: 0.2657\n",
"start index for training is 288000\n",
"Train on 10215 samples, validate on 10215 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10215/10215 [==============================] - 1s 50us/sample - loss: 2.0262 - accuracy: 0.3687\n",
"10215/10215 [==============================] - 0s 43us/sample - loss: 2.0475 - accuracy: 0.3604\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.8610 - accuracy: 0.4214\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.8628 - accuracy: 0.3851\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.3737 - accuracy: 0.2707\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3529 - accuracy: 0.2815\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3757 - accuracy: 0.2726\n",
"start index for training is 289000\n",
"Train on 10265 samples, validate on 10270 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10265/10265 [==============================] - 0s 44us/sample - loss: 2.0462 - accuracy: 0.3634\n",
"10270/10270 [==============================] - 0s 43us/sample - loss: 2.0556 - accuracy: 0.3666\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.8787 - accuracy: 0.4067\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.8755 - accuracy: 0.3926\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.3935 - accuracy: 0.2660\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.3579 - accuracy: 0.2789\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.3825 - accuracy: 0.2726\n",
"start index for training is 290000\n",
"Train on 10340 samples, validate on 10340 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10340/10340 [==============================] - 1s 63us/sample - loss: 2.0550 - accuracy: 0.3610\n",
"10340/10340 [==============================] - 0s 44us/sample - loss: 2.0599 - accuracy: 0.3564\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.8706 - accuracy: 0.4181\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.8726 - accuracy: 0.3903\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.3768 - accuracy: 0.2664\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3580 - accuracy: 0.2821\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3848 - accuracy: 0.2750\n",
"start index for training is 291000\n",
"Train on 10145 samples, validate on 10145 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10145/10145 [==============================] - 0s 41us/sample - loss: 2.0583 - accuracy: 0.3679\n",
"10145/10145 [==============================] - 0s 39us/sample - loss: 2.0656 - accuracy: 0.3616\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.8985 - accuracy: 0.4067\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.8956 - accuracy: 0.3874\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.4199 - accuracy: 0.2608\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3819 - accuracy: 0.2825\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4070 - accuracy: 0.2794\n",
"start index for training is 292000\n",
"Train on 9615 samples, validate on 9615 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9615/9615 [==============================] - 0s 46us/sample - loss: 2.0818 - accuracy: 0.3514\n",
"9615/9615 [==============================] - 0s 48us/sample - loss: 2.0785 - accuracy: 0.3588\n",
"5980/5980 [==============================] - 0s 60us/sample - loss: 1.8883 - accuracy: 0.4134\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.8894 - accuracy: 0.3860\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.3938 - accuracy: 0.2653\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.3641 - accuracy: 0.2783\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.3901 - accuracy: 0.2756\n",
"start index for training is 293000\n",
"Train on 7325 samples, validate on 7325 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7325/7325 [==============================] - 0s 48us/sample - loss: 2.1502 - accuracy: 0.3251\n",
"7325/7325 [==============================] - 0s 45us/sample - loss: 2.1793 - accuracy: 0.3166\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8857 - accuracy: 0.4114\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.8914 - accuracy: 0.3809\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4083 - accuracy: 0.2532\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3771 - accuracy: 0.2724\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4052 - accuracy: 0.2654\n",
"start index for training is 294000\n",
"Train on 11085 samples, validate on 11085 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11085/11085 [==============================] - 1s 51us/sample - loss: 2.0719 - accuracy: 0.3600\n",
"11085/11085 [==============================] - 1s 62us/sample - loss: 2.0590 - accuracy: 0.3681\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.9255 - accuracy: 0.4149\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 1.9134 - accuracy: 0.3804\n",
"14070/14070 [==============================] - 1s 69us/sample - loss: 2.4466 - accuracy: 0.2588\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.3887 - accuracy: 0.2847\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.4129 - accuracy: 0.2794\n",
"start index for training is 295000\n",
"Train on 11100 samples, validate on 11105 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11100/11100 [==============================] - 1s 48us/sample - loss: 2.0520 - accuracy: 0.3584\n",
"11105/11105 [==============================] - 1s 46us/sample - loss: 2.0851 - accuracy: 0.3489\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 1.8863 - accuracy: 0.4273\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.8843 - accuracy: 0.3838\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.4081 - accuracy: 0.2651\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.3682 - accuracy: 0.2762\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.3907 - accuracy: 0.2704\n",
"start index for training is 296000\n",
"Train on 10545 samples, validate on 10550 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10545/10545 [==============================] - 1s 54us/sample - loss: 2.0569 - accuracy: 0.3640\n",
"10550/10550 [==============================] - 1s 50us/sample - loss: 2.0687 - accuracy: 0.3604\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 1.8858 - accuracy: 0.4085\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 1.9000 - accuracy: 0.3803\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.4051 - accuracy: 0.2601\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.3712 - accuracy: 0.2816\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.3972 - accuracy: 0.2764\n",
"start index for training is 297000\n",
"Train on 9115 samples, validate on 9115 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9115/9115 [==============================] - 0s 49us/sample - loss: 2.0503 - accuracy: 0.3751\n",
"9115/9115 [==============================] - 1s 61us/sample - loss: 2.0717 - accuracy: 0.3696\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.9221 - accuracy: 0.4100\n",
"12255/12255 [==============================] - 1s 56us/sample - loss: 1.9302 - accuracy: 0.3745\n",
"14070/14070 [==============================] - 1s 57us/sample - loss: 2.4275 - accuracy: 0.2563\n",
"11565/11565 [==============================] - 1s 55us/sample - loss: 2.3883 - accuracy: 0.2796\n",
"7000/7000 [==============================] - 0s 59us/sample - loss: 2.4176 - accuracy: 0.2804\n",
"start index for training is 298000\n",
"Train on 8575 samples, validate on 8575 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8575/8575 [==============================] - 0s 50us/sample - loss: 2.1492 - accuracy: 0.3227\n",
"8575/8575 [==============================] - 0s 48us/sample - loss: 2.1479 - accuracy: 0.3233\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.8954 - accuracy: 0.4169\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.9098 - accuracy: 0.3811\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.4181 - accuracy: 0.2490\n",
"11565/11565 [==============================] - 1s 51us/sample - loss: 2.3781 - accuracy: 0.2783\n",
"7000/7000 [==============================] - 0s 51us/sample - loss: 2.4059 - accuracy: 0.2707\n",
"start index for training is 299000\n",
"Train on 11475 samples, validate on 11480 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11475/11475 [==============================] - 1s 57us/sample - loss: 2.0475 - accuracy: 0.3739\n",
"11480/11480 [==============================] - 1s 54us/sample - loss: 2.0612 - accuracy: 0.3579\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.9009 - accuracy: 0.4166\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 1.9171 - accuracy: 0.3775\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.4121 - accuracy: 0.2518\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.3797 - accuracy: 0.2768\n",
"7000/7000 [==============================] - 0s 55us/sample - loss: 2.4078 - accuracy: 0.2700\n",
"start index for training is 300000\n",
"Train on 10130 samples, validate on 10130 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10130/10130 [==============================] - 1s 63us/sample - loss: 2.0595 - accuracy: 0.3654\n",
"10130/10130 [==============================] - 1s 54us/sample - loss: 2.0708 - accuracy: 0.3654\n",
"5980/5980 [==============================] - 0s 53us/sample - loss: 1.8995 - accuracy: 0.4092\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.9165 - accuracy: 0.3749\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4104 - accuracy: 0.2551\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3768 - accuracy: 0.2798\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4014 - accuracy: 0.2753\n",
"start index for training is 301000\n",
"Train on 6785 samples, validate on 6790 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6785/6785 [==============================] - 0s 53us/sample - loss: 2.1402 - accuracy: 0.3319\n",
"6790/6790 [==============================] - 0s 46us/sample - loss: 2.1579 - accuracy: 0.3328\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9120 - accuracy: 0.4027\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.9339 - accuracy: 0.3582\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.4467 - accuracy: 0.2468\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.4148 - accuracy: 0.2724\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4425 - accuracy: 0.2674\n",
"start index for training is 302000\n",
"Train on 11075 samples, validate on 11080 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11075/11075 [==============================] - 0s 43us/sample - loss: 2.0582 - accuracy: 0.3683\n",
"11080/11080 [==============================] - 0s 40us/sample - loss: 2.0661 - accuracy: 0.3722\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9273 - accuracy: 0.4030\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9441 - accuracy: 0.3632\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4261 - accuracy: 0.2422\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3980 - accuracy: 0.2723\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4240 - accuracy: 0.2691\n",
"start index for training is 303000\n",
"Train on 10265 samples, validate on 10270 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10265/10265 [==============================] - 0s 44us/sample - loss: 2.0653 - accuracy: 0.3744\n",
"10270/10270 [==============================] - 0s 39us/sample - loss: 2.0584 - accuracy: 0.3733\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.9264 - accuracy: 0.3918\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9484 - accuracy: 0.3619\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.4325 - accuracy: 0.2403\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.4026 - accuracy: 0.2748\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4272 - accuracy: 0.2700\n",
"start index for training is 304000\n",
"Train on 9400 samples, validate on 9405 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9400/9400 [==============================] - 0s 44us/sample - loss: 2.0650 - accuracy: 0.3641\n",
"9405/9405 [==============================] - 0s 43us/sample - loss: 2.1054 - accuracy: 0.3554\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9409 - accuracy: 0.3987\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9603 - accuracy: 0.3570\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4370 - accuracy: 0.2509\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.4074 - accuracy: 0.2728\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4323 - accuracy: 0.2701\n",
"start index for training is 305000\n",
"Train on 7815 samples, validate on 7815 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7815/7815 [==============================] - 0s 46us/sample - loss: 2.1010 - accuracy: 0.3555\n",
"7815/7815 [==============================] - 0s 40us/sample - loss: 2.1153 - accuracy: 0.3495\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9270 - accuracy: 0.3855\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9579 - accuracy: 0.3585\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.4170 - accuracy: 0.2392\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.4068 - accuracy: 0.2680\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4318 - accuracy: 0.2646\n",
"start index for training is 306000\n",
"Train on 9230 samples, validate on 9235 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9230/9230 [==============================] - 0s 48us/sample - loss: 2.0706 - accuracy: 0.3652\n",
"9235/9235 [==============================] - 0s 43us/sample - loss: 2.0903 - accuracy: 0.3474\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9185 - accuracy: 0.4042\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9528 - accuracy: 0.3550\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.4197 - accuracy: 0.2469\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3985 - accuracy: 0.2713\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4238 - accuracy: 0.2673\n",
"start index for training is 307000\n",
"Train on 10480 samples, validate on 10485 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10480/10480 [==============================] - 0s 44us/sample - loss: 2.0541 - accuracy: 0.3713\n",
"10485/10485 [==============================] - 0s 40us/sample - loss: 2.0719 - accuracy: 0.3601\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.9113 - accuracy: 0.4035\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9671 - accuracy: 0.3536\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.4059 - accuracy: 0.2537\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.4001 - accuracy: 0.2711\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4282 - accuracy: 0.2681\n",
"start index for training is 308000\n",
"Train on 9950 samples, validate on 9950 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9950/9950 [==============================] - 0s 44us/sample - loss: 2.0657 - accuracy: 0.3687\n",
"9950/9950 [==============================] - 0s 42us/sample - loss: 2.0801 - accuracy: 0.3634\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9144 - accuracy: 0.3898\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.9574 - accuracy: 0.3539\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.3958 - accuracy: 0.2466\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3909 - accuracy: 0.2750\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4140 - accuracy: 0.2723\n",
"start index for training is 309000\n",
"Train on 6215 samples, validate on 6215 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6215/6215 [==============================] - 0s 45us/sample - loss: 2.1816 - accuracy: 0.3191\n",
"6215/6215 [==============================] - 0s 43us/sample - loss: 2.1862 - accuracy: 0.3168\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.8773 - accuracy: 0.3926\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.9432 - accuracy: 0.3532\n",
"14070/14070 [==============================] - 1s 56us/sample - loss: 2.2953 - accuracy: 0.2790\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.3433 - accuracy: 0.2872\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.3698 - accuracy: 0.2776\n",
"start index for training is 310000\n",
"Train on 8485 samples, validate on 8485 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8485/8485 [==============================] - 0s 44us/sample - loss: 2.0522 - accuracy: 0.3433\n",
"8485/8485 [==============================] - 0s 44us/sample - loss: 2.0600 - accuracy: 0.3446\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9028 - accuracy: 0.3846\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0325 - accuracy: 0.3017\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.1212 - accuracy: 0.3253\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3115 - accuracy: 0.2740\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.3424 - accuracy: 0.2636\n",
"start index for training is 311000\n",
"Train on 8365 samples, validate on 8370 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8365/8365 [==============================] - 0s 45us/sample - loss: 2.0127 - accuracy: 0.3681\n",
"8370/8370 [==============================] - 0s 44us/sample - loss: 2.0501 - accuracy: 0.3523\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.9194 - accuracy: 0.3686\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0644 - accuracy: 0.3004\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.0678 - accuracy: 0.3507\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.3107 - accuracy: 0.2826\n",
"7000/7000 [==============================] - 0s 53us/sample - loss: 2.3466 - accuracy: 0.2641\n",
"start index for training is 312000\n",
"Train on 9115 samples, validate on 9120 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 10/10\n",
"9115/9115 [==============================] - 0s 49us/sample - loss: 1.9920 - accuracy: 0.3676\n",
"9120/9120 [==============================] - 0s 44us/sample - loss: 1.9883 - accuracy: 0.3626\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 1.9516 - accuracy: 0.3403\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.0991 - accuracy: 0.2882\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.0395 - accuracy: 0.3564\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3204 - accuracy: 0.2800\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.3586 - accuracy: 0.2634\n",
"start index for training is 313000\n",
"Train on 8805 samples, validate on 8810 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8805/8805 [==============================] - 0s 44us/sample - loss: 1.9245 - accuracy: 0.3859\n",
"8810/8810 [==============================] - 0s 41us/sample - loss: 1.9431 - accuracy: 0.3748\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9579 - accuracy: 0.3482\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1107 - accuracy: 0.2967\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.0151 - accuracy: 0.3619\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3120 - accuracy: 0.2922\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.3529 - accuracy: 0.2739s - loss: 2.3720 - accuracy\n",
"start index for training is 314000\n",
"Train on 9605 samples, validate on 9610 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9605/9605 [==============================] - 0s 47us/sample - loss: 1.8694 - accuracy: 0.3993\n",
"9610/9610 [==============================] - 0s 46us/sample - loss: 1.8742 - accuracy: 0.3985\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.9740 - accuracy: 0.3460\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.1330 - accuracy: 0.2863\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.9908 - accuracy: 0.3787\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3265 - accuracy: 0.2882\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.3679 - accuracy: 0.2710\n",
"start index for training is 315000\n",
"Train on 9800 samples, validate on 9800 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9800/9800 [==============================] - 0s 45us/sample - loss: 1.8557 - accuracy: 0.4241\n",
"9800/9800 [==============================] - 0s 44us/sample - loss: 1.8821 - accuracy: 0.4079\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9684 - accuracy: 0.3386\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.1345 - accuracy: 0.2788\n",
"14070/14070 [==============================] - 1s 51us/sample - loss: 1.9734 - accuracy: 0.3888\n",
"11565/11565 [==============================] - 1s 49us/sample - loss: 2.3185 - accuracy: 0.2859\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.3612 - accuracy: 0.2700\n",
"start index for training is 316000\n",
"Train on 10890 samples, validate on 10895 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10890/10890 [==============================] - 1s 47us/sample - loss: 1.8573 - accuracy: 0.4174\n",
"10895/10895 [==============================] - 0s 40us/sample - loss: 1.8487 - accuracy: 0.4077\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.9806 - accuracy: 0.3373\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1424 - accuracy: 0.2814\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.9608 - accuracy: 0.3975\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.3073 - accuracy: 0.2928\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.3518 - accuracy: 0.2790\n",
"start index for training is 317000\n",
"Train on 11225 samples, validate on 11225 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11225/11225 [==============================] - 0s 44us/sample - loss: 1.8408 - accuracy: 0.4166\n",
"11225/11225 [==============================] - 0s 42us/sample - loss: 1.8324 - accuracy: 0.4212\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.9926 - accuracy: 0.3336\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.1511 - accuracy: 0.2814\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.9553 - accuracy: 0.4001\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.3133 - accuracy: 0.2977\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.3632 - accuracy: 0.2807\n",
"start index for training is 318000\n",
"Train on 11290 samples, validate on 11295 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11290/11290 [==============================] - 1s 46us/sample - loss: 1.8700 - accuracy: 0.4123\n",
"11295/11295 [==============================] - 1s 46us/sample - loss: 1.8726 - accuracy: 0.4053\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.9922 - accuracy: 0.3256\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1422 - accuracy: 0.2885\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.9475 - accuracy: 0.4034\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.2942 - accuracy: 0.3068\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.3438 - accuracy: 0.2887\n",
"start index for training is 319000\n",
"Train on 11430 samples, validate on 11435 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11430/11430 [==============================] - 1s 46us/sample - loss: 1.8918 - accuracy: 0.4033\n",
"11435/11435 [==============================] - 1s 44us/sample - loss: 1.9130 - accuracy: 0.3942\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 2.0027 - accuracy: 0.3271\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1617 - accuracy: 0.2849\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.9443 - accuracy: 0.4058\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.3037 - accuracy: 0.3138\n",
"7000/7000 [==============================] - 0s 48us/sample - loss: 2.3577 - accuracy: 0.2926\n",
"start index for training is 320000\n",
"Train on 12600 samples, validate on 12605 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12600/12600 [==============================] - 1s 43us/sample - loss: 1.8588 - accuracy: 0.4156\n",
"12605/12605 [==============================] - 1s 48us/sample - loss: 1.8451 - accuracy: 0.4175\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0054 - accuracy: 0.3152\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 2.1542 - accuracy: 0.2925\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.9407 - accuracy: 0.4089\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.2874 - accuracy: 0.3101\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.3430 - accuracy: 0.2904\n",
"start index for training is 321000\n",
"Train on 11385 samples, validate on 11390 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11385/11385 [==============================] - 0s 43us/sample - loss: 1.8938 - accuracy: 0.4040\n",
"11390/11390 [==============================] - 0s 40us/sample - loss: 1.9318 - accuracy: 0.3867\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0135 - accuracy: 0.3033\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1602 - accuracy: 0.2712\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.9424 - accuracy: 0.4055s - loss: 1.967\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.2886 - accuracy: 0.2904\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3480 - accuracy: 0.2670\n",
"start index for training is 322000\n",
"Train on 11505 samples, validate on 11510 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11505/11505 [==============================] - 0s 43us/sample - loss: 1.8676 - accuracy: 0.4269\n",
"11510/11510 [==============================] - 0s 39us/sample - loss: 1.8559 - accuracy: 0.4336\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0213 - accuracy: 0.2963\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1645 - accuracy: 0.2754\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.9384 - accuracy: 0.4154\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.2872 - accuracy: 0.3128\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.3486 - accuracy: 0.2874\n",
"start index for training is 323000\n",
"Train on 11530 samples, validate on 11535 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11530/11530 [==============================] - 1s 45us/sample - loss: 1.8629 - accuracy: 0.4133\n",
"11535/11535 [==============================] - 0s 41us/sample - loss: 1.8696 - accuracy: 0.4084\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.0220 - accuracy: 0.3027\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1662 - accuracy: 0.2778\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.9383 - accuracy: 0.4146\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.2764 - accuracy: 0.3163\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3355 - accuracy: 0.2943\n",
"start index for training is 324000\n",
"Train on 10550 samples, validate on 10555 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10550/10550 [==============================] - 1s 48us/sample - loss: 1.8728 - accuracy: 0.4141\n",
"10555/10555 [==============================] - 0s 44us/sample - loss: 1.8828 - accuracy: 0.4169\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0234 - accuracy: 0.3007\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.1545 - accuracy: 0.2857\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 1.9376 - accuracy: 0.4171\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2561 - accuracy: 0.3147\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3203 - accuracy: 0.2881\n",
"start index for training is 325000\n",
"Train on 12430 samples, validate on 12435 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12430/12430 [==============================] - 1s 50us/sample - loss: 1.8441 - accuracy: 0.4356\n",
"12435/12435 [==============================] - 1s 43us/sample - loss: 1.8548 - accuracy: 0.4292\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0405 - accuracy: 0.3095\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 2.1559 - accuracy: 0.2911\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.9497 - accuracy: 0.4113\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2497 - accuracy: 0.3238\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.3114 - accuracy: 0.2997\n",
"start index for training is 326000\n",
"Train on 11275 samples, validate on 11275 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11275/11275 [==============================] - 0s 43us/sample - loss: 1.9013 - accuracy: 0.4103\n",
"11275/11275 [==============================] - 0s 42us/sample - loss: 1.8966 - accuracy: 0.4169\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0410 - accuracy: 0.3037\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1598 - accuracy: 0.2785\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.9471 - accuracy: 0.4105\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.2334 - accuracy: 0.3235\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3009 - accuracy: 0.2954\n",
"start index for training is 327000\n",
"Train on 11115 samples, validate on 11115 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11115/11115 [==============================] - 1s 45us/sample - loss: 1.9092 - accuracy: 0.4176\n",
"11115/11115 [==============================] - 0s 41us/sample - loss: 1.9243 - accuracy: 0.4097\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0456 - accuracy: 0.2945\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1593 - accuracy: 0.2831\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9519 - accuracy: 0.4052\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.2148 - accuracy: 0.3262\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.2844 - accuracy: 0.2953\n",
"start index for training is 328000\n",
"Train on 11215 samples, validate on 11220 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11215/11215 [==============================] - 0s 43us/sample - loss: 1.8956 - accuracy: 0.4210\n",
"11220/11220 [==============================] - 0s 38us/sample - loss: 1.9340 - accuracy: 0.4075\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0398 - accuracy: 0.3149\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1503 - accuracy: 0.2906\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.9575 - accuracy: 0.4035\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1997 - accuracy: 0.3262\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2692 - accuracy: 0.3047\n",
"start index for training is 329000\n",
"Train on 11915 samples, validate on 11915 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11915/11915 [==============================] - 1s 48us/sample - loss: 1.8923 - accuracy: 0.4263\n",
"11915/11915 [==============================] - 0s 40us/sample - loss: 1.9052 - accuracy: 0.4178\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0481 - accuracy: 0.3241\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1434 - accuracy: 0.2980\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.9679 - accuracy: 0.3931\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1856 - accuracy: 0.3386\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2574 - accuracy: 0.3114\n",
"start index for training is 330000\n",
"Train on 12265 samples, validate on 12265 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12265/12265 [==============================] - 1s 43us/sample - loss: 1.8799 - accuracy: 0.4272\n",
"12265/12265 [==============================] - 1s 43us/sample - loss: 1.9094 - accuracy: 0.4126\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 2.0454 - accuracy: 0.3309\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.1419 - accuracy: 0.3035\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.9640 - accuracy: 0.3945\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1726 - accuracy: 0.3407\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2446 - accuracy: 0.3131\n",
"start index for training is 331000\n",
"Train on 12430 samples, validate on 12435 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12430/12430 [==============================] - 1s 50us/sample - loss: 1.8833 - accuracy: 0.4327\n",
"12435/12435 [==============================] - 1s 41us/sample - loss: 1.9054 - accuracy: 0.4223\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0437 - accuracy: 0.3276\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1357 - accuracy: 0.2925\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.9707 - accuracy: 0.3963\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1556 - accuracy: 0.3473\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.2232 - accuracy: 0.3181\n",
"start index for training is 332000\n",
"Train on 12970 samples, validate on 12970 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12970/12970 [==============================] - 1s 47us/sample - loss: 1.8767 - accuracy: 0.4301\n",
"12970/12970 [==============================] - 1s 47us/sample - loss: 1.8893 - accuracy: 0.4237\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 2.0609 - accuracy: 0.3331\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.1444 - accuracy: 0.2925\n",
"14070/14070 [==============================] - 1s 61us/sample - loss: 1.9790 - accuracy: 0.3772\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.1460 - accuracy: 0.3496\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2173 - accuracy: 0.3226\n",
"start index for training is 333000\n",
"Train on 13000 samples, validate on 13005 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13000/13000 [==============================] - 1s 44us/sample - loss: 1.8958 - accuracy: 0.4214\n",
"13005/13005 [==============================] - 1s 49us/sample - loss: 1.8937 - accuracy: 0.4146\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 2.0581 - accuracy: 0.3363\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1344 - accuracy: 0.3018\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9887 - accuracy: 0.3777\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1256 - accuracy: 0.3463\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.1958 - accuracy: 0.3213\n",
"start index for training is 334000\n",
"Train on 10445 samples, validate on 10450 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10445/10445 [==============================] - 0s 45us/sample - loss: 2.0153 - accuracy: 0.3835\n",
"10450/10450 [==============================] - 0s 45us/sample - loss: 2.0358 - accuracy: 0.3790\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0619 - accuracy: 0.3247\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1360 - accuracy: 0.2964\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9730 - accuracy: 0.4016\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.1178 - accuracy: 0.3489\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.1883 - accuracy: 0.3197\n",
"start index for training is 335000\n",
"Train on 14175 samples, validate on 14175 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14175/14175 [==============================] - 1s 47us/sample - loss: 1.9031 - accuracy: 0.4126\n",
"14175/14175 [==============================] - 1s 42us/sample - loss: 1.9390 - accuracy: 0.4030\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0824 - accuracy: 0.3139\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1378 - accuracy: 0.2940\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.9960 - accuracy: 0.3828\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.1024 - accuracy: 0.3500\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1694 - accuracy: 0.3229\n",
"start index for training is 336000\n",
"Train on 12345 samples, validate on 12345 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12345/12345 [==============================] - 1s 43us/sample - loss: 1.9245 - accuracy: 0.4093\n",
"12345/12345 [==============================] - 0s 39us/sample - loss: 1.9395 - accuracy: 0.4055\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0804 - accuracy: 0.3234\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1309 - accuracy: 0.3035\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0048 - accuracy: 0.3792\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.0826 - accuracy: 0.3566\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1483 - accuracy: 0.3283\n",
"start index for training is 337000\n",
"Train on 12580 samples, validate on 12580 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12580/12580 [==============================] - 1s 44us/sample - loss: 2.0118 - accuracy: 0.3742\n",
"12580/12580 [==============================] - 1s 44us/sample - loss: 2.0171 - accuracy: 0.3614\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0822 - accuracy: 0.3227\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.1407 - accuracy: 0.3017\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.0002 - accuracy: 0.3758\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.0752 - accuracy: 0.3475\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1495 - accuracy: 0.3083\n",
"start index for training is 338000\n",
"Train on 12385 samples, validate on 12390 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12385/12385 [==============================] - 1s 43us/sample - loss: 1.9517 - accuracy: 0.4023\n",
"12390/12390 [==============================] - 0s 38us/sample - loss: 1.9517 - accuracy: 0.4061\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0887 - accuracy: 0.3012\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1290 - accuracy: 0.2987\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.0210 - accuracy: 0.3721\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.0585 - accuracy: 0.3621\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1211 - accuracy: 0.3413\n",
"start index for training is 339000\n",
"Train on 13315 samples, validate on 13320 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13315/13315 [==============================] - 1s 46us/sample - loss: 2.0110 - accuracy: 0.3733\n",
"13320/13320 [==============================] - 1s 42us/sample - loss: 2.0236 - accuracy: 0.3755\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 2.0841 - accuracy: 0.2997\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1343 - accuracy: 0.2943\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0205 - accuracy: 0.3754\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.0453 - accuracy: 0.3748\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1122 - accuracy: 0.3469\n",
"start index for training is 340000\n",
"Train on 10900 samples, validate on 10905 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10900/10900 [==============================] - 0s 42us/sample - loss: 2.0399 - accuracy: 0.3748s - loss: 2.0354 - accuracy: 0.\n",
"10905/10905 [==============================] - 0s 39us/sample - loss: 2.0579 - accuracy: 0.3701\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0865 - accuracy: 0.2977\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1352 - accuracy: 0.2984\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.0270 - accuracy: 0.3659\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.0340 - accuracy: 0.3820\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.0961 - accuracy: 0.3597\n",
"start index for training is 341000\n",
"Train on 13780 samples, validate on 13780 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13780/13780 [==============================] - 1s 50us/sample - loss: 1.9616 - accuracy: 0.4078\n",
"13780/13780 [==============================] - 1s 43us/sample - loss: 1.9434 - accuracy: 0.4101\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.1205 - accuracy: 0.2985\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1480 - accuracy: 0.3006\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0473 - accuracy: 0.3598\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.0228 - accuracy: 0.3777\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.0754 - accuracy: 0.3594\n",
"start index for training is 342000\n",
"Train on 13165 samples, validate on 13170 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13165/13165 [==============================] - 1s 43us/sample - loss: 2.0375 - accuracy: 0.3817\n",
"13170/13170 [==============================] - 1s 39us/sample - loss: 2.0483 - accuracy: 0.3756\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1114 - accuracy: 0.2886\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1511 - accuracy: 0.2835\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.0500 - accuracy: 0.3741\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.0196 - accuracy: 0.3858\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.0784 - accuracy: 0.3564\n",
"start index for training is 343000\n",
"Train on 11910 samples, validate on 11910 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11910/11910 [==============================] - 0s 41us/sample - loss: 2.0477 - accuracy: 0.3732\n",
"11910/11910 [==============================] - 0s 39us/sample - loss: 2.0751 - accuracy: 0.3719\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1162 - accuracy: 0.2846s - loss: 2.1114 - accuracy: \n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.1496 - accuracy: 0.3044\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.0436 - accuracy: 0.3678s - loss: 2.0512 - accuracy\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.0081 - accuracy: 0.3880\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0597 - accuracy: 0.3661\n",
"start index for training is 344000\n",
"Train on 11505 samples, validate on 11510 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11505/11505 [==============================] - 0s 43us/sample - loss: 2.0540 - accuracy: 0.3818\n",
"11510/11510 [==============================] - 1s 45us/sample - loss: 2.0715 - accuracy: 0.3758\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1295 - accuracy: 0.3065\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1486 - accuracy: 0.3011\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.0588 - accuracy: 0.3628\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.9948 - accuracy: 0.3961\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0405 - accuracy: 0.3737\n",
"start index for training is 345000\n",
"Train on 11530 samples, validate on 11530 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11530/11530 [==============================] - 0s 42us/sample - loss: 2.0522 - accuracy: 0.3736\n",
"11530/11530 [==============================] - 0s 39us/sample - loss: 2.0695 - accuracy: 0.3776\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1193 - accuracy: 0.2920\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1489 - accuracy: 0.2985\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.0533 - accuracy: 0.3625\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 1.9911 - accuracy: 0.3953\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.0366 - accuracy: 0.3756\n",
"start index for training is 346000\n",
"Train on 11730 samples, validate on 11730 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11730/11730 [==============================] - 0s 43us/sample - loss: 2.0734 - accuracy: 0.3688\n",
"11730/11730 [==============================] - 0s 38us/sample - loss: 2.0512 - accuracy: 0.3772\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1296 - accuracy: 0.2898\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1585 - accuracy: 0.3038\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.0680 - accuracy: 0.3619\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 1.9862 - accuracy: 0.3910\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.0273 - accuracy: 0.3764\n",
"start index for training is 347000\n",
"Train on 12080 samples, validate on 12085 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12080/12080 [==============================] - 1s 44us/sample - loss: 2.0663 - accuracy: 0.3740\n",
"12085/12085 [==============================] - 0s 38us/sample - loss: 2.0640 - accuracy: 0.3775\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1346 - accuracy: 0.3054\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1603 - accuracy: 0.2948\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0617 - accuracy: 0.3726\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.9805 - accuracy: 0.4042\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.0182 - accuracy: 0.3836\n",
"start index for training is 348000\n",
"Train on 12115 samples, validate on 12115 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12115/12115 [==============================] - 1s 44us/sample - loss: 2.0588 - accuracy: 0.3770\n",
"12115/12115 [==============================] - 0s 41us/sample - loss: 2.0724 - accuracy: 0.3772\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1406 - accuracy: 0.2875\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1665 - accuracy: 0.2901\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.0646 - accuracy: 0.3646\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 1.9766 - accuracy: 0.4032\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.0130 - accuracy: 0.3817\n",
"start index for training is 349000\n",
"Train on 11955 samples, validate on 11955 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11955/11955 [==============================] - 1s 42us/sample - loss: 2.0646 - accuracy: 0.3721\n",
"11955/11955 [==============================] - 0s 38us/sample - loss: 2.0652 - accuracy: 0.3720\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1482 - accuracy: 0.3074\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1637 - accuracy: 0.2980\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.0853 - accuracy: 0.3536\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 1.9682 - accuracy: 0.4048\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9948 - accuracy: 0.3897\n",
"start index for training is 350000\n",
"Train on 11580 samples, validate on 11580 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11580/11580 [==============================] - 1s 48us/sample - loss: 2.0859 - accuracy: 0.3668\n",
"11580/11580 [==============================] - 0s 39us/sample - loss: 2.0653 - accuracy: 0.3729\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1491 - accuracy: 0.3157\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.1605 - accuracy: 0.3044\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.0884 - accuracy: 0.3551\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 1.9645 - accuracy: 0.4025\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 1.9833 - accuracy: 0.3910\n",
"start index for training is 351000\n",
"Train on 11235 samples, validate on 11240 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11235/11235 [==============================] - 0s 42us/sample - loss: 2.0972 - accuracy: 0.3664\n",
"11240/11240 [==============================] - 0s 37us/sample - loss: 2.0873 - accuracy: 0.3637\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1446 - accuracy: 0.3042\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.1585 - accuracy: 0.2960\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.0834 - accuracy: 0.3557\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 1.9584 - accuracy: 0.4085\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.9713 - accuracy: 0.3913\n",
"start index for training is 352000\n",
"Train on 11185 samples, validate on 11190 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11185/11185 [==============================] - 0s 43us/sample - loss: 2.0950 - accuracy: 0.3620\n",
"11190/11190 [==============================] - 0s 43us/sample - loss: 2.0757 - accuracy: 0.3653\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1641 - accuracy: 0.2923\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1696 - accuracy: 0.3032\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.1031 - accuracy: 0.3420\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 1.9579 - accuracy: 0.4087\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 1.9616 - accuracy: 0.3983\n",
"start index for training is 353000\n",
"Train on 11225 samples, validate on 11225 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11225/11225 [==============================] - 0s 40us/sample - loss: 2.0922 - accuracy: 0.3623\n",
"11225/11225 [==============================] - 0s 38us/sample - loss: 2.0878 - accuracy: 0.3626\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1617 - accuracy: 0.3033\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.1711 - accuracy: 0.3076\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0878 - accuracy: 0.3460\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.9542 - accuracy: 0.4092\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9542 - accuracy: 0.3991\n",
"start index for training is 354000\n",
"Train on 11235 samples, validate on 11235 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11235/11235 [==============================] - 0s 44us/sample - loss: 2.1017 - accuracy: 0.3668\n",
"11235/11235 [==============================] - 0s 41us/sample - loss: 2.1125 - accuracy: 0.3618\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1584 - accuracy: 0.2982\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1734 - accuracy: 0.2964\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.0849 - accuracy: 0.3412\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 1.9555 - accuracy: 0.4177\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.9513 - accuracy: 0.4107\n",
"start index for training is 355000\n",
"Train on 11350 samples, validate on 11350 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11350/11350 [==============================] - 1s 48us/sample - loss: 2.1196 - accuracy: 0.3551\n",
"11350/11350 [==============================] - 0s 39us/sample - loss: 2.1049 - accuracy: 0.3619\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1797 - accuracy: 0.2997s - loss: 2.1718 - accuracy\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1833 - accuracy: 0.2935\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0905 - accuracy: 0.3510\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.9509 - accuracy: 0.4171\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 1.9423 - accuracy: 0.4126\n",
"start index for training is 356000\n",
"Train on 11190 samples, validate on 11190 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11190/11190 [==============================] - 0s 43us/sample - loss: 2.0614 - accuracy: 0.3450\n",
"11190/11190 [==============================] - 0s 39us/sample - loss: 2.0988 - accuracy: 0.3340\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9110 - accuracy: 0.3763\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1845 - accuracy: 0.2659\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.0854 - accuracy: 0.3369\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.0900 - accuracy: 0.3253\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1053 - accuracy: 0.3136\n",
"start index for training is 357000\n",
"Train on 11620 samples, validate on 11625 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11620/11620 [==============================] - 0s 42us/sample - loss: 2.0362 - accuracy: 0.3498\n",
"11625/11625 [==============================] - 0s 38us/sample - loss: 2.0706 - accuracy: 0.3410\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.8200 - accuracy: 0.4254\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.1741 - accuracy: 0.2835\n",
"14070/14070 [==============================] - 0s 36us/sample - loss: 2.0989 - accuracy: 0.3288\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.1212 - accuracy: 0.3242\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.1433 - accuracy: 0.3070\n",
"start index for training is 358000\n",
"Train on 12625 samples, validate on 12625 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12625/12625 [==============================] - 1s 43us/sample - loss: 2.0395 - accuracy: 0.3593\n",
"12625/12625 [==============================] - 0s 37us/sample - loss: 2.0359 - accuracy: 0.3608\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.7715 - accuracy: 0.4651\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.1529 - accuracy: 0.2866\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1071 - accuracy: 0.3351\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.1376 - accuracy: 0.3132\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.1576 - accuracy: 0.2946\n",
"start index for training is 359000\n",
"Train on 11980 samples, validate on 11980 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11980/11980 [==============================] - 1s 43us/sample - loss: 2.0403 - accuracy: 0.3742\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11980/11980 [==============================] - 0s 41us/sample - loss: 2.0479 - accuracy: 0.3655\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7402 - accuracy: 0.4779\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1401 - accuracy: 0.2904\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1173 - accuracy: 0.3234\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.1478 - accuracy: 0.3121\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1716 - accuracy: 0.2947\n",
"start index for training is 360000\n",
"Train on 11840 samples, validate on 11840 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11840/11840 [==============================] - 0s 40us/sample - loss: 2.0835 - accuracy: 0.3568\n",
"11840/11840 [==============================] - 0s 35us/sample - loss: 2.0924 - accuracy: 0.3567\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.7339 - accuracy: 0.4960\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.1366 - accuracy: 0.2978\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.1191 - accuracy: 0.3186\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1501 - accuracy: 0.3069\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.1717 - accuracy: 0.2866\n",
"start index for training is 361000\n",
"Train on 14050 samples, validate on 14055 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14050/14050 [==============================] - 1s 42us/sample - loss: 1.9778 - accuracy: 0.3883\n",
"14055/14055 [==============================] - 1s 38us/sample - loss: 1.9957 - accuracy: 0.3794\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 1.6998 - accuracy: 0.4933\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.1429 - accuracy: 0.2781\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1202 - accuracy: 0.3144\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.1834 - accuracy: 0.2947\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.2088 - accuracy: 0.2734\n",
"start index for training is 362000\n",
"Train on 10825 samples, validate on 10825 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10825/10825 [==============================] - 0s 40us/sample - loss: 2.0686 - accuracy: 0.3698\n",
"10825/10825 [==============================] - 0s 38us/sample - loss: 2.0631 - accuracy: 0.3686\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 1.6875 - accuracy: 0.4975\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 2.1222 - accuracy: 0.2946\n",
"14070/14070 [==============================] - 0s 33us/sample - loss: 2.1220 - accuracy: 0.3250\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.1750 - accuracy: 0.2971\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.2012 - accuracy: 0.2806\n",
"start index for training is 363000\n",
"Train on 14680 samples, validate on 14685 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14680/14680 [==============================] - 1s 38us/sample - loss: 1.9317 - accuracy: 0.4096\n",
"14685/14685 [==============================] - 1s 35us/sample - loss: 1.9395 - accuracy: 0.4093\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 1.6547 - accuracy: 0.5191\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.1325 - accuracy: 0.2953\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.1314 - accuracy: 0.3227\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1949 - accuracy: 0.2912\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2179 - accuracy: 0.2777\n",
"start index for training is 364000\n",
"Train on 11160 samples, validate on 11165 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11160/11160 [==============================] - 0s 41us/sample - loss: 2.0275 - accuracy: 0.3800\n",
"11165/11165 [==============================] - 0s 39us/sample - loss: 2.0252 - accuracy: 0.3745\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6556 - accuracy: 0.5177\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.1335 - accuracy: 0.2863\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.1242 - accuracy: 0.3205\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.2103 - accuracy: 0.2883\n",
"7000/7000 [==============================] - 0s 35us/sample - loss: 2.2356 - accuracy: 0.2720\n",
"start index for training is 365000\n",
"Train on 14250 samples, validate on 14255 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14250/14250 [==============================] - 1s 39us/sample - loss: 1.8804 - accuracy: 0.4286\n",
"14255/14255 [==============================] - 1s 35us/sample - loss: 1.9045 - accuracy: 0.4183\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 1.6321 - accuracy: 0.5324\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1458 - accuracy: 0.2871\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1412 - accuracy: 0.3125\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.2243 - accuracy: 0.2813\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.2554 - accuracy: 0.2640\n",
"start index for training is 366000\n",
"Train on 11600 samples, validate on 11600 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11600/11600 [==============================] - 0s 41us/sample - loss: 1.9599 - accuracy: 0.3944\n",
"11600/11600 [==============================] - 0s 39us/sample - loss: 1.9818 - accuracy: 0.3865\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.6314 - accuracy: 0.5334s - loss: 1.6221 - accuracy: \n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1301 - accuracy: 0.2929\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.1300 - accuracy: 0.3193\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2229 - accuracy: 0.2817\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2554 - accuracy: 0.2669\n",
"start index for training is 367000\n",
"Train on 14205 samples, validate on 14205 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14205/14205 [==============================] - 1s 45us/sample - loss: 1.8469 - accuracy: 0.4413\n",
"14205/14205 [==============================] - 1s 38us/sample - loss: 1.8606 - accuracy: 0.4367\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6056 - accuracy: 0.5500\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1326 - accuracy: 0.2986\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.1369 - accuracy: 0.3108\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.2317 - accuracy: 0.2821\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.2579 - accuracy: 0.2690\n",
"start index for training is 368000\n",
"Train on 10590 samples, validate on 10595 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10590/10590 [==============================] - 0s 41us/sample - loss: 1.9435 - accuracy: 0.4044\n",
"10595/10595 [==============================] - 0s 38us/sample - loss: 1.9514 - accuracy: 0.4086\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6071 - accuracy: 0.5533\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1329 - accuracy: 0.2996\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.1274 - accuracy: 0.3141\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.2348 - accuracy: 0.2795\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.2673 - accuracy: 0.2664\n",
"start index for training is 369000\n",
"Train on 14805 samples, validate on 14810 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14805/14805 [==============================] - 1s 40us/sample - loss: 1.8290 - accuracy: 0.4394\n",
"14810/14810 [==============================] - 1s 36us/sample - loss: 1.8346 - accuracy: 0.4387\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.5919 - accuracy: 0.5540\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 2.1343 - accuracy: 0.2969\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.1489 - accuracy: 0.3053\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.2515 - accuracy: 0.2774\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.2832 - accuracy: 0.2657\n",
"start index for training is 370000\n",
"Train on 12300 samples, validate on 12305 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12300/12300 [==============================] - 1s 47us/sample - loss: 1.8178 - accuracy: 0.4472\n",
"12305/12305 [==============================] - 0s 40us/sample - loss: 1.8459 - accuracy: 0.4353\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5671 - accuracy: 0.5552\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1293 - accuracy: 0.2947\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1648 - accuracy: 0.2978\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.2704 - accuracy: 0.2751\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.3062 - accuracy: 0.2693\n",
"start index for training is 371000\n",
"Train on 14615 samples, validate on 14615 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14615/14615 [==============================] - 1s 41us/sample - loss: 1.8553 - accuracy: 0.4226\n",
"14615/14615 [==============================] - 1s 38us/sample - loss: 1.8615 - accuracy: 0.4140\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 1.5815 - accuracy: 0.5162\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 2.1220 - accuracy: 0.3014\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.1557 - accuracy: 0.3139\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.2630 - accuracy: 0.2936\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.2943 - accuracy: 0.2879\n",
"start index for training is 372000\n",
"Train on 11675 samples, validate on 11680 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11675/11675 [==============================] - 1s 48us/sample - loss: 1.8475 - accuracy: 0.4168\n",
"11680/11680 [==============================] - 0s 40us/sample - loss: 1.8866 - accuracy: 0.4039\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.5683 - accuracy: 0.5483\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1146 - accuracy: 0.2978\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.1601 - accuracy: 0.3072\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.2740 - accuracy: 0.2803\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3086 - accuracy: 0.2667\n",
"start index for training is 373000\n",
"Train on 15285 samples, validate on 15290 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15285/15285 [==============================] - 1s 42us/sample - loss: 1.7785 - accuracy: 0.4396\n",
"15290/15290 [==============================] - 1s 37us/sample - loss: 1.7759 - accuracy: 0.4451\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.5563 - accuracy: 0.5085\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1169 - accuracy: 0.2973\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1770 - accuracy: 0.3065\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.2906 - accuracy: 0.2923\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3256 - accuracy: 0.2846\n",
"start index for training is 374000\n",
"Train on 15410 samples, validate on 15410 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15410/15410 [==============================] - 1s 45us/sample - loss: 1.8239 - accuracy: 0.4160\n",
"15410/15410 [==============================] - 1s 42us/sample - loss: 1.8385 - accuracy: 0.4087\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5639 - accuracy: 0.5490\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1072 - accuracy: 0.3040\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.1781 - accuracy: 0.2967\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.2926 - accuracy: 0.2832\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3258 - accuracy: 0.2710\n",
"start index for training is 375000\n",
"Train on 14525 samples, validate on 14530 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14525/14525 [==============================] - 1s 47us/sample - loss: 1.8208 - accuracy: 0.4207\n",
"14530/14530 [==============================] - 1s 44us/sample - loss: 1.8598 - accuracy: 0.4021\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.5594 - accuracy: 0.5401\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 2.0972 - accuracy: 0.2974\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.1815 - accuracy: 0.2993\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.2984 - accuracy: 0.2827\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.3362 - accuracy: 0.2644\n",
"start index for training is 376000\n",
"Train on 14190 samples, validate on 14190 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14190/14190 [==============================] - 1s 45us/sample - loss: 1.8247 - accuracy: 0.4094\n",
"14190/14190 [==============================] - 1s 45us/sample - loss: 1.8277 - accuracy: 0.4123\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5581 - accuracy: 0.5483\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0788 - accuracy: 0.2996\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.1902 - accuracy: 0.2940\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.2963 - accuracy: 0.2817\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.3328 - accuracy: 0.2673\n",
"start index for training is 377000\n",
"Train on 14630 samples, validate on 14630 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14630/14630 [==============================] - 1s 44us/sample - loss: 1.8047 - accuracy: 0.4198\n",
"14630/14630 [==============================] - 1s 42us/sample - loss: 1.8304 - accuracy: 0.4135\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.5624 - accuracy: 0.5087\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0771 - accuracy: 0.3024\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.1931 - accuracy: 0.3085\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.3059 - accuracy: 0.2975\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.3436 - accuracy: 0.2886\n",
"start index for training is 378000\n",
"Train on 15320 samples, validate on 15320 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"15320/15320 [==============================] - 1s 55us/sample - loss: 1.8047 - accuracy: 0.4164\n",
"15320/15320 [==============================] - 1s 45us/sample - loss: 1.8162 - accuracy: 0.4095\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.5644 - accuracy: 0.5079\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 2.0641 - accuracy: 0.3101\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.2105 - accuracy: 0.3022\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.3069 - accuracy: 0.2901\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.3389 - accuracy: 0.2846\n",
"start index for training is 379000\n",
"Train on 14445 samples, validate on 14445 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14445/14445 [==============================] - 1s 49us/sample - loss: 1.7832 - accuracy: 0.4278\n",
"14445/14445 [==============================] - 1s 51us/sample - loss: 1.8112 - accuracy: 0.4175\n",
"5980/5980 [==============================] - 0s 53us/sample - loss: 1.5594 - accuracy: 0.5010\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 2.0667 - accuracy: 0.3030\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.2004 - accuracy: 0.3117s - loss: 2.188\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.3135 - accuracy: 0.3009\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.3489 - accuracy: 0.2920\n",
"start index for training is 380000\n",
"Train on 9480 samples, validate on 9480 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9480/9480 [==============================] - 0s 44us/sample - loss: 1.9882 - accuracy: 0.3517\n",
"9480/9480 [==============================] - 0s 44us/sample - loss: 1.9959 - accuracy: 0.3499\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.5810 - accuracy: 0.5294\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0593 - accuracy: 0.3052\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.1907 - accuracy: 0.3062\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3192 - accuracy: 0.2749\n",
"7000/7000 [==============================] - 0s 48us/sample - loss: 2.3581 - accuracy: 0.2524\n",
"start index for training is 381000\n",
"Train on 17025 samples, validate on 17030 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17025/17025 [==============================] - 1s 43us/sample - loss: 1.8196 - accuracy: 0.4134\n",
"17030/17030 [==============================] - 1s 40us/sample - loss: 1.8167 - accuracy: 0.4104\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.5612 - accuracy: 0.5296\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0605 - accuracy: 0.3077\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.1964 - accuracy: 0.3021\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.3336 - accuracy: 0.2675\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.3727 - accuracy: 0.2579\n",
"start index for training is 382000\n",
"Train on 16970 samples, validate on 16970 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16970/16970 [==============================] - 1s 41us/sample - loss: 1.7985 - accuracy: 0.4186\n",
"16970/16970 [==============================] - 1s 37us/sample - loss: 1.8068 - accuracy: 0.4126\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.5590 - accuracy: 0.5025\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0448 - accuracy: 0.3013\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.2031 - accuracy: 0.3144\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3213 - accuracy: 0.2914\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.3588 - accuracy: 0.2814\n",
"start index for training is 383000\n",
"Train on 16395 samples, validate on 16400 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16395/16395 [==============================] - 1s 45us/sample - loss: 1.7932 - accuracy: 0.4229\n",
"16400/16400 [==============================] - 1s 39us/sample - loss: 1.7978 - accuracy: 0.4187\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.5641 - accuracy: 0.5084\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0355 - accuracy: 0.3120\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2115 - accuracy: 0.2991\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3239 - accuracy: 0.2875\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3643 - accuracy: 0.2770\n",
"start index for training is 384000\n",
"Train on 15575 samples, validate on 15575 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15575/15575 [==============================] - 1s 44us/sample - loss: 1.7861 - accuracy: 0.4252\n",
"15575/15575 [==============================] - 1s 40us/sample - loss: 1.7914 - accuracy: 0.4234\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5705 - accuracy: 0.5010\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.0339 - accuracy: 0.3122\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2201 - accuracy: 0.3048\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3359 - accuracy: 0.2782\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3760 - accuracy: 0.2699\n",
"start index for training is 385000\n",
"Train on 8560 samples, validate on 8565 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8560/8560 [==============================] - 0s 48us/sample - loss: 2.0136 - accuracy: 0.3487\n",
"8565/8565 [==============================] - 0s 43us/sample - loss: 2.0159 - accuracy: 0.3449\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5895 - accuracy: 0.5237\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.0295 - accuracy: 0.3069\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2104 - accuracy: 0.3039\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3421 - accuracy: 0.2656\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3893 - accuracy: 0.2466\n",
"start index for training is 386000\n",
"Train on 18775 samples, validate on 18780 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18775/18775 [==============================] - 1s 43us/sample - loss: 1.8002 - accuracy: 0.4103\n",
"18780/18780 [==============================] - 1s 40us/sample - loss: 1.7977 - accuracy: 0.4126\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.5726 - accuracy: 0.4915\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0181 - accuracy: 0.3100\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2204 - accuracy: 0.3149\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3389 - accuracy: 0.2833\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3818 - accuracy: 0.2739\n",
"start index for training is 387000\n",
"Train on 18665 samples, validate on 18670 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18665/18665 [==============================] - 1s 42us/sample - loss: 1.7838 - accuracy: 0.4230\n",
"18670/18670 [==============================] - 1s 39us/sample - loss: 1.7999 - accuracy: 0.4172\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.5719 - accuracy: 0.5043\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0125 - accuracy: 0.3228\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2192 - accuracy: 0.3077\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3373 - accuracy: 0.2843\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3796 - accuracy: 0.2760\n",
"start index for training is 388000\n",
"Train on 16240 samples, validate on 16240 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16240/16240 [==============================] - 1s 49us/sample - loss: 1.7765 - accuracy: 0.4291\n",
"16240/16240 [==============================] - 1s 43us/sample - loss: 1.7784 - accuracy: 0.4246\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.5817 - accuracy: 0.5209\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0121 - accuracy: 0.3269\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2279 - accuracy: 0.2977\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3494 - accuracy: 0.2700\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.3885 - accuracy: 0.2709\n",
"start index for training is 389000\n",
"Train on 9415 samples, validate on 9420 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9415/9415 [==============================] - 0s 42us/sample - loss: 1.9921 - accuracy: 0.3486\n",
"9420/9420 [==============================] - 0s 39us/sample - loss: 2.0137 - accuracy: 0.3455\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.6042 - accuracy: 0.5446\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0038 - accuracy: 0.3164\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2370 - accuracy: 0.2877\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3565 - accuracy: 0.2588\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4021 - accuracy: 0.2396\n",
"start index for training is 390000\n",
"Train on 19845 samples, validate on 19845 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19845/19845 [==============================] - 1s 43us/sample - loss: 1.7955 - accuracy: 0.4151\n",
"19845/19845 [==============================] - 1s 40us/sample - loss: 1.7896 - accuracy: 0.4170\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.5870 - accuracy: 0.5057\n",
"12255/12255 [==============================] - ETA: 0s - loss: 2.0081 - accuracy: 0.30 - 0s 40us/sample - loss: 2.0040 - accuracy: 0.3108\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2279 - accuracy: 0.3033\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3544 - accuracy: 0.2773\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3991 - accuracy: 0.2659\n",
"start index for training is 391000\n",
"Train on 18055 samples, validate on 18055 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18055/18055 [==============================] - 1s 43us/sample - loss: 1.7598 - accuracy: 0.4198\n",
"18055/18055 [==============================] - 1s 39us/sample - loss: 1.7787 - accuracy: 0.4160\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.5938 - accuracy: 0.5005\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0041 - accuracy: 0.3244\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2437 - accuracy: 0.2890\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3640 - accuracy: 0.2674\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4100 - accuracy: 0.2640\n",
"start index for training is 392000\n",
"Train on 8670 samples, validate on 8670 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8670/8670 [==============================] - 0s 43us/sample - loss: 2.0304 - accuracy: 0.3336\n",
"8670/8670 [==============================] - 0s 39us/sample - loss: 2.0442 - accuracy: 0.3349\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.6201 - accuracy: 0.4940\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9991 - accuracy: 0.3044\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2321 - accuracy: 0.2928\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3643 - accuracy: 0.2542\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4175 - accuracy: 0.2464\n",
"start index for training is 393000\n",
"Train on 21325 samples, validate on 21325 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21325/21325 [==============================] - 1s 43us/sample - loss: 1.7820 - accuracy: 0.4222\n",
"21325/21325 [==============================] - 1s 40us/sample - loss: 1.7835 - accuracy: 0.4213\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.5995 - accuracy: 0.5219\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9883 - accuracy: 0.3332\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2460 - accuracy: 0.2940\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3705 - accuracy: 0.2662\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4196 - accuracy: 0.2581\n",
"start index for training is 394000\n",
"Train on 15165 samples, validate on 15170 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15165/15165 [==============================] - 1s 44us/sample - loss: 1.7572 - accuracy: 0.4334\n",
"15170/15170 [==============================] - 1s 42us/sample - loss: 1.7658 - accuracy: 0.4303\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.6022 - accuracy: 0.5219\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.9894 - accuracy: 0.3324\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.2521 - accuracy: 0.2925\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3752 - accuracy: 0.2692\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4233 - accuracy: 0.2710\n",
"start index for training is 395000\n",
"Train on 12860 samples, validate on 12865 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12860/12860 [==============================] - 1s 46us/sample - loss: 1.9637 - accuracy: 0.3589\n",
"12865/12865 [==============================] - 1s 40us/sample - loss: 1.9492 - accuracy: 0.3664\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6183 - accuracy: 0.5211\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9809 - accuracy: 0.3164\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2367 - accuracy: 0.2734\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3690 - accuracy: 0.2434\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4178 - accuracy: 0.2351\n",
"start index for training is 396000\n",
"Train on 20365 samples, validate on 20365 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20365/20365 [==============================] - 1s 48us/sample - loss: 1.7645 - accuracy: 0.4208\n",
"20365/20365 [==============================] - 1s 41us/sample - loss: 1.7593 - accuracy: 0.4198\n",
"5980/5980 [==============================] - ETA: 0s - loss: 1.6046 - accuracy: 0.51 - 0s 40us/sample - loss: 1.6010 - accuracy: 0.5132\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9718 - accuracy: 0.3300\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2594 - accuracy: 0.2887\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3840 - accuracy: 0.2532\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4338 - accuracy: 0.2526\n",
"start index for training is 397000\n",
"Train on 7305 samples, validate on 7310 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7305/7305 [==============================] - 0s 45us/sample - loss: 2.0769 - accuracy: 0.3064\n",
"7310/7310 [==============================] - 0s 41us/sample - loss: 2.0954 - accuracy: 0.3042\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6401 - accuracy: 0.4982\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9823 - accuracy: 0.3074\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2529 - accuracy: 0.2950\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3858 - accuracy: 0.2445\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4458 - accuracy: 0.2226\n",
"start index for training is 398000\n",
"Train on 22565 samples, validate on 22570 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"22565/22565 [==============================] - 1s 48us/sample - loss: 1.7777 - accuracy: 0.4136\n",
"22570/22570 [==============================] - 1s 42us/sample - loss: 1.7815 - accuracy: 0.4167\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.6093 - accuracy: 0.5167\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9636 - accuracy: 0.3411\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 2.2589 - accuracy: 0.2834\n",
"11565/11565 [==============================] - 1s 66us/sample - loss: 2.3808 - accuracy: 0.2672\n",
"7000/7000 [==============================] - 0s 57us/sample - loss: 2.4334 - accuracy: 0.2644\n",
"start index for training is 399000\n",
"Train on 11680 samples, validate on 11685 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11680/11680 [==============================] - 0s 41us/sample - loss: 1.7609 - accuracy: 0.4390\n",
"11685/11685 [==============================] - 0s 40us/sample - loss: 1.7921 - accuracy: 0.4265\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.6262 - accuracy: 0.4945\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9646 - accuracy: 0.3472\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2768 - accuracy: 0.2781\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3957 - accuracy: 0.2623\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4488 - accuracy: 0.2626\n",
"start index for training is 400000\n",
"Train on 17490 samples, validate on 17495 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17490/17490 [==============================] - 1s 46us/sample - loss: 1.8712 - accuracy: 0.3919\n",
"17495/17495 [==============================] - 1s 49us/sample - loss: 1.8912 - accuracy: 0.3825\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 1.6238 - accuracy: 0.5089\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.9579 - accuracy: 0.3302\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2549 - accuracy: 0.2846\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3842 - accuracy: 0.2635\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4364 - accuracy: 0.2519\n",
"start index for training is 401000\n",
"Train on 16810 samples, validate on 16810 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16810/16810 [==============================] - 1s 43us/sample - loss: 1.7234 - accuracy: 0.4363\n",
"16810/16810 [==============================] - 1s 38us/sample - loss: 1.7477 - accuracy: 0.4308\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6210 - accuracy: 0.5085\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.9586 - accuracy: 0.3572\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2602 - accuracy: 0.2838\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.4030 - accuracy: 0.2696s - loss: 2.4531 - ac\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4571 - accuracy: 0.2707\n",
"start index for training is 402000\n",
"Train on 12170 samples, validate on 12175 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12170/12170 [==============================] - 1s 44us/sample - loss: 1.9628 - accuracy: 0.3514\n",
"12175/12175 [==============================] - 0s 40us/sample - loss: 1.9828 - accuracy: 0.3538\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.6348 - accuracy: 0.4930\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9448 - accuracy: 0.3326\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2676 - accuracy: 0.2798\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3869 - accuracy: 0.2585\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4444 - accuracy: 0.2437\n",
"start index for training is 403000\n",
"Train on 19860 samples, validate on 19860 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19860/19860 [==============================] - 1s 44us/sample - loss: 1.7333 - accuracy: 0.4334\n",
"19860/19860 [==============================] - 1s 41us/sample - loss: 1.7348 - accuracy: 0.4288\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6228 - accuracy: 0.5080\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.9367 - accuracy: 0.3560\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2814 - accuracy: 0.2785\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.4037 - accuracy: 0.2655\n",
"7000/7000 [==============================] - ETA: 0s - loss: 2.4623 - accuracy: 0.26 - 0s 41us/sample - loss: 2.4567 - accuracy: 0.2681\n",
"start index for training is 404000\n",
"Train on 9005 samples, validate on 9005 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9005/9005 [==============================] - 0s 44us/sample - loss: 2.1348 - accuracy: 0.3034\n",
"9005/9005 [==============================] - 0s 43us/sample - loss: 2.1457 - accuracy: 0.2972\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.7241 - accuracy: 0.4557\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0109 - accuracy: 0.3528\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.3616 - accuracy: 0.2505\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.4422 - accuracy: 0.2573\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4975 - accuracy: 0.2533\n",
"start index for training is 405000\n",
"Train on 21415 samples, validate on 21415 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21415/21415 [==============================] - 1s 44us/sample - loss: 1.7442 - accuracy: 0.4272\n",
"21415/21415 [==============================] - 1s 40us/sample - loss: 1.7675 - accuracy: 0.4188\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6145 - accuracy: 0.4973\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.9274 - accuracy: 0.3532\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.2648 - accuracy: 0.2572\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3948 - accuracy: 0.2405\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4510 - accuracy: 0.2299\n",
"start index for training is 406000\n",
"Train on 7445 samples, validate on 7450 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7445/7445 [==============================] - 0s 44us/sample - loss: 2.0519 - accuracy: 0.3277\n",
"7450/7450 [==============================] - 0s 42us/sample - loss: 2.0845 - accuracy: 0.3228\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6472 - accuracy: 0.4925\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9244 - accuracy: 0.3393\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2516 - accuracy: 0.2774\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3824 - accuracy: 0.2648\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4370 - accuracy: 0.2546s - loss: 2.4388 - accuracy: \n",
"start index for training is 407000\n",
"Train on 21505 samples, validate on 21510 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21505/21505 [==============================] - 1s 42us/sample - loss: 1.7617 - accuracy: 0.4248\n",
"21510/21510 [==============================] - 1s 38us/sample - loss: 1.7774 - accuracy: 0.4181\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6224 - accuracy: 0.5023\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.9070 - accuracy: 0.3653\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2697 - accuracy: 0.2647\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3828 - accuracy: 0.2681\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4356 - accuracy: 0.2673\n",
"start index for training is 408000\n",
"Train on 6585 samples, validate on 6590 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6585/6585 [==============================] - 0s 46us/sample - loss: 2.0632 - accuracy: 0.3209\n",
"6590/6590 [==============================] - 0s 43us/sample - loss: 2.0443 - accuracy: 0.3215\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6465 - accuracy: 0.5172\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9206 - accuracy: 0.3492\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2523 - accuracy: 0.2803\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3935 - accuracy: 0.2508\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4515 - accuracy: 0.2390s - loss: 2.4509 - accuracy: 0.\n",
"start index for training is 409000\n",
"Train on 21620 samples, validate on 21625 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21620/21620 [==============================] - 1s 40us/sample - loss: 1.7687 - accuracy: 0.4229\n",
"21625/21625 [==============================] - 1s 38us/sample - loss: 1.7674 - accuracy: 0.4187\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.6234 - accuracy: 0.4988\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8963 - accuracy: 0.3631\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.2728 - accuracy: 0.2749\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3864 - accuracy: 0.2668\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4448 - accuracy: 0.2623\n",
"start index for training is 410000\n",
"Train on 7885 samples, validate on 7890 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7885/7885 [==============================] - 0s 43us/sample - loss: 1.8783 - accuracy: 0.3990\n",
"7890/7890 [==============================] - 0s 40us/sample - loss: 1.8955 - accuracy: 0.3959\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6577 - accuracy: 0.5139\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.9066 - accuracy: 0.3571\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2942 - accuracy: 0.2682\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3971 - accuracy: 0.2544\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4571 - accuracy: 0.2423\n",
"start index for training is 411000\n",
"Train on 20045 samples, validate on 20050 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20045/20045 [==============================] - 1s 40us/sample - loss: 1.8225 - accuracy: 0.3969\n",
"20050/20050 [==============================] - 1s 37us/sample - loss: 1.8202 - accuracy: 0.3984\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.6402 - accuracy: 0.5166\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9101 - accuracy: 0.3681\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2539 - accuracy: 0.2691\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.4054 - accuracy: 0.2473\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4640 - accuracy: 0.2297\n",
"start index for training is 412000\n",
"Train on 12745 samples, validate on 12750 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12745/12745 [==============================] - 1s 42us/sample - loss: 1.7478 - accuracy: 0.4471\n",
"12750/12750 [==============================] - 0s 38us/sample - loss: 1.7638 - accuracy: 0.4345\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6574 - accuracy: 0.5042\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.8937 - accuracy: 0.3749\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2973 - accuracy: 0.2581\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.4101 - accuracy: 0.2473\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4693 - accuracy: 0.2414\n",
"start index for training is 413000\n",
"Train on 15265 samples, validate on 15270 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15265/15265 [==============================] - 1s 48us/sample - loss: 1.8864 - accuracy: 0.3830\n",
"15270/15270 [==============================] - 1s 43us/sample - loss: 1.8873 - accuracy: 0.3764\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.6485 - accuracy: 0.4783\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8810 - accuracy: 0.3654\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2730 - accuracy: 0.2807\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.3873 - accuracy: 0.2606\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4476 - accuracy: 0.2519\n",
"start index for training is 414000\n",
"Train on 13970 samples, validate on 13975 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13970/13970 [==============================] - 1s 44us/sample - loss: 1.7236 - accuracy: 0.4487\n",
"13975/13975 [==============================] - 1s 43us/sample - loss: 1.7578 - accuracy: 0.4391\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.6627 - accuracy: 0.4890\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.8720 - accuracy: 0.3780\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2957 - accuracy: 0.2612\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3990 - accuracy: 0.2473s - loss: 2.4405 - accura\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4607 - accuracy: 0.2377\n",
"start index for training is 415000\n",
"Train on 14665 samples, validate on 14670 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14665/14665 [==============================] - 1s 41us/sample - loss: 1.8971 - accuracy: 0.3723\n",
"14670/14670 [==============================] - 1s 37us/sample - loss: 1.9102 - accuracy: 0.3658\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.6525 - accuracy: 0.4811\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8762 - accuracy: 0.3593\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2773 - accuracy: 0.2638\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.3810 - accuracy: 0.2425\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4435 - accuracy: 0.2393\n",
"start index for training is 416000\n",
"Train on 11365 samples, validate on 11365 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11365/11365 [==============================] - 0s 43us/sample - loss: 1.7895 - accuracy: 0.4306\n",
"11365/11365 [==============================] - 0s 40us/sample - loss: 1.7706 - accuracy: 0.4237\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6665 - accuracy: 0.4853\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.8769 - accuracy: 0.3713\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2971 - accuracy: 0.2699\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.4057 - accuracy: 0.2498\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4695 - accuracy: 0.2354\n",
"start index for training is 417000\n",
"Train on 17445 samples, validate on 17450 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17445/17445 [==============================] - 1s 42us/sample - loss: 1.8647 - accuracy: 0.3891\n",
"17450/17450 [==============================] - 1s 38us/sample - loss: 1.8585 - accuracy: 0.3897\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.6606 - accuracy: 0.4607\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8576 - accuracy: 0.3716\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.2844 - accuracy: 0.2566\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.3755 - accuracy: 0.2521\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4393 - accuracy: 0.2459\n",
"start index for training is 418000\n",
"Train on 5865 samples, validate on 5870 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5865/5865 [==============================] - 0s 49us/sample - loss: 2.1160 - accuracy: 0.3088\n",
"5870/5870 [==============================] - 0s 41us/sample - loss: 2.1294 - accuracy: 0.3019s - loss: 2.1173 - accuracy: \n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6662 - accuracy: 0.5028\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.8680 - accuracy: 0.3679\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2765 - accuracy: 0.2756\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3695 - accuracy: 0.2600\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4340 - accuracy: 0.2440\n",
"start index for training is 419000\n",
"Train on 21730 samples, validate on 21735 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21730/21730 [==============================] - 1s 40us/sample - loss: 1.7654 - accuracy: 0.4166\n",
"21735/21735 [==============================] - 1s 38us/sample - loss: 1.7645 - accuracy: 0.4152\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.6552 - accuracy: 0.4833\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.8448 - accuracy: 0.3792\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.2918 - accuracy: 0.2625\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.3867 - accuracy: 0.2554\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.4530 - accuracy: 0.2391\n",
"start index for training is 420000\n",
"Train on 6255 samples, validate on 6255 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6255/6255 [==============================] - 0s 44us/sample - loss: 2.1322 - accuracy: 0.2967\n",
"6255/6255 [==============================] - 0s 42us/sample - loss: 2.1446 - accuracy: 0.3106\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6725 - accuracy: 0.5037\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.8525 - accuracy: 0.3798\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2786 - accuracy: 0.2773\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3690 - accuracy: 0.2570\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4298 - accuracy: 0.2460\n",
"start index for training is 421000\n",
"Train on 20270 samples, validate on 20275 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20270/20270 [==============================] - 1s 40us/sample - loss: 1.7811 - accuracy: 0.4238\n",
"20275/20275 [==============================] - 1s 39us/sample - loss: 1.7585 - accuracy: 0.4297\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6605 - accuracy: 0.4696\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8432 - accuracy: 0.3867\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.2993 - accuracy: 0.2532\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3932 - accuracy: 0.2517\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.4590 - accuracy: 0.2441\n",
"start index for training is 422000\n",
"Train on 6750 samples, validate on 6755 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6750/6750 [==============================] - 0s 44us/sample - loss: 2.1186 - accuracy: 0.3196\n",
"6755/6755 [==============================] - 0s 40us/sample - loss: 2.1004 - accuracy: 0.3135\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.6901 - accuracy: 0.4799\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.8510 - accuracy: 0.3768\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2930 - accuracy: 0.2692\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3781 - accuracy: 0.2461\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4423 - accuracy: 0.2441\n",
"start index for training is 423000\n",
"Train on 19745 samples, validate on 19745 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19745/19745 [==============================] - 1s 42us/sample - loss: 1.7720 - accuracy: 0.4248\n",
"19745/19745 [==============================] - 1s 41us/sample - loss: 1.7771 - accuracy: 0.4205\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6548 - accuracy: 0.5087\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.8262 - accuracy: 0.3936\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2986 - accuracy: 0.2643\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3855 - accuracy: 0.2609\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4469 - accuracy: 0.2496\n",
"start index for training is 424000\n",
"Train on 6835 samples, validate on 6840 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6835/6835 [==============================] - 0s 43us/sample - loss: 2.0994 - accuracy: 0.3163\n",
"6840/6840 [==============================] - 0s 42us/sample - loss: 2.1323 - accuracy: 0.3064\n",
"5980/5980 [==============================] - ETA: 0s - loss: 1.6959 - accuracy: 0.46 - 0s 39us/sample - loss: 1.6906 - accuracy: 0.4711\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8342 - accuracy: 0.3958\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2834 - accuracy: 0.2775\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3659 - accuracy: 0.2531\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4242 - accuracy: 0.2470\n",
"start index for training is 425000\n",
"Train on 19780 samples, validate on 19785 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"19780/19780 [==============================] - 1s 48us/sample - loss: 1.7714 - accuracy: 0.4250\n",
"19785/19785 [==============================] - ETA: 0s - loss: 1.7880 - accuracy: 0.41 - 1s 45us/sample - loss: 1.7871 - accuracy: 0.4190\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.6576 - accuracy: 0.5164\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.8118 - accuracy: 0.3940\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2929 - accuracy: 0.2618\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3806 - accuracy: 0.2569\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4407 - accuracy: 0.2503\n",
"start index for training is 426000\n",
"Train on 7360 samples, validate on 7360 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7360/7360 [==============================] - 0s 42us/sample - loss: 2.0927 - accuracy: 0.3209\n",
"7360/7360 [==============================] - 0s 39us/sample - loss: 2.1027 - accuracy: 0.3174\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7058 - accuracy: 0.4567\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.8337 - accuracy: 0.3798\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2938 - accuracy: 0.2738\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3780 - accuracy: 0.2483\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4442 - accuracy: 0.2466\n",
"start index for training is 427000\n",
"Train on 18800 samples, validate on 18805 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18800/18800 [==============================] - 1s 42us/sample - loss: 1.7668 - accuracy: 0.4226\n",
"18805/18805 [==============================] - 1s 38us/sample - loss: 1.7921 - accuracy: 0.4191\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6582 - accuracy: 0.5017\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.8024 - accuracy: 0.3901\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.3011 - accuracy: 0.2593\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3772 - accuracy: 0.2577\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4432 - accuracy: 0.2460\n",
"start index for training is 428000\n",
"Train on 8630 samples, validate on 8635 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8630/8630 [==============================] - 0s 42us/sample - loss: 2.0460 - accuracy: 0.3482\n",
"8635/8635 [==============================] - 0s 38us/sample - loss: 2.1014 - accuracy: 0.3301\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7071 - accuracy: 0.4788\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8265 - accuracy: 0.3961\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3094 - accuracy: 0.2682\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3752 - accuracy: 0.2636\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4412 - accuracy: 0.2527\n",
"start index for training is 429000\n",
"Train on 16720 samples, validate on 16725 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16720/16720 [==============================] - 1s 41us/sample - loss: 1.7638 - accuracy: 0.4334\n",
"16725/16725 [==============================] - 1s 38us/sample - loss: 1.7649 - accuracy: 0.4346\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6775 - accuracy: 0.4759\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7920 - accuracy: 0.4100\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3085 - accuracy: 0.2507s - loss: 2.3106 - ac\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3808 - accuracy: 0.2622\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4476 - accuracy: 0.2526\n",
"start index for training is 430000\n",
"Train on 10950 samples, validate on 10955 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10950/10950 [==============================] - 0s 43us/sample - loss: 2.0384 - accuracy: 0.3499\n",
"10955/10955 [==============================] - 0s 41us/sample - loss: 2.0069 - accuracy: 0.3482\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7024 - accuracy: 0.4572\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8231 - accuracy: 0.3842\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2994 - accuracy: 0.2674\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3683 - accuracy: 0.2458\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4363 - accuracy: 0.2323\n",
"start index for training is 431000\n",
"Train on 11325 samples, validate on 11330 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11325/11325 [==============================] - 0s 42us/sample - loss: 1.7872 - accuracy: 0.4408\n",
"11330/11330 [==============================] - 0s 38us/sample - loss: 1.8061 - accuracy: 0.4337\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7267 - accuracy: 0.4722\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7881 - accuracy: 0.4084\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.3384 - accuracy: 0.2580\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3926 - accuracy: 0.2591\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4594 - accuracy: 0.2491\n",
"start index for training is 432000\n",
"Train on 16490 samples, validate on 16490 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16490/16490 [==============================] - 1s 44us/sample - loss: 1.9128 - accuracy: 0.3797\n",
"16490/16490 [==============================] - 1s 39us/sample - loss: 1.9002 - accuracy: 0.3733\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6620 - accuracy: 0.5007\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7983 - accuracy: 0.4101\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2969 - accuracy: 0.2606\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3619 - accuracy: 0.2694\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4258 - accuracy: 0.2599\n",
"start index for training is 433000\n",
"Train on 6010 samples, validate on 6010 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6010/6010 [==============================] - 0s 51us/sample - loss: 2.1870 - accuracy: 0.3208\n",
"6010/6010 [==============================] - 0s 43us/sample - loss: 2.2146 - accuracy: 0.3012\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7480 - accuracy: 0.4475\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.8794 - accuracy: 0.3826\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3663 - accuracy: 0.2536\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.4567 - accuracy: 0.2553\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.5239 - accuracy: 0.2491\n",
"start index for training is 434000\n",
"Train on 21105 samples, validate on 21110 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21105/21105 [==============================] - 1s 51us/sample - loss: 1.7951 - accuracy: 0.4196\n",
"21110/21110 [==============================] - 1s 42us/sample - loss: 1.7891 - accuracy: 0.4190\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.6675 - accuracy: 0.4783\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.7760 - accuracy: 0.3996\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3177 - accuracy: 0.2480\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3723 - accuracy: 0.2513\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4368 - accuracy: 0.2427\n",
"start index for training is 435000\n",
"Train on 7870 samples, validate on 7875 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7870/7870 [==============================] - 0s 46us/sample - loss: 2.0732 - accuracy: 0.3428\n",
"7875/7875 [==============================] - 0s 42us/sample - loss: 2.0954 - accuracy: 0.3309\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7109 - accuracy: 0.4656\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7974 - accuracy: 0.4003\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3102 - accuracy: 0.2752\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3631 - accuracy: 0.2694\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4263 - accuracy: 0.2684\n",
"start index for training is 436000\n",
"Train on 17015 samples, validate on 17015 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17015/17015 [==============================] - 1s 44us/sample - loss: 1.9474 - accuracy: 0.4061\n",
"17015/17015 [==============================] - 1s 39us/sample - loss: 1.9645 - accuracy: 0.3999\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8750 - accuracy: 0.4140\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9433 - accuracy: 0.3931\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.5596 - accuracy: 0.2408\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.5535 - accuracy: 0.2573\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.6258 - accuracy: 0.2554\n",
"start index for training is 437000\n",
"Train on 12240 samples, validate on 12240 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12240/12240 [==============================] - 1s 42us/sample - loss: 1.9870 - accuracy: 0.3551\n",
"12240/12240 [==============================] - 0s 39us/sample - loss: 1.9973 - accuracy: 0.3507\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.6979 - accuracy: 0.4764\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.7846 - accuracy: 0.3922\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.3190 - accuracy: 0.2711\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3634 - accuracy: 0.2672\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4306 - accuracy: 0.2590\n",
"start index for training is 438000\n",
"Train on 5780 samples, validate on 5780 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5780/5780 [==============================] - 0s 47us/sample - loss: 2.1605 - accuracy: 0.3050\n",
"5780/5780 [==============================] - 0s 41us/sample - loss: 2.2083 - accuracy: 0.3092\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7049 - accuracy: 0.4883\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7951 - accuracy: 0.3945\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.3042 - accuracy: 0.2792\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3506 - accuracy: 0.2657\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4207 - accuracy: 0.2539\n",
"start index for training is 439000\n",
"Train on 22845 samples, validate on 22845 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"22845/22845 [==============================] - 1s 42us/sample - loss: 1.7838 - accuracy: 0.4276\n",
"22845/22845 [==============================] - 1s 41us/sample - loss: 1.7830 - accuracy: 0.4218\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.6629 - accuracy: 0.4975\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7551 - accuracy: 0.4109\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3212 - accuracy: 0.2571\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3664 - accuracy: 0.2681\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4357 - accuracy: 0.2543\n",
"start index for training is 440000\n",
"Train on 8000 samples, validate on 8000 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8000/8000 [==============================] - 0s 43us/sample - loss: 2.0991 - accuracy: 0.3266\n",
"8000/8000 [==============================] - 0s 38us/sample - loss: 2.1294 - accuracy: 0.3187\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7206 - accuracy: 0.4609\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.7790 - accuracy: 0.4105\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.3339 - accuracy: 0.2543\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3620 - accuracy: 0.2738\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4306 - accuracy: 0.2613\n",
"start index for training is 441000\n",
"Train on 14775 samples, validate on 14775 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14775/14775 [==============================] - 1s 41us/sample - loss: 1.7504 - accuracy: 0.4524\n",
"14775/14775 [==============================] - 1s 39us/sample - loss: 1.7781 - accuracy: 0.4397\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6912 - accuracy: 0.4843\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.7506 - accuracy: 0.4203\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3469 - accuracy: 0.2507\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3765 - accuracy: 0.2729\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4455 - accuracy: 0.2631\n",
"start index for training is 442000\n",
"Train on 15385 samples, validate on 15390 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15385/15385 [==============================] - 1s 48us/sample - loss: 1.9464 - accuracy: 0.3591\n",
"15390/15390 [==============================] - 1s 42us/sample - loss: 1.9476 - accuracy: 0.3555\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.6834 - accuracy: 0.4918\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.7691 - accuracy: 0.4040\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.3281 - accuracy: 0.2579\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3558 - accuracy: 0.2609\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4267 - accuracy: 0.2493\n",
"start index for training is 443000\n",
"Train on 6280 samples, validate on 6285 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6280/6280 [==============================] - 0s 45us/sample - loss: 2.1411 - accuracy: 0.3145\n",
"6285/6285 [==============================] - 0s 41us/sample - loss: 2.1927 - accuracy: 0.3090\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7272 - accuracy: 0.4441\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7704 - accuracy: 0.4086\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.3160 - accuracy: 0.2766\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3426 - accuracy: 0.2817\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4048 - accuracy: 0.2743\n",
"start index for training is 444000\n",
"Train on 20680 samples, validate on 20685 samples\n",
"Epoch 1/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20680/20680 [==============================] - 1s 42us/sample - loss: 1.7610 - accuracy: 0.4321\n",
"20685/20685 [==============================] - 1s 39us/sample - loss: 1.7693 - accuracy: 0.4287\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6763 - accuracy: 0.5043\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.7387 - accuracy: 0.4134\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3404 - accuracy: 0.2561\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3798 - accuracy: 0.2623\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4517 - accuracy: 0.2497\n",
"start index for training is 445000\n",
"Train on 10540 samples, validate on 10545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10540/10540 [==============================] - 0s 42us/sample - loss: 2.0413 - accuracy: 0.3431\n",
"10545/10545 [==============================] - 0s 39us/sample - loss: 2.0293 - accuracy: 0.3436\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7050 - accuracy: 0.4453\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.7599 - accuracy: 0.4076\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3258 - accuracy: 0.2712\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3531 - accuracy: 0.2692\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4186 - accuracy: 0.2556\n",
"start index for training is 446000\n",
"Train on 5570 samples, validate on 5575 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5570/5570 [==============================] - 0s 40us/sample - loss: 2.2017 - accuracy: 0.3059\n",
"5575/5575 [==============================] - 0s 43us/sample - loss: 2.2000 - accuracy: 0.3055\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7209 - accuracy: 0.4818\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7785 - accuracy: 0.4019\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.3335 - accuracy: 0.2572\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3526 - accuracy: 0.2622\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4251 - accuracy: 0.2507\n",
"start index for training is 447000\n",
"Train on 23290 samples, validate on 23295 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"23290/23290 [==============================] - 1s 40us/sample - loss: 1.7713 - accuracy: 0.4228\n",
"23295/23295 [==============================] - ETA: 0s - loss: 1.7830 - accuracy: 0.42 - 1s 40us/sample - loss: 1.7821 - accuracy: 0.4203\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6801 - accuracy: 0.5050\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.7267 - accuracy: 0.4161\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.3442 - accuracy: 0.2488\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3737 - accuracy: 0.2625\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4461 - accuracy: 0.2500\n",
"start index for training is 448000\n",
"Train on 8515 samples, validate on 8515 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8515/8515 [==============================] - 0s 42us/sample - loss: 2.0708 - accuracy: 0.3385\n",
"8515/8515 [==============================] - 0s 40us/sample - loss: 2.1476 - accuracy: 0.3150\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.7261 - accuracy: 0.4644\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7543 - accuracy: 0.4162\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.3471 - accuracy: 0.2559\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3536 - accuracy: 0.2722\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4238 - accuracy: 0.2599\n",
"start index for training is 449000\n",
"Train on 10335 samples, validate on 10335 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10335/10335 [==============================] - 0s 43us/sample - loss: 1.7783 - accuracy: 0.4383\n",
"10335/10335 [==============================] - 0s 39us/sample - loss: 1.8072 - accuracy: 0.4346\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.7248 - accuracy: 0.5028\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.7224 - accuracy: 0.4258\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.3696 - accuracy: 0.2575\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3884 - accuracy: 0.2561\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4544 - accuracy: 0.2447\n",
"start index for training is 450000\n",
"Train on 19865 samples, validate on 19865 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19865/19865 [==============================] - 1s 43us/sample - loss: 1.8660 - accuracy: 0.3871\n",
"19865/19865 [==============================] - 1s 40us/sample - loss: 1.8850 - accuracy: 0.3835\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6856 - accuracy: 0.4694\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.7241 - accuracy: 0.4183\n",
"14070/14070 [==============================] - 0s 36us/sample - loss: 2.3502 - accuracy: 0.2527\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3631 - accuracy: 0.2728\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4335 - accuracy: 0.2611\n",
"start index for training is 451000\n",
"Train on 7030 samples, validate on 7030 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7030/7030 [==============================] - 0s 39us/sample - loss: 2.1209 - accuracy: 0.3255\n",
"7030/7030 [==============================] - 0s 40us/sample - loss: 2.1653 - accuracy: 0.3158\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7241 - accuracy: 0.4661\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.7513 - accuracy: 0.4269\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3354 - accuracy: 0.2543\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.3591 - accuracy: 0.2597\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4329 - accuracy: 0.2484\n",
"start index for training is 452000\n",
"Train on 17605 samples, validate on 17605 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17605/17605 [==============================] - ETA: 0s - loss: 1.7475 - accuracy: 0.4494 ETA: 0s - loss: 1.7511 - ac - 1s 45us/sample - loss: 1.7474 - accuracy: 0.4494\n",
"17605/17605 [==============================] - 1s 45us/sample - loss: 1.7619 - accuracy: 0.4422\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7043 - accuracy: 0.4811\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.7079 - accuracy: 0.4339\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.3804 - accuracy: 0.2547\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.3684 - accuracy: 0.2816\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.4417 - accuracy: 0.2740\n",
"start index for training is 453000\n",
"Train on 14155 samples, validate on 14160 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14155/14155 [==============================] - 1s 45us/sample - loss: 1.9719 - accuracy: 0.3550\n",
"14160/14160 [==============================] - 1s 53us/sample - loss: 1.9640 - accuracy: 0.3628\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7102 - accuracy: 0.4538\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 1.7279 - accuracy: 0.4161\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.3583 - accuracy: 0.2542\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.3548 - accuracy: 0.2642\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4264 - accuracy: 0.2590\n",
"start index for training is 454000\n",
"Train on 6350 samples, validate on 6350 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6350/6350 [==============================] - 0s 47us/sample - loss: 2.1082 - accuracy: 0.3317\n",
"6350/6350 [==============================] - 0s 47us/sample - loss: 2.1148 - accuracy: 0.3320\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.7237 - accuracy: 0.4405\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.7298 - accuracy: 0.4175\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.3541 - accuracy: 0.2615\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.3628 - accuracy: 0.2636\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4339 - accuracy: 0.2491\n",
"start index for training is 455000\n",
"Train on 19800 samples, validate on 19805 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19800/19800 [==============================] - 1s 44us/sample - loss: 1.7526 - accuracy: 0.4379\n",
"19805/19805 [==============================] - 1s 43us/sample - loss: 1.7759 - accuracy: 0.4306\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7032 - accuracy: 0.4681\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 1.6980 - accuracy: 0.4366\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.3803 - accuracy: 0.2500\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.3665 - accuracy: 0.2737\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.4348 - accuracy: 0.2610\n",
"start index for training is 456000\n",
"Train on 12680 samples, validate on 12680 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12680/12680 [==============================] - 1s 49us/sample - loss: 1.9954 - accuracy: 0.3588\n",
"12680/12680 [==============================] - 1s 48us/sample - loss: 1.9825 - accuracy: 0.3543\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.7160 - accuracy: 0.4385\n",
"12255/12255 [==============================] - 1s 53us/sample - loss: 1.7211 - accuracy: 0.4167\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.3563 - accuracy: 0.2644\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3533 - accuracy: 0.2755\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4201 - accuracy: 0.2679\n",
"start index for training is 457000\n",
"Train on 6310 samples, validate on 6310 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6310/6310 [==============================] - 0s 51us/sample - loss: 2.1569 - accuracy: 0.3162\n",
"6310/6310 [==============================] - 0s 48us/sample - loss: 2.1594 - accuracy: 0.3152\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7298 - accuracy: 0.4595\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.7285 - accuracy: 0.4273\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.3395 - accuracy: 0.2641\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.3404 - accuracy: 0.2808\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4085 - accuracy: 0.2620\n",
"start index for training is 458000\n",
"Train on 18960 samples, validate on 18960 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18960/18960 [==============================] - 1s 48us/sample - loss: 1.7315 - accuracy: 0.4563\n",
"18960/18960 [==============================] - 1s 45us/sample - loss: 1.7635 - accuracy: 0.4478\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7004 - accuracy: 0.4793\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.6944 - accuracy: 0.4428\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3922 - accuracy: 0.2539\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3762 - accuracy: 0.2765\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4488 - accuracy: 0.2681\n",
"start index for training is 459000\n",
"Train on 14040 samples, validate on 14045 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14040/14040 [==============================] - 1s 45us/sample - loss: 1.9917 - accuracy: 0.3572\n",
"14045/14045 [==============================] - 1s 44us/sample - loss: 1.9959 - accuracy: 0.3563\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.7458 - accuracy: 0.4408\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.7391 - accuracy: 0.4221\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3806 - accuracy: 0.2716\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3796 - accuracy: 0.2501\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4463 - accuracy: 0.2421\n",
"start index for training is 460000\n",
"Train on 6535 samples, validate on 6540 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6535/6535 [==============================] - 0s 56us/sample - loss: 2.1216 - accuracy: 0.3256\n",
"6540/6540 [==============================] - 0s 67us/sample - loss: 2.1481 - accuracy: 0.3202\n",
"5980/5980 [==============================] - 0s 76us/sample - loss: 1.7357 - accuracy: 0.4513\n",
"12255/12255 [==============================] - 1s 57us/sample - loss: 1.7237 - accuracy: 0.4410\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 2.3680 - accuracy: 0.2601\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3542 - accuracy: 0.2746\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4266 - accuracy: 0.2581\n",
"start index for training is 461000\n",
"Train on 17375 samples, validate on 17380 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17375/17375 [==============================] - 1s 43us/sample - loss: 1.7342 - accuracy: 0.4473\n",
"17380/17380 [==============================] - 1s 45us/sample - loss: 1.7513 - accuracy: 0.4486\n",
"5980/5980 [==============================] - 0s 60us/sample - loss: 1.7239 - accuracy: 0.4846\n",
"12255/12255 [==============================] - 1s 89us/sample - loss: 1.6901 - accuracy: 0.4348\n",
"14070/14070 [==============================] - 1s 61us/sample - loss: 2.3897 - accuracy: 0.2564\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3683 - accuracy: 0.2827\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4382 - accuracy: 0.2727\n",
"start index for training is 462000\n",
"Train on 16115 samples, validate on 16115 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16115/16115 [==============================] - 1s 44us/sample - loss: 1.9359 - accuracy: 0.3704\n",
"16115/16115 [==============================] - 1s 40us/sample - loss: 1.9618 - accuracy: 0.3595\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7127 - accuracy: 0.4855\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.7066 - accuracy: 0.4246\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.3482 - accuracy: 0.2634\n",
"11565/11565 [==============================] - 1s 57us/sample - loss: 2.3640 - accuracy: 0.2549\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.4352 - accuracy: 0.2359\n",
"start index for training is 463000\n",
"Train on 7330 samples, validate on 7335 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7330/7330 [==============================] - 0s 46us/sample - loss: 2.1437 - accuracy: 0.3202\n",
"7335/7335 [==============================] - 0s 41us/sample - loss: 2.1505 - accuracy: 0.3219\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7383 - accuracy: 0.4358\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7157 - accuracy: 0.4233\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3577 - accuracy: 0.2593\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3572 - accuracy: 0.2664\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4289 - accuracy: 0.2564\n",
"start index for training is 464000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 48us/sample - loss: 2.2061 - accuracy: 0.3143\n",
"4995/4995 [==============================] - 0s 42us/sample - loss: 2.2138 - accuracy: 0.3063\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7466 - accuracy: 0.4644\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7312 - accuracy: 0.4259\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.3506 - accuracy: 0.2650\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3453 - accuracy: 0.2674\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.4183 - accuracy: 0.2526\n",
"start index for training is 465000\n",
"Train on 27735 samples, validate on 27735 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"27735/27735 [==============================] - 1s 40us/sample - loss: 1.7875 - accuracy: 0.4279\n",
"27735/27735 [==============================] - 1s 37us/sample - loss: 1.7720 - accuracy: 0.4368\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7060 - accuracy: 0.4753\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.6882 - accuracy: 0.4392\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3791 - accuracy: 0.2603\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3635 - accuracy: 0.2724\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4346 - accuracy: 0.2594\n",
"start index for training is 466000\n",
"Train on 9155 samples, validate on 9155 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9155/9155 [==============================] - 0s 42us/sample - loss: 2.0987 - accuracy: 0.3298\n",
"9155/9155 [==============================] - 0s 40us/sample - loss: 2.1059 - accuracy: 0.3144\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7155 - accuracy: 0.4441\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7179 - accuracy: 0.4113\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.3620 - accuracy: 0.2714\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3670 - accuracy: 0.2625\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4454 - accuracy: 0.2574\n",
"start index for training is 467000\n",
"Train on 5580 samples, validate on 5580 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5580/5580 [==============================] - 0s 44us/sample - loss: 2.1641 - accuracy: 0.3213\n",
"5580/5580 [==============================] - 0s 41us/sample - loss: 2.2031 - accuracy: 0.3011\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7300 - accuracy: 0.4584\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7211 - accuracy: 0.4306\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3507 - accuracy: 0.2527\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3504 - accuracy: 0.2603\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4314 - accuracy: 0.2484\n",
"start index for training is 468000\n",
"Train on 21995 samples, validate on 21995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21995/21995 [==============================] - 1s 41us/sample - loss: 1.7490 - accuracy: 0.4554\n",
"21995/21995 [==============================] - 1s 38us/sample - loss: 1.7706 - accuracy: 0.4462\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7066 - accuracy: 0.4744\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.6857 - accuracy: 0.4508\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.3924 - accuracy: 0.2601\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3634 - accuracy: 0.2748\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4352 - accuracy: 0.2604\n",
"start index for training is 469000\n",
"Train on 14755 samples, validate on 14755 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14755/14755 [==============================] - 1s 43us/sample - loss: 1.9830 - accuracy: 0.3567\n",
"14755/14755 [==============================] - 1s 38us/sample - loss: 2.0182 - accuracy: 0.3534\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7361 - accuracy: 0.4538\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.7064 - accuracy: 0.4373\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3841 - accuracy: 0.2625\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.3627 - accuracy: 0.2673\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4395 - accuracy: 0.2490\n",
"start index for training is 470000\n",
"Train on 7750 samples, validate on 7755 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7750/7750 [==============================] - 0s 45us/sample - loss: 2.1502 - accuracy: 0.3209\n",
"7755/7755 [==============================] - 0s 44us/sample - loss: 2.1309 - accuracy: 0.3320\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7582 - accuracy: 0.4533\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7256 - accuracy: 0.4295\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.3967 - accuracy: 0.2504\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3592 - accuracy: 0.2741\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4391 - accuracy: 0.2566\n",
"start index for training is 471000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 48us/sample - loss: 2.2132 - accuracy: 0.3155\n",
"4995/4995 [==============================] - 0s 43us/sample - loss: 2.1905 - accuracy: 0.3187\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7513 - accuracy: 0.4607\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.7254 - accuracy: 0.4384\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3733 - accuracy: 0.2626\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.3365 - accuracy: 0.2799\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4086 - accuracy: 0.2594\n",
"start index for training is 472000\n",
"Train on 26085 samples, validate on 26090 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"26085/26085 [==============================] - 1s 56us/sample - loss: 1.7859 - accuracy: 0.4320\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"26090/26090 [==============================] - 1s 44us/sample - loss: 1.7829 - accuracy: 0.4319\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7212 - accuracy: 0.4818\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7059 - accuracy: 0.4395\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.4104 - accuracy: 0.2569\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3836 - accuracy: 0.2687\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4572 - accuracy: 0.2531\n",
"start index for training is 473000\n",
"Train on 11685 samples, validate on 11685 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11685/11685 [==============================] - 0s 41us/sample - loss: 2.0413 - accuracy: 0.3502\n",
"11685/11685 [==============================] - 0s 38us/sample - loss: 2.0478 - accuracy: 0.3400\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 1.7315 - accuracy: 0.4462\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.7043 - accuracy: 0.4399\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.3866 - accuracy: 0.2596\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3512 - accuracy: 0.2674\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4296 - accuracy: 0.2447\n",
"start index for training is 474000\n",
"Train on 6730 samples, validate on 6735 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6730/6730 [==============================] - 0s 43us/sample - loss: 2.1536 - accuracy: 0.3256\n",
"6735/6735 [==============================] - 0s 40us/sample - loss: 2.1584 - accuracy: 0.3195\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7395 - accuracy: 0.4500\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.7137 - accuracy: 0.4339\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.3852 - accuracy: 0.2598\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3458 - accuracy: 0.2801\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4212 - accuracy: 0.2621\n",
"start index for training is 475000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 43us/sample - loss: 2.2264 - accuracy: 0.3099\n",
"4995/4995 [==============================] - 0s 41us/sample - loss: 2.2415 - accuracy: 0.3111\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7250 - accuracy: 0.4913\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7259 - accuracy: 0.4262\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.3537 - accuracy: 0.2561\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3440 - accuracy: 0.2647\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4259 - accuracy: 0.2446\n",
"start index for training is 476000\n",
"Train on 28800 samples, validate on 28800 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"28800/28800 [==============================] - 1s 40us/sample - loss: 1.7832 - accuracy: 0.4288\n",
"28800/28800 [==============================] - 1s 39us/sample - loss: 1.7878 - accuracy: 0.4332\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.7116 - accuracy: 0.4537\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.6865 - accuracy: 0.4416\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.4029 - accuracy: 0.2598\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3539 - accuracy: 0.2855\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4292 - accuracy: 0.2664\n",
"start index for training is 477000\n",
"Train on 9525 samples, validate on 9530 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9525/9525 [==============================] - 0s 41us/sample - loss: 2.1028 - accuracy: 0.3339\n",
"9530/9530 [==============================] - 0s 40us/sample - loss: 2.1146 - accuracy: 0.3301\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7347 - accuracy: 0.4671\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7024 - accuracy: 0.4416\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.3680 - accuracy: 0.2613\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3415 - accuracy: 0.2775\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4185 - accuracy: 0.2544\n",
"start index for training is 478000\n",
"Train on 6065 samples, validate on 6065 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6065/6065 [==============================] - 0s 42us/sample - loss: 2.1985 - accuracy: 0.3162\n",
"6065/6065 [==============================] - 0s 40us/sample - loss: 2.1885 - accuracy: 0.3123\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7590 - accuracy: 0.4692\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7244 - accuracy: 0.4344\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.3841 - accuracy: 0.2576\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3453 - accuracy: 0.2764\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4193 - accuracy: 0.2613\n",
"start index for training is 479000\n",
"Train on 16815 samples, validate on 16820 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16815/16815 [==============================] - 1s 45us/sample - loss: 1.7513 - accuracy: 0.4639\n",
"16820/16820 [==============================] - 1s 42us/sample - loss: 1.7805 - accuracy: 0.4606\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7442 - accuracy: 0.4348\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.6901 - accuracy: 0.4454\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4057 - accuracy: 0.2561\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3487 - accuracy: 0.2859\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4228 - accuracy: 0.2624\n",
"start index for training is 480000\n",
"Train on 18435 samples, validate on 18440 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18435/18435 [==============================] - 1s 47us/sample - loss: 1.9364 - accuracy: 0.3745\n",
"18440/18440 [==============================] - 1s 41us/sample - loss: 1.9503 - accuracy: 0.3752\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.7409 - accuracy: 0.4507\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.6997 - accuracy: 0.4292\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3970 - accuracy: 0.2496\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3437 - accuracy: 0.2688\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4267 - accuracy: 0.2521\n",
"start index for training is 481000\n",
"Train on 8370 samples, validate on 8370 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8370/8370 [==============================] - 0s 49us/sample - loss: 2.1350 - accuracy: 0.3295\n",
"8370/8370 [==============================] - 0s 46us/sample - loss: 2.1312 - accuracy: 0.3301\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7535 - accuracy: 0.4378\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.7146 - accuracy: 0.4287\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3733 - accuracy: 0.2569\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3377 - accuracy: 0.2836\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4176 - accuracy: 0.2639\n",
"start index for training is 482000\n",
"Train on 5305 samples, validate on 5305 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5305/5305 [==============================] - 0s 43us/sample - loss: 2.2112 - accuracy: 0.3071\n",
"5305/5305 [==============================] - 0s 41us/sample - loss: 2.2362 - accuracy: 0.2988\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7685 - accuracy: 0.4196\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7316 - accuracy: 0.4236\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.3882 - accuracy: 0.2485\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3432 - accuracy: 0.2694\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4225 - accuracy: 0.2511\n",
"start index for training is 483000\n",
"Train on 22280 samples, validate on 22280 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"22280/22280 [==============================] - 1s 43us/sample - loss: 1.7810 - accuracy: 0.4483\n",
"22280/22280 [==============================] - 1s 41us/sample - loss: 1.7850 - accuracy: 0.4447\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7326 - accuracy: 0.4764\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.6860 - accuracy: 0.4371\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4123 - accuracy: 0.2590\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3471 - accuracy: 0.2821\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4230 - accuracy: 0.2600\n",
"start index for training is 484000\n",
"Train on 13830 samples, validate on 13835 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13830/13830 [==============================] - 1s 44us/sample - loss: 2.0124 - accuracy: 0.3586\n",
"13835/13835 [==============================] - 1s 42us/sample - loss: 2.0180 - accuracy: 0.3592\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7551 - accuracy: 0.4278\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.7082 - accuracy: 0.4293\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.4022 - accuracy: 0.2570\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.3392 - accuracy: 0.2816\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4229 - accuracy: 0.2607\n",
"start index for training is 485000\n",
"Train on 7395 samples, validate on 7400 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7395/7395 [==============================] - 0s 50us/sample - loss: 2.1720 - accuracy: 0.3151\n",
"7400/7400 [==============================] - 0s 42us/sample - loss: 2.1658 - accuracy: 0.3128\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7572 - accuracy: 0.4386\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.7302 - accuracy: 0.4282\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.3732 - accuracy: 0.2489\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3489 - accuracy: 0.2588\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4384 - accuracy: 0.2393\n",
"start index for training is 486000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 48us/sample - loss: 2.2494 - accuracy: 0.2961\n",
"4995/4995 [==============================] - 0s 44us/sample - loss: 2.1987 - accuracy: 0.3153\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.7714 - accuracy: 0.4587\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.7304 - accuracy: 0.4220\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.3901 - accuracy: 0.2516\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3224 - accuracy: 0.2833\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4028 - accuracy: 0.2686\n",
"start index for training is 487000\n",
"Train on 26530 samples, validate on 26530 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"26530/26530 [==============================] - 1s 41us/sample - loss: 1.8011 - accuracy: 0.4393\n",
"26530/26530 [==============================] - 1s 38us/sample - loss: 1.8079 - accuracy: 0.4392\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7338 - accuracy: 0.4692\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.6931 - accuracy: 0.4469\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4143 - accuracy: 0.2532\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3440 - accuracy: 0.2840\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4232 - accuracy: 0.2680\n",
"start index for training is 488000\n",
"Train on 10170 samples, validate on 10170 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10170/10170 [==============================] - 0s 44us/sample - loss: 2.0756 - accuracy: 0.3373\n",
"10170/10170 [==============================] - 0s 40us/sample - loss: 2.0626 - accuracy: 0.3367\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7752 - accuracy: 0.4460\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7195 - accuracy: 0.4453\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.4260 - accuracy: 0.2459\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3534 - accuracy: 0.2732\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4367 - accuracy: 0.2530\n",
"start index for training is 489000\n",
"Train on 6175 samples, validate on 6180 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6175/6175 [==============================] - 0s 44us/sample - loss: 2.1948 - accuracy: 0.3182\n",
"6180/6180 [==============================] - 0s 42us/sample - loss: 2.1978 - accuracy: 0.3154\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7833 - accuracy: 0.4289\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.7358 - accuracy: 0.4295\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4135 - accuracy: 0.2478\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3584 - accuracy: 0.2777\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4468 - accuracy: 0.2530\n",
"start index for training is 490000\n",
"Train on 15450 samples, validate on 15455 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15450/15450 [==============================] - 1s 46us/sample - loss: 1.7644 - accuracy: 0.4559\n",
"15455/15455 [==============================] - 1s 40us/sample - loss: 1.7769 - accuracy: 0.4541\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7667 - accuracy: 0.4513\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.6933 - accuracy: 0.4304\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.4211 - accuracy: 0.2545\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3435 - accuracy: 0.2898\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4243 - accuracy: 0.2654\n",
"start index for training is 491000\n",
"Train on 18685 samples, validate on 18690 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"18685/18685 [==============================] - 1s 42us/sample - loss: 1.9591 - accuracy: 0.3736\n",
"18690/18690 [==============================] - ETA: 0s - loss: 1.9579 - accuracy: 0.37 - 1s 37us/sample - loss: 1.9567 - accuracy: 0.3712\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7383 - accuracy: 0.4619\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7053 - accuracy: 0.4390\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4309 - accuracy: 0.2463\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3581 - accuracy: 0.2824\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4461 - accuracy: 0.2707s - loss: 2.4229 - accuracy\n",
"start index for training is 492000\n",
"Train on 8305 samples, validate on 8310 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8305/8305 [==============================] - 0s 45us/sample - loss: 2.1444 - accuracy: 0.3239\n",
"8310/8310 [==============================] - 0s 58us/sample - loss: 2.1149 - accuracy: 0.3288\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.7855 - accuracy: 0.4304\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.7344 - accuracy: 0.4244\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.4272 - accuracy: 0.2386\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3491 - accuracy: 0.2829\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4317 - accuracy: 0.2724\n",
"start index for training is 493000\n",
"Train on 5195 samples, validate on 5200 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5195/5195 [==============================] - 0s 52us/sample - loss: 2.2222 - accuracy: 0.3118\n",
"5200/5200 [==============================] - 0s 46us/sample - loss: 2.2532 - accuracy: 0.3100\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.7841 - accuracy: 0.4497\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7264 - accuracy: 0.4365\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.4115 - accuracy: 0.2502\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.3525 - accuracy: 0.2801\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.4328 - accuracy: 0.2617\n",
"start index for training is 494000\n",
"Train on 24185 samples, validate on 24185 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"24185/24185 [==============================] - 1s 41us/sample - loss: 1.8016 - accuracy: 0.4299\n",
"24185/24185 [==============================] - 1s 38us/sample - loss: 1.8126 - accuracy: 0.4307\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7476 - accuracy: 0.4426\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.6972 - accuracy: 0.4273\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.4242 - accuracy: 0.2549\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3537 - accuracy: 0.2713\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4367 - accuracy: 0.2547\n",
"start index for training is 495000\n",
"Train on 11400 samples, validate on 11405 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11400/11400 [==============================] - 1s 44us/sample - loss: 2.0437 - accuracy: 0.3578\n",
"11405/11405 [==============================] - 0s 42us/sample - loss: 2.0364 - accuracy: 0.3569\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7563 - accuracy: 0.4460\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.7094 - accuracy: 0.4317\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4146 - accuracy: 0.2548\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3511 - accuracy: 0.2826\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4347 - accuracy: 0.2614\n",
"start index for training is 496000\n",
"Train on 6540 samples, validate on 6540 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6540/6540 [==============================] - 0s 43us/sample - loss: 2.1679 - accuracy: 0.3190\n",
"6540/6540 [==============================] - 0s 41us/sample - loss: 2.1752 - accuracy: 0.3144\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7761 - accuracy: 0.4381\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.7310 - accuracy: 0.4326\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4275 - accuracy: 0.2471\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3502 - accuracy: 0.2777\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4355 - accuracy: 0.2594\n",
"start index for training is 497000\n",
"Train on 12605 samples, validate on 12605 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12605/12605 [==============================] - 1s 48us/sample - loss: 1.8031 - accuracy: 0.4696\n",
"12605/12605 [==============================] - 1s 41us/sample - loss: 1.8193 - accuracy: 0.4657\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7930 - accuracy: 0.4166\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7126 - accuracy: 0.4346\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4436 - accuracy: 0.2397\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3504 - accuracy: 0.2885\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4297 - accuracy: 0.2654\n",
"start index for training is 498000\n",
"Train on 20750 samples, validate on 20755 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20750/20750 [==============================] - 1s 41us/sample - loss: 1.9194 - accuracy: 0.3858\n",
"20755/20755 [==============================] - 1s 40us/sample - loss: 1.9276 - accuracy: 0.3847\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7468 - accuracy: 0.4537\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.7086 - accuracy: 0.4362\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.4275 - accuracy: 0.2480\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3583 - accuracy: 0.2726\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4445 - accuracy: 0.2590\n",
"start index for training is 499000\n",
"Train on 8395 samples, validate on 8400 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8395/8395 [==============================] - 0s 44us/sample - loss: 2.1145 - accuracy: 0.3315\n",
"8400/8400 [==============================] - 0s 42us/sample - loss: 2.1319 - accuracy: 0.3196\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7857 - accuracy: 0.4343\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7354 - accuracy: 0.4284\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.4424 - accuracy: 0.2402\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.3666 - accuracy: 0.2861\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.4537 - accuracy: 0.2706\n",
"start index for training is 500000\n",
"Train on 5405 samples, validate on 5405 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5405/5405 [==============================] - 0s 49us/sample - loss: 2.1958 - accuracy: 0.3238\n",
"5405/5405 [==============================] - 0s 41us/sample - loss: 2.1994 - accuracy: 0.3245\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.8046 - accuracy: 0.4100\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7583 - accuracy: 0.4261\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.4524 - accuracy: 0.2366\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3629 - accuracy: 0.2798\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4496 - accuracy: 0.2670\n",
"start index for training is 501000\n",
"Train on 23320 samples, validate on 23320 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"23320/23320 [==============================] - 1s 49us/sample - loss: 1.8102 - accuracy: 0.4351\n",
"23320/23320 [==============================] - 1s 42us/sample - loss: 1.8217 - accuracy: 0.4284\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7569 - accuracy: 0.4396\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 1.7006 - accuracy: 0.4276\n",
"14070/14070 [==============================] - 1s 63us/sample - loss: 2.4262 - accuracy: 0.2534\n",
"11565/11565 [==============================] - 1s 59us/sample - loss: 2.3437 - accuracy: 0.2785\n",
"7000/7000 [==============================] - 0s 53us/sample - loss: 2.4294 - accuracy: 0.2606\n",
"start index for training is 502000\n",
"Train on 12165 samples, validate on 12165 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12165/12165 [==============================] - 1s 45us/sample - loss: 2.0161 - accuracy: 0.3520\n",
"12165/12165 [==============================] - 1s 41us/sample - loss: 2.0166 - accuracy: 0.3471\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8179 - accuracy: 0.4055\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7479 - accuracy: 0.4321\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4856 - accuracy: 0.2330\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3893 - accuracy: 0.2740\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4694 - accuracy: 0.2624\n",
"start index for training is 503000\n",
"Train on 6705 samples, validate on 6705 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6705/6705 [==============================] - 0s 45us/sample - loss: 2.1445 - accuracy: 0.3309\n",
"6705/6705 [==============================] - 0s 41us/sample - loss: 2.1788 - accuracy: 0.3223\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.7882 - accuracy: 0.4565\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7250 - accuracy: 0.4305\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.4371 - accuracy: 0.2569\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3530 - accuracy: 0.2783\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4398 - accuracy: 0.2613\n",
"start index for training is 504000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 44us/sample - loss: 2.2707 - accuracy: 0.2941\n",
"4995/4995 [==============================] - 0s 56us/sample - loss: 2.2654 - accuracy: 0.2885\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.7930 - accuracy: 0.4371\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7421 - accuracy: 0.4264\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.4301 - accuracy: 0.2550\n",
"11565/11565 [==============================] - 1s 49us/sample - loss: 2.3576 - accuracy: 0.2811\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4426 - accuracy: 0.2639\n",
"start index for training is 505000\n",
"Train on 27765 samples, validate on 27765 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"27765/27765 [==============================] - 1s 50us/sample - loss: 1.8141 - accuracy: 0.4326\n",
"27765/27765 [==============================] - 1s 45us/sample - loss: 1.8176 - accuracy: 0.4317\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.7727 - accuracy: 0.4234\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.7024 - accuracy: 0.4413\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4387 - accuracy: 0.2571\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3517 - accuracy: 0.2955\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.4327 - accuracy: 0.2816\n",
"start index for training is 506000\n",
"Train on 9265 samples, validate on 9270 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9265/9265 [==============================] - 0s 48us/sample - loss: 2.1032 - accuracy: 0.3237\n",
"9270/9270 [==============================] - 0s 47us/sample - loss: 2.0914 - accuracy: 0.3369\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7919 - accuracy: 0.4318\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.7417 - accuracy: 0.4262\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.4446 - accuracy: 0.2517\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3761 - accuracy: 0.2904\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.4663 - accuracy: 0.2741\n",
"start index for training is 507000\n",
"Train on 5925 samples, validate on 5925 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5925/5925 [==============================] - 0s 46us/sample - loss: 2.2093 - accuracy: 0.3197\n",
"5925/5925 [==============================] - 0s 42us/sample - loss: 2.2148 - accuracy: 0.3170\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8138 - accuracy: 0.4355\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7469 - accuracy: 0.4283\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.4420 - accuracy: 0.2466\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3523 - accuracy: 0.2827\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4406 - accuracy: 0.2707\n",
"start index for training is 508000\n",
"Train on 16260 samples, validate on 16260 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16260/16260 [==============================] - 1s 46us/sample - loss: 1.7789 - accuracy: 0.4644\n",
"16260/16260 [==============================] - 1s 41us/sample - loss: 1.8141 - accuracy: 0.4552\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8141 - accuracy: 0.4085\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.7119 - accuracy: 0.4493\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.4617 - accuracy: 0.2467\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3523 - accuracy: 0.2892\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4303 - accuracy: 0.2701\n",
"start index for training is 509000\n",
"Train on 18020 samples, validate on 18020 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18020/18020 [==============================] - 1s 42us/sample - loss: 1.9933 - accuracy: 0.3578\n",
"18020/18020 [==============================] - 1s 41us/sample - loss: 1.9973 - accuracy: 0.3637\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7686 - accuracy: 0.4313\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7416 - accuracy: 0.3994\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4394 - accuracy: 0.2468\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3894 - accuracy: 0.2653\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4822 - accuracy: 0.2403\n",
"start index for training is 510000\n",
"Train on 8380 samples, validate on 8385 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8380/8380 [==============================] - 0s 54us/sample - loss: 2.1088 - accuracy: 0.3300\n",
"8385/8385 [==============================] - 0s 43us/sample - loss: 2.1501 - accuracy: 0.3175\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8111 - accuracy: 0.4159\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.7543 - accuracy: 0.4082\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.4567 - accuracy: 0.2406\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3779 - accuracy: 0.2762\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4619 - accuracy: 0.2630\n",
"start index for training is 511000\n",
"Train on 5430 samples, validate on 5430 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5430/5430 [==============================] - 0s 51us/sample - loss: 2.2438 - accuracy: 0.3039\n",
"5430/5430 [==============================] - 0s 53us/sample - loss: 2.2060 - accuracy: 0.3145\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.8267 - accuracy: 0.4371\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.7707 - accuracy: 0.4192\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.4549 - accuracy: 0.2472\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3610 - accuracy: 0.2853\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4436 - accuracy: 0.2694\n",
"start index for training is 512000\n",
"Train on 21095 samples, validate on 21100 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21095/21095 [==============================] - 1s 42us/sample - loss: 1.8109 - accuracy: 0.4561\n",
"21100/21100 [==============================] - 1s 39us/sample - loss: 1.8156 - accuracy: 0.4559\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.8269 - accuracy: 0.4040\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7431 - accuracy: 0.4311\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.4941 - accuracy: 0.2465\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.3813 - accuracy: 0.2899\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4585 - accuracy: 0.2806\n",
"start index for training is 513000\n",
"Train on 14290 samples, validate on 14295 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14290/14290 [==============================] - 1s 44us/sample - loss: 2.0235 - accuracy: 0.3522\n",
"14295/14295 [==============================] - 1s 48us/sample - loss: 2.0219 - accuracy: 0.3556\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.8436 - accuracy: 0.3963\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.7656 - accuracy: 0.4206\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.5063 - accuracy: 0.2333\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.3990 - accuracy: 0.2784\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4811 - accuracy: 0.2681\n",
"start index for training is 514000\n",
"Train on 7740 samples, validate on 7740 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7740/7740 [==============================] - 0s 45us/sample - loss: 2.1088 - accuracy: 0.3322\n",
"7740/7740 [==============================] - 0s 44us/sample - loss: 2.1839 - accuracy: 0.3088\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7974 - accuracy: 0.4416\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 1.7563 - accuracy: 0.4193\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.4443 - accuracy: 0.2434\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3683 - accuracy: 0.2770\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4531 - accuracy: 0.2637\n",
"start index for training is 515000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 58us/sample - loss: 2.2310 - accuracy: 0.3337\n",
"4995/4995 [==============================] - 0s 53us/sample - loss: 2.2857 - accuracy: 0.3037\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.8314 - accuracy: 0.4181\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.7662 - accuracy: 0.4275\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.4712 - accuracy: 0.2455\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3698 - accuracy: 0.2847\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4491 - accuracy: 0.2724\n",
"start index for training is 516000\n",
"Train on 23535 samples, validate on 23540 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"23535/23535 [==============================] - 1s 42us/sample - loss: 1.8018 - accuracy: 0.4444\n",
"23540/23540 [==============================] - 1s 62us/sample - loss: 1.8233 - accuracy: 0.4354\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.7756 - accuracy: 0.4052\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.7149 - accuracy: 0.4395\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4547 - accuracy: 0.2494\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3615 - accuracy: 0.2885\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4457 - accuracy: 0.2757\n",
"start index for training is 517000\n",
"Train on 12940 samples, validate on 12945 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12940/12940 [==============================] - 1s 42us/sample - loss: 2.0220 - accuracy: 0.3563\n",
"12945/12945 [==============================] - 1s 39us/sample - loss: 2.0409 - accuracy: 0.3541\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8108 - accuracy: 0.4130\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7339 - accuracy: 0.4277\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.4568 - accuracy: 0.2498s - loss: 2.4574 \n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3689 - accuracy: 0.2859\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4497 - accuracy: 0.2690\n",
"start index for training is 518000\n",
"Train on 7240 samples, validate on 7240 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7240/7240 [==============================] - 0s 46us/sample - loss: 2.1516 - accuracy: 0.3227\n",
"7240/7240 [==============================] - 0s 41us/sample - loss: 2.1638 - accuracy: 0.3249\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8185 - accuracy: 0.4196\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.7511 - accuracy: 0.4202\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.4628 - accuracy: 0.2497\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3746 - accuracy: 0.2820\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4602 - accuracy: 0.2644\n",
"start index for training is 519000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 46us/sample - loss: 2.2388 - accuracy: 0.3193\n",
"4995/4995 [==============================] - 0s 43us/sample - loss: 2.2942 - accuracy: 0.3041\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.8182 - accuracy: 0.4164\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 1.7720 - accuracy: 0.4094\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.4517 - accuracy: 0.2497\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.3686 - accuracy: 0.2878\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4529 - accuracy: 0.2724\n",
"start index for training is 520000\n",
"Train on 24945 samples, validate on 24950 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"24945/24945 [==============================] - 1s 41us/sample - loss: 1.8172 - accuracy: 0.4349\n",
"24950/24950 [==============================] - 1s 38us/sample - loss: 1.8120 - accuracy: 0.4347\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.7940 - accuracy: 0.4129\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7191 - accuracy: 0.4340\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.4533 - accuracy: 0.2349\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3584 - accuracy: 0.2806s - loss: 2.3594 - accuracy: 0.28\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4376 - accuracy: 0.2714\n",
"start index for training is 521000\n",
"Train on 12145 samples, validate on 12150 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12145/12145 [==============================] - 1s 47us/sample - loss: 2.0426 - accuracy: 0.3464\n",
"12150/12150 [==============================] - 0s 41us/sample - loss: 2.0289 - accuracy: 0.3452\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8047 - accuracy: 0.4520\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7459 - accuracy: 0.4017\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.4603 - accuracy: 0.2569\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3932 - accuracy: 0.2731\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4751 - accuracy: 0.2551\n",
"start index for training is 522000\n",
"Train on 7040 samples, validate on 7040 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7040/7040 [==============================] - 0s 42us/sample - loss: 2.2025 - accuracy: 0.3121\n",
"7040/7040 [==============================] - 0s 38us/sample - loss: 2.1977 - accuracy: 0.3081\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8315 - accuracy: 0.4296\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7816 - accuracy: 0.4062\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4682 - accuracy: 0.2560\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3903 - accuracy: 0.2669\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4766 - accuracy: 0.2504\n",
"start index for training is 523000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 42us/sample - loss: 2.2589 - accuracy: 0.3125\n",
"4995/4995 [==============================] - 0s 41us/sample - loss: 2.2538 - accuracy: 0.3073\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8389 - accuracy: 0.4279\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7855 - accuracy: 0.4094\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4564 - accuracy: 0.2458\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3655 - accuracy: 0.2745\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4446 - accuracy: 0.2590s - loss: 2.4498 - accuracy: \n",
"start index for training is 524000\n",
"Train on 24750 samples, validate on 24750 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"24750/24750 [==============================] - 1s 40us/sample - loss: 1.8107 - accuracy: 0.4386\n",
"24750/24750 [==============================] - 1s 37us/sample - loss: 1.8247 - accuracy: 0.4345\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.7846 - accuracy: 0.4256\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.7192 - accuracy: 0.4321\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4383 - accuracy: 0.2426\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3512 - accuracy: 0.2816\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4299 - accuracy: 0.2694\n",
"start index for training is 525000\n",
"Train on 12520 samples, validate on 12525 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12520/12520 [==============================] - 1s 42us/sample - loss: 2.0326 - accuracy: 0.3569\n",
"12525/12525 [==============================] - 1s 43us/sample - loss: 2.0205 - accuracy: 0.3572\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8424 - accuracy: 0.3931\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.7638 - accuracy: 0.4086\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.4825 - accuracy: 0.2434\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3904 - accuracy: 0.2792\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4684 - accuracy: 0.2676\n",
"start index for training is 526000\n",
"Train on 7260 samples, validate on 7265 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7260/7260 [==============================] - 0s 43us/sample - loss: 2.1937 - accuracy: 0.3234\n",
"7265/7265 [==============================] - 0s 41us/sample - loss: 2.1855 - accuracy: 0.3133\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8082 - accuracy: 0.4259\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7586 - accuracy: 0.4158\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.4397 - accuracy: 0.2519\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3575 - accuracy: 0.2812\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4345 - accuracy: 0.2617\n",
"start index for training is 527000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 44us/sample - loss: 2.2301 - accuracy: 0.3095\n",
"4995/4995 [==============================] - 0s 42us/sample - loss: 2.2735 - accuracy: 0.3135\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8463 - accuracy: 0.4281\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7872 - accuracy: 0.4118\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.4746 - accuracy: 0.2354\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3793 - accuracy: 0.2744\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4544 - accuracy: 0.2659\n",
"start index for training is 528000\n",
"Train on 23450 samples, validate on 23450 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"23450/23450 [==============================] - 1s 40us/sample - loss: 1.7997 - accuracy: 0.4482\n",
"23450/23450 [==============================] - 1s 36us/sample - loss: 1.8140 - accuracy: 0.4445\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7935 - accuracy: 0.4142\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7291 - accuracy: 0.4379\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.4502 - accuracy: 0.2469\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3613 - accuracy: 0.2808\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4387 - accuracy: 0.2704\n",
"start index for training is 529000\n",
"Train on 13675 samples, validate on 13680 samples\n",
"Epoch 1/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13675/13675 [==============================] - 1s 41us/sample - loss: 2.0063 - accuracy: 0.3633\n",
"13680/13680 [==============================] - 1s 37us/sample - loss: 2.0303 - accuracy: 0.3518s - loss: 2.0738 \n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8318 - accuracy: 0.4092\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7624 - accuracy: 0.4121\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.4847 - accuracy: 0.2449\n",
"11565/11565 [==============================] - ETA: 0s - loss: 2.3987 - accuracy: 0.27 - 0s 37us/sample - loss: 2.3962 - accuracy: 0.2794\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4755 - accuracy: 0.2670\n",
"start index for training is 530000\n",
"Train on 7945 samples, validate on 7950 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7945/7945 [==============================] - 0s 52us/sample - loss: 2.1505 - accuracy: 0.3217\n",
"7950/7950 [==============================] - 0s 51us/sample - loss: 2.1735 - accuracy: 0.3284\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.8289 - accuracy: 0.4189\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.7723 - accuracy: 0.4098\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.4604 - accuracy: 0.2486\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.3850 - accuracy: 0.2720\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.4653 - accuracy: 0.2553\n",
"start index for training is 531000\n",
"Train on 5195 samples, validate on 5200 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5195/5195 [==============================] - 0s 44us/sample - loss: 2.2274 - accuracy: 0.3080\n",
"5200/5200 [==============================] - 0s 45us/sample - loss: 2.2584 - accuracy: 0.3015\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.8576 - accuracy: 0.4084\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.7860 - accuracy: 0.4163\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.4846 - accuracy: 0.2428\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.3895 - accuracy: 0.2797\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4660 - accuracy: 0.2704\n",
"start index for training is 532000\n",
"Train on 19575 samples, validate on 19580 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19575/19575 [==============================] - 1s 47us/sample - loss: 1.7863 - accuracy: 0.4609\n",
"19580/19580 [==============================] - 1s 45us/sample - loss: 1.8118 - accuracy: 0.4525\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.8475 - accuracy: 0.3908\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.7618 - accuracy: 0.4235\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.4798 - accuracy: 0.2480\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.3768 - accuracy: 0.2848\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4538 - accuracy: 0.2709\n",
"start index for training is 533000\n",
"Train on 16740 samples, validate on 16745 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16740/16740 [==============================] - 1s 47us/sample - loss: 1.9805 - accuracy: 0.3700\n",
"16745/16745 [==============================] - 1s 43us/sample - loss: 1.9890 - accuracy: 0.3630\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8267 - accuracy: 0.3941\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.7562 - accuracy: 0.4060\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.4807 - accuracy: 0.2429\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.3820 - accuracy: 0.2826\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.4607 - accuracy: 0.2676\n",
"start index for training is 534000\n",
"Train on 8470 samples, validate on 8475 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8470/8470 [==============================] - 0s 50us/sample - loss: 2.0943 - accuracy: 0.3425\n",
"8475/8475 [==============================] - 0s 45us/sample - loss: 2.1073 - accuracy: 0.3440\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.8410 - accuracy: 0.3988\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.7801 - accuracy: 0.4078\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.4812 - accuracy: 0.2451\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.3944 - accuracy: 0.2834\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.4770 - accuracy: 0.2686\n",
"start index for training is 535000\n",
"Train on 5845 samples, validate on 5850 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5845/5845 [==============================] - 0s 47us/sample - loss: 2.2504 - accuracy: 0.3148\n",
"5850/5850 [==============================] - 0s 44us/sample - loss: 2.2489 - accuracy: 0.3027\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.8581 - accuracy: 0.3893\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.8005 - accuracy: 0.4051\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.4765 - accuracy: 0.2402\n",
"11565/11565 [==============================] - ETA: 0s - loss: 2.3840 - accuracy: 0.28 - 0s 42us/sample - loss: 2.3804 - accuracy: 0.2800\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4565 - accuracy: 0.2659\n",
"start index for training is 536000\n",
"Train on 9760 samples, validate on 9760 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9760/9760 [==============================] - 0s 47us/sample - loss: 1.8367 - accuracy: 0.4672\n",
"9760/9760 [==============================] - 0s 42us/sample - loss: 1.8759 - accuracy: 0.4496\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8705 - accuracy: 0.3736\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.7888 - accuracy: 0.4141\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.4913 - accuracy: 0.2466\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.3976 - accuracy: 0.2859\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4812 - accuracy: 0.2671\n",
"start index for training is 537000\n",
"Train on 24255 samples, validate on 24260 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"24255/24255 [==============================] - 1s 39us/sample - loss: 1.8924 - accuracy: 0.4025\n",
"24260/24260 [==============================] - 1s 39us/sample - loss: 1.8939 - accuracy: 0.4046\n",
"5980/5980 [==============================] - 0s 55us/sample - loss: 1.8481 - accuracy: 0.3930\n",
"12255/12255 [==============================] - 1s 53us/sample - loss: 1.7722 - accuracy: 0.4142\n",
"14070/14070 [==============================] - 1s 60us/sample - loss: 2.5022 - accuracy: 0.2281\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 2.3937 - accuracy: 0.2819\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.4671 - accuracy: 0.2690\n",
"start index for training is 538000\n",
"Train on 9755 samples, validate on 9760 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9755/9755 [==============================] - 0s 44us/sample - loss: 2.0554 - accuracy: 0.3564\n",
"9760/9760 [==============================] - 0s 43us/sample - loss: 2.0977 - accuracy: 0.3512\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.8183 - accuracy: 0.4089\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7773 - accuracy: 0.4077\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.4634 - accuracy: 0.2335\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.3789 - accuracy: 0.2754\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.4594 - accuracy: 0.2616\n",
"start index for training is 539000\n",
"Train on 6480 samples, validate on 6485 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6480/6480 [==============================] - 0s 46us/sample - loss: 2.1741 - accuracy: 0.3119\n",
"6485/6485 [==============================] - 0s 48us/sample - loss: 2.2424 - accuracy: 0.2973\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8456 - accuracy: 0.4296\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7843 - accuracy: 0.4078\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.4659 - accuracy: 0.2385\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3843 - accuracy: 0.2661\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4594 - accuracy: 0.2584\n",
"start index for training is 540000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 54us/sample - loss: 2.1622 - accuracy: 0.3221\n",
"4995/4995 [==============================] - 0s 63us/sample - loss: 2.2218 - accuracy: 0.3033\n",
"5980/5980 [==============================] - 0s 62us/sample - loss: 1.8709 - accuracy: 0.4052\n",
"12255/12255 [==============================] - 1s 54us/sample - loss: 1.8054 - accuracy: 0.4002\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.5067 - accuracy: 0.2432\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.4083 - accuracy: 0.2800\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.4859 - accuracy: 0.2687\n",
"start index for training is 541000\n",
"Train on 26005 samples, validate on 26005 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"26005/26005 [==============================] - 1s 38us/sample - loss: 2.0236 - accuracy: 0.3780\n",
"26005/26005 [==============================] - 1s 35us/sample - loss: 2.0264 - accuracy: 0.3792\n",
"5980/5980 [==============================] - 0s 33us/sample - loss: 1.9516 - accuracy: 0.3308\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 1.9083 - accuracy: 0.3714\n",
"14070/14070 [==============================] - 0s 34us/sample - loss: 2.6093 - accuracy: 0.2353s - loss: 2.6079 - ac\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.5575 - accuracy: 0.2466\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.6297 - accuracy: 0.2343\n",
"start index for training is 542000\n",
"Train on 11285 samples, validate on 11290 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11285/11285 [==============================] - 0s 41us/sample - loss: 2.0622 - accuracy: 0.3529\n",
"11290/11290 [==============================] - 0s 37us/sample - loss: 2.0692 - accuracy: 0.3475\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8608 - accuracy: 0.4008\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7825 - accuracy: 0.4016\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.4990 - accuracy: 0.2402\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.4036 - accuracy: 0.2688\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4859 - accuracy: 0.2601\n",
"start index for training is 543000\n",
"Train on 7000 samples, validate on 7000 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.1722 - accuracy: 0.3184\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.1978 - accuracy: 0.3190\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 1.8612 - accuracy: 0.3993\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 1.8032 - accuracy: 0.4040\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.4977 - accuracy: 0.2387\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.4046 - accuracy: 0.2744\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4778 - accuracy: 0.2649\n",
"start index for training is 544000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 45us/sample - loss: 2.2198 - accuracy: 0.3171\n",
"4995/4995 [==============================] - 0s 41us/sample - loss: 2.2590 - accuracy: 0.3135\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8706 - accuracy: 0.3941\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.8050 - accuracy: 0.4042\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4852 - accuracy: 0.2363\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3925 - accuracy: 0.2748\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.4675 - accuracy: 0.2619\n",
"start index for training is 545000\n",
"Train on 23320 samples, validate on 23320 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"23320/23320 [==============================] - 1s 48us/sample - loss: 1.8116 - accuracy: 0.4416s - loss: 1.8084 - accuracy: \n",
"23320/23320 [==============================] - 1s 42us/sample - loss: 1.8174 - accuracy: 0.4366\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8339 - accuracy: 0.4032\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.7562 - accuracy: 0.4215\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4656 - accuracy: 0.2552\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3733 - accuracy: 0.2864\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4420 - accuracy: 0.2724\n",
"start index for training is 546000\n",
"Train on 12685 samples, validate on 12690 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12685/12685 [==============================] - 1s 43us/sample - loss: 2.0550 - accuracy: 0.3515\n",
"12690/12690 [==============================] - 0s 37us/sample - loss: 2.0551 - accuracy: 0.3542\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.8489 - accuracy: 0.3982\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7827 - accuracy: 0.4023\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.4842 - accuracy: 0.2303\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.3884 - accuracy: 0.2758\n",
"7000/7000 [==============================] - 0s 35us/sample - loss: 2.4628 - accuracy: 0.2663\n",
"start index for training is 547000\n",
"Train on 7565 samples, validate on 7565 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7565/7565 [==============================] - 0s 53us/sample - loss: 2.1408 - accuracy: 0.3298\n",
"7565/7565 [==============================] - 0s 42us/sample - loss: 2.1386 - accuracy: 0.3297\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8655 - accuracy: 0.3766\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8000 - accuracy: 0.3976\n",
"14070/14070 [==============================] - 0s 36us/sample - loss: 2.4855 - accuracy: 0.2451\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.4084 - accuracy: 0.2692\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4787 - accuracy: 0.2503\n",
"start index for training is 548000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 40us/sample - loss: 2.2395 - accuracy: 0.3177\n",
"4995/4995 [==============================] - ETA: 0s - loss: 2.2547 - accuracy: 0.31 - 0s 38us/sample - loss: 2.2673 - accuracy: 0.3129\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.8703 - accuracy: 0.3836\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 1.8095 - accuracy: 0.4009\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.5034 - accuracy: 0.2438\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.4057 - accuracy: 0.2809\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.4689 - accuracy: 0.2694\n",
"start index for training is 549000\n",
"Train on 21805 samples, validate on 21805 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21805/21805 [==============================] - 1s 40us/sample - loss: 1.8019 - accuracy: 0.4405\n",
"21805/21805 [==============================] - 1s 36us/sample - loss: 1.8294 - accuracy: 0.4310\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 1.8227 - accuracy: 0.3913s - loss: 1.8002 - accuracy: 0.\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 1.7560 - accuracy: 0.4183\n",
"14070/14070 [==============================] - 0s 34us/sample - loss: 2.4558 - accuracy: 0.2581\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.3766 - accuracy: 0.2815\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.4479 - accuracy: 0.2661\n",
"start index for training is 550000\n",
"Train on 13355 samples, validate on 13355 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13355/13355 [==============================] - 1s 39us/sample - loss: 2.0030 - accuracy: 0.3624\n",
"13355/13355 [==============================] - 0s 36us/sample - loss: 2.0217 - accuracy: 0.3617\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8568 - accuracy: 0.3936\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 1.7855 - accuracy: 0.4003s - loss: 1.7867 - accura\n",
"14070/14070 [==============================] - 0s 34us/sample - loss: 2.4927 - accuracy: 0.2407\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.4039 - accuracy: 0.2805\n",
"7000/7000 [==============================] - 0s 33us/sample - loss: 2.4761 - accuracy: 0.2686\n",
"start index for training is 551000\n",
"Train on 7845 samples, validate on 7850 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7845/7845 [==============================] - 0s 42us/sample - loss: 2.1374 - accuracy: 0.3324\n",
"7850/7850 [==============================] - 0s 38us/sample - loss: 2.1708 - accuracy: 0.3355\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.8376 - accuracy: 0.4005\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 1.7873 - accuracy: 0.4068\n",
"14070/14070 [==============================] - 0s 35us/sample - loss: 2.4638 - accuracy: 0.2409\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.3870 - accuracy: 0.2768\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.4563 - accuracy: 0.2594\n",
"start index for training is 552000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 40us/sample - loss: 2.2469 - accuracy: 0.3163\n",
"4995/4995 [==============================] - 0s 38us/sample - loss: 2.2376 - accuracy: 0.3087\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.8710 - accuracy: 0.4037\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 1.8076 - accuracy: 0.4116\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.4862 - accuracy: 0.2434\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3948 - accuracy: 0.2750\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.4608 - accuracy: 0.2590\n",
"start index for training is 553000\n",
"Train on 22015 samples, validate on 22020 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"22015/22015 [==============================] - 1s 48us/sample - loss: 1.8760 - accuracy: 0.3965\n",
"22020/22020 [==============================] - 1s 45us/sample - loss: 1.8773 - accuracy: 0.3943\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.8414 - accuracy: 0.3900\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.8012 - accuracy: 0.3840\n",
"14070/14070 [==============================] - 1s 58us/sample - loss: 2.4501 - accuracy: 0.2397\n",
"11565/11565 [==============================] - 1s 54us/sample - loss: 2.4120 - accuracy: 0.2468\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.4855 - accuracy: 0.2333\n",
"start index for training is 554000\n",
"Train on 13335 samples, validate on 13335 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13335/13335 [==============================] - 1s 41us/sample - loss: 1.9994 - accuracy: 0.3683\n",
"13335/13335 [==============================] - 1s 38us/sample - loss: 2.0246 - accuracy: 0.3625\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 1.8458 - accuracy: 0.3975\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 1.7852 - accuracy: 0.4049\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.4761 - accuracy: 0.2416\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.3992 - accuracy: 0.2806\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.4673 - accuracy: 0.2656\n",
"start index for training is 555000\n",
"Train on 7810 samples, validate on 7810 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7810/7810 [==============================] - 0s 50us/sample - loss: 2.1749 - accuracy: 0.3214\n",
"7810/7810 [==============================] - 0s 41us/sample - loss: 2.2158 - accuracy: 0.3138\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8557 - accuracy: 0.4075\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.7983 - accuracy: 0.4063\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.4783 - accuracy: 0.2389\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.3861 - accuracy: 0.2751\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4501 - accuracy: 0.2617\n",
"start index for training is 556000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 86us/sample - loss: 2.2125 - accuracy: 0.3321\n",
"4995/4995 [==============================] - 0s 68us/sample - loss: 2.2589 - accuracy: 0.3025\n",
"5980/5980 [==============================] - 0s 75us/sample - loss: 1.8666 - accuracy: 0.3747\n",
"12255/12255 [==============================] - 1s 53us/sample - loss: 1.8064 - accuracy: 0.3963\n",
"14070/14070 [==============================] - 1s 73us/sample - loss: 2.4897 - accuracy: 0.2394s - loss: 2.4871 - ac\n",
"11565/11565 [==============================] - 1s 51us/sample - loss: 2.3975 - accuracy: 0.2751\n",
"7000/7000 [==============================] - 0s 62us/sample - loss: 2.4619 - accuracy: 0.2634s - loss: 2.4798 - ac\n",
"start index for training is 557000\n",
"Train on 20415 samples, validate on 20415 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"20415/20415 [==============================] - 1s 38us/sample - loss: 1.8007 - accuracy: 0.4447\n",
"20415/20415 [==============================] - 1s 34us/sample - loss: 1.8104 - accuracy: 0.4414\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 1.8400 - accuracy: 0.3856\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 1.7830 - accuracy: 0.4024\n",
"14070/14070 [==============================] - 0s 33us/sample - loss: 2.4689 - accuracy: 0.2451\n",
"11565/11565 [==============================] - 0s 33us/sample - loss: 2.3958 - accuracy: 0.2667\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.4629 - accuracy: 0.2546\n",
"start index for training is 558000\n",
"Train on 14220 samples, validate on 14220 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14220/14220 [==============================] - 1s 39us/sample - loss: 2.0049 - accuracy: 0.3669\n",
"14220/14220 [==============================] - 0s 35us/sample - loss: 2.0070 - accuracy: 0.3631\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 1.8359 - accuracy: 0.3943\n",
"12255/12255 [==============================] - 0s 33us/sample - loss: 1.7779 - accuracy: 0.4026\n",
"14070/14070 [==============================] - 0s 34us/sample - loss: 2.4516 - accuracy: 0.2408\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.3774 - accuracy: 0.2783\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4397 - accuracy: 0.2661s - loss: 2.4427 - accuracy: 0.26\n",
"start index for training is 559000\n",
"Train on 7960 samples, validate on 7965 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7960/7960 [==============================] - 0s 39us/sample - loss: 2.1775 - accuracy: 0.3334\n",
"7965/7965 [==============================] - 0s 36us/sample - loss: 2.1823 - accuracy: 0.3264\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8369 - accuracy: 0.4054\n",
"12255/12255 [==============================] - 0s 34us/sample - loss: 1.7947 - accuracy: 0.4100\n",
"14070/14070 [==============================] - 0s 34us/sample - loss: 2.4540 - accuracy: 0.2429\n",
"11565/11565 [==============================] - 0s 33us/sample - loss: 2.3714 - accuracy: 0.2827\n",
"7000/7000 [==============================] - 0s 33us/sample - loss: 2.4364 - accuracy: 0.2724\n",
"start index for training is 560000\n",
"Train on 5035 samples, validate on 5035 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5035/5035 [==============================] - 0s 42us/sample - loss: 2.2467 - accuracy: 0.3104\n",
"5035/5035 [==============================] - 0s 40us/sample - loss: 2.2667 - accuracy: 0.3092\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.8435 - accuracy: 0.4154\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.8092 - accuracy: 0.4009\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.4544 - accuracy: 0.2529\n",
"11565/11565 [==============================] - 0s 34us/sample - loss: 2.3890 - accuracy: 0.2725\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.4569 - accuracy: 0.2566\n",
"start index for training is 561000\n",
"Train on 21450 samples, validate on 21450 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21450/21450 [==============================] - 1s 69us/sample - loss: 1.8173 - accuracy: 0.4391\n",
"21450/21450 [==============================] - 1s 38us/sample - loss: 1.8179 - accuracy: 0.4442\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8337 - accuracy: 0.4097\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.7795 - accuracy: 0.4164\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.4502 - accuracy: 0.2606\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.3741 - accuracy: 0.2802\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4359 - accuracy: 0.2663\n",
"start index for training is 562000\n",
"Train on 13740 samples, validate on 13745 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13740/13740 [==============================] - 1s 49us/sample - loss: 2.0022 - accuracy: 0.3663\n",
"13745/13745 [==============================] - 1s 45us/sample - loss: 2.0250 - accuracy: 0.3574\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8531 - accuracy: 0.3982\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.8051 - accuracy: 0.3898\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.4786 - accuracy: 0.2414\n",
"11565/11565 [==============================] - 1s 58us/sample - loss: 2.3969 - accuracy: 0.2794\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.4633 - accuracy: 0.2654\n",
"start index for training is 563000\n",
"Train on 7835 samples, validate on 7840 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7835/7835 [==============================] - 0s 55us/sample - loss: 2.1586 - accuracy: 0.3288\n",
"7840/7840 [==============================] - 0s 50us/sample - loss: 2.2279 - accuracy: 0.3231\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.8523 - accuracy: 0.4115\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 1.8128 - accuracy: 0.4060\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.4762 - accuracy: 0.2510\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.3875 - accuracy: 0.2815\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.4479 - accuracy: 0.2691\n",
"start index for training is 564000\n",
"Train on 4995 samples, validate on 4995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"4995/4995 [==============================] - 0s 42us/sample - loss: 2.2119 - accuracy: 0.3271\n",
"4995/4995 [==============================] - 0s 42us/sample - loss: 2.2593 - accuracy: 0.3131\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8581 - accuracy: 0.3821\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.8246 - accuracy: 0.3987\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.4770 - accuracy: 0.2440\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.3990 - accuracy: 0.2804\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.4605 - accuracy: 0.2683\n",
"start index for training is 565000\n",
"Train on 7620 samples, validate on 7625 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7620/7620 [==============================] - 0s 46us/sample - loss: 2.1960 - accuracy: 0.2923\n",
"7625/7625 [==============================] - 0s 40us/sample - loss: 2.2180 - accuracy: 0.2922\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.8237 - accuracy: 0.4157\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8516 - accuracy: 0.3621\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1853 - accuracy: 0.2893\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.3164 - accuracy: 0.2623\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3845 - accuracy: 0.2437\n",
"start index for training is 566000\n",
"Train on 11300 samples, validate on 11305 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11300/11300 [==============================] - 0s 41us/sample - loss: 2.0495 - accuracy: 0.3292\n",
"11305/11305 [==============================] - 0s 39us/sample - loss: 2.0948 - accuracy: 0.3134\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.9038 - accuracy: 0.3706\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.9461 - accuracy: 0.3319\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.0569 - accuracy: 0.3253\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.3097 - accuracy: 0.2836\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.3804 - accuracy: 0.2659\n",
"start index for training is 567000\n",
"Train on 13285 samples, validate on 13290 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13285/13285 [==============================] - 1s 47us/sample - loss: 2.0003 - accuracy: 0.3684\n",
"13290/13290 [==============================] - 1s 39us/sample - loss: 2.0144 - accuracy: 0.3632\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9496 - accuracy: 0.3528\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0034 - accuracy: 0.3089\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 1.9966 - accuracy: 0.3633\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.3224 - accuracy: 0.2765\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3988 - accuracy: 0.2567\n",
"start index for training is 568000\n",
"Train on 11885 samples, validate on 11890 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11885/11885 [==============================] - 0s 42us/sample - loss: 2.0224 - accuracy: 0.3756\n",
"11890/11890 [==============================] - 0s 40us/sample - loss: 2.0597 - accuracy: 0.3547\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9567 - accuracy: 0.3543\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0019 - accuracy: 0.3129\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9630 - accuracy: 0.3900\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.2987 - accuracy: 0.3033\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.3763 - accuracy: 0.2839\n",
"start index for training is 569000\n",
"Train on 12770 samples, validate on 12775 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12770/12770 [==============================] - 1s 43us/sample - loss: 1.9932 - accuracy: 0.3919\n",
"12775/12775 [==============================] - 0s 38us/sample - loss: 2.0223 - accuracy: 0.3759\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.9640 - accuracy: 0.3513\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0161 - accuracy: 0.3178\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 1.9375 - accuracy: 0.4090\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.2874 - accuracy: 0.3052\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.3678 - accuracy: 0.2920\n",
"start index for training is 570000\n",
"Train on 13315 samples, validate on 13320 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13315/13315 [==============================] - 1s 53us/sample - loss: 1.9675 - accuracy: 0.3959\n",
"13320/13320 [==============================] - 1s 48us/sample - loss: 1.9740 - accuracy: 0.3920\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.9802 - accuracy: 0.3530\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.0513 - accuracy: 0.2829\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 1.9122 - accuracy: 0.4159\n",
"11565/11565 [==============================] - 1s 62us/sample - loss: 2.3010 - accuracy: 0.2802\n",
"7000/7000 [==============================] - 0s 58us/sample - loss: 2.3871 - accuracy: 0.2546\n",
"start index for training is 571000\n",
"Train on 11085 samples, validate on 11085 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11085/11085 [==============================] - 1s 59us/sample - loss: 2.0689 - accuracy: 0.3638\n",
"11085/11085 [==============================] - 1s 49us/sample - loss: 2.0808 - accuracy: 0.3581\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.9694 - accuracy: 0.3559\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.0259 - accuracy: 0.3027\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.9026 - accuracy: 0.4149\n",
"11565/11565 [==============================] - 1s 54us/sample - loss: 2.2738 - accuracy: 0.3014\n",
"7000/7000 [==============================] - 0s 56us/sample - loss: 2.3589 - accuracy: 0.2831\n",
"start index for training is 572000\n",
"Train on 14585 samples, validate on 14590 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14585/14585 [==============================] - 1s 49us/sample - loss: 1.9154 - accuracy: 0.4167\n",
"14590/14590 [==============================] - 1s 45us/sample - loss: 1.9451 - accuracy: 0.4051\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.9964 - accuracy: 0.3371\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 2.0594 - accuracy: 0.2899\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.8801 - accuracy: 0.4267\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.2850 - accuracy: 0.2781\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.3755 - accuracy: 0.2571\n",
"start index for training is 573000\n",
"Train on 13635 samples, validate on 13640 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13635/13635 [==============================] - 1s 63us/sample - loss: 1.9044 - accuracy: 0.4232\n",
"13640/13640 [==============================] - 1s 46us/sample - loss: 1.9186 - accuracy: 0.4216\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.9944 - accuracy: 0.3264\n",
"12255/12255 [==============================] - 1s 54us/sample - loss: 2.0604 - accuracy: 0.2974\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.8663 - accuracy: 0.4404\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.2801 - accuracy: 0.3024\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.3720 - accuracy: 0.2827\n",
"start index for training is 574000\n",
"Train on 11185 samples, validate on 11190 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11185/11185 [==============================] - 1s 47us/sample - loss: 2.0133 - accuracy: 0.3827\n",
"11190/11190 [==============================] - 1s 45us/sample - loss: 2.0190 - accuracy: 0.3812\n",
"5980/5980 [==============================] - 0s 55us/sample - loss: 1.9889 - accuracy: 0.3298\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.0724 - accuracy: 0.2888\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.8633 - accuracy: 0.4326\n",
"11565/11565 [==============================] - 1s 52us/sample - loss: 2.2833 - accuracy: 0.2879\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.3784 - accuracy: 0.2619\n",
"start index for training is 575000\n",
"Train on 14435 samples, validate on 14435 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14435/14435 [==============================] - 1s 49us/sample - loss: 1.8671 - accuracy: 0.4226\n",
"14435/14435 [==============================] - 1s 44us/sample - loss: 1.8649 - accuracy: 0.4196\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.9902 - accuracy: 0.3396\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.0754 - accuracy: 0.3006\n",
"14070/14070 [==============================] - 1s 53us/sample - loss: 1.8428 - accuracy: 0.4432\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.2776 - accuracy: 0.2984\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.3739 - accuracy: 0.2761\n",
"start index for training is 576000\n",
"Train on 14095 samples, validate on 14095 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14095/14095 [==============================] - 1s 52us/sample - loss: 1.8424 - accuracy: 0.4297\n",
"14095/14095 [==============================] - 1s 49us/sample - loss: 1.8473 - accuracy: 0.4254\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.0038 - accuracy: 0.3537\n",
"12255/12255 [==============================] - 1s 50us/sample - loss: 2.0955 - accuracy: 0.2988\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.8398 - accuracy: 0.4452\n",
"11565/11565 [==============================] - 1s 69us/sample - loss: 2.2828 - accuracy: 0.3012\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.3850 - accuracy: 0.2804\n",
"start index for training is 577000\n",
"Train on 14435 samples, validate on 14440 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14435/14435 [==============================] - 1s 47us/sample - loss: 1.8117 - accuracy: 0.4341\n",
"14440/14440 [==============================] - 1s 45us/sample - loss: 1.8220 - accuracy: 0.4339\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.0177 - accuracy: 0.3405\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.1122 - accuracy: 0.2865\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.8230 - accuracy: 0.4448\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.3001 - accuracy: 0.2776\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.4053 - accuracy: 0.2491\n",
"start index for training is 578000\n",
"Train on 15100 samples, validate on 15105 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15100/15100 [==============================] - 1s 57us/sample - loss: 1.7836 - accuracy: 0.4378\n",
"15105/15105 [==============================] - 1s 56us/sample - loss: 1.7875 - accuracy: 0.4375\n",
"5980/5980 [==============================] - 0s 67us/sample - loss: 2.0251 - accuracy: 0.3391\n",
"12255/12255 [==============================] - 1s 54us/sample - loss: 2.1205 - accuracy: 0.2910\n",
"14070/14070 [==============================] - 1s 54us/sample - loss: 1.8138 - accuracy: 0.4467\n",
"11565/11565 [==============================] - 1s 58us/sample - loss: 2.2891 - accuracy: 0.2969\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.3957 - accuracy: 0.2741\n",
"start index for training is 579000\n",
"Train on 11795 samples, validate on 11800 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11795/11795 [==============================] - 1s 46us/sample - loss: 1.8897 - accuracy: 0.4006\n",
"11800/11800 [==============================] - 1s 42us/sample - loss: 1.9194 - accuracy: 0.3913\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0088 - accuracy: 0.3405\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1122 - accuracy: 0.2831\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.8150 - accuracy: 0.4471\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.2859 - accuracy: 0.2802\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3932 - accuracy: 0.2507\n",
"start index for training is 580000\n",
"Train on 17540 samples, validate on 17545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17540/17540 [==============================] - 1s 55us/sample - loss: 1.7618 - accuracy: 0.4461\n",
"17545/17545 [==============================] - 1s 40us/sample - loss: 1.7601 - accuracy: 0.4493\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0252 - accuracy: 0.3338\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1160 - accuracy: 0.2806\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8048 - accuracy: 0.4490\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.2922 - accuracy: 0.2805\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.3983 - accuracy: 0.2534\n",
"start index for training is 581000\n",
"Train on 17220 samples, validate on 17220 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17220/17220 [==============================] - 1s 41us/sample - loss: 1.7035 - accuracy: 0.4725\n",
"17220/17220 [==============================] - 1s 39us/sample - loss: 1.7468 - accuracy: 0.4653\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0418 - accuracy: 0.3273\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1263 - accuracy: 0.2807\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.8034 - accuracy: 0.4505\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.2906 - accuracy: 0.2840\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.3994 - accuracy: 0.2553\n",
"start index for training is 582000\n",
"Train on 16760 samples, validate on 16765 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16760/16760 [==============================] - ETA: 0s - loss: 1.8309 - accuracy: 0.41 - 1s 42us/sample - loss: 1.8350 - accuracy: 0.4168\n",
"16765/16765 [==============================] - 1s 45us/sample - loss: 1.8219 - accuracy: 0.4197\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.0452 - accuracy: 0.3274\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1295 - accuracy: 0.2729\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.7945 - accuracy: 0.4482\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.2927 - accuracy: 0.2798\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.4043 - accuracy: 0.2476\n",
"start index for training is 583000\n",
"Train on 14080 samples, validate on 14085 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14080/14080 [==============================] - 1s 41us/sample - loss: 1.8605 - accuracy: 0.4116\n",
"14085/14085 [==============================] - 1s 40us/sample - loss: 1.8553 - accuracy: 0.4112\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0593 - accuracy: 0.3244\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1376 - accuracy: 0.2838\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.8014 - accuracy: 0.4480\n",
"11565/11565 [==============================] - 1s 63us/sample - loss: 2.2829 - accuracy: 0.3069\n",
"7000/7000 [==============================] - 0s 58us/sample - loss: 2.3988 - accuracy: 0.2733\n",
"start index for training is 584000\n",
"Train on 21915 samples, validate on 21920 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21915/21915 [==============================] - 1s 43us/sample - loss: 1.6858 - accuracy: 0.4753\n",
"21920/21920 [==============================] - 1s 36us/sample - loss: 1.6768 - accuracy: 0.4764\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0735 - accuracy: 0.3251\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1484 - accuracy: 0.2773\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.7892 - accuracy: 0.4503\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.2966 - accuracy: 0.2871\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.4137 - accuracy: 0.2581\n",
"start index for training is 585000\n",
"Train on 17920 samples, validate on 17920 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17920/17920 [==============================] - 1s 44us/sample - loss: 1.8094 - accuracy: 0.4342\n",
"17920/17920 [==============================] - 1s 41us/sample - loss: 1.8173 - accuracy: 0.4269\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0674 - accuracy: 0.3221\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1374 - accuracy: 0.2767\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.7863 - accuracy: 0.4567\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.2813 - accuracy: 0.2866\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3974 - accuracy: 0.2511\n",
"start index for training is 586000\n",
"Train on 16675 samples, validate on 16680 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16675/16675 [==============================] - 1s 48us/sample - loss: 1.8175 - accuracy: 0.4239\n",
"16680/16680 [==============================] - 1s 40us/sample - loss: 1.8377 - accuracy: 0.4180\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0542 - accuracy: 0.3281\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1137 - accuracy: 0.2990\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7759 - accuracy: 0.4574\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.2443 - accuracy: 0.3159\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3593 - accuracy: 0.2837s - loss: 2.3569 - accura\n",
"start index for training is 587000\n",
"Train on 16265 samples, validate on 16265 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16265/16265 [==============================] - 1s 43us/sample - loss: 1.8133 - accuracy: 0.4388\n",
"16265/16265 [==============================] - 1s 39us/sample - loss: 1.8319 - accuracy: 0.4281\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0769 - accuracy: 0.2985\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1466 - accuracy: 0.2833\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7897 - accuracy: 0.4552\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2787 - accuracy: 0.2971\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.4010 - accuracy: 0.2564\n",
"start index for training is 588000\n",
"Train on 16245 samples, validate on 16245 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16245/16245 [==============================] - 1s 43us/sample - loss: 1.7941 - accuracy: 0.4408\n",
"16245/16245 [==============================] - 1s 41us/sample - loss: 1.8139 - accuracy: 0.4337\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.0831 - accuracy: 0.3084\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.1466 - accuracy: 0.2858\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.7867 - accuracy: 0.4523\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.2689 - accuracy: 0.3040\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3833 - accuracy: 0.2667\n",
"start index for training is 589000\n",
"Train on 16895 samples, validate on 16895 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16895/16895 [==============================] - 1s 49us/sample - loss: 1.7917 - accuracy: 0.4423\n",
"16895/16895 [==============================] - 1s 43us/sample - loss: 1.8056 - accuracy: 0.4372\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 2.0649 - accuracy: 0.3142\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.1226 - accuracy: 0.2833\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.7839 - accuracy: 0.4511\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.2395 - accuracy: 0.3085\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3545 - accuracy: 0.2760\n",
"start index for training is 590000\n",
"Train on 18470 samples, validate on 18475 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18470/18470 [==============================] - 1s 41us/sample - loss: 1.7614 - accuracy: 0.4500\n",
"18475/18475 [==============================] - 1s 37us/sample - loss: 1.7486 - accuracy: 0.4565\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0758 - accuracy: 0.3134\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1204 - accuracy: 0.2956\n",
"14070/14070 [==============================] - ETA: 0s - loss: 1.7766 - accuracy: 0.45 - 1s 40us/sample - loss: 1.7784 - accuracy: 0.4532\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.2403 - accuracy: 0.3076s - loss: 2.2655 - accura\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.3534 - accuracy: 0.2791\n",
"start index for training is 591000\n",
"Train on 21520 samples, validate on 21525 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21520/21520 [==============================] - 1s 42us/sample - loss: 1.6941 - accuracy: 0.4776\n",
"21525/21525 [==============================] - 1s 38us/sample - loss: 1.7081 - accuracy: 0.4730\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.0920 - accuracy: 0.3171\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.1315 - accuracy: 0.2884\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.7869 - accuracy: 0.4475\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.2507 - accuracy: 0.3075\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.3699 - accuracy: 0.2770\n",
"start index for training is 592000\n",
"Train on 17395 samples, validate on 17395 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17395/17395 [==============================] - 1s 45us/sample - loss: 1.8049 - accuracy: 0.4401\n",
"17395/17395 [==============================] - 1s 41us/sample - loss: 1.7994 - accuracy: 0.4414\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.0926 - accuracy: 0.3037\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1321 - accuracy: 0.2796\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7810 - accuracy: 0.4629\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.2344 - accuracy: 0.3101\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.3557 - accuracy: 0.2771\n",
"start index for training is 593000\n",
"Train on 16265 samples, validate on 16265 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16265/16265 [==============================] - 1s 43us/sample - loss: 1.8548 - accuracy: 0.4132\n",
"16265/16265 [==============================] - 1s 42us/sample - loss: 1.8500 - accuracy: 0.4176\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 2.0841 - accuracy: 0.2901\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1344 - accuracy: 0.2778\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7807 - accuracy: 0.4583\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.2375 - accuracy: 0.3045\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3564 - accuracy: 0.2666\n",
"start index for training is 594000\n",
"Train on 18015 samples, validate on 18020 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18015/18015 [==============================] - 1s 53us/sample - loss: 1.8970 - accuracy: 0.3954\n",
"18020/18020 [==============================] - 1s 44us/sample - loss: 1.8734 - accuracy: 0.4041\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.1782 - accuracy: 0.2973\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1903 - accuracy: 0.2803\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8343 - accuracy: 0.4331\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.2835 - accuracy: 0.3103\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.4028 - accuracy: 0.2763\n",
"start index for training is 595000\n",
"Train on 19795 samples, validate on 19800 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19795/19795 [==============================] - 1s 47us/sample - loss: 1.7819 - accuracy: 0.4415\n",
"19800/19800 [==============================] - 1s 42us/sample - loss: 1.7735 - accuracy: 0.4435\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.0814 - accuracy: 0.3099\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1227 - accuracy: 0.2786\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.7813 - accuracy: 0.4528\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.2161 - accuracy: 0.3213\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.3422 - accuracy: 0.2880\n",
"start index for training is 596000\n",
"Train on 20310 samples, validate on 20310 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20310/20310 [==============================] - 1s 43us/sample - loss: 1.7821 - accuracy: 0.4375\n",
"20310/20310 [==============================] - 1s 39us/sample - loss: 1.7836 - accuracy: 0.4404\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.0860 - accuracy: 0.3070\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 2.1239 - accuracy: 0.2956\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.7809 - accuracy: 0.4527\n",
"11565/11565 [==============================] - 1s 49us/sample - loss: 2.2106 - accuracy: 0.3398\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.3323 - accuracy: 0.3096\n",
"start index for training is 597000\n",
"Train on 20795 samples, validate on 20800 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20795/20795 [==============================] - 1s 48us/sample - loss: 1.7729 - accuracy: 0.4415\n",
"20800/20800 [==============================] - 1s 42us/sample - loss: 1.7837 - accuracy: 0.4407\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 2.0973 - accuracy: 0.2978\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 2.1315 - accuracy: 0.2753\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 1.7863 - accuracy: 0.4503\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.2144 - accuracy: 0.3167\n",
"7000/7000 [==============================] - 0s 51us/sample - loss: 2.3406 - accuracy: 0.2834\n",
"start index for training is 598000\n",
"Train on 20675 samples, validate on 20675 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20675/20675 [==============================] - 1s 43us/sample - loss: 1.7652 - accuracy: 0.4473\n",
"20675/20675 [==============================] - 1s 41us/sample - loss: 1.7692 - accuracy: 0.4421\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.1080 - accuracy: 0.3057\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1245 - accuracy: 0.2856\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.7819 - accuracy: 0.4602\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1969 - accuracy: 0.3422\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3227 - accuracy: 0.3111\n",
"start index for training is 599000\n",
"Train on 20130 samples, validate on 20135 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20130/20130 [==============================] - 1s 44us/sample - loss: 1.7553 - accuracy: 0.4480\n",
"20135/20135 [==============================] - 1s 44us/sample - loss: 1.7760 - accuracy: 0.4431\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1337 - accuracy: 0.2855\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1584 - accuracy: 0.2849\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7915 - accuracy: 0.4475\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.2235 - accuracy: 0.3160\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3559 - accuracy: 0.2791\n",
"start index for training is 600000\n",
"Train on 19275 samples, validate on 19280 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19275/19275 [==============================] - 1s 41us/sample - loss: 1.7450 - accuracy: 0.4546\n",
"19280/19280 [==============================] - 1s 38us/sample - loss: 1.7645 - accuracy: 0.4442\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1270 - accuracy: 0.2910\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1507 - accuracy: 0.2796\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.7812 - accuracy: 0.4507\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.2135 - accuracy: 0.3161\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3439 - accuracy: 0.2779\n",
"start index for training is 601000\n",
"Train on 17080 samples, validate on 17080 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17080/17080 [==============================] - 1s 42us/sample - loss: 1.7952 - accuracy: 0.4467\n",
"17080/17080 [==============================] - 1s 40us/sample - loss: 1.7844 - accuracy: 0.4480\n",
"5980/5980 [==============================] - ETA: 0s - loss: 2.1121 - accuracy: 0.30 - 0s 40us/sample - loss: 2.1082 - accuracy: 0.3067\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1261 - accuracy: 0.2856\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.7938 - accuracy: 0.4490\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1699 - accuracy: 0.3495\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2870 - accuracy: 0.3280\n",
"start index for training is 602000\n",
"Train on 11660 samples, validate on 11660 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11660/11660 [==============================] - 1s 44us/sample - loss: 2.0715 - accuracy: 0.3403\n",
"11660/11660 [==============================] - 0s 40us/sample - loss: 2.0668 - accuracy: 0.3435\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0850 - accuracy: 0.2958\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.1163 - accuracy: 0.2719\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.7793 - accuracy: 0.4526\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1653 - accuracy: 0.3316\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2909 - accuracy: 0.2886\n",
"start index for training is 603000\n",
"Train on 20420 samples, validate on 20425 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20420/20420 [==============================] - 1s 45us/sample - loss: 1.7736 - accuracy: 0.4418\n",
"20425/20425 [==============================] - 1s 42us/sample - loss: 1.7480 - accuracy: 0.4485\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.1068 - accuracy: 0.2935\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1241 - accuracy: 0.2833\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.7864 - accuracy: 0.4505\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.1749 - accuracy: 0.3211\n",
"7000/7000 [==============================] - 0s 51us/sample - loss: 2.3047 - accuracy: 0.2871\n",
"start index for training is 604000\n",
"Train on 19690 samples, validate on 19690 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"19690/19690 [==============================] - 1s 49us/sample - loss: 1.7569 - accuracy: 0.4467\n",
"19690/19690 [==============================] - 1s 50us/sample - loss: 1.7643 - accuracy: 0.4440\n",
"5980/5980 [==============================] - 0s 53us/sample - loss: 2.1134 - accuracy: 0.3027\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 2.1152 - accuracy: 0.2892\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 1.7824 - accuracy: 0.4608\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.1536 - accuracy: 0.3511\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2830 - accuracy: 0.3226\n",
"start index for training is 605000\n",
"Train on 19560 samples, validate on 19565 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19560/19560 [==============================] - 1s 50us/sample - loss: 1.7495 - accuracy: 0.4466\n",
"19565/19565 [==============================] - 1s 45us/sample - loss: 1.7660 - accuracy: 0.4452\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 2.1094 - accuracy: 0.2960\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 2.1169 - accuracy: 0.2910\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.7812 - accuracy: 0.4618\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.1505 - accuracy: 0.3505\n",
"7000/7000 [==============================] - 0s 57us/sample - loss: 2.2839 - accuracy: 0.3220\n",
"start index for training is 606000\n",
"Train on 18925 samples, validate on 18930 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18925/18925 [==============================] - 1s 50us/sample - loss: 1.7581 - accuracy: 0.4524\n",
"18930/18930 [==============================] - 1s 46us/sample - loss: 1.7561 - accuracy: 0.4498\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 2.1196 - accuracy: 0.2957\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.1160 - accuracy: 0.2909\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.7855 - accuracy: 0.4606\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.1424 - accuracy: 0.3507\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.2801 - accuracy: 0.3196\n",
"start index for training is 607000\n",
"Train on 17035 samples, validate on 17035 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17035/17035 [==============================] - 1s 48us/sample - loss: 1.7648 - accuracy: 0.4430\n",
"17035/17035 [==============================] - 1s 45us/sample - loss: 1.7923 - accuracy: 0.4288\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.1455 - accuracy: 0.2983\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.1670 - accuracy: 0.2772\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.8247 - accuracy: 0.4345\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.1800 - accuracy: 0.3226\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.3167 - accuracy: 0.2919\n",
"start index for training is 608000\n",
"Train on 10530 samples, validate on 10530 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10530/10530 [==============================] - 1s 48us/sample - loss: 2.0942 - accuracy: 0.3228\n",
"10530/10530 [==============================] - 0s 46us/sample - loss: 2.1380 - accuracy: 0.3123\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 2.1024 - accuracy: 0.3172\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 2.1171 - accuracy: 0.2893\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.7918 - accuracy: 0.4455\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.1268 - accuracy: 0.3375\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.2622 - accuracy: 0.2939\n",
"start index for training is 609000\n",
"Train on 21120 samples, validate on 21120 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21120/21120 [==============================] - 1s 47us/sample - loss: 1.8023 - accuracy: 0.4241\n",
"21120/21120 [==============================] - 1s 40us/sample - loss: 1.8037 - accuracy: 0.4248\n",
"5980/5980 [==============================] - 0s 46us/sample - loss: 2.1255 - accuracy: 0.3017s - loss: 2.1310 - accuracy: \n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 2.1280 - accuracy: 0.2831\n",
"14070/14070 [==============================] - 1s 54us/sample - loss: 1.8075 - accuracy: 0.4427\n",
"11565/11565 [==============================] - 1s 58us/sample - loss: 2.1359 - accuracy: 0.3403\n",
"7000/7000 [==============================] - 0s 58us/sample - loss: 2.2768 - accuracy: 0.3023\n",
"start index for training is 610000\n",
"Train on 19250 samples, validate on 19255 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19250/19250 [==============================] - 1s 45us/sample - loss: 1.7655 - accuracy: 0.4575\n",
"19255/19255 [==============================] - 1s 42us/sample - loss: 1.7954 - accuracy: 0.4434\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1222 - accuracy: 0.2965\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1184 - accuracy: 0.2898\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7838 - accuracy: 0.4534\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1126 - accuracy: 0.3696\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2519 - accuracy: 0.3400\n",
"start index for training is 611000\n",
"Train on 15170 samples, validate on 15175 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15170/15170 [==============================] - 1s 43us/sample - loss: 1.7627 - accuracy: 0.4579\n",
"15175/15175 [==============================] - 1s 41us/sample - loss: 1.8016 - accuracy: 0.4515\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1328 - accuracy: 0.3005\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.0992 - accuracy: 0.2964\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8025 - accuracy: 0.4563\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.1060 - accuracy: 0.3722\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2332 - accuracy: 0.3443\n",
"start index for training is 612000\n",
"Train on 10830 samples, validate on 10830 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10830/10830 [==============================] - 0s 44us/sample - loss: 2.0891 - accuracy: 0.3380\n",
"10830/10830 [==============================] - 0s 44us/sample - loss: 2.0897 - accuracy: 0.3333\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0979 - accuracy: 0.3002\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0992 - accuracy: 0.2743\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.7959 - accuracy: 0.4483\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.0914 - accuracy: 0.3464\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2198 - accuracy: 0.3069\n",
"start index for training is 613000\n",
"Train on 19160 samples, validate on 19160 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19160/19160 [==============================] - 1s 42us/sample - loss: 1.8153 - accuracy: 0.4316\n",
"19160/19160 [==============================] - 1s 40us/sample - loss: 1.8244 - accuracy: 0.4269\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1371 - accuracy: 0.2918\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1356 - accuracy: 0.2761\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8126 - accuracy: 0.4357\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1315 - accuracy: 0.3415\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.2685 - accuracy: 0.3049\n",
"start index for training is 614000\n",
"Train on 18530 samples, validate on 18530 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18530/18530 [==============================] - 1s 41us/sample - loss: 1.7914 - accuracy: 0.4510\n",
"18530/18530 [==============================] - 1s 37us/sample - loss: 1.8024 - accuracy: 0.4442\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1257 - accuracy: 0.3052\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0992 - accuracy: 0.2913\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 1.7968 - accuracy: 0.4536\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.0744 - accuracy: 0.3771\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.2097 - accuracy: 0.3457\n",
"start index for training is 615000\n",
"Train on 13280 samples, validate on 13285 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13280/13280 [==============================] - 1s 40us/sample - loss: 1.7948 - accuracy: 0.4537\n",
"13285/13285 [==============================] - 1s 38us/sample - loss: 1.8193 - accuracy: 0.4487\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1471 - accuracy: 0.2998\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0938 - accuracy: 0.2929\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.8226 - accuracy: 0.4434\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.0663 - accuracy: 0.3780\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.1894 - accuracy: 0.3407\n",
"start index for training is 616000\n",
"Train on 13490 samples, validate on 13495 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13490/13490 [==============================] - 1s 43us/sample - loss: 2.0126 - accuracy: 0.3646\n",
"13495/13495 [==============================] - 1s 39us/sample - loss: 2.0230 - accuracy: 0.3599\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0960 - accuracy: 0.2913\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0969 - accuracy: 0.2840\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.7996 - accuracy: 0.4411\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.0719 - accuracy: 0.3486\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2094 - accuracy: 0.3050\n",
"start index for training is 617000\n",
"Train on 19680 samples, validate on 19680 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19680/19680 [==============================] - 1s 40us/sample - loss: 1.7834 - accuracy: 0.4565\n",
"19680/19680 [==============================] - 1s 36us/sample - loss: 1.7956 - accuracy: 0.4482\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1277 - accuracy: 0.3002\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0788 - accuracy: 0.2958\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8052 - accuracy: 0.4505\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.0444 - accuracy: 0.3874\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.1777 - accuracy: 0.3559\n",
"start index for training is 618000\n",
"Train on 14825 samples, validate on 14825 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14825/14825 [==============================] - 1s 41us/sample - loss: 1.7721 - accuracy: 0.4647\n",
"14825/14825 [==============================] - 1s 38us/sample - loss: 1.7969 - accuracy: 0.4543\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1304 - accuracy: 0.3124\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0801 - accuracy: 0.2898\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8238 - accuracy: 0.4404\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.0422 - accuracy: 0.3803\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.1713 - accuracy: 0.3490\n",
"start index for training is 619000\n",
"Train on 12145 samples, validate on 12150 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12145/12145 [==============================] - 1s 41us/sample - loss: 2.0731 - accuracy: 0.3509\n",
"12150/12150 [==============================] - 0s 37us/sample - loss: 2.0745 - accuracy: 0.3449\n",
"5980/5980 [==============================] - 0s 35us/sample - loss: 2.0957 - accuracy: 0.3201\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0648 - accuracy: 0.2972\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8087 - accuracy: 0.4503\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.0225 - accuracy: 0.3847\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.1464 - accuracy: 0.3503\n",
"start index for training is 620000\n",
"Train on 20175 samples, validate on 20175 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20175/20175 [==============================] - 1s 41us/sample - loss: 1.7760 - accuracy: 0.4542\n",
"20175/20175 [==============================] - 1s 38us/sample - loss: 1.8026 - accuracy: 0.4487\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1160 - accuracy: 0.3151\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0727 - accuracy: 0.3032\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.8185 - accuracy: 0.4468\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.0305 - accuracy: 0.3862\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1674 - accuracy: 0.3471\n",
"start index for training is 621000\n",
"Train on 14500 samples, validate on 14505 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14500/14500 [==============================] - 1s 43us/sample - loss: 1.7731 - accuracy: 0.4670\n",
"14505/14505 [==============================] - 1s 39us/sample - loss: 1.7808 - accuracy: 0.4577\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1365 - accuracy: 0.3072\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0796 - accuracy: 0.3047\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.8568 - accuracy: 0.4301\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.0320 - accuracy: 0.3846\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1609 - accuracy: 0.3649\n",
"start index for training is 622000\n",
"Train on 13630 samples, validate on 13635 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13630/13630 [==============================] - 1s 44us/sample - loss: 2.0327 - accuracy: 0.3597\n",
"13635/13635 [==============================] - 1s 40us/sample - loss: 2.0331 - accuracy: 0.3569\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0885 - accuracy: 0.3194\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0722 - accuracy: 0.3009\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8056 - accuracy: 0.4500\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.0227 - accuracy: 0.3881\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.1590 - accuracy: 0.3491\n",
"start index for training is 623000\n",
"Train on 20430 samples, validate on 20430 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20430/20430 [==============================] - 1s 47us/sample - loss: 1.7704 - accuracy: 0.4583\n",
"20430/20430 [==============================] - 1s 44us/sample - loss: 1.7708 - accuracy: 0.4616\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1097 - accuracy: 0.3219\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.0709 - accuracy: 0.3032\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.8161 - accuracy: 0.4515\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.0076 - accuracy: 0.3933\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.1459 - accuracy: 0.3634\n",
"start index for training is 624000\n",
"Train on 7540 samples, validate on 7540 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7540/7540 [==============================] - 0s 44us/sample - loss: 2.2694 - accuracy: 0.2996\n",
"7540/7540 [==============================] - 0s 41us/sample - loss: 2.2854 - accuracy: 0.2960\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1010 - accuracy: 0.3162\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0628 - accuracy: 0.2953\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.8264 - accuracy: 0.4458\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.9992 - accuracy: 0.3901\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.1254 - accuracy: 0.3570\n",
"start index for training is 625000\n",
"Train on 22595 samples, validate on 22600 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"22595/22595 [==============================] - 1s 46us/sample - loss: 1.7927 - accuracy: 0.4477\n",
"22600/22600 [==============================] - 1s 38us/sample - loss: 1.7834 - accuracy: 0.4512\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1006 - accuracy: 0.3084\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0612 - accuracy: 0.3051\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8156 - accuracy: 0.4492\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.9975 - accuracy: 0.3955\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.1352 - accuracy: 0.3617\n",
"start index for training is 626000\n",
"Train on 9090 samples, validate on 9095 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9090/9090 [==============================] - 0s 44us/sample - loss: 1.9455 - accuracy: 0.4399\n",
"9095/9095 [==============================] - 0s 40us/sample - loss: 1.9517 - accuracy: 0.4321\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1476 - accuracy: 0.3164\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0866 - accuracy: 0.3017\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8570 - accuracy: 0.4273\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.0275 - accuracy: 0.3859\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1501 - accuracy: 0.3550\n",
"start index for training is 627000\n",
"Train on 20020 samples, validate on 20020 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20020/20020 [==============================] - 1s 47us/sample - loss: 1.8957 - accuracy: 0.4012\n",
"20020/20020 [==============================] - 1s 41us/sample - loss: 1.9039 - accuracy: 0.3978\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1076 - accuracy: 0.3189\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0557 - accuracy: 0.3118\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8441 - accuracy: 0.4205\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.9902 - accuracy: 0.3949\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.1161 - accuracy: 0.3700\n",
"start index for training is 628000\n",
"Train on 16850 samples, validate on 16855 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16850/16850 [==============================] - 1s 43us/sample - loss: 1.7291 - accuracy: 0.4784\n",
"16855/16855 [==============================] - 1s 41us/sample - loss: 1.7548 - accuracy: 0.4685\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1183 - accuracy: 0.3130\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0623 - accuracy: 0.2949\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8434 - accuracy: 0.4321\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.9861 - accuracy: 0.3985\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.1191 - accuracy: 0.3710\n",
"start index for training is 629000\n",
"Train on 12255 samples, validate on 12255 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.1111 - accuracy: 0.3395\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1135 - accuracy: 0.3360\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0935 - accuracy: 0.3161\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0561 - accuracy: 0.3018\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8270 - accuracy: 0.4453\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.9825 - accuracy: 0.3971\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1153 - accuracy: 0.3621\n",
"start index for training is 630000\n",
"Train on 19565 samples, validate on 19570 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19565/19565 [==============================] - 1s 42us/sample - loss: 1.7411 - accuracy: 0.4757\n",
"19570/19570 [==============================] - 1s 38us/sample - loss: 1.7427 - accuracy: 0.4700\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1240 - accuracy: 0.3105\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0640 - accuracy: 0.2978\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8299 - accuracy: 0.4442\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.9742 - accuracy: 0.4019\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1096 - accuracy: 0.3711\n",
"start index for training is 631000\n",
"Train on 9515 samples, validate on 9515 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9515/9515 [==============================] - 0s 44us/sample - loss: 2.1884 - accuracy: 0.3160\n",
"9515/9515 [==============================] - 0s 40us/sample - loss: 2.2181 - accuracy: 0.3048\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.0974 - accuracy: 0.3099\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0658 - accuracy: 0.2972\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8197 - accuracy: 0.4568\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.9823 - accuracy: 0.3937\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1129 - accuracy: 0.3546\n",
"start index for training is 632000\n",
"Train on 21565 samples, validate on 21565 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21565/21565 [==============================] - 1s 41us/sample - loss: 1.7452 - accuracy: 0.4699\n",
"21565/21565 [==============================] - 1s 39us/sample - loss: 1.7534 - accuracy: 0.4673\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.1260 - accuracy: 0.2973\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0667 - accuracy: 0.3002\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8205 - accuracy: 0.4513\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.9719 - accuracy: 0.4055\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1082 - accuracy: 0.3624\n",
"start index for training is 633000\n",
"Train on 8330 samples, validate on 8330 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8330/8330 [==============================] - 0s 43us/sample - loss: 2.2319 - accuracy: 0.3007\n",
"8330/8330 [==============================] - 0s 40us/sample - loss: 2.2103 - accuracy: 0.3049\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1264 - accuracy: 0.3020\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.0625 - accuracy: 0.2919\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.8342 - accuracy: 0.4460\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.9593 - accuracy: 0.4039\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.0800 - accuracy: 0.3670\n",
"start index for training is 634000\n",
"Train on 22225 samples, validate on 22230 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"22225/22225 [==============================] - 1s 41us/sample - loss: 1.7456 - accuracy: 0.4647\n",
"22230/22230 [==============================] - 1s 37us/sample - loss: 1.7660 - accuracy: 0.4587\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1247 - accuracy: 0.3047\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 2.0587 - accuracy: 0.2937\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 1.8259 - accuracy: 0.4436\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.9499 - accuracy: 0.4084\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.0871 - accuracy: 0.3741\n",
"start index for training is 635000\n",
"Train on 8230 samples, validate on 8235 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8230/8230 [==============================] - 0s 55us/sample - loss: 2.2243 - accuracy: 0.3108\n",
"8235/8235 [==============================] - 0s 44us/sample - loss: 2.2437 - accuracy: 0.3050\n",
"5980/5980 [==============================] - 0s 51us/sample - loss: 2.1099 - accuracy: 0.3125\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 2.0618 - accuracy: 0.3006\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.8370 - accuracy: 0.4448\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.9572 - accuracy: 0.4026\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.0792 - accuracy: 0.3650\n",
"start index for training is 636000\n",
"Train on 22090 samples, validate on 22095 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"22090/22090 [==============================] - 1s 42us/sample - loss: 1.7393 - accuracy: 0.4710\n",
"22095/22095 [==============================] - 1s 39us/sample - loss: 1.7576 - accuracy: 0.4613\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1339 - accuracy: 0.3040\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0515 - accuracy: 0.2991\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8352 - accuracy: 0.4320\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 1.9469 - accuracy: 0.4136\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.0822 - accuracy: 0.3811\n",
"start index for training is 637000\n",
"Train on 9190 samples, validate on 9190 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9190/9190 [==============================] - 0s 45us/sample - loss: 2.2148 - accuracy: 0.2984\n",
"9190/9190 [==============================] - 0s 46us/sample - loss: 2.1906 - accuracy: 0.2997\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1232 - accuracy: 0.3258\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.0792 - accuracy: 0.3062\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.8544 - accuracy: 0.4230\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.9505 - accuracy: 0.3878\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.0764 - accuracy: 0.3454\n",
"start index for training is 638000\n",
"Train on 20925 samples, validate on 20925 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20925/20925 [==============================] - 1s 43us/sample - loss: 1.7281 - accuracy: 0.4818\n",
"20925/20925 [==============================] - 1s 47us/sample - loss: 1.7249 - accuracy: 0.4756\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.1302 - accuracy: 0.3104\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.0571 - accuracy: 0.2992\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 1.8382 - accuracy: 0.4396\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 1.9375 - accuracy: 0.4193\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.0755 - accuracy: 0.3849\n",
"start index for training is 639000\n",
"Train on 11205 samples, validate on 11205 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11205/11205 [==============================] - 0s 44us/sample - loss: 2.1537 - accuracy: 0.3193\n",
"11205/11205 [==============================] - 0s 42us/sample - loss: 2.1545 - accuracy: 0.3188\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1110 - accuracy: 0.2963\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.0744 - accuracy: 0.2895\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.8365 - accuracy: 0.4426\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.9458 - accuracy: 0.4078\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.0770 - accuracy: 0.3684\n",
"start index for training is 640000\n",
"Train on 13420 samples, validate on 13425 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13420/13420 [==============================] - 1s 45us/sample - loss: 1.7220 - accuracy: 0.4844\n",
"13425/13425 [==============================] - 1s 41us/sample - loss: 1.7513 - accuracy: 0.4759\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1621 - accuracy: 0.2997\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0689 - accuracy: 0.3026\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.8887 - accuracy: 0.4233\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 1.9405 - accuracy: 0.4073\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.0678 - accuracy: 0.3793\n",
"start index for training is 641000\n",
"Train on 19290 samples, validate on 19295 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19290/19290 [==============================] - 1s 42us/sample - loss: 1.9573 - accuracy: 0.3858\n",
"19295/19295 [==============================] - 1s 38us/sample - loss: 1.9713 - accuracy: 0.3763\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1192 - accuracy: 0.3232\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0693 - accuracy: 0.3080\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8321 - accuracy: 0.4364\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 1.9465 - accuracy: 0.3995\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0816 - accuracy: 0.3569\n",
"start index for training is 642000\n",
"Train on 6025 samples, validate on 6030 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6025/6025 [==============================] - 0s 45us/sample - loss: 2.3538 - accuracy: 0.2898\n",
"6030/6030 [==============================] - 0s 45us/sample - loss: 2.3586 - accuracy: 0.2847\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1439 - accuracy: 0.3301\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 2.0702 - accuracy: 0.3234\n",
"14070/14070 [==============================] - 1s 75us/sample - loss: 1.8938 - accuracy: 0.4055\n",
"11565/11565 [==============================] - 1s 65us/sample - loss: 1.9473 - accuracy: 0.3967\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.0674 - accuracy: 0.3634\n",
"start index for training is 643000\n",
"Train on 26755 samples, validate on 26755 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"26755/26755 [==============================] - 2s 59us/sample - loss: 1.7646 - accuracy: 0.4570\n",
"26755/26755 [==============================] - 1s 50us/sample - loss: 1.7731 - accuracy: 0.4598\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 2.1247 - accuracy: 0.3007\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0647 - accuracy: 0.2943\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.8313 - accuracy: 0.4504\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 1.9173 - accuracy: 0.4221\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.0549 - accuracy: 0.3807\n",
"start index for training is 644000\n",
"Train on 8365 samples, validate on 8370 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8365/8365 [==============================] - 0s 57us/sample - loss: 2.2287 - accuracy: 0.3074\n",
"8370/8370 [==============================] - 0s 59us/sample - loss: 2.2887 - accuracy: 0.2951\n",
"5980/5980 [==============================] - 0s 59us/sample - loss: 2.1155 - accuracy: 0.2985\n",
"12255/12255 [==============================] - 1s 59us/sample - loss: 2.0463 - accuracy: 0.3074\n",
"14070/14070 [==============================] - 1s 52us/sample - loss: 1.8504 - accuracy: 0.4430\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 1.9199 - accuracy: 0.4142\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.0386 - accuracy: 0.3787\n",
"start index for training is 645000\n",
"Train on 17620 samples, validate on 17625 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17620/17620 [==============================] - 1s 50us/sample - loss: 1.7075 - accuracy: 0.4964\n",
"17625/17625 [==============================] - 1s 41us/sample - loss: 1.7298 - accuracy: 0.4871\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1575 - accuracy: 0.2933\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0664 - accuracy: 0.2893\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.8757 - accuracy: 0.4301\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 1.9196 - accuracy: 0.4186\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.0515 - accuracy: 0.3830\n",
"start index for training is 646000\n",
"Train on 16460 samples, validate on 16460 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16460/16460 [==============================] - 1s 45us/sample - loss: 2.0295 - accuracy: 0.3551\n",
"16460/16460 [==============================] - 1s 40us/sample - loss: 2.0480 - accuracy: 0.3481\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1164 - accuracy: 0.3007\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0675 - accuracy: 0.2792\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8356 - accuracy: 0.4276\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.9209 - accuracy: 0.4000\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0535 - accuracy: 0.3533\n",
"start index for training is 647000\n",
"Train on 6035 samples, validate on 6040 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6035/6035 [==============================] - 0s 52us/sample - loss: 2.3790 - accuracy: 0.2833\n",
"6040/6040 [==============================] - 0s 44us/sample - loss: 2.4162 - accuracy: 0.2700\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.1478 - accuracy: 0.3117\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 2.0995 - accuracy: 0.2836\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.9029 - accuracy: 0.4006\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 1.9699 - accuracy: 0.3863\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.0881 - accuracy: 0.3419\n",
"start index for training is 648000\n",
"Train on 26500 samples, validate on 26500 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"26500/26500 [==============================] - 1s 41us/sample - loss: 1.7739 - accuracy: 0.4636\n",
"26500/26500 [==============================] - 1s 40us/sample - loss: 1.7822 - accuracy: 0.4618\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1368 - accuracy: 0.2962\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0663 - accuracy: 0.3007\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.8464 - accuracy: 0.4402\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.9003 - accuracy: 0.4314\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0370 - accuracy: 0.3920\n",
"start index for training is 649000\n",
"Train on 8630 samples, validate on 8635 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8630/8630 [==============================] - 0s 54us/sample - loss: 2.2627 - accuracy: 0.2949\n",
"8635/8635 [==============================] - 0s 47us/sample - loss: 2.2447 - accuracy: 0.2997\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1277 - accuracy: 0.3070\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0545 - accuracy: 0.3083\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.8641 - accuracy: 0.4296\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.9055 - accuracy: 0.4127\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0221 - accuracy: 0.3749\n",
"start index for training is 650000\n",
"Train on 13380 samples, validate on 13385 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13380/13380 [==============================] - 1s 58us/sample - loss: 1.7275 - accuracy: 0.4931\n",
"13385/13385 [==============================] - 1s 45us/sample - loss: 1.7613 - accuracy: 0.4826\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1641 - accuracy: 0.2940\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0812 - accuracy: 0.2907\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8858 - accuracy: 0.4313\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.9152 - accuracy: 0.4202\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.0469 - accuracy: 0.3763\n",
"start index for training is 651000\n",
"Train on 20070 samples, validate on 20075 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"20070/20070 [==============================] - 1s 49us/sample - loss: 1.9742 - accuracy: 0.3851\n",
"20075/20075 [==============================] - 1s 48us/sample - loss: 1.9779 - accuracy: 0.3830\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1413 - accuracy: 0.2972\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0639 - accuracy: 0.2992\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8664 - accuracy: 0.4206\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.8929 - accuracy: 0.4308\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.0192 - accuracy: 0.3923\n",
"start index for training is 652000\n",
"Train on 6220 samples, validate on 6225 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6220/6220 [==============================] - 0s 46us/sample - loss: 2.3499 - accuracy: 0.2810\n",
"6225/6225 [==============================] - 0s 43us/sample - loss: 2.3578 - accuracy: 0.2855\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1502 - accuracy: 0.2893\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0546 - accuracy: 0.2982\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8986 - accuracy: 0.4124\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.9058 - accuracy: 0.4220\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.0251 - accuracy: 0.3861\n",
"start index for training is 653000\n",
"Train on 24700 samples, validate on 24705 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"24700/24700 [==============================] - 1s 43us/sample - loss: 1.7698 - accuracy: 0.4644\n",
"24705/24705 [==============================] - 1s 41us/sample - loss: 1.7910 - accuracy: 0.4650\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1556 - accuracy: 0.2973\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0641 - accuracy: 0.3033\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.8564 - accuracy: 0.4436\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.8808 - accuracy: 0.4316\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.0094 - accuracy: 0.3920\n",
"start index for training is 654000\n",
"Train on 9525 samples, validate on 9525 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9525/9525 [==============================] - 0s 43us/sample - loss: 2.2134 - accuracy: 0.3103s - loss: 2.2148 - accuracy: 0.\n",
"9525/9525 [==============================] - 0s 45us/sample - loss: 2.2192 - accuracy: 0.3130\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1452 - accuracy: 0.3020\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0633 - accuracy: 0.2800\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8655 - accuracy: 0.4346\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8881 - accuracy: 0.4051\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.0052 - accuracy: 0.3571\n",
"start index for training is 655000\n",
"Train on 5075 samples, validate on 5080 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5075/5075 [==============================] - 0s 45us/sample - loss: 2.3996 - accuracy: 0.2753\n",
"5080/5080 [==============================] - 0s 41us/sample - loss: 2.4193 - accuracy: 0.2756\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1683 - accuracy: 0.3135\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0570 - accuracy: 0.3083\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9542 - accuracy: 0.3859\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.9096 - accuracy: 0.4065\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.0116 - accuracy: 0.3710\n",
"start index for training is 656000\n",
"Train on 27400 samples, validate on 27405 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"27400/27400 [==============================] - 1s 43us/sample - loss: 1.7928 - accuracy: 0.4473\n",
"27405/27405 [==============================] - 1s 40us/sample - loss: 1.7974 - accuracy: 0.4465\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1608 - accuracy: 0.2930\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0595 - accuracy: 0.3024\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8638 - accuracy: 0.4311\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.8633 - accuracy: 0.4350\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 1.9855 - accuracy: 0.4000\n",
"start index for training is 657000\n",
"Train on 6570 samples, validate on 6570 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6570/6570 [==============================] - 0s 50us/sample - loss: 2.3293 - accuracy: 0.2921\n",
"6570/6570 [==============================] - 0s 50us/sample - loss: 2.3539 - accuracy: 0.2842\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1508 - accuracy: 0.3042\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0539 - accuracy: 0.2981\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.8884 - accuracy: 0.4452\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8794 - accuracy: 0.4208\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9903 - accuracy: 0.3853\n",
"start index for training is 658000\n",
"Train on 23515 samples, validate on 23520 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"23515/23515 [==============================] - 1s 43us/sample - loss: 1.7624 - accuracy: 0.4653\n",
"23520/23520 [==============================] - 1s 39us/sample - loss: 1.7808 - accuracy: 0.4673\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1666 - accuracy: 0.2950\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0738 - accuracy: 0.2987\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.8736 - accuracy: 0.4256\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 1.8593 - accuracy: 0.4419\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9857 - accuracy: 0.4091\n",
"start index for training is 659000\n",
"Train on 9975 samples, validate on 9980 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9975/9975 [==============================] - 1s 53us/sample - loss: 2.2077 - accuracy: 0.3120\n",
"9980/9980 [==============================] - 0s 43us/sample - loss: 2.2288 - accuracy: 0.3081\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 2.1544 - accuracy: 0.2925\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0684 - accuracy: 0.2995\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.8697 - accuracy: 0.4487\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8674 - accuracy: 0.4295\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.9848 - accuracy: 0.3919\n",
"start index for training is 660000\n",
"Train on 5085 samples, validate on 5085 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5085/5085 [==============================] - 0s 44us/sample - loss: 2.3896 - accuracy: 0.2869\n",
"5085/5085 [==============================] - 0s 49us/sample - loss: 2.4161 - accuracy: 0.2796\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1783 - accuracy: 0.2938\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0698 - accuracy: 0.3182\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9214 - accuracy: 0.4144\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.9059 - accuracy: 0.4069\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.0227 - accuracy: 0.3769\n",
"start index for training is 661000\n",
"Train on 26945 samples, validate on 26950 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"26945/26945 [==============================] - 1s 41us/sample - loss: 1.8036 - accuracy: 0.4501\n",
"26950/26950 [==============================] - 1s 39us/sample - loss: 1.7907 - accuracy: 0.4519\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.1623 - accuracy: 0.2972\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0755 - accuracy: 0.3007\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8649 - accuracy: 0.4360\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.8498 - accuracy: 0.4436\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9743 - accuracy: 0.4016\n",
"start index for training is 662000\n",
"Train on 6365 samples, validate on 6370 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6365/6365 [==============================] - 0s 45us/sample - loss: 2.3528 - accuracy: 0.2775\n",
"6370/6370 [==============================] - 0s 41us/sample - loss: 2.3642 - accuracy: 0.2830\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1604 - accuracy: 0.3032\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0749 - accuracy: 0.2932\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8989 - accuracy: 0.4321\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.8652 - accuracy: 0.4273\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.9779 - accuracy: 0.3913\n",
"start index for training is 663000\n",
"Train on 23905 samples, validate on 23910 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"23905/23905 [==============================] - 1s 41us/sample - loss: 1.7747 - accuracy: 0.4652\n",
"23910/23910 [==============================] - 1s 37us/sample - loss: 1.7964 - accuracy: 0.4568\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.1754 - accuracy: 0.2811\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0745 - accuracy: 0.3000\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8809 - accuracy: 0.4230\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.8370 - accuracy: 0.4432\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 1.9546 - accuracy: 0.4104\n",
"start index for training is 664000\n",
"Train on 9290 samples, validate on 9290 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9290/9290 [==============================] - 0s 43us/sample - loss: 2.2170 - accuracy: 0.3145\n",
"9290/9290 [==============================] - 0s 40us/sample - loss: 2.2227 - accuracy: 0.3072\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1677 - accuracy: 0.2851\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0710 - accuracy: 0.2916\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8905 - accuracy: 0.4276\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.8665 - accuracy: 0.4294\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.9783 - accuracy: 0.3919\n",
"start index for training is 665000\n",
"Train on 13840 samples, validate on 13840 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13840/13840 [==============================] - 1s 42us/sample - loss: 1.7285 - accuracy: 0.4923\n",
"13840/13840 [==============================] - 1s 39us/sample - loss: 1.7685 - accuracy: 0.4819\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2077 - accuracy: 0.2873\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0961 - accuracy: 0.2996\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.9143 - accuracy: 0.4097\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.8569 - accuracy: 0.4311\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.9695 - accuracy: 0.4036\n",
"start index for training is 666000\n",
"Train on 18225 samples, validate on 18230 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"18225/18225 [==============================] - 1s 41us/sample - loss: 2.0063 - accuracy: 0.3760\n",
"18230/18230 [==============================] - 1s 38us/sample - loss: 2.0023 - accuracy: 0.3777\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 2.1637 - accuracy: 0.2935\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0809 - accuracy: 0.3002\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.8771 - accuracy: 0.4264\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.8375 - accuracy: 0.4500\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9514 - accuracy: 0.4119\n",
"start index for training is 667000\n",
"Train on 6095 samples, validate on 6100 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6095/6095 [==============================] - 0s 46us/sample - loss: 2.3768 - accuracy: 0.2817\n",
"6100/6100 [==============================] - 0s 42us/sample - loss: 2.3699 - accuracy: 0.2839\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 2.1761 - accuracy: 0.3132\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.0823 - accuracy: 0.3144\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.9269 - accuracy: 0.4021\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8713 - accuracy: 0.4154\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.9748 - accuracy: 0.3791\n",
"start index for training is 668000\n",
"Train on 25165 samples, validate on 25165 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"25165/25165 [==============================] - 1s 41us/sample - loss: 1.7928 - accuracy: 0.4535\n",
"25165/25165 [==============================] - 1s 41us/sample - loss: 1.8019 - accuracy: 0.4535\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 2.1959 - accuracy: 0.2915\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0926 - accuracy: 0.2869\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.8924 - accuracy: 0.4128\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.8187 - accuracy: 0.4467\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9291 - accuracy: 0.4207\n",
"start index for training is 669000\n",
"Train on 8570 samples, validate on 8575 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8570/8570 [==============================] - 0s 43us/sample - loss: 2.2595 - accuracy: 0.2998\n",
"8575/8575 [==============================] - 0s 43us/sample - loss: 2.2945 - accuracy: 0.2977\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1616 - accuracy: 0.3074\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0804 - accuracy: 0.3142\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8999 - accuracy: 0.4070\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8443 - accuracy: 0.4295\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.9442 - accuracy: 0.3954\n",
"start index for training is 670000\n",
"Train on 14895 samples, validate on 14900 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14895/14895 [==============================] - 1s 45us/sample - loss: 1.7459 - accuracy: 0.4785\n",
"14900/14900 [==============================] - 1s 41us/sample - loss: 1.7718 - accuracy: 0.4713\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2195 - accuracy: 0.3003\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0949 - accuracy: 0.2950\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.9296 - accuracy: 0.4136\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 1.8290 - accuracy: 0.4408\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.9300 - accuracy: 0.4150\n",
"start index for training is 671000\n",
"Train on 17770 samples, validate on 17770 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17770/17770 [==============================] - 1s 44us/sample - loss: 2.0209 - accuracy: 0.3783\n",
"17770/17770 [==============================] - 1s 42us/sample - loss: 2.0442 - accuracy: 0.3701\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1756 - accuracy: 0.3013\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0927 - accuracy: 0.2915\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8828 - accuracy: 0.4252\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8304 - accuracy: 0.4508\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9326 - accuracy: 0.4129\n",
"start index for training is 672000\n",
"Train on 6130 samples, validate on 6130 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6130/6130 [==============================] - 0s 45us/sample - loss: 2.3568 - accuracy: 0.2899\n",
"6130/6130 [==============================] - 0s 41us/sample - loss: 2.3904 - accuracy: 0.2894\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.1752 - accuracy: 0.3062\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0864 - accuracy: 0.3059\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.9358 - accuracy: 0.4053\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8567 - accuracy: 0.4361\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 1.9486 - accuracy: 0.4143\n",
"start index for training is 673000\n",
"Train on 24525 samples, validate on 24525 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"24525/24525 [==============================] - 1s 44us/sample - loss: 1.7873 - accuracy: 0.4586\n",
"24525/24525 [==============================] - 1s 41us/sample - loss: 1.8076 - accuracy: 0.4529\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.1956 - accuracy: 0.2903\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.0942 - accuracy: 0.2936\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8916 - accuracy: 0.4248\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.8064 - accuracy: 0.4531\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 1.9113 - accuracy: 0.4186\n",
"start index for training is 674000\n",
"Train on 9455 samples, validate on 9455 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9455/9455 [==============================] - 0s 47us/sample - loss: 2.2415 - accuracy: 0.3105\n",
"9455/9455 [==============================] - 0s 43us/sample - loss: 2.2539 - accuracy: 0.3057\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1921 - accuracy: 0.3023\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.0921 - accuracy: 0.3063\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.9090 - accuracy: 0.4131\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 1.8313 - accuracy: 0.4327\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 1.9265 - accuracy: 0.3987\n",
"start index for training is 675000\n",
"Train on 8890 samples, validate on 8895 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8890/8890 [==============================] - 0s 44us/sample - loss: 1.8886 - accuracy: 0.4450\n",
"8895/8895 [==============================] - 0s 43us/sample - loss: 1.9249 - accuracy: 0.4333\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.2437 - accuracy: 0.2674\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0943 - accuracy: 0.3124\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.9694 - accuracy: 0.3959\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 1.8422 - accuracy: 0.4236\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.9282 - accuracy: 0.4041\n",
"start index for training is 676000\n",
"Train on 23915 samples, validate on 23920 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"23915/23915 [==============================] - 1s 52us/sample - loss: 1.9032 - accuracy: 0.4148\n",
"23920/23920 [==============================] - 1s 44us/sample - loss: 1.9141 - accuracy: 0.4115\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.1809 - accuracy: 0.3025\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.0881 - accuracy: 0.3003\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.8877 - accuracy: 0.4353\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 1.8035 - accuracy: 0.4581\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 1.9036 - accuracy: 0.4279\n",
"start index for training is 677000\n",
"Train on 6775 samples, validate on 6780 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6775/6775 [==============================] - 0s 49us/sample - loss: 2.2983 - accuracy: 0.2995\n",
"6780/6780 [==============================] - 0s 46us/sample - loss: 2.3651 - accuracy: 0.2824\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 2.1842 - accuracy: 0.3253\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.0843 - accuracy: 0.3093\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 1.9223 - accuracy: 0.4031\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 1.8280 - accuracy: 0.4372\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 1.9204 - accuracy: 0.4061\n",
"start index for training is 678000\n",
"Train on 22710 samples, validate on 22710 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"22710/22710 [==============================] - 1s 50us/sample - loss: 1.7854 - accuracy: 0.4620\n",
"22710/22710 [==============================] - 1s 45us/sample - loss: 1.7868 - accuracy: 0.4635\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.2112 - accuracy: 0.2905\n",
"12255/12255 [==============================] - 1s 50us/sample - loss: 2.0983 - accuracy: 0.2983\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.9167 - accuracy: 0.4154\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 1.7875 - accuracy: 0.4623\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 1.8805 - accuracy: 0.4361\n",
"start index for training is 679000\n",
"Train on 11480 samples, validate on 11480 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11480/11480 [==============================] - 1s 52us/sample - loss: 2.1688 - accuracy: 0.3320\n",
"11480/11480 [==============================] - 1s 49us/sample - loss: 2.1939 - accuracy: 0.3279\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 2.2073 - accuracy: 0.2801\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.1056 - accuracy: 0.2944\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.9080 - accuracy: 0.4176\n",
"11565/11565 [==============================] - 1s 52us/sample - loss: 1.8092 - accuracy: 0.4453\n",
"7000/7000 [==============================] - 0s 54us/sample - loss: 1.8981 - accuracy: 0.4177\n",
"start index for training is 680000\n",
"Train on 5740 samples, validate on 5740 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 9/10\n",
"Epoch 10/10\n",
"5740/5740 [==============================] - 0s 57us/sample - loss: 2.4153 - accuracy: 0.2765\n",
"5740/5740 [==============================] - 0s 51us/sample - loss: 2.4059 - accuracy: 0.2841\n",
"5980/5980 [==============================] - 0s 55us/sample - loss: 2.2061 - accuracy: 0.3090\n",
"12255/12255 [==============================] - 1s 54us/sample - loss: 2.1047 - accuracy: 0.3031\n",
"14070/14070 [==============================] - 1s 73us/sample - loss: 1.9355 - accuracy: 0.3922\n",
"11565/11565 [==============================] - 1s 58us/sample - loss: 1.8353 - accuracy: 0.4284\n",
"7000/7000 [==============================] - 0s 57us/sample - loss: 1.9178 - accuracy: 0.4050\n",
"start index for training is 681000\n",
"Train on 26345 samples, validate on 26345 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"26345/26345 [==============================] - 1s 54us/sample - loss: 1.8054 - accuracy: 0.4506\n",
"26345/26345 [==============================] - 1s 45us/sample - loss: 1.8224 - accuracy: 0.4417\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 2.2111 - accuracy: 0.2774\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1098 - accuracy: 0.2885\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.9034 - accuracy: 0.4173\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.7838 - accuracy: 0.4578\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 1.8735 - accuracy: 0.4286\n",
"start index for training is 682000\n",
"Train on 8910 samples, validate on 8915 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8910/8910 [==============================] - 0s 44us/sample - loss: 2.2947 - accuracy: 0.3043\n",
"8915/8915 [==============================] - 0s 40us/sample - loss: 2.2998 - accuracy: 0.3035\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2066 - accuracy: 0.3074\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1111 - accuracy: 0.3004\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.9058 - accuracy: 0.4136s - loss: 1.8793 \n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.8107 - accuracy: 0.4381\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 1.8908 - accuracy: 0.4049\n",
"start index for training is 683000\n",
"Train on 5150 samples, validate on 5155 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5150/5150 [==============================] - 0s 45us/sample - loss: 2.4272 - accuracy: 0.2837\n",
"5155/5155 [==============================] - 0s 45us/sample - loss: 2.4524 - accuracy: 0.2838\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.2175 - accuracy: 0.3147\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0967 - accuracy: 0.3265\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.9761 - accuracy: 0.3913\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 1.8490 - accuracy: 0.4259\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 1.9261 - accuracy: 0.4069\n",
"start index for training is 684000\n",
"Train on 28250 samples, validate on 28250 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"28250/28250 [==============================] - 1s 41us/sample - loss: 1.8216 - accuracy: 0.4419\n",
"28250/28250 [==============================] - 1s 38us/sample - loss: 1.8307 - accuracy: 0.4435\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2162 - accuracy: 0.2945\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1129 - accuracy: 0.2934\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9043 - accuracy: 0.4125\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.7783 - accuracy: 0.4656\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.8556 - accuracy: 0.4549\n",
"start index for training is 685000\n",
"Train on 7725 samples, validate on 7725 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7725/7725 [==============================] - 0s 61us/sample - loss: 2.3415 - accuracy: 0.2926\n",
"7725/7725 [==============================] - 0s 52us/sample - loss: 2.3376 - accuracy: 0.2902\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 2.2124 - accuracy: 0.3157\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.1025 - accuracy: 0.2933\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9316 - accuracy: 0.4141s - loss: 1.9433 - accura\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8054 - accuracy: 0.4387\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 1.8744 - accuracy: 0.4087\n",
"start index for training is 686000\n",
"Train on 12560 samples, validate on 12560 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12560/12560 [==============================] - 1s 46us/sample - loss: 1.7832 - accuracy: 0.4789\n",
"12560/12560 [==============================] - 1s 44us/sample - loss: 1.8206 - accuracy: 0.4684\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2711 - accuracy: 0.2642\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 2.1257 - accuracy: 0.3044\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.9759 - accuracy: 0.4011\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 1.8010 - accuracy: 0.4436\n",
"7000/7000 [==============================] - 0s 51us/sample - loss: 1.8645 - accuracy: 0.4384\n",
"start index for training is 687000\n",
"Train on 21485 samples, validate on 21490 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21485/21485 [==============================] - 1s 46us/sample - loss: 1.9682 - accuracy: 0.3832\n",
"21490/21490 [==============================] - 1s 41us/sample - loss: 1.9731 - accuracy: 0.3852\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.2086 - accuracy: 0.2813\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1056 - accuracy: 0.2784\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.9024 - accuracy: 0.4182\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 1.7839 - accuracy: 0.4601\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 1.8582 - accuracy: 0.4376\n",
"start index for training is 688000\n",
"Train on 7280 samples, validate on 7285 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7280/7280 [==============================] - 0s 44us/sample - loss: 2.3378 - accuracy: 0.2974\n",
"7285/7285 [==============================] - 0s 39us/sample - loss: 2.3732 - accuracy: 0.2899\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.2048 - accuracy: 0.3107\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1164 - accuracy: 0.2951\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 1.9426 - accuracy: 0.3954\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.8118 - accuracy: 0.4370\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 1.8742 - accuracy: 0.4170\n",
"start index for training is 689000\n",
"Train on 14205 samples, validate on 14210 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14205/14205 [==============================] - 1s 44us/sample - loss: 1.7719 - accuracy: 0.4744\n",
"14210/14210 [==============================] - 1s 40us/sample - loss: 1.7911 - accuracy: 0.4624\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.2547 - accuracy: 0.2918\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1209 - accuracy: 0.2925\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 0s 36us/sample - loss: 1.9612 - accuracy: 0.4102\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 1.7946 - accuracy: 0.4513\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.8504 - accuracy: 0.4410\n",
"start index for training is 690000\n",
"Train on 19755 samples, validate on 19760 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19755/19755 [==============================] - 1s 41us/sample - loss: 2.0044 - accuracy: 0.3772\n",
"19760/19760 [==============================] - 1s 47us/sample - loss: 2.0116 - accuracy: 0.3742\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 2.2046 - accuracy: 0.3107\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.1104 - accuracy: 0.3059\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.9237 - accuracy: 0.3876\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.7821 - accuracy: 0.4546\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.8470 - accuracy: 0.4407\n",
"start index for training is 691000\n",
"Train on 7225 samples, validate on 7230 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7225/7225 [==============================] - 0s 45us/sample - loss: 2.3698 - accuracy: 0.2868\n",
"7230/7230 [==============================] - 0s 43us/sample - loss: 2.3511 - accuracy: 0.2907\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.2131 - accuracy: 0.3127\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1118 - accuracy: 0.3111\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9395 - accuracy: 0.3992\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8108 - accuracy: 0.4411\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.8648 - accuracy: 0.4223\n",
"start index for training is 692000\n",
"Train on 17530 samples, validate on 17530 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"17530/17530 [==============================] - 1s 44us/sample - loss: 1.7726 - accuracy: 0.4751\n",
"17530/17530 [==============================] - 1s 46us/sample - loss: 1.8019 - accuracy: 0.4707\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 2.2437 - accuracy: 0.3027\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.1232 - accuracy: 0.2918\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.9480 - accuracy: 0.4047\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 1.7691 - accuracy: 0.4637\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 1.8195 - accuracy: 0.4637\n",
"start index for training is 693000\n",
"Train on 16480 samples, validate on 16485 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"16480/16480 [==============================] - 1s 42us/sample - loss: 2.0838 - accuracy: 0.3535\n",
"16485/16485 [==============================] - 1s 43us/sample - loss: 2.0908 - accuracy: 0.3509\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 2.2082 - accuracy: 0.3033\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.1158 - accuracy: 0.2913\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.9108 - accuracy: 0.4037\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.7831 - accuracy: 0.4525\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.8446 - accuracy: 0.4356\n",
"start index for training is 694000\n",
"Train on 6655 samples, validate on 6655 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6655/6655 [==============================] - 0s 55us/sample - loss: 2.3936 - accuracy: 0.2766\n",
"6655/6655 [==============================] - 0s 57us/sample - loss: 2.3803 - accuracy: 0.2762\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.2178 - accuracy: 0.3202\n",
"12255/12255 [==============================] - 1s 50us/sample - loss: 2.1115 - accuracy: 0.3103\n",
"14070/14070 [==============================] - 1s 51us/sample - loss: 1.9502 - accuracy: 0.3900\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 1.8182 - accuracy: 0.4329\n",
"7000/7000 [==============================] - 0s 59us/sample - loss: 1.8729 - accuracy: 0.4156\n",
"start index for training is 695000\n",
"Train on 19315 samples, validate on 19320 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"19315/19315 [==============================] - 1s 54us/sample - loss: 1.7869 - accuracy: 0.4614\n",
"19320/19320 [==============================] - 1s 48us/sample - loss: 1.8087 - accuracy: 0.4612\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.2442 - accuracy: 0.3067\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1322 - accuracy: 0.2928\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.9391 - accuracy: 0.4024\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.7622 - accuracy: 0.4682\n",
"7000/7000 [==============================] - 0s 53us/sample - loss: 1.8015 - accuracy: 0.4664\n",
"start index for training is 696000\n",
"Train on 14440 samples, validate on 14445 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14440/14440 [==============================] - 1s 48us/sample - loss: 2.1294 - accuracy: 0.3427\n",
"14445/14445 [==============================] - 1s 44us/sample - loss: 2.1534 - accuracy: 0.3376\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.2082 - accuracy: 0.3117\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1155 - accuracy: 0.3000\n",
"14070/14070 [==============================] - 1s 61us/sample - loss: 1.9348 - accuracy: 0.3906\n",
"11565/11565 [==============================] - 1s 58us/sample - loss: 1.7864 - accuracy: 0.4519\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 1.8396 - accuracy: 0.4393\n",
"start index for training is 697000\n",
"Train on 6390 samples, validate on 6390 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6390/6390 [==============================] - 0s 70us/sample - loss: 2.3520 - accuracy: 0.2911\n",
"6390/6390 [==============================] - 0s 55us/sample - loss: 2.3860 - accuracy: 0.2793\n",
"5980/5980 [==============================] - 0s 46us/sample - loss: 2.2396 - accuracy: 0.3079\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1279 - accuracy: 0.3141\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.9882 - accuracy: 0.3832\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.8248 - accuracy: 0.4321\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 1.8639 - accuracy: 0.4241\n",
"start index for training is 698000\n",
"Train on 21120 samples, validate on 21125 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"21120/21120 [==============================] - 1s 43us/sample - loss: 1.8113 - accuracy: 0.4568\n",
"21125/21125 [==============================] - 1s 39us/sample - loss: 1.8280 - accuracy: 0.4475\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.2627 - accuracy: 0.3043\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1318 - accuracy: 0.2937\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.9614 - accuracy: 0.3983\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.7615 - accuracy: 0.4691\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.7911 - accuracy: 0.4737\n",
"start index for training is 699000\n",
"Train on 12725 samples, validate on 12730 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12725/12725 [==============================] - 1s 45us/sample - loss: 2.1750 - accuracy: 0.3338\n",
"12730/12730 [==============================] - 1s 40us/sample - loss: 2.1826 - accuracy: 0.3275\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2275 - accuracy: 0.3181\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.1129 - accuracy: 0.3027\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.9406 - accuracy: 0.3900\n",
"11565/11565 [==============================] - 1s 49us/sample - loss: 1.7798 - accuracy: 0.4493\n",
"7000/7000 [==============================] - 0s 48us/sample - loss: 1.8231 - accuracy: 0.4420\n",
"start index for training is 700000\n",
"Train on 6210 samples, validate on 6210 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6210/6210 [==============================] - 0s 64us/sample - loss: 2.3758 - accuracy: 0.2739\n",
"6210/6210 [==============================] - 0s 47us/sample - loss: 2.3854 - accuracy: 0.2676\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 2.2319 - accuracy: 0.2985\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.1152 - accuracy: 0.2837\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.9486 - accuracy: 0.4146\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 1.8124 - accuracy: 0.4543\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 1.8476 - accuracy: 0.4449\n",
"start index for training is 701000\n",
"Train on 22990 samples, validate on 22995 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"22990/22990 [==============================] - 1s 45us/sample - loss: 1.8287 - accuracy: 0.4441\n",
"22995/22995 [==============================] - 1s 38us/sample - loss: 1.8504 - accuracy: 0.4407\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.2452 - accuracy: 0.3018\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1295 - accuracy: 0.2932\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.9351 - accuracy: 0.4077\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 1.7553 - accuracy: 0.4688\n",
"7000/7000 [==============================] - 0s 51us/sample - loss: 1.7816 - accuracy: 0.4719\n",
"start index for training is 702000\n",
"Train on 11340 samples, validate on 11345 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11340/11340 [==============================] - 1s 63us/sample - loss: 2.2011 - accuracy: 0.3221\n",
"11345/11345 [==============================] - 1s 45us/sample - loss: 2.2142 - accuracy: 0.3247\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 2.2285 - accuracy: 0.3299\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 2.1139 - accuracy: 0.2968\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 1.9379 - accuracy: 0.3979\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 1.7839 - accuracy: 0.4482\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 1.8200 - accuracy: 0.4421\n",
"start index for training is 703000\n",
"Train on 5920 samples, validate on 5920 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5920/5920 [==============================] - 0s 46us/sample - loss: 2.3855 - accuracy: 0.2819\n",
"5920/5920 [==============================] - 0s 42us/sample - loss: 2.4185 - accuracy: 0.2696\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 2.2290 - accuracy: 0.3142\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1269 - accuracy: 0.3032\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.9710 - accuracy: 0.3871\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.8105 - accuracy: 0.4440\n",
"7000/7000 [==============================] - 0s 52us/sample - loss: 1.8448 - accuracy: 0.4353\n",
"start index for training is 704000\n",
"Train on 24135 samples, validate on 24140 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"24135/24135 [==============================] - 1s 49us/sample - loss: 1.8462 - accuracy: 0.4376\n",
"24140/24140 [==============================] - 1s 46us/sample - loss: 1.8485 - accuracy: 0.4362\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.2755 - accuracy: 0.2624\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.1363 - accuracy: 0.2950\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.9651 - accuracy: 0.3950\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.7540 - accuracy: 0.4648\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.7681 - accuracy: 0.4747\n",
"start index for training is 705000\n",
"Train on 10340 samples, validate on 10345 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10340/10340 [==============================] - 0s 43us/sample - loss: 2.2535 - accuracy: 0.3079\n",
"10345/10345 [==============================] - 0s 38us/sample - loss: 2.2749 - accuracy: 0.3016\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.2454 - accuracy: 0.3211\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1299 - accuracy: 0.3002\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9525 - accuracy: 0.3926\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.7912 - accuracy: 0.4457\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 1.8173 - accuracy: 0.4359\n",
"start index for training is 706000\n",
"Train on 5570 samples, validate on 5575 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5570/5570 [==============================] - 0s 43us/sample - loss: 2.4138 - accuracy: 0.2788\n",
"5575/5575 [==============================] - 0s 41us/sample - loss: 2.4604 - accuracy: 0.2714\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.2669 - accuracy: 0.3276\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1383 - accuracy: 0.3113\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.9888 - accuracy: 0.3864\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.8137 - accuracy: 0.4389\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.8338 - accuracy: 0.4404\n",
"start index for training is 707000\n",
"Train on 25540 samples, validate on 25545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"25540/25540 [==============================] - 1s 41us/sample - loss: 1.8450 - accuracy: 0.4372\n",
"25545/25545 [==============================] - 1s 37us/sample - loss: 1.8771 - accuracy: 0.4337\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.2517 - accuracy: 0.3047\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1409 - accuracy: 0.2920\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.9283 - accuracy: 0.4067\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.7534 - accuracy: 0.4687\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 1.7717 - accuracy: 0.4709\n",
"start index for training is 708000\n",
"Train on 9680 samples, validate on 9680 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9680/9680 [==============================] - 0s 50us/sample - loss: 2.2694 - accuracy: 0.3044\n",
"9680/9680 [==============================] - 0s 52us/sample - loss: 2.2800 - accuracy: 0.3018\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.2503 - accuracy: 0.3258\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.1318 - accuracy: 0.2992\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.9389 - accuracy: 0.3934\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.7854 - accuracy: 0.4386\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.8045 - accuracy: 0.4339\n",
"start index for training is 709000\n",
"Train on 5480 samples, validate on 5485 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"5480/5480 [==============================] - 0s 42us/sample - loss: 2.4200 - accuracy: 0.2843\n",
"5485/5485 [==============================] - 0s 40us/sample - loss: 2.4470 - accuracy: 0.2749\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.2546 - accuracy: 0.3278\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.1493 - accuracy: 0.3075\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.9746 - accuracy: 0.3745\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 1.8144 - accuracy: 0.4386\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 1.8351 - accuracy: 0.4396\n",
"start index for training is 710000\n",
"Train on 8175 samples, validate on 8175 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8175/8175 [==============================] - 0s 55us/sample - loss: 2.0916 - accuracy: 0.3518\n",
"8175/8175 [==============================] - 0s 48us/sample - loss: 2.1104 - accuracy: 0.3523\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.9293 - accuracy: 0.4010\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.1258 - accuracy: 0.2854\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.9747 - accuracy: 0.3707\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.9078 - accuracy: 0.3949\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 1.9351 - accuracy: 0.3759\n",
"start index for training is 711000\n",
"Train on 10345 samples, validate on 10350 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10345/10345 [==============================] - 0s 45us/sample - loss: 1.9135 - accuracy: 0.4183\n",
"10350/10350 [==============================] - 0s 44us/sample - loss: 1.9246 - accuracy: 0.4154\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.7847 - accuracy: 0.4590\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 2.1280 - accuracy: 0.2876\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0134 - accuracy: 0.3584\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.9779 - accuracy: 0.3774\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.0084 - accuracy: 0.3630\n",
"start index for training is 712000\n",
"Train on 11260 samples, validate on 11260 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11260/11260 [==============================] - 1s 52us/sample - loss: 1.8305 - accuracy: 0.4290\n",
"11260/11260 [==============================] - 1s 52us/sample - loss: 1.8454 - accuracy: 0.4287\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 1.6940 - accuracy: 0.4870\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 2.1298 - accuracy: 0.2833\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.0197 - accuracy: 0.3625\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.0066 - accuracy: 0.3467\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0380 - accuracy: 0.3247\n",
"start index for training is 713000\n",
"Train on 10135 samples, validate on 10135 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10135/10135 [==============================] - 0s 43us/sample - loss: 1.8518 - accuracy: 0.4259\n",
"10135/10135 [==============================] - 0s 39us/sample - loss: 1.8325 - accuracy: 0.4319\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.6459 - accuracy: 0.4913\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.1158 - accuracy: 0.2895\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.0508 - accuracy: 0.3438\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.0325 - accuracy: 0.3426\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.0615 - accuracy: 0.3233\n",
"start index for training is 714000\n",
"Train on 10825 samples, validate on 10830 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10825/10825 [==============================] - 0s 44us/sample - loss: 1.7250 - accuracy: 0.4624\n",
"10830/10830 [==============================] - 1s 46us/sample - loss: 1.7690 - accuracy: 0.4475\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.5925 - accuracy: 0.5259\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1255 - accuracy: 0.2951\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.0458 - accuracy: 0.3475\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.0544 - accuracy: 0.3306\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0907 - accuracy: 0.3117\n",
"start index for training is 715000\n",
"Train on 9895 samples, validate on 9895 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9895/9895 [==============================] - 0s 45us/sample - loss: 1.7336 - accuracy: 0.4589\n",
"9895/9895 [==============================] - 0s 41us/sample - loss: 1.7605 - accuracy: 0.4411\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.5700 - accuracy: 0.5368\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.1248 - accuracy: 0.2976\n",
"14070/14070 [==============================] - 1s 54us/sample - loss: 2.0624 - accuracy: 0.3327\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.0700 - accuracy: 0.3166\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.1070 - accuracy: 0.2981\n",
"start index for training is 716000\n",
"Train on 10845 samples, validate on 10845 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10845/10845 [==============================] - 1s 53us/sample - loss: 1.6845 - accuracy: 0.4810\n",
"10845/10845 [==============================] - 1s 50us/sample - loss: 1.6789 - accuracy: 0.4792\n",
"5980/5980 [==============================] - 0s 53us/sample - loss: 1.5310 - accuracy: 0.5530\n",
"12255/12255 [==============================] - 1s 61us/sample - loss: 2.1057 - accuracy: 0.3050\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.0518 - accuracy: 0.3369\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.0709 - accuracy: 0.3211\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.1079 - accuracy: 0.2947\n",
"start index for training is 717000\n",
"Train on 10805 samples, validate on 10810 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10805/10805 [==============================] - 1s 46us/sample - loss: 1.6745 - accuracy: 0.4829\n",
"10810/10810 [==============================] - 0s 44us/sample - loss: 1.6664 - accuracy: 0.4784\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5048 - accuracy: 0.5356\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0932 - accuracy: 0.3142\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.0860 - accuracy: 0.3199\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.0912 - accuracy: 0.3361\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.1313 - accuracy: 0.3319\n",
"start index for training is 718000\n",
"Train on 11010 samples, validate on 11010 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11010/11010 [==============================] - 0s 44us/sample - loss: 1.7059 - accuracy: 0.4360\n",
"11010/11010 [==============================] - 0s 44us/sample - loss: 1.7212 - accuracy: 0.4300\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5278 - accuracy: 0.5127\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1251 - accuracy: 0.3119\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2138 - accuracy: 0.2868\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1662 - accuracy: 0.3141\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2006 - accuracy: 0.3131\n",
"start index for training is 719000\n",
"Train on 10985 samples, validate on 10985 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10985/10985 [==============================] - 0s 45us/sample - loss: 1.6374 - accuracy: 0.4905\n",
"10985/10985 [==============================] - 0s 41us/sample - loss: 1.6471 - accuracy: 0.4870\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.4864 - accuracy: 0.5513\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0499 - accuracy: 0.3104\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.1161 - accuracy: 0.3221\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1062 - accuracy: 0.3286\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.1533 - accuracy: 0.3217\n",
"start index for training is 720000\n",
"Train on 11650 samples, validate on 11650 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11650/11650 [==============================] - 1s 44us/sample - loss: 1.6417 - accuracy: 0.4762\n",
"11650/11650 [==============================] - 0s 43us/sample - loss: 1.6588 - accuracy: 0.4749\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.4787 - accuracy: 0.5543\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.0262 - accuracy: 0.3237\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.1224 - accuracy: 0.3267\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1202 - accuracy: 0.3249\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.1735 - accuracy: 0.3211\n",
"start index for training is 721000\n",
"Train on 10675 samples, validate on 10675 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10675/10675 [==============================] - 0s 43us/sample - loss: 1.6649 - accuracy: 0.4636\n",
"10675/10675 [==============================] - 0s 39us/sample - loss: 1.6970 - accuracy: 0.4552\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.4932 - accuracy: 0.5286\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9962 - accuracy: 0.3279\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1332 - accuracy: 0.3258\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1165 - accuracy: 0.3201\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1663 - accuracy: 0.3153\n",
"start index for training is 722000\n",
"Train on 12770 samples, validate on 12770 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12770/12770 [==============================] - 1s 44us/sample - loss: 1.6388 - accuracy: 0.4753\n",
"12770/12770 [==============================] - 1s 40us/sample - loss: 1.6382 - accuracy: 0.4756\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.4949 - accuracy: 0.5388\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9749 - accuracy: 0.3401\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1369 - accuracy: 0.3229\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1260 - accuracy: 0.3225\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1769 - accuracy: 0.3237\n",
"start index for training is 723000\n",
"Train on 11805 samples, validate on 11810 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11805/11805 [==============================] - 1s 46us/sample - loss: 1.6630 - accuracy: 0.4672\n",
"11810/11810 [==============================] - 0s 41us/sample - loss: 1.6798 - accuracy: 0.4647\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.5134 - accuracy: 0.5318\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9538 - accuracy: 0.3421\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.1254 - accuracy: 0.3365\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.1322 - accuracy: 0.3261\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.1880 - accuracy: 0.3167\n",
"start index for training is 724000\n",
"Train on 11490 samples, validate on 11490 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11490/11490 [==============================] - 1s 49us/sample - loss: 1.6807 - accuracy: 0.4537\n",
"11490/11490 [==============================] - 0s 42us/sample - loss: 1.6691 - accuracy: 0.4472\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.5237 - accuracy: 0.5271\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9327 - accuracy: 0.3457\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.1507 - accuracy: 0.3225\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1491 - accuracy: 0.3171\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2031 - accuracy: 0.3114\n",
"start index for training is 725000\n",
"Train on 11690 samples, validate on 11690 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11690/11690 [==============================] - 0s 41us/sample - loss: 1.6606 - accuracy: 0.4539\n",
"11690/11690 [==============================] - 0s 42us/sample - loss: 1.6872 - accuracy: 0.4466\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 1.5324 - accuracy: 0.5323\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.9180 - accuracy: 0.3524\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.1528 - accuracy: 0.3259\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1592 - accuracy: 0.3208\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.2165 - accuracy: 0.3160\n",
"start index for training is 726000\n",
"Train on 11560 samples, validate on 11560 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11560/11560 [==============================] - 0s 42us/sample - loss: 1.6574 - accuracy: 0.4526\n",
"11560/11560 [==============================] - 0s 41us/sample - loss: 1.6795 - accuracy: 0.4488\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 1.5381 - accuracy: 0.5293\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.8913 - accuracy: 0.3704\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.1776 - accuracy: 0.3289\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.1635 - accuracy: 0.3185\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2239 - accuracy: 0.3087\n",
"start index for training is 727000\n",
"Train on 11460 samples, validate on 11465 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11460/11460 [==============================] - 1s 45us/sample - loss: 1.6529 - accuracy: 0.4575\n",
"11465/11465 [==============================] - 0s 41us/sample - loss: 1.6587 - accuracy: 0.4535\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.5388 - accuracy: 0.5416\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.8671 - accuracy: 0.3648\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.1689 - accuracy: 0.3039\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1701 - accuracy: 0.2955\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2330 - accuracy: 0.2884\n",
"start index for training is 728000\n",
"Train on 10925 samples, validate on 10930 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10925/10925 [==============================] - 1s 49us/sample - loss: 1.6602 - accuracy: 0.4528\n",
"10930/10930 [==============================] - 1s 46us/sample - loss: 1.6712 - accuracy: 0.4471\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.5656 - accuracy: 0.5012\n",
"12255/12255 [==============================] - 1s 54us/sample - loss: 1.8513 - accuracy: 0.3692\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.1846 - accuracy: 0.2969\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 2.1704 - accuracy: 0.3019\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.2317 - accuracy: 0.2926\n",
"start index for training is 729000\n",
"Train on 10770 samples, validate on 10775 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10770/10770 [==============================] - 0s 46us/sample - loss: 1.6345 - accuracy: 0.4591\n",
"10775/10775 [==============================] - 0s 41us/sample - loss: 1.6543 - accuracy: 0.4462\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.5748 - accuracy: 0.5010\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.8273 - accuracy: 0.3774\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.1930 - accuracy: 0.3069\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1810 - accuracy: 0.2947\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2446 - accuracy: 0.2854\n",
"start index for training is 730000\n",
"Train on 10980 samples, validate on 10980 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10980/10980 [==============================] - 0s 43us/sample - loss: 1.6373 - accuracy: 0.4465\n",
"10980/10980 [==============================] - 0s 40us/sample - loss: 1.6438 - accuracy: 0.4452\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.5745 - accuracy: 0.4958\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7991 - accuracy: 0.3863\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1972 - accuracy: 0.2957\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1836 - accuracy: 0.2986\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2531 - accuracy: 0.2881\n",
"start index for training is 731000\n",
"Train on 10385 samples, validate on 10385 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10385/10385 [==============================] - 0s 44us/sample - loss: 1.6463 - accuracy: 0.4518\n",
"10385/10385 [==============================] - 0s 41us/sample - loss: 1.6401 - accuracy: 0.4510\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.5834 - accuracy: 0.4855\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7890 - accuracy: 0.3842\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.1927 - accuracy: 0.3007\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1791 - accuracy: 0.2994s - loss: 2.1985 - accura\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2562 - accuracy: 0.2824\n",
"start index for training is 732000\n",
"Train on 9600 samples, validate on 9600 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9600/9600 [==============================] - 0s 42us/sample - loss: 1.6569 - accuracy: 0.4406\n",
"9600/9600 [==============================] - 0s 38us/sample - loss: 1.6765 - accuracy: 0.4173\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.6067 - accuracy: 0.4926\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7563 - accuracy: 0.3906\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2060 - accuracy: 0.2808\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.1820 - accuracy: 0.2963\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2513 - accuracy: 0.2893\n",
"start index for training is 733000\n",
"Train on 9730 samples, validate on 9730 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9730/9730 [==============================] - 0s 48us/sample - loss: 1.6657 - accuracy: 0.4347\n",
"9730/9730 [==============================] - 0s 43us/sample - loss: 1.6783 - accuracy: 0.4342\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.6118 - accuracy: 0.4779\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7366 - accuracy: 0.3938\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2056 - accuracy: 0.3088\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1697 - accuracy: 0.3159\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2403 - accuracy: 0.3067\n",
"start index for training is 734000\n",
"Train on 10810 samples, validate on 10810 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10810/10810 [==============================] - 0s 43us/sample - loss: 1.6421 - accuracy: 0.4557\n",
"10810/10810 [==============================] - 0s 40us/sample - loss: 1.6442 - accuracy: 0.4457\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6154 - accuracy: 0.4946\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7055 - accuracy: 0.4206\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2071 - accuracy: 0.3086\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1749 - accuracy: 0.3237\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2460 - accuracy: 0.3157\n",
"start index for training is 735000\n",
"Train on 10980 samples, validate on 10980 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10980/10980 [==============================] - 1s 46us/sample - loss: 1.6335 - accuracy: 0.4500\n",
"10980/10980 [==============================] - 0s 40us/sample - loss: 1.6485 - accuracy: 0.4471\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6163 - accuracy: 0.5244\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.6761 - accuracy: 0.4190\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.2214 - accuracy: 0.2900\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.1858 - accuracy: 0.3069\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2569 - accuracy: 0.2943\n",
"start index for training is 736000\n",
"Train on 10555 samples, validate on 10555 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10555/10555 [==============================] - 0s 43us/sample - loss: 1.6431 - accuracy: 0.4521\n",
"10555/10555 [==============================] - 0s 40us/sample - loss: 1.6748 - accuracy: 0.4388\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6373 - accuracy: 0.5089\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.6570 - accuracy: 0.4304\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2234 - accuracy: 0.2984\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1790 - accuracy: 0.3029\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.2512 - accuracy: 0.2900\n",
"start index for training is 737000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Train on 10000 samples, validate on 10005 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10000/10000 [==============================] - 0s 43us/sample - loss: 1.6950 - accuracy: 0.4334\n",
"10005/10005 [==============================] - 0s 39us/sample - loss: 1.6946 - accuracy: 0.4396\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6370 - accuracy: 0.4786\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.6367 - accuracy: 0.4520\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2315 - accuracy: 0.2873\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1714 - accuracy: 0.3101\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2392 - accuracy: 0.2990\n",
"start index for training is 738000\n",
"Train on 11065 samples, validate on 11065 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11065/11065 [==============================] - 0s 43us/sample - loss: 1.6396 - accuracy: 0.4449\n",
"11065/11065 [==============================] - 0s 39us/sample - loss: 1.6526 - accuracy: 0.4428\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6694 - accuracy: 0.4582\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.6230 - accuracy: 0.4404\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2647 - accuracy: 0.3056\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.1811 - accuracy: 0.3159\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2498 - accuracy: 0.3067\n",
"start index for training is 739000\n",
"Train on 9605 samples, validate on 9605 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9605/9605 [==============================] - 0s 44us/sample - loss: 1.6879 - accuracy: 0.4323\n",
"9605/9605 [==============================] - 0s 42us/sample - loss: 1.6952 - accuracy: 0.4324\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.6488 - accuracy: 0.4763\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.6081 - accuracy: 0.4586\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2447 - accuracy: 0.2966\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1736 - accuracy: 0.3225\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2415 - accuracy: 0.3124\n",
"start index for training is 740000\n",
"Train on 11380 samples, validate on 11385 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11380/11380 [==============================] - 1s 52us/sample - loss: 1.6090 - accuracy: 0.4716\n",
"11385/11385 [==============================] - 1s 46us/sample - loss: 1.6405 - accuracy: 0.4578\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.6592 - accuracy: 0.4834\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.5932 - accuracy: 0.4708\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2594 - accuracy: 0.2937\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1766 - accuracy: 0.3142\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2462 - accuracy: 0.3047\n",
"start index for training is 741000\n",
"Train on 9050 samples, validate on 9055 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9050/9050 [==============================] - 0s 43us/sample - loss: 1.7031 - accuracy: 0.4389\n",
"9055/9055 [==============================] - ETA: 0s - loss: 1.7031 - accuracy: 0.43 - 0s 42us/sample - loss: 1.6945 - accuracy: 0.4396\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6769 - accuracy: 0.4721\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.5885 - accuracy: 0.4711\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2696 - accuracy: 0.2910\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1762 - accuracy: 0.3146\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2392 - accuracy: 0.3006\n",
"start index for training is 742000\n",
"Train on 11515 samples, validate on 11520 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11515/11515 [==============================] - 1s 46us/sample - loss: 1.6243 - accuracy: 0.4722\n",
"11520/11520 [==============================] - 0s 39us/sample - loss: 1.6367 - accuracy: 0.4704\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6891 - accuracy: 0.4707\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.5752 - accuracy: 0.4774\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.2929 - accuracy: 0.2891\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.1821 - accuracy: 0.3167\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2483 - accuracy: 0.3009\n",
"start index for training is 743000\n",
"Train on 8895 samples, validate on 8900 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8895/8895 [==============================] - 0s 44us/sample - loss: 1.7145 - accuracy: 0.4418\n",
"8900/8900 [==============================] - 0s 41us/sample - loss: 1.7267 - accuracy: 0.4381\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.6902 - accuracy: 0.4734\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.5828 - accuracy: 0.4703\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2784 - accuracy: 0.2895\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1685 - accuracy: 0.3178\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2322 - accuracy: 0.3003\n",
"start index for training is 744000\n",
"Train on 10735 samples, validate on 10740 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10735/10735 [==============================] - 0s 46us/sample - loss: 1.6517 - accuracy: 0.4733\n",
"10740/10740 [==============================] - 0s 42us/sample - loss: 1.6622 - accuracy: 0.4685\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.6899 - accuracy: 0.4401\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.5756 - accuracy: 0.4729\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2845 - accuracy: 0.3051\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1742 - accuracy: 0.3273\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.2399 - accuracy: 0.3144s - loss: 2.2347 - accuracy: 0.\n",
"start index for training is 745000\n",
"Train on 9820 samples, validate on 9825 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9820/9820 [==============================] - 0s 44us/sample - loss: 1.7332 - accuracy: 0.4546\n",
"9825/9825 [==============================] - 0s 40us/sample - loss: 1.7408 - accuracy: 0.4499\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6856 - accuracy: 0.4804\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.5746 - accuracy: 0.4885\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2856 - accuracy: 0.3014\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1678 - accuracy: 0.3271\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2382 - accuracy: 0.3130\n",
"start index for training is 746000\n",
"Train on 8625 samples, validate on 8630 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8625/8625 [==============================] - 0s 45us/sample - loss: 1.7558 - accuracy: 0.4454\n",
"8630/8630 [==============================] - 0s 43us/sample - loss: 1.7635 - accuracy: 0.4435\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.6920 - accuracy: 0.4729\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.5836 - accuracy: 0.4828\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2940 - accuracy: 0.2905\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.1674 - accuracy: 0.3287\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2374 - accuracy: 0.3123\n",
"start index for training is 747000\n",
"Train on 11010 samples, validate on 11010 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11010/11010 [==============================] - 1s 46us/sample - loss: 1.7567 - accuracy: 0.4150\n",
"11010/11010 [==============================] - 0s 43us/sample - loss: 1.7623 - accuracy: 0.4157\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7803 - accuracy: 0.3883\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.6631 - accuracy: 0.4401\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.3396 - accuracy: 0.2552\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.2406 - accuracy: 0.2804\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.3183 - accuracy: 0.2639\n",
"start index for training is 748000\n",
"Train on 9985 samples, validate on 9985 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9985/9985 [==============================] - 0s 46us/sample - loss: 1.7780 - accuracy: 0.4434\n",
"9985/9985 [==============================] - 0s 45us/sample - loss: 1.7835 - accuracy: 0.4405\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.6997 - accuracy: 0.4701\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.5981 - accuracy: 0.4795\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2874 - accuracy: 0.2927\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1619 - accuracy: 0.3275\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2330 - accuracy: 0.3181s - loss: 2.2356 - accuracy: \n",
"start index for training is 749000\n",
"Train on 9455 samples, validate on 9460 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9455/9455 [==============================] - 0s 45us/sample - loss: 1.7848 - accuracy: 0.4398\n",
"9460/9460 [==============================] - 0s 43us/sample - loss: 1.8223 - accuracy: 0.4337\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.6795 - accuracy: 0.4736\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.5958 - accuracy: 0.4827\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.2715 - accuracy: 0.2845\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.1585 - accuracy: 0.3243\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2311 - accuracy: 0.3129\n",
"start index for training is 750000\n",
"Train on 9540 samples, validate on 9545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9540/9540 [==============================] - 0s 47us/sample - loss: 1.8106 - accuracy: 0.4355\n",
"9545/9545 [==============================] - 1s 69us/sample - loss: 1.8174 - accuracy: 0.4290\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.7163 - accuracy: 0.4694\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.6132 - accuracy: 0.4747\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.2993 - accuracy: 0.2949\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.1694 - accuracy: 0.3254\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.2395 - accuracy: 0.3161\n",
"start index for training is 751000\n",
"Train on 9450 samples, validate on 9450 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9450/9450 [==============================] - 0s 51us/sample - loss: 1.8180 - accuracy: 0.4383\n",
"9450/9450 [==============================] - 0s 48us/sample - loss: 1.8338 - accuracy: 0.4266\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.7046 - accuracy: 0.4692\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.6160 - accuracy: 0.4730\n",
"14070/14070 [==============================] - 1s 57us/sample - loss: 2.2873 - accuracy: 0.2852\n",
"11565/11565 [==============================] - 1s 68us/sample - loss: 2.1623 - accuracy: 0.3248\n",
"7000/7000 [==============================] - 0s 65us/sample - loss: 2.2344 - accuracy: 0.3146\n",
"start index for training is 752000\n",
"Train on 9525 samples, validate on 9525 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9525/9525 [==============================] - 0s 52us/sample - loss: 1.8065 - accuracy: 0.4406\n",
"9525/9525 [==============================] - 0s 45us/sample - loss: 1.8306 - accuracy: 0.4308\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7090 - accuracy: 0.4600\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.6234 - accuracy: 0.4703\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2801 - accuracy: 0.3013\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.1619 - accuracy: 0.3268\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.2334 - accuracy: 0.3194\n",
"start index for training is 753000\n",
"Train on 9575 samples, validate on 9580 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9575/9575 [==============================] - 0s 45us/sample - loss: 1.8228 - accuracy: 0.4302\n",
"9580/9580 [==============================] - 0s 44us/sample - loss: 1.8438 - accuracy: 0.4266\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.7003 - accuracy: 0.4858\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.6242 - accuracy: 0.4717\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.2789 - accuracy: 0.2954\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.1563 - accuracy: 0.3283\n",
"7000/7000 [==============================] - 0s 54us/sample - loss: 2.2269 - accuracy: 0.3216\n",
"start index for training is 754000\n",
"Train on 9625 samples, validate on 9630 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9625/9625 [==============================] - 1s 69us/sample - loss: 1.8244 - accuracy: 0.4349\n",
"9630/9630 [==============================] - 1s 60us/sample - loss: 1.8535 - accuracy: 0.4306\n",
"5980/5980 [==============================] - 0s 80us/sample - loss: 1.6990 - accuracy: 0.4687\n",
"12255/12255 [==============================] - 1s 75us/sample - loss: 1.6371 - accuracy: 0.4606\n",
"14070/14070 [==============================] - 1s 55us/sample - loss: 2.2655 - accuracy: 0.2937\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.1581 - accuracy: 0.3252\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.2329 - accuracy: 0.3176\n",
"start index for training is 755000\n",
"Train on 9535 samples, validate on 9540 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9535/9535 [==============================] - 1s 57us/sample - loss: 1.8279 - accuracy: 0.4358\n",
"9540/9540 [==============================] - 1s 61us/sample - loss: 1.8011 - accuracy: 0.4392\n",
"5980/5980 [==============================] - 0s 59us/sample - loss: 1.7161 - accuracy: 0.4818\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 1.6463 - accuracy: 0.4712\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.2900 - accuracy: 0.2955\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.1730 - accuracy: 0.3332\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"7000/7000 [==============================] - 0s 51us/sample - loss: 2.2434 - accuracy: 0.3223\n",
"start index for training is 756000\n",
"Train on 9670 samples, validate on 9675 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9670/9670 [==============================] - 1s 55us/sample - loss: 1.8352 - accuracy: 0.4386\n",
"9675/9675 [==============================] - 0s 50us/sample - loss: 1.8443 - accuracy: 0.4333\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 1.7086 - accuracy: 0.4759\n",
"12255/12255 [==============================] - 1s 50us/sample - loss: 1.6531 - accuracy: 0.4694\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.2690 - accuracy: 0.2972\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.1609 - accuracy: 0.3317\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.2326 - accuracy: 0.3211\n",
"start index for training is 757000\n",
"Train on 9610 samples, validate on 9615 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9610/9610 [==============================] - 1s 78us/sample - loss: 1.8244 - accuracy: 0.4399\n",
"9615/9615 [==============================] - 1s 72us/sample - loss: 1.8458 - accuracy: 0.4359\n",
"5980/5980 [==============================] - 0s 72us/sample - loss: 1.7287 - accuracy: 0.4508\n",
"12255/12255 [==============================] - 1s 64us/sample - loss: 1.6731 - accuracy: 0.4552\n",
"14070/14070 [==============================] - 1s 65us/sample - loss: 2.2860 - accuracy: 0.2887\n",
"11565/11565 [==============================] - 1s 51us/sample - loss: 2.1798 - accuracy: 0.3261\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.2520 - accuracy: 0.3140\n",
"start index for training is 758000\n",
"Train on 9460 samples, validate on 9460 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9460/9460 [==============================] - 1s 55us/sample - loss: 1.8102 - accuracy: 0.4425\n",
"9460/9460 [==============================] - 0s 48us/sample - loss: 1.8468 - accuracy: 0.4320\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7125 - accuracy: 0.4769\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.6717 - accuracy: 0.4450\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 2.2789 - accuracy: 0.2954\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.1774 - accuracy: 0.3248\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.2489 - accuracy: 0.3139\n",
"start index for training is 759000\n",
"Train on 9330 samples, validate on 9335 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9330/9330 [==============================] - 0s 54us/sample - loss: 1.8271 - accuracy: 0.4427\n",
"9335/9335 [==============================] - 0s 49us/sample - loss: 1.8621 - accuracy: 0.4303\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 1.7326 - accuracy: 0.4627\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.6873 - accuracy: 0.4391\n",
"14070/14070 [==============================] - 1s 52us/sample - loss: 2.2855 - accuracy: 0.2957\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 2.1848 - accuracy: 0.3294\n",
"7000/7000 [==============================] - 0s 54us/sample - loss: 2.2584 - accuracy: 0.3190\n",
"start index for training is 760000\n",
"Train on 9080 samples, validate on 9080 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9080/9080 [==============================] - 0s 48us/sample - loss: 1.8579 - accuracy: 0.4121\n",
"9080/9080 [==============================] - 0s 45us/sample - loss: 1.8708 - accuracy: 0.4162\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.7178 - accuracy: 0.4898\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.6901 - accuracy: 0.4244\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.2594 - accuracy: 0.2999\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.1923 - accuracy: 0.3121\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.2705 - accuracy: 0.2981\n",
"start index for training is 761000\n",
"Train on 9090 samples, validate on 9095 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9090/9090 [==============================] - 0s 46us/sample - loss: 1.8443 - accuracy: 0.4310\n",
"9095/9095 [==============================] - 0s 42us/sample - loss: 1.8748 - accuracy: 0.4224\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7588 - accuracy: 0.4605\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7211 - accuracy: 0.4344\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2955 - accuracy: 0.2955\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2094 - accuracy: 0.3212\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2840 - accuracy: 0.3087\n",
"start index for training is 762000\n",
"Train on 9055 samples, validate on 9055 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9055/9055 [==============================] - 0s 46us/sample - loss: 1.8717 - accuracy: 0.4210\n",
"9055/9055 [==============================] - 0s 41us/sample - loss: 1.8647 - accuracy: 0.4306\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.8262 - accuracy: 0.4508\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7772 - accuracy: 0.4217\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.3574 - accuracy: 0.2879\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.2532 - accuracy: 0.3128\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3204 - accuracy: 0.3023\n",
"start index for training is 763000\n",
"Train on 9225 samples, validate on 9230 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9225/9225 [==============================] - 0s 44us/sample - loss: 1.8561 - accuracy: 0.4361\n",
"9230/9230 [==============================] - 0s 41us/sample - loss: 1.8610 - accuracy: 0.4328\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7284 - accuracy: 0.4666\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.7141 - accuracy: 0.4267\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.2789 - accuracy: 0.3006\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.2021 - accuracy: 0.3125\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.2732 - accuracy: 0.3031\n",
"start index for training is 764000\n",
"Train on 9165 samples, validate on 9170 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9165/9165 [==============================] - 0s 45us/sample - loss: 1.8695 - accuracy: 0.4300\n",
"9170/9170 [==============================] - 0s 41us/sample - loss: 1.8999 - accuracy: 0.4224\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.7759 - accuracy: 0.4672\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7549 - accuracy: 0.4198\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.3194 - accuracy: 0.2898\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.2296 - accuracy: 0.3144\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2973 - accuracy: 0.3097\n",
"start index for training is 765000\n",
"Train on 6545 samples, validate on 6545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6545/6545 [==============================] - 0s 46us/sample - loss: 1.9747 - accuracy: 0.3647\n",
"6545/6545 [==============================] - 0s 41us/sample - loss: 1.9994 - accuracy: 0.3626\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.6894 - accuracy: 0.4761\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.7159 - accuracy: 0.4289\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.0756 - accuracy: 0.3360\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.1288 - accuracy: 0.3124\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1998 - accuracy: 0.3023\n",
"start index for training is 766000\n",
"Train on 10600 samples, validate on 10600 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10600/10600 [==============================] - 0s 45us/sample - loss: 1.6933 - accuracy: 0.4711\n",
"10600/10600 [==============================] - 0s 41us/sample - loss: 1.7184 - accuracy: 0.4604\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.7865 - accuracy: 0.4140\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.8758 - accuracy: 0.3599\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8611 - accuracy: 0.4220\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1185 - accuracy: 0.3336\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.1984 - accuracy: 0.3116\n",
"start index for training is 767000\n",
"Train on 10800 samples, validate on 10800 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10800/10800 [==============================] - 0s 44us/sample - loss: 1.6919 - accuracy: 0.4660\n",
"10800/10800 [==============================] - 0s 42us/sample - loss: 1.7083 - accuracy: 0.4593\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.8268 - accuracy: 0.3849\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9169 - accuracy: 0.3466\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.7977 - accuracy: 0.4394\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.0989 - accuracy: 0.3462\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.1813 - accuracy: 0.3241\n",
"start index for training is 768000\n",
"Train on 10970 samples, validate on 10970 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10970/10970 [==============================] - 1s 49us/sample - loss: 1.6310 - accuracy: 0.4778\n",
"10970/10970 [==============================] - 0s 44us/sample - loss: 1.6771 - accuracy: 0.4640\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8643 - accuracy: 0.3753\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.9563 - accuracy: 0.3341\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.7615 - accuracy: 0.4478\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1092 - accuracy: 0.3396\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.1980 - accuracy: 0.3076\n",
"start index for training is 769000\n",
"Train on 10890 samples, validate on 10890 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10890/10890 [==============================] - 0s 44us/sample - loss: 1.5987 - accuracy: 0.4975\n",
"10890/10890 [==============================] - 0s 43us/sample - loss: 1.6324 - accuracy: 0.4777\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.8879 - accuracy: 0.3560\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.9924 - accuracy: 0.3114\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.7358 - accuracy: 0.4633\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1108 - accuracy: 0.3400\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2071 - accuracy: 0.3127\n",
"start index for training is 770000\n",
"Train on 11025 samples, validate on 11025 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11025/11025 [==============================] - 1s 49us/sample - loss: 1.6741 - accuracy: 0.4542\n",
"11025/11025 [==============================] - 1s 49us/sample - loss: 1.7034 - accuracy: 0.4405\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 2.0234 - accuracy: 0.3191\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1668 - accuracy: 0.2702\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8122 - accuracy: 0.4277\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.2628 - accuracy: 0.2928\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.3760 - accuracy: 0.2644\n",
"start index for training is 771000\n",
"Train on 11150 samples, validate on 11150 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11150/11150 [==============================] - 0s 44us/sample - loss: 1.5437 - accuracy: 0.4976\n",
"11150/11150 [==============================] - 0s 41us/sample - loss: 1.5576 - accuracy: 0.4933\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.9597 - accuracy: 0.3517\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.0504 - accuracy: 0.3026\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.7099 - accuracy: 0.4660\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1266 - accuracy: 0.3388\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2246 - accuracy: 0.3129\n",
"start index for training is 772000\n",
"Train on 11610 samples, validate on 11615 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11610/11610 [==============================] - 1s 45us/sample - loss: 1.5118 - accuracy: 0.5175\n",
"11615/11615 [==============================] - 0s 43us/sample - loss: 1.5432 - accuracy: 0.5075\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9546 - accuracy: 0.3388\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.0487 - accuracy: 0.2938\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.7001 - accuracy: 0.4720\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1239 - accuracy: 0.3349\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2330 - accuracy: 0.3043\n",
"start index for training is 773000\n",
"Train on 11770 samples, validate on 11775 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11770/11770 [==============================] - 1s 46us/sample - loss: 1.4948 - accuracy: 0.5254\n",
"11775/11775 [==============================] - 0s 42us/sample - loss: 1.4992 - accuracy: 0.5210\n",
"5980/5980 [==============================] - ETA: 0s - loss: 1.9732 - accuracy: 0.32 - 0s 40us/sample - loss: 1.9721 - accuracy: 0.3264\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0535 - accuracy: 0.2986\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.6991 - accuracy: 0.4723\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.1245 - accuracy: 0.3418\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2372 - accuracy: 0.3104\n",
"start index for training is 774000\n",
"Train on 12930 samples, validate on 12935 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12930/12930 [==============================] - 1s 50us/sample - loss: 1.5021 - accuracy: 0.5126\n",
"12935/12935 [==============================] - 1s 44us/sample - loss: 1.5074 - accuracy: 0.5161\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.9911 - accuracy: 0.3189\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0542 - accuracy: 0.2829\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.7057 - accuracy: 0.4709\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.1250 - accuracy: 0.3286\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2416 - accuracy: 0.2887\n",
"start index for training is 775000\n",
"Train on 12930 samples, validate on 12930 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12930/12930 [==============================] - 1s 46us/sample - loss: 1.5235 - accuracy: 0.5046\n",
"12930/12930 [==============================] - 1s 42us/sample - loss: 1.4979 - accuracy: 0.5125\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9947 - accuracy: 0.3274\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0447 - accuracy: 0.2905\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7031 - accuracy: 0.4735\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1042 - accuracy: 0.3314\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2177 - accuracy: 0.2960\n",
"start index for training is 776000\n",
"Train on 13360 samples, validate on 13365 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13360/13360 [==============================] - 1s 46us/sample - loss: 1.5008 - accuracy: 0.5220\n",
"13365/13365 [==============================] - 1s 42us/sample - loss: 1.5212 - accuracy: 0.5176\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0208 - accuracy: 0.3177\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.0549 - accuracy: 0.2970\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.7162 - accuracy: 0.4778\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.1032 - accuracy: 0.3619\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2215 - accuracy: 0.3253\n",
"start index for training is 777000\n",
"Train on 12905 samples, validate on 12910 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12905/12905 [==============================] - 1s 47us/sample - loss: 1.5149 - accuracy: 0.5126\n",
"12910/12910 [==============================] - 1s 45us/sample - loss: 1.5341 - accuracy: 0.5092\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0131 - accuracy: 0.3222\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0463 - accuracy: 0.3044\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7206 - accuracy: 0.4806\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.0880 - accuracy: 0.3633\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2116 - accuracy: 0.3306\n",
"start index for training is 778000\n",
"Train on 13075 samples, validate on 13080 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13075/13075 [==============================] - 1s 47us/sample - loss: 1.5678 - accuracy: 0.4913\n",
"13080/13080 [==============================] - 1s 44us/sample - loss: 1.5731 - accuracy: 0.4840\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 2.0231 - accuracy: 0.3241\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0581 - accuracy: 0.2866\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.7259 - accuracy: 0.4703\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.0808 - accuracy: 0.3413\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.2076 - accuracy: 0.3071\n",
"start index for training is 779000\n",
"Train on 13550 samples, validate on 13555 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13550/13550 [==============================] - 1s 46us/sample - loss: 1.4992 - accuracy: 0.5228\n",
"13555/13555 [==============================] - 1s 43us/sample - loss: 1.5266 - accuracy: 0.5140\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0407 - accuracy: 0.3202\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.0577 - accuracy: 0.3033\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.7225 - accuracy: 0.4800\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.0768 - accuracy: 0.3684\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2074 - accuracy: 0.3306\n",
"start index for training is 780000\n",
"Train on 12400 samples, validate on 12405 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12400/12400 [==============================] - 1s 53us/sample - loss: 1.5481 - accuracy: 0.5025\n",
"12405/12405 [==============================] - 1s 46us/sample - loss: 1.5666 - accuracy: 0.4950\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 2.0579 - accuracy: 0.3221\n",
"12255/12255 [==============================] - 1s 60us/sample - loss: 2.0771 - accuracy: 0.2960\n",
"14070/14070 [==============================] - 1s 53us/sample - loss: 1.7363 - accuracy: 0.4795\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.0922 - accuracy: 0.3651\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.2208 - accuracy: 0.3296\n",
"start index for training is 781000\n",
"Train on 12645 samples, validate on 12645 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12645/12645 [==============================] - 1s 46us/sample - loss: 1.4806 - accuracy: 0.5253\n",
"12645/12645 [==============================] - 1s 42us/sample - loss: 1.4919 - accuracy: 0.5164\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 2.0647 - accuracy: 0.3281\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0454 - accuracy: 0.3004\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.7397 - accuracy: 0.4737\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 2.0503 - accuracy: 0.3727\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.1762 - accuracy: 0.3379\n",
"start index for training is 782000\n",
"Train on 11510 samples, validate on 11515 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11510/11510 [==============================] - 1s 45us/sample - loss: 1.5334 - accuracy: 0.5009\n",
"11515/11515 [==============================] - 0s 43us/sample - loss: 1.5745 - accuracy: 0.4915\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.0361 - accuracy: 0.3380\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 2.0608 - accuracy: 0.3023\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.7333 - accuracy: 0.4764\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.0353 - accuracy: 0.3766\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.1673 - accuracy: 0.3513\n",
"start index for training is 783000\n",
"Train on 12465 samples, validate on 12470 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12465/12465 [==============================] - 1s 45us/sample - loss: 1.5151 - accuracy: 0.5147\n",
"12470/12470 [==============================] - 1s 42us/sample - loss: 1.5043 - accuracy: 0.5189\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 2.0560 - accuracy: 0.3368\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0407 - accuracy: 0.3044\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.7464 - accuracy: 0.4758\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.0017 - accuracy: 0.3871\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.1308 - accuracy: 0.3530\n",
"start index for training is 784000\n",
"Train on 11830 samples, validate on 11830 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11830/11830 [==============================] - 1s 50us/sample - loss: 1.5382 - accuracy: 0.5168s - loss: 1.5390 - accuracy: 0.51\n",
"11830/11830 [==============================] - 1s 53us/sample - loss: 1.5564 - accuracy: 0.5022\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 2.0328 - accuracy: 0.3478\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 2.0375 - accuracy: 0.3004\n",
"14070/14070 [==============================] - 1s 53us/sample - loss: 1.7443 - accuracy: 0.4757\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 1.9728 - accuracy: 0.3999\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.1034 - accuracy: 0.3647\n",
"start index for training is 785000\n",
"Train on 11010 samples, validate on 11015 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11010/11010 [==============================] - 1s 47us/sample - loss: 1.7874 - accuracy: 0.4361\n",
"11015/11015 [==============================] - 0s 44us/sample - loss: 1.8306 - accuracy: 0.4261\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.2073 - accuracy: 0.3625\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.1953 - accuracy: 0.3157\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.9742 - accuracy: 0.4052\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1232 - accuracy: 0.3665\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2368 - accuracy: 0.3464\n",
"start index for training is 786000\n",
"Train on 13135 samples, validate on 13135 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13135/13135 [==============================] - 1s 45us/sample - loss: 1.5215 - accuracy: 0.5281\n",
"13135/13135 [==============================] - 1s 51us/sample - loss: 1.5229 - accuracy: 0.5265\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.0383 - accuracy: 0.3505\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0234 - accuracy: 0.3062\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7781 - accuracy: 0.4613\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.9195 - accuracy: 0.4134\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.0382 - accuracy: 0.3844\n",
"start index for training is 787000\n",
"Train on 12725 samples, validate on 12725 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12725/12725 [==============================] - 1s 46us/sample - loss: 1.5653 - accuracy: 0.5141\n",
"12725/12725 [==============================] - 1s 42us/sample - loss: 1.5457 - accuracy: 0.5205\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0369 - accuracy: 0.3443\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0205 - accuracy: 0.3146\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.7672 - accuracy: 0.4649\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.8931 - accuracy: 0.4222\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.0107 - accuracy: 0.3900\n",
"start index for training is 788000\n",
"Train on 12545 samples, validate on 12550 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12545/12545 [==============================] - 1s 46us/sample - loss: 1.5563 - accuracy: 0.5085\n",
"12550/12550 [==============================] - 1s 43us/sample - loss: 1.5599 - accuracy: 0.5039\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.0442 - accuracy: 0.3401\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 2.0030 - accuracy: 0.3182\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 1.7861 - accuracy: 0.4514\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.8731 - accuracy: 0.4325\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 1.9802 - accuracy: 0.4079\n",
"start index for training is 789000\n",
"Train on 12605 samples, validate on 12610 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12605/12605 [==============================] - 1s 84us/sample - loss: 1.5657 - accuracy: 0.5139\n",
"12610/12610 [==============================] - 1s 92us/sample - loss: 1.5695 - accuracy: 0.5142\n",
"5980/5980 [==============================] - 0s 58us/sample - loss: 2.0541 - accuracy: 0.3482\n",
"12255/12255 [==============================] - 1s 53us/sample - loss: 2.0195 - accuracy: 0.3171\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 1.7871 - accuracy: 0.4500\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 1.8667 - accuracy: 0.4340\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.9799 - accuracy: 0.3997\n",
"start index for training is 790000\n",
"Train on 12195 samples, validate on 12200 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12195/12195 [==============================] - 1s 63us/sample - loss: 1.5632 - accuracy: 0.5138\n",
"12200/12200 [==============================] - 1s 65us/sample - loss: 1.5837 - accuracy: 0.4989\n",
"5980/5980 [==============================] - 0s 67us/sample - loss: 2.0556 - accuracy: 0.3346\n",
"12255/12255 [==============================] - 1s 57us/sample - loss: 2.0262 - accuracy: 0.3145\n",
"14070/14070 [==============================] - 1s 55us/sample - loss: 1.7899 - accuracy: 0.4498\n",
"11565/11565 [==============================] - 1s 54us/sample - loss: 1.8574 - accuracy: 0.4367\n",
"7000/7000 [==============================] - 0s 67us/sample - loss: 1.9696 - accuracy: 0.4060\n",
"start index for training is 791000\n",
"Train on 12295 samples, validate on 12300 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12295/12295 [==============================] - 1s 48us/sample - loss: 1.5792 - accuracy: 0.5026\n",
"12300/12300 [==============================] - 1s 47us/sample - loss: 1.6343 - accuracy: 0.4875\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.0688 - accuracy: 0.3365\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0106 - accuracy: 0.3077\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.8086 - accuracy: 0.4557\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.8253 - accuracy: 0.4385\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.9348 - accuracy: 0.4053\n",
"start index for training is 792000\n",
"Train on 12380 samples, validate on 12385 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12380/12380 [==============================] - 1s 45us/sample - loss: 1.6124 - accuracy: 0.4913\n",
"12385/12385 [==============================] - 1s 45us/sample - loss: 1.6293 - accuracy: 0.4913\n",
"5980/5980 [==============================] - 0s 51us/sample - loss: 2.0584 - accuracy: 0.3204\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.0145 - accuracy: 0.3060\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.8099 - accuracy: 0.4546\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.8047 - accuracy: 0.4435\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 1.9126 - accuracy: 0.4123\n",
"start index for training is 793000\n",
"Train on 11615 samples, validate on 11620 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11615/11615 [==============================] - 1s 46us/sample - loss: 1.6399 - accuracy: 0.4861\n",
"11620/11620 [==============================] - 1s 46us/sample - loss: 1.6429 - accuracy: 0.4849\n",
"5980/5980 [==============================] - 0s 53us/sample - loss: 2.0703 - accuracy: 0.3214\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 2.0127 - accuracy: 0.3048\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 57us/sample - loss: 1.8249 - accuracy: 0.4442\n",
"11565/11565 [==============================] - 1s 52us/sample - loss: 1.7903 - accuracy: 0.4553\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 1.8990 - accuracy: 0.4220\n",
"start index for training is 794000\n",
"Train on 10705 samples, validate on 10705 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10705/10705 [==============================] - 1s 47us/sample - loss: 1.7078 - accuracy: 0.4651\n",
"10705/10705 [==============================] - 0s 41us/sample - loss: 1.7377 - accuracy: 0.4532\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0521 - accuracy: 0.3251\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.9989 - accuracy: 0.3061\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.8321 - accuracy: 0.4394\n",
"11565/11565 [==============================] - 1s 55us/sample - loss: 1.7709 - accuracy: 0.4593\n",
"7000/7000 [==============================] - 0s 58us/sample - loss: 1.8687 - accuracy: 0.4320\n",
"start index for training is 795000\n",
"Train on 13005 samples, validate on 13010 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13005/13005 [==============================] - 1s 47us/sample - loss: 2.1506 - accuracy: 0.3616\n",
"13010/13010 [==============================] - 1s 42us/sample - loss: 2.1493 - accuracy: 0.3653\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 2.5042 - accuracy: 0.2823\n",
"12255/12255 [==============================] - 1s 50us/sample - loss: 2.4662 - accuracy: 0.2511\n",
"14070/14070 [==============================] - 1s 58us/sample - loss: 2.2796 - accuracy: 0.3448\n",
"11565/11565 [==============================] - 1s 68us/sample - loss: 2.2572 - accuracy: 0.3417\n",
"7000/7000 [==============================] - 1s 85us/sample - loss: 2.3663 - accuracy: 0.3137\n",
"start index for training is 796000\n",
"Train on 11475 samples, validate on 11480 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11475/11475 [==============================] - 1s 51us/sample - loss: 1.6818 - accuracy: 0.4863\n",
"11480/11480 [==============================] - 0s 43us/sample - loss: 1.6988 - accuracy: 0.4854\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.0630 - accuracy: 0.3206\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 2.0286 - accuracy: 0.3046\n",
"14070/14070 [==============================] - 1s 60us/sample - loss: 1.8412 - accuracy: 0.4461\n",
"11565/11565 [==============================] - 1s 51us/sample - loss: 1.7484 - accuracy: 0.4717s - loss: 1.7491 - accuracy: 0.\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 1.8362 - accuracy: 0.4421\n",
"start index for training is 797000\n",
"Train on 12340 samples, validate on 12345 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12340/12340 [==============================] - 1s 58us/sample - loss: 1.7372 - accuracy: 0.4695s - loss: 1.7335 \n",
"12345/12345 [==============================] - 1s 49us/sample - loss: 1.7470 - accuracy: 0.4654\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.0647 - accuracy: 0.3189\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0220 - accuracy: 0.2993\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 1.8530 - accuracy: 0.4385\n",
"11565/11565 [==============================] - 1s 54us/sample - loss: 1.7387 - accuracy: 0.4732\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 1.8222 - accuracy: 0.4437\n",
"start index for training is 798000\n",
"Train on 10220 samples, validate on 10220 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10220/10220 [==============================] - 1s 54us/sample - loss: 1.7970 - accuracy: 0.4474\n",
"10220/10220 [==============================] - 0s 45us/sample - loss: 1.8192 - accuracy: 0.4408\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 2.0709 - accuracy: 0.3328\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0290 - accuracy: 0.3020\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.8549 - accuracy: 0.4296\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 1.7277 - accuracy: 0.4761\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.8030 - accuracy: 0.4500\n",
"start index for training is 799000\n",
"Train on 14265 samples, validate on 14265 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14265/14265 [==============================] - 1s 49us/sample - loss: 1.6774 - accuracy: 0.4894\n",
"14265/14265 [==============================] - 1s 41us/sample - loss: 1.6931 - accuracy: 0.4869\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 2.0884 - accuracy: 0.3253\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 2.0355 - accuracy: 0.3099\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 1.8741 - accuracy: 0.4213\n",
"11565/11565 [==============================] - 1s 61us/sample - loss: 1.7108 - accuracy: 0.4792\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 1.7788 - accuracy: 0.4656\n",
"start index for training is 800000\n",
"Train on 10905 samples, validate on 10905 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10905/10905 [==============================] - 1s 68us/sample - loss: 1.8154 - accuracy: 0.4376\n",
"10905/10905 [==============================] - 1s 57us/sample - loss: 1.8142 - accuracy: 0.4465\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 2.0834 - accuracy: 0.3263\n",
"12255/12255 [==============================] - 1s 62us/sample - loss: 2.0342 - accuracy: 0.3072\n",
"14070/14070 [==============================] - 1s 52us/sample - loss: 1.8667 - accuracy: 0.4269\n",
"11565/11565 [==============================] - 1s 55us/sample - loss: 1.7045 - accuracy: 0.4803\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 1.7633 - accuracy: 0.4671\n",
"start index for training is 801000\n",
"Train on 10250 samples, validate on 10250 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10250/10250 [==============================] - 0s 49us/sample - loss: 1.8206 - accuracy: 0.4430\n",
"10250/10250 [==============================] - 0s 45us/sample - loss: 1.8400 - accuracy: 0.4386\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 2.0891 - accuracy: 0.3304\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0312 - accuracy: 0.3049\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8700 - accuracy: 0.4294\n",
"11565/11565 [==============================] - 1s 55us/sample - loss: 1.7019 - accuracy: 0.4799\n",
"7000/7000 [==============================] - 0s 53us/sample - loss: 1.7565 - accuracy: 0.4706\n",
"start index for training is 802000\n",
"Train on 13005 samples, validate on 13005 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13005/13005 [==============================] - ETA: 0s - loss: 1.8489 - accuracy: 0.43 - 1s 65us/sample - loss: 1.8505 - accuracy: 0.4381\n",
"13005/13005 [==============================] - 1s 52us/sample - loss: 1.8474 - accuracy: 0.4343s - loss: 1.832\n",
"5980/5980 [==============================] - 0s 61us/sample - loss: 2.2106 - accuracy: 0.2855\n",
"12255/12255 [==============================] - 1s 53us/sample - loss: 2.1369 - accuracy: 0.2950\n",
"14070/14070 [==============================] - 1s 55us/sample - loss: 2.0349 - accuracy: 0.3677\n",
"11565/11565 [==============================] - 1s 58us/sample - loss: 1.8070 - accuracy: 0.4444\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 1.8351 - accuracy: 0.4377\n",
"start index for training is 803000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Train on 11635 samples, validate on 11635 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11635/11635 [==============================] - 1s 52us/sample - loss: 1.7986 - accuracy: 0.4418\n",
"11635/11635 [==============================] - 1s 58us/sample - loss: 1.8343 - accuracy: 0.4401\n",
"5980/5980 [==============================] - 0s 55us/sample - loss: 2.0942 - accuracy: 0.3214\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 2.0409 - accuracy: 0.3058\n",
"14070/14070 [==============================] - 1s 68us/sample - loss: 1.8748 - accuracy: 0.4284\n",
"11565/11565 [==============================] - 1s 64us/sample - loss: 1.6892 - accuracy: 0.4834\n",
"7000/7000 [==============================] - 0s 66us/sample - loss: 1.7287 - accuracy: 0.4787\n",
"start index for training is 804000\n",
"Train on 10720 samples, validate on 10725 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10720/10720 [==============================] - 1s 48us/sample - loss: 1.8637 - accuracy: 0.4231\n",
"10725/10725 [==============================] - 1s 49us/sample - loss: 1.8592 - accuracy: 0.4249\n",
"5980/5980 [==============================] - 0s 56us/sample - loss: 2.0901 - accuracy: 0.3356\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 2.0547 - accuracy: 0.3060\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.8783 - accuracy: 0.4172\n",
"11565/11565 [==============================] - 1s 49us/sample - loss: 1.6915 - accuracy: 0.4840\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 1.7248 - accuracy: 0.4793\n",
"start index for training is 805000\n",
"Train on 10290 samples, validate on 10290 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10290/10290 [==============================] - 1s 52us/sample - loss: 1.8908 - accuracy: 0.4177\n",
"10290/10290 [==============================] - 0s 47us/sample - loss: 1.8801 - accuracy: 0.4271\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 2.0931 - accuracy: 0.3395\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 2.0631 - accuracy: 0.3145\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.8907 - accuracy: 0.4267\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.6931 - accuracy: 0.4834\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 1.7150 - accuracy: 0.4879\n",
"start index for training is 806000\n",
"Train on 9845 samples, validate on 9845 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9845/9845 [==============================] - 1s 67us/sample - loss: 1.8680 - accuracy: 0.4244\n",
"9845/9845 [==============================] - 1s 87us/sample - loss: 1.9047 - accuracy: 0.4233\n",
"5980/5980 [==============================] - 0s 77us/sample - loss: 2.0975 - accuracy: 0.3279\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 2.0548 - accuracy: 0.2991\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 1.8832 - accuracy: 0.4278\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 1.6891 - accuracy: 0.4834\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 1.7043 - accuracy: 0.4914\n",
"start index for training is 807000\n",
"Train on 10585 samples, validate on 10590 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10585/10585 [==============================] - 0s 46us/sample - loss: 1.8623 - accuracy: 0.4347\n",
"10590/10590 [==============================] - 0s 43us/sample - loss: 1.8615 - accuracy: 0.4389\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0940 - accuracy: 0.3640\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0489 - accuracy: 0.3127\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.8889 - accuracy: 0.4271\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.6865 - accuracy: 0.4851\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.6894 - accuracy: 0.4979\n",
"start index for training is 808000\n",
"Train on 12235 samples, validate on 12235 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12235/12235 [==============================] - 1s 66us/sample - loss: 1.8247 - accuracy: 0.4390\n",
"12235/12235 [==============================] - 1s 70us/sample - loss: 1.8319 - accuracy: 0.4320\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 2.1322 - accuracy: 0.3528\n",
"12255/12255 [==============================] - 1s 58us/sample - loss: 2.0719 - accuracy: 0.3126\n",
"14070/14070 [==============================] - 1s 58us/sample - loss: 1.9099 - accuracy: 0.4031\n",
"11565/11565 [==============================] - 1s 54us/sample - loss: 1.6887 - accuracy: 0.4726\n",
"7000/7000 [==============================] - 0s 55us/sample - loss: 1.6724 - accuracy: 0.4817\n",
"start index for training is 809000\n",
"Train on 8325 samples, validate on 8330 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8325/8325 [==============================] - 0s 59us/sample - loss: 2.0596 - accuracy: 0.3550\n",
"8330/8330 [==============================] - 0s 55us/sample - loss: 2.0497 - accuracy: 0.3533\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 1.8768 - accuracy: 0.4299\n",
"12255/12255 [==============================] - 1s 56us/sample - loss: 2.0089 - accuracy: 0.3049\n",
"14070/14070 [==============================] - 1s 61us/sample - loss: 1.8810 - accuracy: 0.4078\n",
"11565/11565 [==============================] - 1s 55us/sample - loss: 1.7221 - accuracy: 0.4529\n",
"7000/7000 [==============================] - 0s 54us/sample - loss: 1.7356 - accuracy: 0.4477\n",
"start index for training is 810000\n",
"Train on 12630 samples, validate on 12635 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12630/12630 [==============================] - 1s 62us/sample - loss: 1.7357 - accuracy: 0.4788\n",
"12635/12635 [==============================] - 1s 62us/sample - loss: 1.7410 - accuracy: 0.4739\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 1.6178 - accuracy: 0.5204\n",
"12255/12255 [==============================] - 1s 52us/sample - loss: 1.9939 - accuracy: 0.3147\n",
"14070/14070 [==============================] - 1s 55us/sample - loss: 1.9622 - accuracy: 0.3748\n",
"11565/11565 [==============================] - 1s 52us/sample - loss: 1.8781 - accuracy: 0.3788\n",
"7000/7000 [==============================] - 0s 59us/sample - loss: 1.8929 - accuracy: 0.3726\n",
"start index for training is 811000\n",
"Train on 13040 samples, validate on 13040 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13040/13040 [==============================] - 1s 65us/sample - loss: 1.6982 - accuracy: 0.4663\n",
"13040/13040 [==============================] - 1s 54us/sample - loss: 1.7172 - accuracy: 0.4567\n",
"5980/5980 [==============================] - 0s 59us/sample - loss: 1.5394 - accuracy: 0.5030\n",
"12255/12255 [==============================] - 1s 65us/sample - loss: 2.0067 - accuracy: 0.3221\n",
"14070/14070 [==============================] - 1s 58us/sample - loss: 2.0374 - accuracy: 0.3454\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 1.9712 - accuracy: 0.3749\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 1.9968 - accuracy: 0.3646\n",
"start index for training is 812000\n",
"Train on 13055 samples, validate on 13060 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13055/13055 [==============================] - 1s 55us/sample - loss: 1.6564 - accuracy: 0.4863\n",
"13060/13060 [==============================] - 1s 51us/sample - loss: 1.6628 - accuracy: 0.4870\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"5980/5980 [==============================] - 0s 49us/sample - loss: 1.4766 - accuracy: 0.5181\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 1.9848 - accuracy: 0.3253\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.0149 - accuracy: 0.3500\n",
"11565/11565 [==============================] - 1s 78us/sample - loss: 1.9996 - accuracy: 0.3517\n",
"7000/7000 [==============================] - 1s 91us/sample - loss: 2.0190 - accuracy: 0.3389\n",
"start index for training is 813000\n",
"Train on 13385 samples, validate on 13390 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13385/13385 [==============================] - 1s 55us/sample - loss: 1.5724 - accuracy: 0.5139\n",
"13390/13390 [==============================] - 1s 49us/sample - loss: 1.5853 - accuracy: 0.5114\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.4161 - accuracy: 0.5585\n",
"12255/12255 [==============================] - 1s 50us/sample - loss: 1.9914 - accuracy: 0.3173\n",
"14070/14070 [==============================] - 1s 54us/sample - loss: 2.0421 - accuracy: 0.3446\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.0392 - accuracy: 0.3336\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.0701 - accuracy: 0.3223\n",
"start index for training is 814000\n",
"Train on 12685 samples, validate on 12690 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12685/12685 [==============================] - 1s 50us/sample - loss: 1.5400 - accuracy: 0.5217\n",
"12690/12690 [==============================] - 1s 52us/sample - loss: 1.5450 - accuracy: 0.5193\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 1.3978 - accuracy: 0.5649\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 2.0043 - accuracy: 0.3254\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 2.0578 - accuracy: 0.3432\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.0654 - accuracy: 0.3272\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.1011 - accuracy: 0.3151\n",
"start index for training is 815000\n",
"Train on 11745 samples, validate on 11745 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11745/11745 [==============================] - ETA: 0s - loss: 1.5117 - accuracy: 0.53 - 1s 50us/sample - loss: 1.5117 - accuracy: 0.5361\n",
"11745/11745 [==============================] - 0s 42us/sample - loss: 1.5156 - accuracy: 0.5426\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.3802 - accuracy: 0.5550\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 2.0002 - accuracy: 0.3350\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.0749 - accuracy: 0.3431\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.0838 - accuracy: 0.3326\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.1203 - accuracy: 0.3327\n",
"start index for training is 816000\n",
"Train on 11855 samples, validate on 11855 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11855/11855 [==============================] - 1s 50us/sample - loss: 1.4833 - accuracy: 0.5403\n",
"11855/11855 [==============================] - 0s 42us/sample - loss: 1.4938 - accuracy: 0.5361s - loss: 1.5053 - \n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.3603 - accuracy: 0.5540\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.9943 - accuracy: 0.3400\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.0980 - accuracy: 0.3356\n",
"11565/11565 [==============================] - 1s 51us/sample - loss: 2.1040 - accuracy: 0.3373\n",
"7000/7000 [==============================] - 0s 62us/sample - loss: 2.1482 - accuracy: 0.3354\n",
"start index for training is 817000\n",
"Train on 13405 samples, validate on 13405 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13405/13405 [==============================] - 1s 50us/sample - loss: 1.4750 - accuracy: 0.5376\n",
"13405/13405 [==============================] - 1s 47us/sample - loss: 1.4847 - accuracy: 0.5402\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.3574 - accuracy: 0.5930\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.9826 - accuracy: 0.3396\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.1130 - accuracy: 0.3216\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.1292 - accuracy: 0.3130\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.1766 - accuracy: 0.3081\n",
"start index for training is 818000\n",
"Train on 12475 samples, validate on 12475 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12475/12475 [==============================] - 1s 50us/sample - loss: 1.5066 - accuracy: 0.5257\n",
"12475/12475 [==============================] - 1s 43us/sample - loss: 1.5309 - accuracy: 0.5139\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.3601 - accuracy: 0.5848\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.9682 - accuracy: 0.3421\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.1347 - accuracy: 0.3190\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.1402 - accuracy: 0.3096\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.1933 - accuracy: 0.3014\n",
"start index for training is 819000\n",
"Train on 13230 samples, validate on 13230 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13230/13230 [==============================] - 1s 46us/sample - loss: 1.5131 - accuracy: 0.5160\n",
"13230/13230 [==============================] - 1s 44us/sample - loss: 1.5117 - accuracy: 0.5161\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.3618 - accuracy: 0.5612\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.9303 - accuracy: 0.3543\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.1322 - accuracy: 0.3306\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.1371 - accuracy: 0.3308\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.1968 - accuracy: 0.3236\n",
"start index for training is 820000\n",
"Train on 13470 samples, validate on 13470 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13470/13470 [==============================] - 1s 46us/sample - loss: 1.5080 - accuracy: 0.5126\n",
"13470/13470 [==============================] - 1s 45us/sample - loss: 1.5081 - accuracy: 0.5134\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.3724 - accuracy: 0.5493\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.8970 - accuracy: 0.3665\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.1375 - accuracy: 0.3339\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1421 - accuracy: 0.3287\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2008 - accuracy: 0.3209\n",
"start index for training is 821000\n",
"Train on 12995 samples, validate on 13000 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12995/12995 [==============================] - 1s 48us/sample - loss: 1.5094 - accuracy: 0.5093\n",
"13000/13000 [==============================] - 1s 44us/sample - loss: 1.5332 - accuracy: 0.5030\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.3853 - accuracy: 0.5569\n",
"12255/12255 [==============================] - 1s 50us/sample - loss: 1.8862 - accuracy: 0.3690\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.1586 - accuracy: 0.3314\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.1661 - accuracy: 0.3258\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.2295 - accuracy: 0.3220\n",
"start index for training is 822000\n",
"Train on 13765 samples, validate on 13770 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13765/13765 [==============================] - 1s 47us/sample - loss: 1.5554 - accuracy: 0.4908\n",
"13770/13770 [==============================] - 1s 42us/sample - loss: 1.5437 - accuracy: 0.4926\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.3988 - accuracy: 0.5900\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.8674 - accuracy: 0.3640\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.1427 - accuracy: 0.3151\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.1586 - accuracy: 0.3094\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2197 - accuracy: 0.2954\n",
"start index for training is 823000\n",
"Train on 12720 samples, validate on 12720 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12720/12720 [==============================] - 1s 56us/sample - loss: 1.5395 - accuracy: 0.5009\n",
"12720/12720 [==============================] - 1s 64us/sample - loss: 1.5944 - accuracy: 0.4762\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.4013 - accuracy: 0.5488\n",
"12255/12255 [==============================] - 1s 54us/sample - loss: 1.8495 - accuracy: 0.3734\n",
"14070/14070 [==============================] - 1s 54us/sample - loss: 2.1509 - accuracy: 0.3198\n",
"11565/11565 [==============================] - 1s 56us/sample - loss: 2.1645 - accuracy: 0.3153\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.2300 - accuracy: 0.3086\n",
"start index for training is 824000\n",
"Train on 12710 samples, validate on 12710 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12710/12710 [==============================] - 1s 46us/sample - loss: 1.5539 - accuracy: 0.4899\n",
"12710/12710 [==============================] - 1s 45us/sample - loss: 1.5697 - accuracy: 0.4826\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.4080 - accuracy: 0.5923\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.8214 - accuracy: 0.3858\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.1513 - accuracy: 0.3118\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.1685 - accuracy: 0.3087\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2422 - accuracy: 0.2951\n",
"start index for training is 825000\n",
"Train on 12575 samples, validate on 12575 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12575/12575 [==============================] - 1s 59us/sample - loss: 1.5555 - accuracy: 0.4882\n",
"12575/12575 [==============================] - 1s 50us/sample - loss: 1.5751 - accuracy: 0.4787\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.4266 - accuracy: 0.5788\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.7962 - accuracy: 0.3842\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.1721 - accuracy: 0.3070\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1815 - accuracy: 0.3037\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2490 - accuracy: 0.2933\n",
"start index for training is 826000\n",
"Train on 12540 samples, validate on 12540 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12540/12540 [==============================] - 1s 46us/sample - loss: 1.5514 - accuracy: 0.4793\n",
"12540/12540 [==============================] - 1s 43us/sample - loss: 1.5564 - accuracy: 0.4794\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.4339 - accuracy: 0.5926\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.7812 - accuracy: 0.3946\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 2.1665 - accuracy: 0.3026\n",
"11565/11565 [==============================] - 1s 70us/sample - loss: 2.1865 - accuracy: 0.3081\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2577 - accuracy: 0.2941\n",
"start index for training is 827000\n",
"Train on 12035 samples, validate on 12035 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12035/12035 [==============================] - 1s 52us/sample - loss: 1.5684 - accuracy: 0.4744\n",
"12035/12035 [==============================] - 1s 51us/sample - loss: 1.5907 - accuracy: 0.4656\n",
"5980/5980 [==============================] - 0s 53us/sample - loss: 1.4537 - accuracy: 0.5480\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 1.7590 - accuracy: 0.4196\n",
"14070/14070 [==============================] - 1s 51us/sample - loss: 2.2107 - accuracy: 0.2949\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.2035 - accuracy: 0.3054\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.2664 - accuracy: 0.2980\n",
"start index for training is 828000\n",
"Train on 11915 samples, validate on 11915 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11915/11915 [==============================] - 1s 67us/sample - loss: 1.5430 - accuracy: 0.4885\n",
"11915/11915 [==============================] - 1s 65us/sample - loss: 1.5661 - accuracy: 0.4817\n",
"5980/5980 [==============================] - 0s 64us/sample - loss: 1.4618 - accuracy: 0.5592\n",
"12255/12255 [==============================] - 1s 61us/sample - loss: 1.7330 - accuracy: 0.4140\n",
"14070/14070 [==============================] - 1s 60us/sample - loss: 2.1992 - accuracy: 0.2961\n",
"11565/11565 [==============================] - 1s 61us/sample - loss: 2.2131 - accuracy: 0.3033\n",
"7000/7000 [==============================] - 0s 56us/sample - loss: 2.2869 - accuracy: 0.2904\n",
"start index for training is 829000\n",
"Train on 11590 samples, validate on 11590 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11590/11590 [==============================] - 1s 67us/sample - loss: 1.5374 - accuracy: 0.4878\n",
"11590/11590 [==============================] - 1s 55us/sample - loss: 1.5666 - accuracy: 0.4815\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.4724 - accuracy: 0.5607\n",
"12255/12255 [==============================] - 1s 50us/sample - loss: 1.7117 - accuracy: 0.4200\n",
"14070/14070 [==============================] - 1s 58us/sample - loss: 2.1991 - accuracy: 0.2926\n",
"11565/11565 [==============================] - 1s 62us/sample - loss: 2.2076 - accuracy: 0.3064\n",
"7000/7000 [==============================] - 0s 54us/sample - loss: 2.2847 - accuracy: 0.2919\n",
"start index for training is 830000\n",
"Train on 10340 samples, validate on 10345 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10340/10340 [==============================] - 1s 61us/sample - loss: 1.5589 - accuracy: 0.4767\n",
"10345/10345 [==============================] - 1s 53us/sample - loss: 1.5889 - accuracy: 0.4635\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.4913 - accuracy: 0.5468\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 1.6910 - accuracy: 0.4255\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.2265 - accuracy: 0.2846\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.2194 - accuracy: 0.3058\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2968 - accuracy: 0.2921\n",
"start index for training is 831000\n",
"Train on 9890 samples, validate on 9890 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"9890/9890 [==============================] - 1s 55us/sample - loss: 1.5735 - accuracy: 0.4730\n",
"9890/9890 [==============================] - 0s 51us/sample - loss: 1.5780 - accuracy: 0.4623\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.5143 - accuracy: 0.5510\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 1.6595 - accuracy: 0.4313\n",
"14070/14070 [==============================] - 1s 51us/sample - loss: 2.2318 - accuracy: 0.2848\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.2138 - accuracy: 0.3030\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.2836 - accuracy: 0.2919\n",
"start index for training is 832000\n",
"Train on 11425 samples, validate on 11430 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11425/11425 [==============================] - 1s 54us/sample - loss: 1.5240 - accuracy: 0.4966\n",
"11430/11430 [==============================] - 1s 55us/sample - loss: 1.5211 - accuracy: 0.4890\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 1.5419 - accuracy: 0.5273\n",
"12255/12255 [==============================] - 1s 58us/sample - loss: 1.6353 - accuracy: 0.4555\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 2.2484 - accuracy: 0.2783\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.2213 - accuracy: 0.3138\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.2938 - accuracy: 0.2974\n",
"start index for training is 833000\n",
"Train on 10500 samples, validate on 10500 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10500/10500 [==============================] - 0s 47us/sample - loss: 1.5667 - accuracy: 0.4792\n",
"10500/10500 [==============================] - 0s 43us/sample - loss: 1.5715 - accuracy: 0.4702\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.5472 - accuracy: 0.5194\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.6118 - accuracy: 0.4615\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2429 - accuracy: 0.2864\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.2095 - accuracy: 0.3136\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2817 - accuracy: 0.3070\n",
"start index for training is 834000\n",
"Train on 10495 samples, validate on 10500 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10495/10495 [==============================] - 0s 47us/sample - loss: 1.5262 - accuracy: 0.4985\n",
"10500/10500 [==============================] - 0s 46us/sample - loss: 1.5862 - accuracy: 0.4683\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.5630 - accuracy: 0.4970\n",
"12255/12255 [==============================] - ETA: 0s - loss: 1.6015 - accuracy: 0.46 - 1s 42us/sample - loss: 1.5994 - accuracy: 0.4672\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2495 - accuracy: 0.2982\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2205 - accuracy: 0.3176\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2978 - accuracy: 0.3053\n",
"start index for training is 835000\n",
"Train on 10460 samples, validate on 10460 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10460/10460 [==============================] - 0s 46us/sample - loss: 1.5569 - accuracy: 0.4833\n",
"10460/10460 [==============================] - 0s 41us/sample - loss: 1.5535 - accuracy: 0.4812\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.5460 - accuracy: 0.5333\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.5774 - accuracy: 0.4706\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2454 - accuracy: 0.2751\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2015 - accuracy: 0.3028\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2754 - accuracy: 0.2916\n",
"start index for training is 836000\n",
"Train on 10645 samples, validate on 10650 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10645/10645 [==============================] - 1s 49us/sample - loss: 1.5287 - accuracy: 0.4951\n",
"10650/10650 [==============================] - 0s 45us/sample - loss: 1.5641 - accuracy: 0.4870\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5706 - accuracy: 0.5145\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.5581 - accuracy: 0.4817\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2640 - accuracy: 0.2845\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2029 - accuracy: 0.3142\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2714 - accuracy: 0.3031\n",
"start index for training is 837000\n",
"Train on 11015 samples, validate on 11015 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11015/11015 [==============================] - 1s 46us/sample - loss: 1.6130 - accuracy: 0.4803\n",
"11015/11015 [==============================] - 0s 43us/sample - loss: 1.6116 - accuracy: 0.4804\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.6201 - accuracy: 0.4848\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.6019 - accuracy: 0.4778\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.3404 - accuracy: 0.2792\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2495 - accuracy: 0.3062s - loss: 2.3469 - \n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3171 - accuracy: 0.2986\n",
"start index for training is 838000\n",
"Train on 11165 samples, validate on 11170 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11165/11165 [==============================] - 1s 46us/sample - loss: 1.5365 - accuracy: 0.4954\n",
"11170/11170 [==============================] - 0s 45us/sample - loss: 1.5769 - accuracy: 0.4845\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.5723 - accuracy: 0.5196\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.5446 - accuracy: 0.4830\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.2741 - accuracy: 0.2769\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.2068 - accuracy: 0.3162\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2776 - accuracy: 0.3040\n",
"start index for training is 839000\n",
"Train on 10850 samples, validate on 10855 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10850/10850 [==============================] - 1s 47us/sample - loss: 1.5312 - accuracy: 0.5094\n",
"10855/10855 [==============================] - 0s 45us/sample - loss: 1.5617 - accuracy: 0.4931\n",
"5980/5980 [==============================] - 0s 46us/sample - loss: 1.5898 - accuracy: 0.5080\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.5350 - accuracy: 0.4845\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.2827 - accuracy: 0.2859\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.1909 - accuracy: 0.3249\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2584 - accuracy: 0.3096\n",
"start index for training is 840000\n",
"Train on 10300 samples, validate on 10300 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10300/10300 [==============================] - 0s 45us/sample - loss: 1.5604 - accuracy: 0.5038\n",
"10300/10300 [==============================] - 0s 45us/sample - loss: 1.5779 - accuracy: 0.4945\n",
"5980/5980 [==============================] - 0s 46us/sample - loss: 1.5878 - accuracy: 0.4881\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.5388 - accuracy: 0.4843\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.2716 - accuracy: 0.2856\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.1824 - accuracy: 0.3255\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2483 - accuracy: 0.3089\n",
"start index for training is 841000\n",
"Train on 9805 samples, validate on 9805 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9805/9805 [==============================] - 0s 48us/sample - loss: 1.5958 - accuracy: 0.4990\n",
"9805/9805 [==============================] - 0s 43us/sample - loss: 1.5975 - accuracy: 0.4989\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.5778 - accuracy: 0.4843\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.5324 - accuracy: 0.4862\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2692 - accuracy: 0.2882\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.1766 - accuracy: 0.3309\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2458 - accuracy: 0.3146\n",
"start index for training is 842000\n",
"Train on 9570 samples, validate on 9575 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9570/9570 [==============================] - 0s 47us/sample - loss: 1.6408 - accuracy: 0.4728\n",
"9575/9575 [==============================] - 0s 43us/sample - loss: 1.6514 - accuracy: 0.4705\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5955 - accuracy: 0.4749\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.5356 - accuracy: 0.4877\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.2860 - accuracy: 0.2881\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.1752 - accuracy: 0.3195\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2433 - accuracy: 0.3124\n",
"start index for training is 843000\n",
"Train on 10600 samples, validate on 10605 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10600/10600 [==============================] - 0s 46us/sample - loss: 1.6008 - accuracy: 0.4922\n",
"10605/10605 [==============================] - 0s 42us/sample - loss: 1.6039 - accuracy: 0.4917\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.6214 - accuracy: 0.4868\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.5494 - accuracy: 0.4854\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2977 - accuracy: 0.2888\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.1833 - accuracy: 0.3287\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.2521 - accuracy: 0.3161\n",
"start index for training is 844000\n",
"Train on 10410 samples, validate on 10415 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10410/10410 [==============================] - 0s 47us/sample - loss: 1.6027 - accuracy: 0.5097\n",
"10415/10415 [==============================] - 0s 43us/sample - loss: 1.6413 - accuracy: 0.4945\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.6298 - accuracy: 0.4838\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.5608 - accuracy: 0.4876\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.3094 - accuracy: 0.2844\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.1825 - accuracy: 0.3310\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2495 - accuracy: 0.3203\n",
"start index for training is 845000\n",
"Train on 9915 samples, validate on 9920 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9915/9915 [==============================] - 0s 48us/sample - loss: 1.6169 - accuracy: 0.5011\n",
"9920/9920 [==============================] - 0s 43us/sample - loss: 1.6639 - accuracy: 0.4853\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.6305 - accuracy: 0.4977\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.5621 - accuracy: 0.4863\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.2879 - accuracy: 0.2941\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.1819 - accuracy: 0.3296\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.2481 - accuracy: 0.3173\n",
"start index for training is 846000\n",
"Train on 8145 samples, validate on 8150 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8145/8145 [==============================] - 0s 48us/sample - loss: 1.7469 - accuracy: 0.4597\n",
"8150/8150 [==============================] - 0s 44us/sample - loss: 1.7626 - accuracy: 0.4647\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.7026 - accuracy: 0.4809\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.6068 - accuracy: 0.4847\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.3395 - accuracy: 0.2893\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.1968 - accuracy: 0.3299\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2564 - accuracy: 0.3236\n",
"start index for training is 847000\n",
"Train on 10210 samples, validate on 10215 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10210/10210 [==============================] - 1s 49us/sample - loss: 1.6485 - accuracy: 0.4916\n",
"10215/10215 [==============================] - 0s 47us/sample - loss: 1.6605 - accuracy: 0.4928\n",
"5980/5980 [==============================] - 0s 53us/sample - loss: 1.6653 - accuracy: 0.4697\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.5927 - accuracy: 0.4738\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.3128 - accuracy: 0.2856\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1964 - accuracy: 0.3198\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2608 - accuracy: 0.3094\n",
"start index for training is 848000\n",
"Train on 9465 samples, validate on 9465 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9465/9465 [==============================] - 0s 48us/sample - loss: 1.6677 - accuracy: 0.4947\n",
"9465/9465 [==============================] - 0s 45us/sample - loss: 1.6670 - accuracy: 0.4894\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.6728 - accuracy: 0.4834\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.6073 - accuracy: 0.4750\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.3178 - accuracy: 0.2824\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.2018 - accuracy: 0.3149\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2709 - accuracy: 0.3054\n",
"start index for training is 849000\n",
"Train on 7870 samples, validate on 7870 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7870/7870 [==============================] - 0s 49us/sample - loss: 1.7529 - accuracy: 0.4560\n",
"7870/7870 [==============================] - 0s 48us/sample - loss: 1.7655 - accuracy: 0.4511\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7002 - accuracy: 0.4724\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.6297 - accuracy: 0.4623\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.3239 - accuracy: 0.2852\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.2173 - accuracy: 0.3139\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2814 - accuracy: 0.3047\n",
"start index for training is 850000\n",
"Train on 9565 samples, validate on 9570 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9565/9565 [==============================] - 0s 47us/sample - loss: 1.7079 - accuracy: 0.4697\n",
"9570/9570 [==============================] - 0s 43us/sample - loss: 1.7065 - accuracy: 0.4788\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.6650 - accuracy: 0.4843\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.6358 - accuracy: 0.4588\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.2869 - accuracy: 0.2955\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.2047 - accuracy: 0.3125\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.2669 - accuracy: 0.3006\n",
"start index for training is 851000\n",
"Train on 8975 samples, validate on 8980 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8975/8975 [==============================] - 0s 49us/sample - loss: 1.7150 - accuracy: 0.4758\n",
"8980/8980 [==============================] - 0s 45us/sample - loss: 1.7309 - accuracy: 0.4697\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.6839 - accuracy: 0.4763\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.6594 - accuracy: 0.4553\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.3019 - accuracy: 0.2940\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.2228 - accuracy: 0.3108\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.2889 - accuracy: 0.3006\n",
"start index for training is 852000\n",
"Train on 7880 samples, validate on 7880 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7880/7880 [==============================] - 0s 50us/sample - loss: 1.7890 - accuracy: 0.4494\n",
"7880/7880 [==============================] - 0s 52us/sample - loss: 1.8028 - accuracy: 0.4381\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 1.6583 - accuracy: 0.4855\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.6410 - accuracy: 0.4534\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.2470 - accuracy: 0.2938\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.1961 - accuracy: 0.3123\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2672 - accuracy: 0.2989\n",
"start index for training is 853000\n",
"Train on 12265 samples, validate on 12270 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12265/12265 [==============================] - 1s 54us/sample - loss: 1.6094 - accuracy: 0.4993\n",
"12270/12270 [==============================] - 1s 52us/sample - loss: 1.6104 - accuracy: 0.4993\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.7154 - accuracy: 0.4614\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.8231 - accuracy: 0.3931\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.8532 - accuracy: 0.4171\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.0734 - accuracy: 0.3355\n",
"7000/7000 [==============================] - 0s 48us/sample - loss: 2.1549 - accuracy: 0.3106\n",
"start index for training is 854000\n",
"Train on 13285 samples, validate on 13285 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13285/13285 [==============================] - 1s 48us/sample - loss: 1.5840 - accuracy: 0.5145\n",
"13285/13285 [==============================] - 1s 46us/sample - loss: 1.5874 - accuracy: 0.5128\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7708 - accuracy: 0.4313\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.8705 - accuracy: 0.3756\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.7946 - accuracy: 0.4349\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.0447 - accuracy: 0.3520\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.1289 - accuracy: 0.3233\n",
"start index for training is 855000\n",
"Train on 12945 samples, validate on 12945 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12945/12945 [==============================] - 1s 47us/sample - loss: 1.5433 - accuracy: 0.5161\n",
"12945/12945 [==============================] - 1s 46us/sample - loss: 1.5321 - accuracy: 0.5236\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.8084 - accuracy: 0.4100\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.9326 - accuracy: 0.3554\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.7542 - accuracy: 0.4461\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.0616 - accuracy: 0.3557\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.1581 - accuracy: 0.3250\n",
"start index for training is 856000\n",
"Train on 13420 samples, validate on 13420 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13420/13420 [==============================] - 1s 48us/sample - loss: 1.4498 - accuracy: 0.5464\n",
"13420/13420 [==============================] - 1s 47us/sample - loss: 1.4667 - accuracy: 0.5491\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.8373 - accuracy: 0.3798\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.9697 - accuracy: 0.3265\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.7336 - accuracy: 0.4655\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.0692 - accuracy: 0.3441\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.1713 - accuracy: 0.3136\n",
"start index for training is 857000\n",
"Train on 12320 samples, validate on 12325 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12320/12320 [==============================] - 1s 51us/sample - loss: 1.4351 - accuracy: 0.5470\n",
"12325/12325 [==============================] - 1s 48us/sample - loss: 1.4288 - accuracy: 0.5524\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.8690 - accuracy: 0.3789\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.9756 - accuracy: 0.3492\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 1.7248 - accuracy: 0.4524\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 2.0547 - accuracy: 0.3575\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.1522 - accuracy: 0.3309\n",
"start index for training is 858000\n",
"Train on 12875 samples, validate on 12875 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12875/12875 [==============================] - 1s 52us/sample - loss: 1.3643 - accuracy: 0.5722\n",
"12875/12875 [==============================] - 1s 52us/sample - loss: 1.3621 - accuracy: 0.5741\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 1.9071 - accuracy: 0.3533\n",
"12255/12255 [==============================] - 1s 50us/sample - loss: 2.0150 - accuracy: 0.3231\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 1.7084 - accuracy: 0.4729\n",
"11565/11565 [==============================] - 1s 49us/sample - loss: 2.0740 - accuracy: 0.3603\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.1845 - accuracy: 0.3239\n",
"start index for training is 859000\n",
"Train on 14815 samples, validate on 14815 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14815/14815 [==============================] - 1s 55us/sample - loss: 1.3701 - accuracy: 0.5702\n",
"14815/14815 [==============================] - 1s 48us/sample - loss: 1.3681 - accuracy: 0.5687\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.9419 - accuracy: 0.3391\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 1s 50us/sample - loss: 2.0191 - accuracy: 0.3137\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 1.7013 - accuracy: 0.4751\n",
"11565/11565 [==============================] - 1s 52us/sample - loss: 2.0848 - accuracy: 0.3383\n",
"7000/7000 [==============================] - 0s 52us/sample - loss: 2.2000 - accuracy: 0.3001\n",
"start index for training is 860000\n",
"Train on 14960 samples, validate on 14965 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14960/14960 [==============================] - 1s 49us/sample - loss: 1.3609 - accuracy: 0.5733\n",
"14965/14965 [==============================] - 1s 50us/sample - loss: 1.3901 - accuracy: 0.5721\n",
"5980/5980 [==============================] - 0s 52us/sample - loss: 1.9673 - accuracy: 0.3344\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 2.0368 - accuracy: 0.3129\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 1.6997 - accuracy: 0.4767\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 2.0817 - accuracy: 0.3486\n",
"7000/7000 [==============================] - 0s 57us/sample - loss: 2.2003 - accuracy: 0.3126\n",
"start index for training is 861000\n",
"Train on 15310 samples, validate on 15315 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15310/15310 [==============================] - 1s 54us/sample - loss: 1.3613 - accuracy: 0.5769\n",
"15315/15315 [==============================] - 1s 54us/sample - loss: 1.3718 - accuracy: 0.5742\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 1.9937 - accuracy: 0.3468\n",
"12255/12255 [==============================] - 1s 56us/sample - loss: 2.0288 - accuracy: 0.3141\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 1.7139 - accuracy: 0.4794\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.0764 - accuracy: 0.3452\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.1915 - accuracy: 0.3099\n",
"start index for training is 862000\n",
"Train on 15900 samples, validate on 15905 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15900/15900 [==============================] - 1s 49us/sample - loss: 1.3537 - accuracy: 0.5782\n",
"15905/15905 [==============================] - 1s 48us/sample - loss: 1.3728 - accuracy: 0.5723\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.0049 - accuracy: 0.3441\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 2.0431 - accuracy: 0.3279\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.7197 - accuracy: 0.4879\n",
"11565/11565 [==============================] - 1s 49us/sample - loss: 2.0831 - accuracy: 0.3711\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.2047 - accuracy: 0.3411\n",
"start index for training is 863000\n",
"Train on 14515 samples, validate on 14515 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14515/14515 [==============================] - 1s 57us/sample - loss: 1.4188 - accuracy: 0.5494\n",
"14515/14515 [==============================] - 1s 55us/sample - loss: 1.4310 - accuracy: 0.5482\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 2.0189 - accuracy: 0.3334\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 2.0665 - accuracy: 0.3093\n",
"14070/14070 [==============================] - 1s 52us/sample - loss: 1.7211 - accuracy: 0.4760\n",
"11565/11565 [==============================] - 1s 54us/sample - loss: 2.0932 - accuracy: 0.3436\n",
"7000/7000 [==============================] - 0s 53us/sample - loss: 2.2217 - accuracy: 0.3091\n",
"start index for training is 864000\n",
"Train on 13520 samples, validate on 13525 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13520/13520 [==============================] - 1s 47us/sample - loss: 1.4379 - accuracy: 0.5459\n",
"13525/13525 [==============================] - 1s 41us/sample - loss: 1.4560 - accuracy: 0.5395\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0058 - accuracy: 0.3324\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.0437 - accuracy: 0.3247\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7112 - accuracy: 0.4824\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.0500 - accuracy: 0.3720\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.1696 - accuracy: 0.3396\n",
"start index for training is 865000\n",
"Train on 14125 samples, validate on 14125 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"14125/14125 [==============================] - 1s 49us/sample - loss: 1.4329 - accuracy: 0.5447\n",
"14125/14125 [==============================] - 1s 50us/sample - loss: 1.4265 - accuracy: 0.5422\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0080 - accuracy: 0.3405\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0438 - accuracy: 0.3275\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.7112 - accuracy: 0.4803\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.0415 - accuracy: 0.3737\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.1690 - accuracy: 0.3484\n",
"start index for training is 866000\n",
"Train on 13975 samples, validate on 13975 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13975/13975 [==============================] - 1s 43us/sample - loss: 1.4093 - accuracy: 0.5449\n",
"13975/13975 [==============================] - 1s 39us/sample - loss: 1.3999 - accuracy: 0.5522\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.0314 - accuracy: 0.3468\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0551 - accuracy: 0.3125\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.7222 - accuracy: 0.4768\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.0349 - accuracy: 0.3592s - loss: 2.0641 \n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.1607 - accuracy: 0.3297\n",
"start index for training is 867000\n",
"Train on 13790 samples, validate on 13795 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13790/13790 [==============================] - 1s 45us/sample - loss: 1.4287 - accuracy: 0.5431\n",
"13795/13795 [==============================] - 1s 41us/sample - loss: 1.4207 - accuracy: 0.5493\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.0280 - accuracy: 0.3463\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 2.0317 - accuracy: 0.3277\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7256 - accuracy: 0.4773\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.9910 - accuracy: 0.3880\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.1163 - accuracy: 0.3576\n",
"start index for training is 868000\n",
"Train on 12190 samples, validate on 12195 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12190/12190 [==============================] - 1s 44us/sample - loss: 1.4371 - accuracy: 0.5473\n",
"12195/12195 [==============================] - 1s 43us/sample - loss: 1.4527 - accuracy: 0.5452\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.0398 - accuracy: 0.3540\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 2.0166 - accuracy: 0.3324\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 1.7364 - accuracy: 0.4692\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 1.9560 - accuracy: 0.3971\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.0784 - accuracy: 0.3669\n",
"start index for training is 869000\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Train on 12085 samples, validate on 12090 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12085/12085 [==============================] - 1s 43us/sample - loss: 1.4344 - accuracy: 0.5491\n",
"12090/12090 [==============================] - 0s 39us/sample - loss: 1.4417 - accuracy: 0.5457\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0315 - accuracy: 0.3391\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0305 - accuracy: 0.3204\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.7426 - accuracy: 0.4650\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.9507 - accuracy: 0.4025\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.0841 - accuracy: 0.3711\n",
"start index for training is 870000\n",
"Train on 12070 samples, validate on 12070 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12070/12070 [==============================] - 1s 46us/sample - loss: 1.4735 - accuracy: 0.5099\n",
"12070/12070 [==============================] - 1s 48us/sample - loss: 1.5025 - accuracy: 0.5041\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.0507 - accuracy: 0.3729\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0464 - accuracy: 0.3452\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.8037 - accuracy: 0.4317\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.9462 - accuracy: 0.3990\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.0598 - accuracy: 0.3799\n",
"start index for training is 871000\n",
"Train on 12280 samples, validate on 12285 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12280/12280 [==============================] - 1s 44us/sample - loss: 1.4182 - accuracy: 0.5529\n",
"12285/12285 [==============================] - 0s 40us/sample - loss: 1.4471 - accuracy: 0.5452\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0207 - accuracy: 0.3594\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0041 - accuracy: 0.3274\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7574 - accuracy: 0.4603\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.9038 - accuracy: 0.4150\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0257 - accuracy: 0.3864\n",
"start index for training is 872000\n",
"Train on 12040 samples, validate on 12045 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12040/12040 [==============================] - 1s 49us/sample - loss: 1.5286 - accuracy: 0.5019\n",
"12045/12045 [==============================] - 1s 42us/sample - loss: 1.5434 - accuracy: 0.5005\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.1084 - accuracy: 0.3263\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.1074 - accuracy: 0.3169\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8221 - accuracy: 0.4436\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.9974 - accuracy: 0.3832\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.1295 - accuracy: 0.3443\n",
"start index for training is 873000\n",
"Train on 13805 samples, validate on 13810 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13805/13805 [==============================] - 1s 42us/sample - loss: 1.4189 - accuracy: 0.5574\n",
"13810/13810 [==============================] - 1s 41us/sample - loss: 1.4264 - accuracy: 0.5514\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 2.0213 - accuracy: 0.3562\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.9952 - accuracy: 0.3306\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.7681 - accuracy: 0.4559\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.8697 - accuracy: 0.4233\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.9935 - accuracy: 0.3899\n",
"start index for training is 874000\n",
"Train on 11485 samples, validate on 11485 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11485/11485 [==============================] - 0s 43us/sample - loss: 1.4972 - accuracy: 0.5343\n",
"11485/11485 [==============================] - 0s 40us/sample - loss: 1.5559 - accuracy: 0.5135\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0173 - accuracy: 0.3590\n",
"12255/12255 [==============================] - 0s 41us/sample - loss: 1.9948 - accuracy: 0.3243\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.7803 - accuracy: 0.4586\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.8444 - accuracy: 0.4335\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9646 - accuracy: 0.4020\n",
"start index for training is 875000\n",
"Train on 13065 samples, validate on 13070 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13065/13065 [==============================] - 1s 43us/sample - loss: 1.4669 - accuracy: 0.5472\n",
"13070/13070 [==============================] - 1s 39us/sample - loss: 1.4694 - accuracy: 0.5457\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0247 - accuracy: 0.3562\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0147 - accuracy: 0.3212\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.7787 - accuracy: 0.4542\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.8281 - accuracy: 0.4374\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.9494 - accuracy: 0.4030\n",
"start index for training is 876000\n",
"Train on 11845 samples, validate on 11850 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11845/11845 [==============================] - 1s 44us/sample - loss: 1.5362 - accuracy: 0.5167\n",
"11850/11850 [==============================] - 0s 40us/sample - loss: 1.5545 - accuracy: 0.5143\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 2.0156 - accuracy: 0.3443\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9815 - accuracy: 0.3214\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.7895 - accuracy: 0.4604\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.7967 - accuracy: 0.4481\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9021 - accuracy: 0.4126\n",
"start index for training is 877000\n",
"Train on 11135 samples, validate on 11135 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11135/11135 [==============================] - 0s 41us/sample - loss: 1.5705 - accuracy: 0.5164\n",
"11135/11135 [==============================] - 0s 39us/sample - loss: 1.5941 - accuracy: 0.5083\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0014 - accuracy: 0.3604\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0019 - accuracy: 0.3246\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.7938 - accuracy: 0.4506\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8025 - accuracy: 0.4526\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 1.9133 - accuracy: 0.4189\n",
"start index for training is 878000\n",
"Train on 10845 samples, validate on 10845 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10845/10845 [==============================] - 0s 45us/sample - loss: 1.5875 - accuracy: 0.5103\n",
"10845/10845 [==============================] - 0s 40us/sample - loss: 1.6048 - accuracy: 0.5041\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0222 - accuracy: 0.3527\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9939 - accuracy: 0.3228\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8105 - accuracy: 0.4554\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.7581 - accuracy: 0.4611\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.8493 - accuracy: 0.4350\n",
"start index for training is 879000\n",
"Train on 12220 samples, validate on 12225 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12220/12220 [==============================] - 1s 42us/sample - loss: 1.5575 - accuracy: 0.5223\n",
"12225/12225 [==============================] - 0s 40us/sample - loss: 1.5477 - accuracy: 0.5258\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0323 - accuracy: 0.3472\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0104 - accuracy: 0.3178\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8177 - accuracy: 0.4577\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.7628 - accuracy: 0.4556\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.8504 - accuracy: 0.4194\n",
"start index for training is 880000\n",
"Train on 11595 samples, validate on 11600 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11595/11595 [==============================] - 1s 46us/sample - loss: 1.6095 - accuracy: 0.5063\n",
"11600/11600 [==============================] - 0s 42us/sample - loss: 1.5948 - accuracy: 0.5155\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 2.0229 - accuracy: 0.3406\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.9895 - accuracy: 0.3223\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8500 - accuracy: 0.4490\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.7320 - accuracy: 0.4701\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.7969 - accuracy: 0.4519\n",
"start index for training is 881000\n",
"Train on 10720 samples, validate on 10720 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10720/10720 [==============================] - 0s 39us/sample - loss: 1.6636 - accuracy: 0.4889\n",
"10720/10720 [==============================] - 0s 39us/sample - loss: 1.6365 - accuracy: 0.5021\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0167 - accuracy: 0.3515\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0024 - accuracy: 0.3098\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8417 - accuracy: 0.4438\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.7132 - accuracy: 0.4746\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.7724 - accuracy: 0.4589\n",
"start index for training is 882000\n",
"Train on 9920 samples, validate on 9920 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9920/9920 [==============================] - 0s 40us/sample - loss: 1.6993 - accuracy: 0.4805\n",
"9920/9920 [==============================] - 0s 38us/sample - loss: 1.6844 - accuracy: 0.4816s - loss: 1.6692 - ac\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 2.0073 - accuracy: 0.3458\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.9946 - accuracy: 0.3251\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.8356 - accuracy: 0.4477\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.7109 - accuracy: 0.4655\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 1.7649 - accuracy: 0.4571\n",
"start index for training is 883000\n",
"Train on 9325 samples, validate on 9325 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9325/9325 [==============================] - 0s 41us/sample - loss: 1.7474 - accuracy: 0.4590\n",
"9325/9325 [==============================] - 0s 39us/sample - loss: 1.7523 - accuracy: 0.4639\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 2.0289 - accuracy: 0.3436\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 2.0036 - accuracy: 0.3122\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.8469 - accuracy: 0.4409\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.6994 - accuracy: 0.4785\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.7380 - accuracy: 0.4653\n",
"start index for training is 884000\n",
"Train on 10310 samples, validate on 10315 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10310/10310 [==============================] - 0s 43us/sample - loss: 1.6921 - accuracy: 0.4838\n",
"10315/10315 [==============================] - 0s 41us/sample - loss: 1.6927 - accuracy: 0.4860\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 2.0518 - accuracy: 0.3355\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0076 - accuracy: 0.3131\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8853 - accuracy: 0.4301\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.6946 - accuracy: 0.4794\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.7163 - accuracy: 0.4817\n",
"start index for training is 885000\n",
"Train on 10280 samples, validate on 10280 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10280/10280 [==============================] - 0s 42us/sample - loss: 1.7025 - accuracy: 0.4827\n",
"10280/10280 [==============================] - 0s 41us/sample - loss: 1.6983 - accuracy: 0.4839\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 2.0452 - accuracy: 0.3318\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0194 - accuracy: 0.3153\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8635 - accuracy: 0.4325\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.6896 - accuracy: 0.4843\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.7000 - accuracy: 0.4889\n",
"start index for training is 886000\n",
"Train on 8915 samples, validate on 8920 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8915/8915 [==============================] - 0s 42us/sample - loss: 1.7957 - accuracy: 0.4370\n",
"8920/8920 [==============================] - 0s 38us/sample - loss: 1.8096 - accuracy: 0.4261\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.7622 - accuracy: 0.4279\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9502 - accuracy: 0.3309\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8564 - accuracy: 0.4249\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.7253 - accuracy: 0.4528\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 1.7394 - accuracy: 0.4496\n",
"start index for training is 887000\n",
"Train on 9390 samples, validate on 9395 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9390/9390 [==============================] - 0s 41us/sample - loss: 1.5748 - accuracy: 0.5159\n",
"9395/9395 [==============================] - 0s 41us/sample - loss: 1.5988 - accuracy: 0.5114\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.4969 - accuracy: 0.5513\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9911 - accuracy: 0.3250\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9615 - accuracy: 0.3903\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.9140 - accuracy: 0.3736\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"7000/7000 [==============================] - 0s 41us/sample - loss: 1.9488 - accuracy: 0.3627\n",
"start index for training is 888000\n",
"Train on 9720 samples, validate on 9725 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9720/9720 [==============================] - 0s 42us/sample - loss: 1.5021 - accuracy: 0.5430\n",
"9725/9725 [==============================] - 0s 40us/sample - loss: 1.5245 - accuracy: 0.5296\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.4133 - accuracy: 0.5808\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9686 - accuracy: 0.3483\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.9964 - accuracy: 0.3726\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.9686 - accuracy: 0.3517\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 1.9967 - accuracy: 0.3429\n",
"start index for training is 889000\n",
"Train on 9395 samples, validate on 9400 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9395/9395 [==============================] - 0s 43us/sample - loss: 1.4882 - accuracy: 0.5440\n",
"9400/9400 [==============================] - 0s 41us/sample - loss: 1.4811 - accuracy: 0.5414\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.3684 - accuracy: 0.5625\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9563 - accuracy: 0.3599\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.0216 - accuracy: 0.3679\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.0029 - accuracy: 0.3610\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.0325 - accuracy: 0.3583\n",
"start index for training is 890000\n",
"Train on 10710 samples, validate on 10715 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10710/10710 [==============================] - 0s 41us/sample - loss: 1.4403 - accuracy: 0.5631\n",
"10715/10715 [==============================] - 0s 39us/sample - loss: 1.4413 - accuracy: 0.5561\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.3306 - accuracy: 0.5824\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.9449 - accuracy: 0.3690\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.0366 - accuracy: 0.3584\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.0317 - accuracy: 0.3588\n",
"7000/7000 [==============================] - 0s 34us/sample - loss: 2.0702 - accuracy: 0.3550\n",
"start index for training is 891000\n",
"Train on 10695 samples, validate on 10695 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10695/10695 [==============================] - 0s 42us/sample - loss: 1.4980 - accuracy: 0.5361\n",
"10695/10695 [==============================] - 1s 47us/sample - loss: 1.4966 - accuracy: 0.5319\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.3157 - accuracy: 0.5808\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 1.9095 - accuracy: 0.3738\n",
"14070/14070 [==============================] - 1s 66us/sample - loss: 2.0407 - accuracy: 0.3542\n",
"11565/11565 [==============================] - 1s 60us/sample - loss: 2.0475 - accuracy: 0.3497\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.0962 - accuracy: 0.3423\n",
"start index for training is 892000\n",
"Train on 11960 samples, validate on 11960 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11960/11960 [==============================] - 1s 43us/sample - loss: 1.4824 - accuracy: 0.5332\n",
"11960/11960 [==============================] - ETA: 0s - loss: 1.4743 - accuracy: 0.53 - 0s 39us/sample - loss: 1.4787 - accuracy: 0.5370\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.3253 - accuracy: 0.5868\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.8951 - accuracy: 0.3755\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0550 - accuracy: 0.3547\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.0687 - accuracy: 0.3542\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1283 - accuracy: 0.3481\n",
"start index for training is 893000\n",
"Train on 11320 samples, validate on 11320 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11320/11320 [==============================] - 0s 42us/sample - loss: 1.5161 - accuracy: 0.5078\n",
"11320/11320 [==============================] - 0s 41us/sample - loss: 1.5149 - accuracy: 0.5092\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.3393 - accuracy: 0.5706\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.8590 - accuracy: 0.3825\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.0845 - accuracy: 0.3455\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.0840 - accuracy: 0.3390\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.1445 - accuracy: 0.3374\n",
"start index for training is 894000\n",
"Train on 11650 samples, validate on 11655 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11650/11650 [==============================] - 0s 39us/sample - loss: 1.5175 - accuracy: 0.5123\n",
"11655/11655 [==============================] - 0s 38us/sample - loss: 1.5261 - accuracy: 0.5088\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.3433 - accuracy: 0.5692\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.8335 - accuracy: 0.3834\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.0693 - accuracy: 0.3496\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.0773 - accuracy: 0.3354\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1463 - accuracy: 0.3307\n",
"start index for training is 895000\n",
"Train on 11290 samples, validate on 11290 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11290/11290 [==============================] - 0s 40us/sample - loss: 1.5367 - accuracy: 0.5014\n",
"11290/11290 [==============================] - 0s 38us/sample - loss: 1.5459 - accuracy: 0.4973\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.3578 - accuracy: 0.6007\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.8124 - accuracy: 0.3834\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0867 - accuracy: 0.3366\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.0910 - accuracy: 0.3299\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.1621 - accuracy: 0.3187\n",
"start index for training is 896000\n",
"Train on 10770 samples, validate on 10775 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10770/10770 [==============================] - 0s 40us/sample - loss: 1.5639 - accuracy: 0.4880\n",
"10775/10775 [==============================] - 0s 41us/sample - loss: 1.5615 - accuracy: 0.4805\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.3754 - accuracy: 0.5946\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.7838 - accuracy: 0.3909\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.0893 - accuracy: 0.3315\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1047 - accuracy: 0.3172\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1814 - accuracy: 0.3033\n",
"start index for training is 897000\n",
"Train on 11390 samples, validate on 11390 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11390/11390 [==============================] - 0s 40us/sample - loss: 1.5332 - accuracy: 0.4948\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11390/11390 [==============================] - 0s 38us/sample - loss: 1.5318 - accuracy: 0.4946\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.3898 - accuracy: 0.6015\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7631 - accuracy: 0.3979\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.0948 - accuracy: 0.3290\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1023 - accuracy: 0.3218\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.1768 - accuracy: 0.3117\n",
"start index for training is 898000\n",
"Train on 10395 samples, validate on 10400 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10395/10395 [==============================] - 0s 42us/sample - loss: 1.5598 - accuracy: 0.4768\n",
"10400/10400 [==============================] - 0s 36us/sample - loss: 1.5709 - accuracy: 0.4717\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.4123 - accuracy: 0.5880\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.7510 - accuracy: 0.4064\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.0942 - accuracy: 0.3387\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.1212 - accuracy: 0.3207\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1975 - accuracy: 0.3041\n",
"start index for training is 899000\n",
"Train on 9795 samples, validate on 9800 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9795/9795 [==============================] - 0s 40us/sample - loss: 1.5704 - accuracy: 0.4828\n",
"9800/9800 [==============================] - 0s 41us/sample - loss: 1.5550 - accuracy: 0.4845\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.4237 - accuracy: 0.5478\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.7181 - accuracy: 0.4020\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.1086 - accuracy: 0.3131\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1168 - accuracy: 0.3106\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.1931 - accuracy: 0.3010\n",
"start index for training is 900000\n",
"Train on 10240 samples, validate on 10240 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10240/10240 [==============================] - 0s 42us/sample - loss: 1.5352 - accuracy: 0.4897\n",
"10240/10240 [==============================] - 0s 38us/sample - loss: 1.5355 - accuracy: 0.4813\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.4505 - accuracy: 0.5298\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.6981 - accuracy: 0.4255\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.1293 - accuracy: 0.3062\n",
"11565/11565 [==============================] - 1s 43us/sample - loss: 2.1466 - accuracy: 0.3185\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.2250 - accuracy: 0.3119\n",
"start index for training is 901000\n",
"Train on 9175 samples, validate on 9180 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9175/9175 [==============================] - 0s 46us/sample - loss: 1.5578 - accuracy: 0.4955\n",
"9180/9180 [==============================] - 0s 43us/sample - loss: 1.5779 - accuracy: 0.4854\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.4764 - accuracy: 0.5370\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.6725 - accuracy: 0.4333\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.1429 - accuracy: 0.3013\n",
"11565/11565 [==============================] - 1s 56us/sample - loss: 2.1420 - accuracy: 0.3127\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.2209 - accuracy: 0.3026\n",
"start index for training is 902000\n",
"Train on 8255 samples, validate on 8260 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8255/8255 [==============================] - 0s 52us/sample - loss: 1.5769 - accuracy: 0.4722\n",
"8260/8260 [==============================] - 0s 45us/sample - loss: 1.5984 - accuracy: 0.4616\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.5191 - accuracy: 0.5015\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.6613 - accuracy: 0.4470\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 2.1843 - accuracy: 0.2959\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1755 - accuracy: 0.3107\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2580 - accuracy: 0.3010\n",
"start index for training is 903000\n",
"Train on 8735 samples, validate on 8735 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8735/8735 [==============================] - 0s 43us/sample - loss: 1.5606 - accuracy: 0.4978\n",
"8735/8735 [==============================] - 0s 42us/sample - loss: 1.5656 - accuracy: 0.4988\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5232 - accuracy: 0.5137\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.6246 - accuracy: 0.4610\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.1953 - accuracy: 0.2886\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1685 - accuracy: 0.3183\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2467 - accuracy: 0.3121\n",
"start index for training is 904000\n",
"Train on 8540 samples, validate on 8545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8540/8540 [==============================] - 0s 42us/sample - loss: 1.5461 - accuracy: 0.4965\n",
"8545/8545 [==============================] - 0s 42us/sample - loss: 1.5293 - accuracy: 0.5047\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.5421 - accuracy: 0.5152\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.6161 - accuracy: 0.4562\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2061 - accuracy: 0.2967\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.1601 - accuracy: 0.3293s - loss: 2.1611 - accuracy: \n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2336 - accuracy: 0.3254\n",
"start index for training is 905000\n",
"Train on 8640 samples, validate on 8640 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8640/8640 [==============================] - 0s 42us/sample - loss: 1.5221 - accuracy: 0.5042\n",
"8640/8640 [==============================] - 0s 41us/sample - loss: 1.5518 - accuracy: 0.4889\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.5589 - accuracy: 0.5214\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.6038 - accuracy: 0.4647\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.2170 - accuracy: 0.2930\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1583 - accuracy: 0.3255\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2348 - accuracy: 0.3213\n",
"start index for training is 906000\n",
"Train on 8230 samples, validate on 8230 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8230/8230 [==============================] - 0s 44us/sample - loss: 1.5536 - accuracy: 0.4948\n",
"8230/8230 [==============================] - 0s 44us/sample - loss: 1.5663 - accuracy: 0.4882\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.5502 - accuracy: 0.4931\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.5837 - accuracy: 0.4607\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.2113 - accuracy: 0.3001\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.1479 - accuracy: 0.3274\n",
"7000/7000 [==============================] - 0s 54us/sample - loss: 2.2266 - accuracy: 0.3269\n",
"start index for training is 907000\n",
"Train on 7940 samples, validate on 7940 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7940/7940 [==============================] - 0s 46us/sample - loss: 1.5536 - accuracy: 0.5081\n",
"7940/7940 [==============================] - 0s 45us/sample - loss: 1.5928 - accuracy: 0.4965\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.5489 - accuracy: 0.5017\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.5763 - accuracy: 0.4711\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.2243 - accuracy: 0.2929\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1491 - accuracy: 0.3243\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2260 - accuracy: 0.3146\n",
"start index for training is 908000\n",
"Train on 7670 samples, validate on 7675 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7670/7670 [==============================] - 0s 46us/sample - loss: 1.5927 - accuracy: 0.4919\n",
"7675/7675 [==============================] - 0s 42us/sample - loss: 1.6338 - accuracy: 0.4706\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.5417 - accuracy: 0.5261\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.5784 - accuracy: 0.4622\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2148 - accuracy: 0.3019\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1426 - accuracy: 0.3235\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2197 - accuracy: 0.3123\n",
"start index for training is 909000\n",
"Train on 7560 samples, validate on 7560 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7560/7560 [==============================] - 0s 40us/sample - loss: 1.6166 - accuracy: 0.4931\n",
"7560/7560 [==============================] - 0s 38us/sample - loss: 1.6109 - accuracy: 0.4917\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.5775 - accuracy: 0.5038\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.5886 - accuracy: 0.4741\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.2317 - accuracy: 0.2990\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.1418 - accuracy: 0.3313\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2186 - accuracy: 0.3216\n",
"start index for training is 910000\n",
"Train on 7445 samples, validate on 7450 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7445/7445 [==============================] - 0s 42us/sample - loss: 1.6187 - accuracy: 0.4954\n",
"7450/7450 [==============================] - 0s 40us/sample - loss: 1.6147 - accuracy: 0.5000\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.5960 - accuracy: 0.4998\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.6003 - accuracy: 0.4722\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 2.2352 - accuracy: 0.2872\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.1460 - accuracy: 0.3297\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.2239 - accuracy: 0.3146\n",
"start index for training is 911000\n",
"Train on 7060 samples, validate on 7065 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7060/7060 [==============================] - 0s 43us/sample - loss: 1.6727 - accuracy: 0.4955\n",
"7065/7065 [==============================] - 0s 43us/sample - loss: 1.7127 - accuracy: 0.4753\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.7221 - accuracy: 0.4749\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 1.6820 - accuracy: 0.4468\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.3823 - accuracy: 0.2788\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.2395 - accuracy: 0.3160\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.3126 - accuracy: 0.3030\n",
"start index for training is 912000\n",
"Train on 7340 samples, validate on 7345 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7340/7340 [==============================] - 0s 41us/sample - loss: 1.6276 - accuracy: 0.5089\n",
"7345/7345 [==============================] - 0s 42us/sample - loss: 1.6388 - accuracy: 0.5006\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.6064 - accuracy: 0.5003\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.6273 - accuracy: 0.4680\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.2403 - accuracy: 0.2916\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1706 - accuracy: 0.3243\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.2484 - accuracy: 0.3120\n",
"start index for training is 913000\n",
"Train on 6955 samples, validate on 6960 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"6955/6955 [==============================] - 0s 42us/sample - loss: 1.6979 - accuracy: 0.4775\n",
"6960/6960 [==============================] - 0s 40us/sample - loss: 1.6865 - accuracy: 0.4894\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5795 - accuracy: 0.5067\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.6482 - accuracy: 0.4594\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.2227 - accuracy: 0.3090\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.1828 - accuracy: 0.3310\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2636 - accuracy: 0.3169\n",
"start index for training is 914000\n",
"Train on 7095 samples, validate on 7095 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7095/7095 [==============================] - 0s 51us/sample - loss: 1.7410 - accuracy: 0.4490\n",
"7095/7095 [==============================] - 0s 51us/sample - loss: 1.7687 - accuracy: 0.4483\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.5797 - accuracy: 0.5092\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.6663 - accuracy: 0.4516\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.0678 - accuracy: 0.3517\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1230 - accuracy: 0.3437\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2008 - accuracy: 0.3311\n",
"start index for training is 915000\n",
"Train on 10010 samples, validate on 10010 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10010/10010 [==============================] - 0s 45us/sample - loss: 1.5229 - accuracy: 0.4918\n",
"10010/10010 [==============================] - 0s 41us/sample - loss: 1.5445 - accuracy: 0.4944\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.8474 - accuracy: 0.4518\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0360 - accuracy: 0.3385\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 1.9558 - accuracy: 0.3952\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.2537 - accuracy: 0.3016\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.3473 - accuracy: 0.2750\n",
"start index for training is 916000\n",
"Train on 9960 samples, validate on 9960 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"9960/9960 [==============================] - 0s 40us/sample - loss: 1.3538 - accuracy: 0.5723\n",
"9960/9960 [==============================] - 0s 44us/sample - loss: 1.3528 - accuracy: 0.5685\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.7687 - accuracy: 0.4191\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9307 - accuracy: 0.3488\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.7300 - accuracy: 0.4547\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.0750 - accuracy: 0.3386\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1640 - accuracy: 0.3061\n",
"start index for training is 917000\n",
"Train on 10520 samples, validate on 10520 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10520/10520 [==============================] - 0s 42us/sample - loss: 1.3249 - accuracy: 0.5866\n",
"10520/10520 [==============================] - 0s 44us/sample - loss: 1.3468 - accuracy: 0.5847\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8179 - accuracy: 0.4107\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.9725 - accuracy: 0.3322\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.6987 - accuracy: 0.4819\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.0660 - accuracy: 0.3511\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1606 - accuracy: 0.3199\n",
"start index for training is 918000\n",
"Train on 11740 samples, validate on 11740 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11740/11740 [==============================] - 1s 43us/sample - loss: 1.3748 - accuracy: 0.5688\n",
"11740/11740 [==============================] - 0s 40us/sample - loss: 1.3738 - accuracy: 0.5766\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.8431 - accuracy: 0.3928\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9743 - accuracy: 0.3389\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.6852 - accuracy: 0.4855\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.0465 - accuracy: 0.3695\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1488 - accuracy: 0.3360\n",
"start index for training is 919000\n",
"Train on 12425 samples, validate on 12425 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12425/12425 [==============================] - 1s 41us/sample - loss: 1.3975 - accuracy: 0.5643\n",
"12425/12425 [==============================] - 0s 37us/sample - loss: 1.3903 - accuracy: 0.5694\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.8757 - accuracy: 0.3846\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0171 - accuracy: 0.3257\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.6824 - accuracy: 0.4748\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.0549 - accuracy: 0.3500\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1680 - accuracy: 0.3156\n",
"start index for training is 920000\n",
"Train on 12755 samples, validate on 12755 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12755/12755 [==============================] - 1s 49us/sample - loss: 1.4016 - accuracy: 0.5610\n",
"12755/12755 [==============================] - 1s 42us/sample - loss: 1.3905 - accuracy: 0.5634\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.9076 - accuracy: 0.3696\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0071 - accuracy: 0.3186\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 1.6769 - accuracy: 0.4810\n",
"11565/11565 [==============================] - 1s 53us/sample - loss: 2.0407 - accuracy: 0.3575\n",
"7000/7000 [==============================] - 0s 60us/sample - loss: 2.1510 - accuracy: 0.3163\n",
"start index for training is 921000\n",
"Train on 12910 samples, validate on 12910 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12910/12910 [==============================] - 1s 62us/sample - loss: 1.4027 - accuracy: 0.5573\n",
"12910/12910 [==============================] - 1s 74us/sample - loss: 1.3919 - accuracy: 0.5596\n",
"5980/5980 [==============================] - 0s 72us/sample - loss: 1.9063 - accuracy: 0.3612\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 2.0008 - accuracy: 0.3187\n",
"14070/14070 [==============================] - 1s 61us/sample - loss: 1.6783 - accuracy: 0.4829\n",
"11565/11565 [==============================] - 1s 59us/sample - loss: 2.0263 - accuracy: 0.3632\n",
"7000/7000 [==============================] - 0s 61us/sample - loss: 2.1414 - accuracy: 0.3240\n",
"start index for training is 922000\n",
"Train on 12735 samples, validate on 12740 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12735/12735 [==============================] - 1s 52us/sample - loss: 1.4019 - accuracy: 0.5476\n",
"12740/12740 [==============================] - 1s 48us/sample - loss: 1.4074 - accuracy: 0.5509\n",
"5980/5980 [==============================] - 0s 49us/sample - loss: 1.9223 - accuracy: 0.3396\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0221 - accuracy: 0.3079\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.6819 - accuracy: 0.4821\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.0307 - accuracy: 0.3581\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.1522 - accuracy: 0.3170\n",
"start index for training is 923000\n",
"Train on 12070 samples, validate on 12075 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12070/12070 [==============================] - 1s 47us/sample - loss: 1.4293 - accuracy: 0.5307\n",
"12075/12075 [==============================] - 1s 41us/sample - loss: 1.4410 - accuracy: 0.5299\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.9318 - accuracy: 0.3739\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 2.0018 - accuracy: 0.3393\n",
"14070/14070 [==============================] - 1s 52us/sample - loss: 1.6897 - accuracy: 0.4781\n",
"11565/11565 [==============================] - 1s 52us/sample - loss: 2.0009 - accuracy: 0.3804\n",
"7000/7000 [==============================] - 0s 61us/sample - loss: 2.1185 - accuracy: 0.3473\n",
"start index for training is 924000\n",
"Train on 11820 samples, validate on 11820 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11820/11820 [==============================] - 1s 45us/sample - loss: 1.4195 - accuracy: 0.5446\n",
"11820/11820 [==============================] - 1s 44us/sample - loss: 1.4170 - accuracy: 0.5452\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9440 - accuracy: 0.3533\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0143 - accuracy: 0.3306\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.6852 - accuracy: 0.4874\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.9983 - accuracy: 0.3828\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.1190 - accuracy: 0.3474\n",
"start index for training is 925000\n",
"Train on 11030 samples, validate on 11030 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11030/11030 [==============================] - 1s 56us/sample - loss: 1.4371 - accuracy: 0.5138\n",
"11030/11030 [==============================] - 1s 49us/sample - loss: 1.4522 - accuracy: 0.5116\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.9802 - accuracy: 0.3931\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 2.0556 - accuracy: 0.3521\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"14070/14070 [==============================] - 1s 54us/sample - loss: 1.7438 - accuracy: 0.4333\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.0266 - accuracy: 0.3745\n",
"7000/7000 [==============================] - 0s 52us/sample - loss: 2.1414 - accuracy: 0.3464\n",
"start index for training is 926000\n",
"Train on 11690 samples, validate on 11690 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11690/11690 [==============================] - 1s 46us/sample - loss: 1.3844 - accuracy: 0.5581\n",
"11690/11690 [==============================] - 0s 42us/sample - loss: 1.3949 - accuracy: 0.5581\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.9602 - accuracy: 0.3615\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0195 - accuracy: 0.3219\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.7050 - accuracy: 0.4782\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 1.9681 - accuracy: 0.3940\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.0894 - accuracy: 0.3599\n",
"start index for training is 927000\n",
"Train on 10125 samples, validate on 10130 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10125/10125 [==============================] - 1s 53us/sample - loss: 1.4178 - accuracy: 0.5427\n",
"10130/10130 [==============================] - 0s 42us/sample - loss: 1.4287 - accuracy: 0.5462\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.9642 - accuracy: 0.3517\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 2.0307 - accuracy: 0.3080\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.7198 - accuracy: 0.4540\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.9601 - accuracy: 0.3748\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0820 - accuracy: 0.3384\n",
"start index for training is 928000\n",
"Train on 9285 samples, validate on 9285 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9285/9285 [==============================] - 0s 42us/sample - loss: 1.4473 - accuracy: 0.5422\n",
"9285/9285 [==============================] - 0s 39us/sample - loss: 1.4398 - accuracy: 0.5410\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9584 - accuracy: 0.3635\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 2.0218 - accuracy: 0.3229\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.7162 - accuracy: 0.4696\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.9420 - accuracy: 0.4005\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.0677 - accuracy: 0.3761\n",
"start index for training is 929000\n",
"Train on 10495 samples, validate on 10500 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10495/10495 [==============================] - 0s 42us/sample - loss: 1.3779 - accuracy: 0.5630\n",
"10500/10500 [==============================] - 0s 42us/sample - loss: 1.3958 - accuracy: 0.5624\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.9672 - accuracy: 0.3707\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0149 - accuracy: 0.3247\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.7278 - accuracy: 0.4630\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.9254 - accuracy: 0.4088\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.0504 - accuracy: 0.3810\n",
"start index for training is 930000\n",
"Train on 9365 samples, validate on 9370 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9365/9365 [==============================] - 0s 43us/sample - loss: 1.4317 - accuracy: 0.5497\n",
"9370/9370 [==============================] - 0s 42us/sample - loss: 1.4377 - accuracy: 0.5457\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.9537 - accuracy: 0.3537\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 2.0143 - accuracy: 0.3293\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.7256 - accuracy: 0.4655\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.9135 - accuracy: 0.4093\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.0300 - accuracy: 0.3749\n",
"start index for training is 931000\n",
"Train on 9885 samples, validate on 9885 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9885/9885 [==============================] - 0s 46us/sample - loss: 1.4178 - accuracy: 0.5533\n",
"9885/9885 [==============================] - 0s 43us/sample - loss: 1.4429 - accuracy: 0.5415\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.9556 - accuracy: 0.3652\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 2.0058 - accuracy: 0.3271\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.7454 - accuracy: 0.4625\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 1.8945 - accuracy: 0.4208\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.0098 - accuracy: 0.3951\n",
"start index for training is 932000\n",
"Train on 8530 samples, validate on 8535 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8530/8530 [==============================] - 0s 42us/sample - loss: 1.6308 - accuracy: 0.4728\n",
"8535/8535 [==============================] - 0s 39us/sample - loss: 1.6374 - accuracy: 0.4681\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8394 - accuracy: 0.3747\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.8753 - accuracy: 0.3601\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.7652 - accuracy: 0.4550\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8791 - accuracy: 0.4130\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 1.9997 - accuracy: 0.3803\n",
"start index for training is 933000\n",
"Train on 9160 samples, validate on 9160 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9160/9160 [==============================] - 0s 43us/sample - loss: 1.4999 - accuracy: 0.5207\n",
"9160/9160 [==============================] - 0s 42us/sample - loss: 1.5223 - accuracy: 0.5109\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.8896 - accuracy: 0.3719\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9368 - accuracy: 0.3267\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.7789 - accuracy: 0.4456\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.8658 - accuracy: 0.4061\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9878 - accuracy: 0.3691\n",
"start index for training is 934000\n",
"Train on 8390 samples, validate on 8390 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8390/8390 [==============================] - 0s 45us/sample - loss: 1.5392 - accuracy: 0.4974\n",
"8390/8390 [==============================] - 0s 41us/sample - loss: 1.5093 - accuracy: 0.5081\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9187 - accuracy: 0.3732\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.9463 - accuracy: 0.3449\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.7934 - accuracy: 0.4419\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 1.8426 - accuracy: 0.4267\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.9541 - accuracy: 0.3997\n",
"start index for training is 935000\n",
"Train on 8380 samples, validate on 8380 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 9/10\n",
"Epoch 10/10\n",
"8380/8380 [==============================] - 0s 41us/sample - loss: 1.5046 - accuracy: 0.5360\n",
"8380/8380 [==============================] - 0s 39us/sample - loss: 1.5277 - accuracy: 0.5218\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9076 - accuracy: 0.3577\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9548 - accuracy: 0.3270\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 1.8027 - accuracy: 0.4571\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 1.8288 - accuracy: 0.4427\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 1.9396 - accuracy: 0.4207\n",
"start index for training is 936000\n",
"Train on 8190 samples, validate on 8195 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8190/8190 [==============================] - 0s 41us/sample - loss: 1.5451 - accuracy: 0.5242\n",
"8195/8195 [==============================] - 0s 39us/sample - loss: 1.5524 - accuracy: 0.5267\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.9315 - accuracy: 0.3711\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.9615 - accuracy: 0.3227\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.8039 - accuracy: 0.4505\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 1.8140 - accuracy: 0.4420\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.9130 - accuracy: 0.4216\n",
"start index for training is 937000\n",
"Train on 8035 samples, validate on 8035 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8035/8035 [==============================] - 0s 44us/sample - loss: 1.5793 - accuracy: 0.4983\n",
"8035/8035 [==============================] - 0s 42us/sample - loss: 1.6098 - accuracy: 0.4892\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9681 - accuracy: 0.3758\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9722 - accuracy: 0.3409\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8614 - accuracy: 0.4281\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 1.8049 - accuracy: 0.4398\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.8851 - accuracy: 0.4139\n",
"start index for training is 938000\n",
"Train on 8160 samples, validate on 8165 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8160/8160 [==============================] - 0s 39us/sample - loss: 1.5802 - accuracy: 0.5119\n",
"8165/8165 [==============================] - 0s 42us/sample - loss: 1.6102 - accuracy: 0.5135\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9528 - accuracy: 0.3716\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9501 - accuracy: 0.3297\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8375 - accuracy: 0.4534\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.7709 - accuracy: 0.4545\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 1.8364 - accuracy: 0.4450\n",
"start index for training is 939000\n",
"Train on 7620 samples, validate on 7625 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7620/7620 [==============================] - 0s 45us/sample - loss: 1.6955 - accuracy: 0.4738\n",
"7625/7625 [==============================] - 0s 41us/sample - loss: 1.7108 - accuracy: 0.4632\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9044 - accuracy: 0.3871s - loss: 1.8785 - accuracy\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.9545 - accuracy: 0.3399\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8485 - accuracy: 0.4330\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.7551 - accuracy: 0.4562\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 1.8028 - accuracy: 0.4443\n",
"start index for training is 940000\n",
"Train on 8495 samples, validate on 8500 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8495/8495 [==============================] - 0s 44us/sample - loss: 1.4856 - accuracy: 0.5433\n",
"8500/8500 [==============================] - 0s 41us/sample - loss: 1.5231 - accuracy: 0.5293\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.4594 - accuracy: 0.5381\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.9354 - accuracy: 0.3253\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.9479 - accuracy: 0.3906\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 1.9561 - accuracy: 0.3656\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.0168 - accuracy: 0.3454s - loss: 2.0330 - accura\n",
"start index for training is 941000\n",
"Train on 8260 samples, validate on 8260 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8260/8260 [==============================] - 0s 44us/sample - loss: 1.3864 - accuracy: 0.5631\n",
"8260/8260 [==============================] - 0s 42us/sample - loss: 1.3962 - accuracy: 0.5625\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.3427 - accuracy: 0.6008\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.9307 - accuracy: 0.3369\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.9868 - accuracy: 0.3844\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.0315 - accuracy: 0.3454\n",
"7000/7000 [==============================] - 0s 49us/sample - loss: 2.0886 - accuracy: 0.3280\n",
"start index for training is 942000\n",
"Train on 8270 samples, validate on 8275 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8270/8270 [==============================] - 0s 43us/sample - loss: 1.3288 - accuracy: 0.5924\n",
"8275/8275 [==============================] - 0s 40us/sample - loss: 1.3501 - accuracy: 0.5896\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.3129 - accuracy: 0.5910\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9197 - accuracy: 0.3541\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 2.0190 - accuracy: 0.3660\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 2.0571 - accuracy: 0.3624\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.1096 - accuracy: 0.3571\n",
"start index for training is 943000\n",
"Train on 8785 samples, validate on 8785 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8785/8785 [==============================] - 0s 42us/sample - loss: 1.3646 - accuracy: 0.5701\n",
"8785/8785 [==============================] - 0s 38us/sample - loss: 1.3716 - accuracy: 0.5681\n",
"5980/5980 [==============================] - 0s 36us/sample - loss: 1.3075 - accuracy: 0.6030\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.9068 - accuracy: 0.3560\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.0631 - accuracy: 0.3694\n",
"11565/11565 [==============================] - ETA: 0s - loss: 2.0756 - accuracy: 0.36 - 0s 35us/sample - loss: 2.0793 - accuracy: 0.3620\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.1416 - accuracy: 0.3570\n",
"start index for training is 944000\n",
"Train on 9400 samples, validate on 9400 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9400/9400 [==============================] - 0s 40us/sample - loss: 1.3892 - accuracy: 0.5551\n",
"9400/9400 [==============================] - 0s 38us/sample - loss: 1.3982 - accuracy: 0.5530\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.3194 - accuracy: 0.5960\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.8728 - accuracy: 0.3750\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.0453 - accuracy: 0.3554\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.0920 - accuracy: 0.3573\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.1730 - accuracy: 0.3529\n",
"start index for training is 945000\n",
"Train on 9535 samples, validate on 9540 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9535/9535 [==============================] - 0s 41us/sample - loss: 1.4341 - accuracy: 0.5315\n",
"9540/9540 [==============================] - 0s 39us/sample - loss: 1.4194 - accuracy: 0.5401\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.3473 - accuracy: 0.5858\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.8149 - accuracy: 0.3738\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.0538 - accuracy: 0.3397\n",
"11565/11565 [==============================] - 0s 36us/sample - loss: 2.0967 - accuracy: 0.3400\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.1818 - accuracy: 0.3290\n",
"start index for training is 946000\n",
"Train on 9085 samples, validate on 9090 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9085/9085 [==============================] - 0s 46us/sample - loss: 1.4331 - accuracy: 0.5258\n",
"9090/9090 [==============================] - 0s 40us/sample - loss: 1.4444 - accuracy: 0.5262\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.4078 - accuracy: 0.5615\n",
"12255/12255 [==============================] - 0s 35us/sample - loss: 1.7951 - accuracy: 0.3923\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.0978 - accuracy: 0.3475\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.1040 - accuracy: 0.3419\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1849 - accuracy: 0.3366\n",
"start index for training is 947000\n",
"Train on 8675 samples, validate on 8675 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8675/8675 [==============================] - 0s 45us/sample - loss: 1.4012 - accuracy: 0.5359\n",
"8675/8675 [==============================] - ETA: 0s - loss: 1.4121 - accuracy: 0.53 - 0s 40us/sample - loss: 1.4106 - accuracy: 0.5333\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.4216 - accuracy: 0.5607\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.7132 - accuracy: 0.4041\n",
"14070/14070 [==============================] - 1s 44us/sample - loss: 2.1110 - accuracy: 0.3277\n",
"11565/11565 [==============================] - 0s 41us/sample - loss: 2.1227 - accuracy: 0.3248\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2069 - accuracy: 0.3180\n",
"start index for training is 948000\n",
"Train on 8240 samples, validate on 8240 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8240/8240 [==============================] - 0s 46us/sample - loss: 1.3842 - accuracy: 0.5352\n",
"8240/8240 [==============================] - 0s 44us/sample - loss: 1.3799 - accuracy: 0.5280\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.4667 - accuracy: 0.5279\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.6553 - accuracy: 0.4476\n",
"14070/14070 [==============================] - 1s 47us/sample - loss: 2.1470 - accuracy: 0.3110\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 2.1403 - accuracy: 0.3287\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.2270 - accuracy: 0.3221\n",
"start index for training is 949000\n",
"Train on 8430 samples, validate on 8430 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8430/8430 [==============================] - 0s 47us/sample - loss: 1.3721 - accuracy: 0.5407\n",
"8430/8430 [==============================] - 0s 44us/sample - loss: 1.3865 - accuracy: 0.5288\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.5068 - accuracy: 0.5261\n",
"12255/12255 [==============================] - 1s 45us/sample - loss: 1.6049 - accuracy: 0.4654\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.1609 - accuracy: 0.3262\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1508 - accuracy: 0.3460\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2338 - accuracy: 0.3313\n",
"start index for training is 950000\n",
"Train on 8845 samples, validate on 8845 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8845/8845 [==============================] - 0s 45us/sample - loss: 1.3871 - accuracy: 0.5421\n",
"8845/8845 [==============================] - 0s 44us/sample - loss: 1.3860 - accuracy: 0.5457\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.5363 - accuracy: 0.5092\n",
"12255/12255 [==============================] - 1s 41us/sample - loss: 1.5620 - accuracy: 0.4773\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.1704 - accuracy: 0.3174\n",
"11565/11565 [==============================] - 0s 43us/sample - loss: 2.1377 - accuracy: 0.3318\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.2122 - accuracy: 0.3137\n",
"start index for training is 951000\n",
"Train on 8955 samples, validate on 8960 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8955/8955 [==============================] - 0s 52us/sample - loss: 1.4327 - accuracy: 0.5470\n",
"8960/8960 [==============================] - 0s 42us/sample - loss: 1.4371 - accuracy: 0.5462\n",
"5980/5980 [==============================] - 0s 48us/sample - loss: 1.5373 - accuracy: 0.5087\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.5449 - accuracy: 0.4876\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.1752 - accuracy: 0.3230\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.1210 - accuracy: 0.3478\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.1942 - accuracy: 0.3293\n",
"start index for training is 952000\n",
"Train on 8205 samples, validate on 8205 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8205/8205 [==============================] - 0s 46us/sample - loss: 1.5039 - accuracy: 0.5375\n",
"8205/8205 [==============================] - 0s 48us/sample - loss: 1.5008 - accuracy: 0.5300\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.5656 - accuracy: 0.4871\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.5720 - accuracy: 0.4790\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.1643 - accuracy: 0.3291\n",
"11565/11565 [==============================] - 1s 52us/sample - loss: 2.1228 - accuracy: 0.3548\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.2068 - accuracy: 0.3370\n",
"start index for training is 953000\n",
"Train on 7375 samples, validate on 7380 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7375/7375 [==============================] - 0s 49us/sample - loss: 1.5506 - accuracy: 0.5288\n",
"7380/7380 [==============================] - 0s 49us/sample - loss: 1.6054 - accuracy: 0.5107\n",
"5980/5980 [==============================] - 0s 62us/sample - loss: 1.6043 - accuracy: 0.4880\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.5742 - accuracy: 0.4752\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 2.1906 - accuracy: 0.3252\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1161 - accuracy: 0.3597\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.2003 - accuracy: 0.3464\n",
"start index for training is 954000\n",
"Train on 7555 samples, validate on 7560 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7555/7555 [==============================] - 0s 44us/sample - loss: 1.5937 - accuracy: 0.5284\n",
"7560/7560 [==============================] - 0s 45us/sample - loss: 1.6141 - accuracy: 0.5130\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.6167 - accuracy: 0.4666\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.6003 - accuracy: 0.4753\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.1921 - accuracy: 0.3267\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1292 - accuracy: 0.3562\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2163 - accuracy: 0.3423\n",
"start index for training is 955000\n",
"Train on 7040 samples, validate on 7040 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7040/7040 [==============================] - 0s 70us/sample - loss: 1.7165 - accuracy: 0.4706\n",
"7040/7040 [==============================] - 0s 42us/sample - loss: 1.7180 - accuracy: 0.4670\n",
"5980/5980 [==============================] - 0s 42us/sample - loss: 1.6165 - accuracy: 0.5090\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.6381 - accuracy: 0.4453\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.1738 - accuracy: 0.3215\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.1565 - accuracy: 0.3193\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 2.2384 - accuracy: 0.3086\n",
"start index for training is 956000\n",
"Train on 7955 samples, validate on 7955 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"7955/7955 [==============================] - 0s 43us/sample - loss: 1.4997 - accuracy: 0.5353\n",
"7955/7955 [==============================] - 0s 39us/sample - loss: 1.5269 - accuracy: 0.5260\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.6550 - accuracy: 0.4834\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.7374 - accuracy: 0.4169\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.8388 - accuracy: 0.4157\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.0406 - accuracy: 0.3660\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1227 - accuracy: 0.3400\n",
"start index for training is 957000\n",
"Train on 8915 samples, validate on 8920 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8915/8915 [==============================] - 0s 49us/sample - loss: 1.2123 - accuracy: 0.6252\n",
"8920/8920 [==============================] - 0s 52us/sample - loss: 1.2240 - accuracy: 0.6147\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.7620 - accuracy: 0.4343\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.9065 - accuracy: 0.3865\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.7622 - accuracy: 0.4625\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.0912 - accuracy: 0.3631\n",
"7000/7000 [==============================] - 0s 42us/sample - loss: 2.1813 - accuracy: 0.3329\n",
"start index for training is 958000\n",
"Train on 9610 samples, validate on 9615 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9610/9610 [==============================] - 0s 42us/sample - loss: 1.1779 - accuracy: 0.6287\n",
"9615/9615 [==============================] - 0s 45us/sample - loss: 1.1822 - accuracy: 0.6237\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.7976 - accuracy: 0.3773\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.9416 - accuracy: 0.3665\n",
"14070/14070 [==============================] - 1s 42us/sample - loss: 1.7336 - accuracy: 0.4649\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.0645 - accuracy: 0.3705\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.1575 - accuracy: 0.3416\n",
"start index for training is 959000\n",
"Train on 10360 samples, validate on 10360 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10360/10360 [==============================] - 0s 44us/sample - loss: 1.2153 - accuracy: 0.6181\n",
"10360/10360 [==============================] - 0s 43us/sample - loss: 1.2276 - accuracy: 0.6130\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.8627 - accuracy: 0.3682\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.9896 - accuracy: 0.3397\n",
"14070/14070 [==============================] - 1s 50us/sample - loss: 1.7303 - accuracy: 0.4672\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.0848 - accuracy: 0.3543\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.1904 - accuracy: 0.3263\n",
"start index for training is 960000\n",
"Train on 10665 samples, validate on 10670 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10665/10665 [==============================] - 0s 47us/sample - loss: 1.2628 - accuracy: 0.6002\n",
"10670/10670 [==============================] - 0s 43us/sample - loss: 1.2519 - accuracy: 0.6018\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.8757 - accuracy: 0.3724\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9657 - accuracy: 0.3482\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.7162 - accuracy: 0.4800\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.0371 - accuracy: 0.3829\n",
"7000/7000 [==============================] - 0s 41us/sample - loss: 2.1510 - accuracy: 0.3497\n",
"start index for training is 961000\n",
"Train on 10070 samples, validate on 10070 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10070/10070 [==============================] - 1s 53us/sample - loss: 1.2522 - accuracy: 0.6016\n",
"10070/10070 [==============================] - 0s 49us/sample - loss: 1.2586 - accuracy: 0.6012\n",
"5980/5980 [==============================] - 0s 59us/sample - loss: 1.9221 - accuracy: 0.3599\n",
"12255/12255 [==============================] - 1s 61us/sample - loss: 1.9950 - accuracy: 0.3417\n",
"14070/14070 [==============================] - 1s 85us/sample - loss: 1.7370 - accuracy: 0.4847\n",
"11565/11565 [==============================] - 1s 52us/sample - loss: 2.0545 - accuracy: 0.3831\n",
"7000/7000 [==============================] - 0s 44us/sample - loss: 2.1662 - accuracy: 0.3509\n",
"start index for training is 962000\n",
"Train on 9830 samples, validate on 9835 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9830/9830 [==============================] - 0s 44us/sample - loss: 1.2189 - accuracy: 0.6108\n",
"9835/9835 [==============================] - 0s 42us/sample - loss: 1.2310 - accuracy: 0.6033\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.9273 - accuracy: 0.3737\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9938 - accuracy: 0.3448\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.7432 - accuracy: 0.4663\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.0170 - accuracy: 0.3907\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.1317 - accuracy: 0.3647\n",
"start index for training is 963000\n",
"Train on 9660 samples, validate on 9660 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9660/9660 [==============================] - 0s 47us/sample - loss: 1.2199 - accuracy: 0.6157\n",
"9660/9660 [==============================] - 0s 42us/sample - loss: 1.2413 - accuracy: 0.6079\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.9397 - accuracy: 0.3657\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 0s 39us/sample - loss: 2.0008 - accuracy: 0.3445\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 1.7644 - accuracy: 0.4554\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 1.9797 - accuracy: 0.3972\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.0861 - accuracy: 0.3769\n",
"start index for training is 964000\n",
"Train on 9680 samples, validate on 9680 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9680/9680 [==============================] - 0s 45us/sample - loss: 1.2449 - accuracy: 0.6067\n",
"9680/9680 [==============================] - 0s 39us/sample - loss: 1.2570 - accuracy: 0.5986\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9330 - accuracy: 0.3676\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9860 - accuracy: 0.3345\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.7736 - accuracy: 0.4521\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 1.9422 - accuracy: 0.4031\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0390 - accuracy: 0.3871\n",
"start index for training is 965000\n",
"Train on 10095 samples, validate on 10095 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10095/10095 [==============================] - 0s 46us/sample - loss: 1.3297 - accuracy: 0.5660\n",
"10095/10095 [==============================] - 0s 42us/sample - loss: 1.3428 - accuracy: 0.5619\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9255 - accuracy: 0.3903\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9824 - accuracy: 0.3547\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.8140 - accuracy: 0.4326\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.9074 - accuracy: 0.4131\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.0055 - accuracy: 0.3923\n",
"start index for training is 966000\n",
"Train on 9540 samples, validate on 9545 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"9540/9540 [==============================] - 0s 43us/sample - loss: 1.3668 - accuracy: 0.5720\n",
"9545/9545 [==============================] - 0s 41us/sample - loss: 1.3862 - accuracy: 0.5706\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9212 - accuracy: 0.3764\n",
"12255/12255 [==============================] - 1s 42us/sample - loss: 1.9787 - accuracy: 0.3390\n",
"14070/14070 [==============================] - 1s 39us/sample - loss: 1.8114 - accuracy: 0.4511\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.8399 - accuracy: 0.4327\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.9187 - accuracy: 0.4123\n",
"start index for training is 967000\n",
"Train on 8985 samples, validate on 8985 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8985/8985 [==============================] - 0s 43us/sample - loss: 1.4555 - accuracy: 0.5519\n",
"8985/8985 [==============================] - 0s 41us/sample - loss: 1.4602 - accuracy: 0.5436\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.9091 - accuracy: 0.3706\n",
"12255/12255 [==============================] - 0s 40us/sample - loss: 1.9691 - accuracy: 0.3397\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.8309 - accuracy: 0.4416\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.7897 - accuracy: 0.4456\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.8451 - accuracy: 0.4313\n",
"start index for training is 968000\n",
"Train on 8495 samples, validate on 8495 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8495/8495 [==============================] - 0s 46us/sample - loss: 1.5238 - accuracy: 0.5197\n",
"8495/8495 [==============================] - 0s 45us/sample - loss: 1.5501 - accuracy: 0.5177\n",
"5980/5980 [==============================] - 0s 45us/sample - loss: 1.9177 - accuracy: 0.3589\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.9860 - accuracy: 0.3297\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 1.8480 - accuracy: 0.4431\n",
"11565/11565 [==============================] - 1s 48us/sample - loss: 1.7632 - accuracy: 0.4514\n",
"7000/7000 [==============================] - 0s 46us/sample - loss: 1.7994 - accuracy: 0.4407\n",
"start index for training is 969000\n",
"Train on 8495 samples, validate on 8495 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8495/8495 [==============================] - 0s 45us/sample - loss: 1.5500 - accuracy: 0.5220\n",
"8495/8495 [==============================] - 0s 40us/sample - loss: 1.5373 - accuracy: 0.5255\n",
"5980/5980 [==============================] - 0s 38us/sample - loss: 1.9175 - accuracy: 0.3769\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9731 - accuracy: 0.3355\n",
"14070/14070 [==============================] - 1s 41us/sample - loss: 1.8678 - accuracy: 0.4433\n",
"11565/11565 [==============================] - 0s 40us/sample - loss: 1.7400 - accuracy: 0.4623\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 1.7408 - accuracy: 0.4647\n",
"start index for training is 970000\n",
"Train on 8475 samples, validate on 8475 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"8475/8475 [==============================] - 0s 48us/sample - loss: 1.8203 - accuracy: 0.4038\n",
"8475/8475 [==============================] - 0s 49us/sample - loss: 1.8380 - accuracy: 0.4029\n",
"5980/5980 [==============================] - 0s 41us/sample - loss: 1.5976 - accuracy: 0.4542\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.8798 - accuracy: 0.3458\n",
"14070/14070 [==============================] - 1s 63us/sample - loss: 1.8638 - accuracy: 0.4320\n",
"11565/11565 [==============================] - 1s 45us/sample - loss: 1.8456 - accuracy: 0.4065\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 1.8570 - accuracy: 0.3987\n",
"start index for training is 971000\n",
"Train on 10660 samples, validate on 10665 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10660/10660 [==============================] - 0s 43us/sample - loss: 1.6973 - accuracy: 0.4616\n",
"10665/10665 [==============================] - 0s 42us/sample - loss: 1.7002 - accuracy: 0.4650\n",
"5980/5980 [==============================] - 0s 43us/sample - loss: 1.4426 - accuracy: 0.5455\n",
"12255/12255 [==============================] - 0s 39us/sample - loss: 1.8691 - accuracy: 0.3661\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 1.9326 - accuracy: 0.3965\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 1.9827 - accuracy: 0.3627\n",
"7000/7000 [==============================] - 0s 39us/sample - loss: 2.0039 - accuracy: 0.3471\n",
"start index for training is 972000\n",
"Train on 10485 samples, validate on 10490 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10485/10485 [==============================] - 1s 51us/sample - loss: 1.6806 - accuracy: 0.4736\n",
"10490/10490 [==============================] - 0s 40us/sample - loss: 1.6885 - accuracy: 0.4677\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.3883 - accuracy: 0.5848\n",
"12255/12255 [==============================] - 1s 44us/sample - loss: 1.8714 - accuracy: 0.3664\n",
"14070/14070 [==============================] - 1s 38us/sample - loss: 1.9696 - accuracy: 0.3839\n",
"11565/11565 [==============================] - 0s 35us/sample - loss: 2.0362 - accuracy: 0.3486\n",
"7000/7000 [==============================] - 0s 36us/sample - loss: 2.0607 - accuracy: 0.3370\n",
"start index for training is 973000\n",
"Train on 11035 samples, validate on 11035 samples\n",
"Epoch 1/10\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11035/11035 [==============================] - 1s 67us/sample - loss: 1.7173 - accuracy: 0.4711\n",
"11035/11035 [==============================] - 0s 44us/sample - loss: 1.7265 - accuracy: 0.4635\n",
"5980/5980 [==============================] - 0s 59us/sample - loss: 1.4451 - accuracy: 0.5301\n",
"12255/12255 [==============================] - 1s 53us/sample - loss: 1.9596 - accuracy: 0.3594\n",
"14070/14070 [==============================] - 1s 67us/sample - loss: 2.0296 - accuracy: 0.3701\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.1761 - accuracy: 0.3187\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.1967 - accuracy: 0.3100\n",
"start index for training is 974000\n",
"Train on 10480 samples, validate on 10485 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10480/10480 [==============================] - 0s 40us/sample - loss: 1.6616 - accuracy: 0.4877\n",
"10485/10485 [==============================] - 0s 38us/sample - loss: 1.6662 - accuracy: 0.4778\n",
"5980/5980 [==============================] - 0s 37us/sample - loss: 1.3348 - accuracy: 0.5876\n",
"12255/12255 [==============================] - 0s 36us/sample - loss: 1.8929 - accuracy: 0.3589\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 1.9760 - accuracy: 0.3783\n",
"11565/11565 [==============================] - 0s 37us/sample - loss: 2.1020 - accuracy: 0.3238\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1337 - accuracy: 0.3213\n",
"start index for training is 975000\n",
"Train on 12320 samples, validate on 12325 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12320/12320 [==============================] - 1s 46us/sample - loss: 1.6280 - accuracy: 0.4925\n",
"12325/12325 [==============================] - 1s 41us/sample - loss: 1.6172 - accuracy: 0.4893\n",
"5980/5980 [==============================] - 0s 44us/sample - loss: 1.3427 - accuracy: 0.5829\n",
"12255/12255 [==============================] - 0s 38us/sample - loss: 1.9057 - accuracy: 0.3656\n",
"14070/14070 [==============================] - 1s 37us/sample - loss: 2.0094 - accuracy: 0.3722\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1468 - accuracy: 0.3073\n",
"7000/7000 [==============================] - 0s 38us/sample - loss: 2.1794 - accuracy: 0.3061\n",
"start index for training is 976000\n",
"Train on 10120 samples, validate on 10125 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10120/10120 [==============================] - 0s 42us/sample - loss: 1.6489 - accuracy: 0.4856\n",
"10125/10125 [==============================] - 0s 40us/sample - loss: 1.6806 - accuracy: 0.4766\n",
"5980/5980 [==============================] - 0s 39us/sample - loss: 1.3327 - accuracy: 0.6077\n",
"12255/12255 [==============================] - 0s 37us/sample - loss: 1.9210 - accuracy: 0.3571\n",
"14070/14070 [==============================] - 1s 36us/sample - loss: 2.0280 - accuracy: 0.3598\n",
"11565/11565 [==============================] - 0s 39us/sample - loss: 2.1497 - accuracy: 0.3165\n",
"7000/7000 [==============================] - 0s 37us/sample - loss: 2.1943 - accuracy: 0.3019\n",
"start index for training is 977000\n",
"Train on 11300 samples, validate on 11300 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11300/11300 [==============================] - 1s 48us/sample - loss: 1.5660 - accuracy: 0.5138\n",
"11300/11300 [==============================] - 0s 43us/sample - loss: 1.5605 - accuracy: 0.5116\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.2949 - accuracy: 0.6366\n",
"12255/12255 [==============================] - 1s 43us/sample - loss: 1.9030 - accuracy: 0.3612\n",
"14070/14070 [==============================] - 1s 40us/sample - loss: 2.0046 - accuracy: 0.3579\n",
"11565/11565 [==============================] - 0s 38us/sample - loss: 2.1570 - accuracy: 0.3147\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2040 - accuracy: 0.2986\n",
"start index for training is 978000\n",
"Train on 11205 samples, validate on 11210 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11205/11205 [==============================] - 1s 50us/sample - loss: 1.5489 - accuracy: 0.5151\n",
"11210/11210 [==============================] - 1s 57us/sample - loss: 1.5419 - accuracy: 0.5182\n",
"5980/5980 [==============================] - 0s 59us/sample - loss: 1.2839 - accuracy: 0.5963\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 1.9319 - accuracy: 0.3577\n",
"14070/14070 [==============================] - 1s 43us/sample - loss: 2.0275 - accuracy: 0.3527\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.2034 - accuracy: 0.2971\n",
"7000/7000 [==============================] - 0s 40us/sample - loss: 2.2435 - accuracy: 0.2899\n",
"start index for training is 979000\n",
"Train on 10770 samples, validate on 10770 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10770/10770 [==============================] - 1s 84us/sample - loss: 1.5534 - accuracy: 0.5197\n",
"10770/10770 [==============================] - 1s 84us/sample - loss: 1.5498 - accuracy: 0.5232\n",
"5980/5980 [==============================] - 0s 57us/sample - loss: 1.2609 - accuracy: 0.6510\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 1.9068 - accuracy: 0.3705\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.0180 - accuracy: 0.3478\n",
"11565/11565 [==============================] - 1s 57us/sample - loss: 2.1761 - accuracy: 0.3044\n",
"7000/7000 [==============================] - 0s 56us/sample - loss: 2.2189 - accuracy: 0.2846\n",
"start index for training is 980000\n",
"Train on 11450 samples, validate on 11455 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11450/11450 [==============================] - 1s 62us/sample - loss: 1.5408 - accuracy: 0.5153\n",
"11455/11455 [==============================] - 1s 53us/sample - loss: 1.5525 - accuracy: 0.5095\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.2591 - accuracy: 0.6545\n",
"12255/12255 [==============================] - 1s 53us/sample - loss: 1.9050 - accuracy: 0.3737\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.0210 - accuracy: 0.3398\n",
"11565/11565 [==============================] - 1s 46us/sample - loss: 2.1751 - accuracy: 0.3029\n",
"7000/7000 [==============================] - 0s 57us/sample - loss: 2.2232 - accuracy: 0.2847\n",
"start index for training is 981000\n",
"Train on 10885 samples, validate on 10890 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10885/10885 [==============================] - 1s 50us/sample - loss: 1.5532 - accuracy: 0.5079\n",
"10890/10890 [==============================] - 1s 51us/sample - loss: 1.5845 - accuracy: 0.4981\n",
"5980/5980 [==============================] - 0s 50us/sample - loss: 1.2640 - accuracy: 0.6169\n",
"12255/12255 [==============================] - 1s 47us/sample - loss: 1.8951 - accuracy: 0.3710\n",
"14070/14070 [==============================] - 1s 49us/sample - loss: 2.0317 - accuracy: 0.3547\n",
"11565/11565 [==============================] - 1s 44us/sample - loss: 2.1841 - accuracy: 0.3203\n",
"7000/7000 [==============================] - 0s 45us/sample - loss: 2.2363 - accuracy: 0.3089\n",
"start index for training is 982000\n",
"Train on 11915 samples, validate on 11915 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11915/11915 [==============================] - 1s 109us/sample - loss: 1.5349 - accuracy: 0.5108\n",
"11915/11915 [==============================] - 1s 91us/sample - loss: 1.5580 - accuracy: 0.4986\n",
"5980/5980 [==============================] - 0s 79us/sample - loss: 1.2595 - accuracy: 0.6047\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"12255/12255 [==============================] - 1s 71us/sample - loss: 1.8693 - accuracy: 0.3744\n",
"14070/14070 [==============================] - 1s 65us/sample - loss: 2.0447 - accuracy: 0.3562\n",
"11565/11565 [==============================] - 1s 58us/sample - loss: 2.1762 - accuracy: 0.3208\n",
"7000/7000 [==============================] - 0s 54us/sample - loss: 2.2287 - accuracy: 0.3134\n",
"start index for training is 983000\n",
"Train on 12370 samples, validate on 12370 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"12370/12370 [==============================] - 1s 67us/sample - loss: 1.5322 - accuracy: 0.5171\n",
"12370/12370 [==============================] - 1s 58us/sample - loss: 1.5552 - accuracy: 0.5036\n",
"5980/5980 [==============================] - 0s 54us/sample - loss: 1.2579 - accuracy: 0.6109\n",
"12255/12255 [==============================] - 1s 51us/sample - loss: 1.8656 - accuracy: 0.3688\n",
"14070/14070 [==============================] - 1s 45us/sample - loss: 2.0363 - accuracy: 0.3602\n",
"11565/11565 [==============================] - 0s 42us/sample - loss: 2.1866 - accuracy: 0.3178\n",
"7000/7000 [==============================] - 0s 43us/sample - loss: 2.2548 - accuracy: 0.3059\n",
"start index for training is 984000\n",
"Train on 13145 samples, validate on 13150 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13145/13145 [==============================] - 1s 42us/sample - loss: 1.5333 - accuracy: 0.5093\n",
"13150/13150 [==============================] - 1s 41us/sample - loss: 1.5420 - accuracy: 0.5109\n",
"5980/5980 [==============================] - 0s 40us/sample - loss: 1.2665 - accuracy: 0.6005\n",
"12255/12255 [==============================] - 1s 46us/sample - loss: 1.8503 - accuracy: 0.3858\n",
"14070/14070 [==============================] - 1s 48us/sample - loss: 2.0679 - accuracy: 0.3536\n",
"11565/11565 [==============================] - 1s 60us/sample - loss: 2.1867 - accuracy: 0.3294\n",
"7000/7000 [==============================] - 0s 67us/sample - loss: 2.2391 - accuracy: 0.3317\n",
"start index for training is 985000\n",
"Train on 13355 samples, validate on 13360 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13355/13355 [==============================] - 1s 54us/sample - loss: 1.4951 - accuracy: 0.5140\n",
"13360/13360 [==============================] - 1s 48us/sample - loss: 1.5195 - accuracy: 0.5119\n",
"5980/5980 [==============================] - 0s 55us/sample - loss: 1.2603 - accuracy: 0.6000\n",
"12255/12255 [==============================] - 1s 49us/sample - loss: 1.8405 - accuracy: 0.3806\n",
"14070/14070 [==============================] - 1s 46us/sample - loss: 2.0594 - accuracy: 0.3513\n",
"11565/11565 [==============================] - 1s 47us/sample - loss: 2.1961 - accuracy: 0.3197\n",
"7000/7000 [==============================] - 0s 47us/sample - loss: 2.2600 - accuracy: 0.3107\n",
"start index for training is 986000\n",
"Train on 13850 samples, validate on 13850 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"13850/13850 [==============================] - 1s 54us/sample - loss: 1.5087 - accuracy: 0.5168\n",
"13850/13850 [==============================] - 1s 59us/sample - loss: 1.5157 - accuracy: 0.5131\n",
"5980/5980 [==============================] - 0s 46us/sample - loss: 1.2650 - accuracy: 0.6017\n",
"12255/12255 [==============================] - 1s 55us/sample - loss: 1.8334 - accuracy: 0.3979\n",
"14070/14070 [==============================] - 1s 78us/sample - loss: 2.0581 - accuracy: 0.3546\n",
"11565/11565 [==============================] - 1s 69us/sample - loss: 2.1956 - accuracy: 0.3228\n",
"7000/7000 [==============================] - 0s 54us/sample - loss: 2.2648 - accuracy: 0.3183\n",
"start index for training is 987000\n",
"Train on 10845 samples, validate on 10850 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"10845/10845 [==============================] - 1s 52us/sample - loss: 1.6297 - accuracy: 0.4727\n",
"10850/10850 [==============================] - 1s 58us/sample - loss: 1.6345 - accuracy: 0.4760\n",
"5980/5980 [==============================] - 0s 74us/sample - loss: 1.2905 - accuracy: 0.6333\n",
"12255/12255 [==============================] - 1s 70us/sample - loss: 1.8116 - accuracy: 0.3927\n",
"14070/14070 [==============================] - 1s 64us/sample - loss: 2.0534 - accuracy: 0.3353\n",
"11565/11565 [==============================] - 1s 59us/sample - loss: 2.1991 - accuracy: 0.2998\n",
"7000/7000 [==============================] - 0s 66us/sample - loss: 2.2718 - accuracy: 0.2831\n",
"start index for training is 988000\n",
"Train on 15530 samples, validate on 15530 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"15530/15530 [==============================] - 1s 50us/sample - loss: 1.5043 - accuracy: 0.5073\n",
"15530/15530 [==============================] - 1s 48us/sample - loss: 1.4987 - accuracy: 0.5139\n",
"5980/5980 [==============================] - 0s 53us/sample - loss: 1.2797 - accuracy: 0.5998\n",
"12255/12255 [==============================] - 1s 54us/sample - loss: 1.7979 - accuracy: 0.4064\n",
"14070/14070 [==============================] - 1s 52us/sample - loss: 2.0631 - accuracy: 0.3500\n",
"11565/11565 [==============================] - 1s 50us/sample - loss: 2.2032 - accuracy: 0.3217\n",
"7000/7000 [==============================] - 0s 50us/sample - loss: 2.2773 - accuracy: 0.3136\n",
"start index for training is 989000\n",
"Train on 11595 samples, validate on 11595 samples\n",
"Epoch 1/10\n",
"Epoch 2/10\n",
"Epoch 3/10\n",
"Epoch 4/10\n",
"Epoch 5/10\n",
"Epoch 6/10\n",
"Epoch 7/10\n",
"Epoch 8/10\n",
"Epoch 9/10\n",
"Epoch 10/10\n",
"11595/11595 [==============================] - 1s 54us/sample - loss: 1.6062 - accuracy: 0.4777\n",
"11595/11595 [==============================] - 1s 48us/sample - loss: 1.6194 - accuracy: 0.4662\n",
"5980/5980 [==============================] - 0s 47us/sample - loss: 1.3056 - accuracy: 0.5931\n",
"12255/12255 [==============================] - 1s 48us/sample - loss: 1.7871 - accuracy: 0.3998\n",
"14070/14070 [==============================] - 1s 55us/sample - loss: 2.0565 - accuracy: 0.3578\n",
"11565/11565 [==============================] - 1s 61us/sample - loss: 2.1967 - accuracy: 0.3162\n",
"3296/7000 [=============>................] - ETA: 0s - loss: 2.2581 - accuracy: 0.3134"
]
},
{
"ename": "KeyboardInterrupt",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-15-3dc3fccdd48b>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 50\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 51\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnb_sets\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 52\u001b[1;33m \u001b[0mhistory\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mevaluate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx_list\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_list\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 53\u001b[0m \u001b[0maccuracy_list\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhistory\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 54\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\keras\\engine\\training.py\u001b[0m in \u001b[0;36mevaluate\u001b[1;34m(self, x, y, batch_size, verbose, sample_weight, steps, callbacks, max_queue_size, workers, use_multiprocessing)\u001b[0m\n\u001b[0;32m 928\u001b[0m \u001b[0mmax_queue_size\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmax_queue_size\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 929\u001b[0m \u001b[0mworkers\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mworkers\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 930\u001b[1;33m use_multiprocessing=use_multiprocessing)\n\u001b[0m\u001b[0;32m 931\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 932\u001b[0m def predict(self,\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\keras\\engine\\training_v2.py\u001b[0m in \u001b[0;36mevaluate\u001b[1;34m(self, model, x, y, batch_size, verbose, sample_weight, steps, callbacks, max_queue_size, workers, use_multiprocessing, **kwargs)\u001b[0m\n\u001b[0;32m 488\u001b[0m \u001b[0msample_weight\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msample_weight\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msteps\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msteps\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcallbacks\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcallbacks\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 489\u001b[0m \u001b[0mmax_queue_size\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmax_queue_size\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mworkers\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mworkers\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 490\u001b[1;33m use_multiprocessing=use_multiprocessing, **kwargs)\n\u001b[0m\u001b[0;32m 491\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 492\u001b[0m def predict(self, model, x, batch_size=None, verbose=0, steps=None,\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\keras\\engine\\training_v2.py\u001b[0m in \u001b[0;36m_model_iteration\u001b[1;34m(self, model, mode, x, y, batch_size, verbose, sample_weight, steps, callbacks, max_queue_size, workers, use_multiprocessing, **kwargs)\u001b[0m\n\u001b[0;32m 473\u001b[0m \u001b[0mmode\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmode\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 474\u001b[0m \u001b[0mtraining_context\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mtraining_context\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 475\u001b[1;33m total_epochs=1)\n\u001b[0m\u001b[0;32m 476\u001b[0m \u001b[0mcbks\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmake_logs\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mepoch_logs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 477\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\keras\\engine\\training_v2.py\u001b[0m in \u001b[0;36mrun_one_epoch\u001b[1;34m(model, iterator, execution_function, dataset_size, batch_size, strategy, steps_per_epoch, num_samples, mode, training_context, total_epochs)\u001b[0m\n\u001b[0;32m 126\u001b[0m step=step, mode=mode, size=current_batch_size) as batch_logs:\n\u001b[0;32m 127\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 128\u001b[1;33m \u001b[0mbatch_outs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mexecution_function\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0miterator\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 129\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mStopIteration\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mOutOfRangeError\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 130\u001b[0m \u001b[1;31m# TODO(kaftan): File bug about tf function and errors.OutOfRangeError?\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\keras\\engine\\training_v2_utils.py\u001b[0m in \u001b[0;36mexecution_function\u001b[1;34m(input_fn)\u001b[0m\n\u001b[0;32m 96\u001b[0m \u001b[1;31m# `numpy` translates Tensors to values in Eager mode.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 97\u001b[0m return nest.map_structure(_non_none_constant_value,\n\u001b[1;32m---> 98\u001b[1;33m distributed_function(input_fn))\n\u001b[0m\u001b[0;32m 99\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 100\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mexecution_function\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\eager\\def_function.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args, **kwds)\u001b[0m\n\u001b[0;32m 566\u001b[0m \u001b[0mxla_context\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mExit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 567\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 568\u001b[1;33m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_call\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 569\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 570\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mtracing_count\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_tracing_count\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\eager\\def_function.py\u001b[0m in \u001b[0;36m_call\u001b[1;34m(self, *args, **kwds)\u001b[0m\n\u001b[0;32m 604\u001b[0m \u001b[1;31m# In this case we have not created variables on the first call. So we can\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 605\u001b[0m \u001b[1;31m# run the first trace but we should fail if variables are created.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 606\u001b[1;33m \u001b[0mresults\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_stateful_fn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 607\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_created_variables\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 608\u001b[0m raise ValueError(\"Creating variables on a non-first call to a function\"\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\eager\\function.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 2361\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_lock\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2362\u001b[0m \u001b[0mgraph_function\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwargs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_maybe_define_function\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2363\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mgraph_function\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_filtered_call\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m# pylint: disable=protected-access\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2364\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2365\u001b[0m \u001b[1;33m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\eager\\function.py\u001b[0m in \u001b[0;36m_filtered_call\u001b[1;34m(self, args, kwargs)\u001b[0m\n\u001b[0;32m 1609\u001b[0m if isinstance(t, (ops.Tensor,\n\u001b[0;32m 1610\u001b[0m resource_variable_ops.BaseResourceVariable))),\n\u001b[1;32m-> 1611\u001b[1;33m self.captured_inputs)\n\u001b[0m\u001b[0;32m 1612\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1613\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_call_flat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcaptured_inputs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcancellation_manager\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\eager\\function.py\u001b[0m in \u001b[0;36m_call_flat\u001b[1;34m(self, args, captured_inputs, cancellation_manager)\u001b[0m\n\u001b[0;32m 1690\u001b[0m \u001b[1;31m# No tape is watching; skip to running the function.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1691\u001b[0m return self._build_call_outputs(self._inference_function.call(\n\u001b[1;32m-> 1692\u001b[1;33m ctx, args, cancellation_manager=cancellation_manager))\n\u001b[0m\u001b[0;32m 1693\u001b[0m forward_backward = self._select_forward_and_backward_functions(\n\u001b[0;32m 1694\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\eager\\function.py\u001b[0m in \u001b[0;36mcall\u001b[1;34m(self, ctx, args, cancellation_manager)\u001b[0m\n\u001b[0;32m 543\u001b[0m \u001b[0minputs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 544\u001b[0m \u001b[0mattrs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"executor_type\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexecutor_type\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"config_proto\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 545\u001b[1;33m ctx=ctx)\n\u001b[0m\u001b[0;32m 546\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 547\u001b[0m outputs = execute.execute_with_cancellation(\n",
"\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\tensorflow_core\\python\\eager\\execute.py\u001b[0m in \u001b[0;36mquick_execute\u001b[1;34m(op_name, num_outputs, inputs, attrs, ctx, name)\u001b[0m\n\u001b[0;32m 59\u001b[0m tensors = pywrap_tensorflow.TFE_Py_Execute(ctx._handle, device_name,\n\u001b[0;32m 60\u001b[0m \u001b[0mop_name\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minputs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mattrs\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 61\u001b[1;33m num_outputs)\n\u001b[0m\u001b[0;32m 62\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mcore\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_NotOkStatusException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 63\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mname\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mKeyboardInterrupt\u001b[0m: "
]
}
],
"source": [
"# generate reference sets\n",
"\n",
"nb_sets = 5\n",
"nb = 1000\n",
"\n",
"x_list = []\n",
"y_list = []\n",
"accuracy_list = []\n",
"\n",
"for i in range(nb_sets):\n",
" id0 = int(int(len(data))/(nb_sets-1)*(i)-nb)-100 # ignore the 100 last entries\n",
" if id0 < 0:\n",
" id0 = 0\n",
" names, s_year, e_year, count = get_names(data, nb=nb, id0=id0)\n",
" names_train, names_test = split_and_shuffle(names)\n",
" print(\"id \" + str(id0) + \", from year \" + str(s_year) + \" to \" + str(e_year))\n",
" \n",
" one_hot_names_test = to_one_hot(names_test)\n",
"\n",
" x_test_set, y_test_set = to_sequence(one_hot_names_test)\n",
" \n",
" x_list.append(x_test_set)\n",
" y_list.append(y_test_set)\n",
" accuracy_list.append([])\n",
"\n",
"nb=1000\n",
"id_list = []\n",
"train_acc = []\n",
"test_acc = []\n",
"for id0 in range(0, len(data)-2*nb, nb):\n",
" print(\"start index for training is \" + str(id0) + \" out of \" + str(len(data)))\n",
" id_list.append(id0)\n",
" \n",
" names, s_year, e_year, count = get_names(data, nb=nb, id0=id0)\n",
" names_train, names_test = split_and_shuffle(names)\n",
"\n",
" one_hot_names_train, one_hot_names_test = to_one_hot(names_train, names_test)\n",
"\n",
" x_train, y_train, x_test, y_test = to_sequence(one_hot_names_train, one_hot_names_test)\n",
" \n",
" history = model.fit(\n",
" x_train, y_train, validation_data=(x_test, y_test), batch_size=1000, epochs=10, verbose=3\n",
" )\n",
" \n",
" history = model.evaluate(x_train, y_train)\n",
" train_acc.append(history[1])\n",
" \n",
" history = model.evaluate(x_test, y_test)\n",
" test_acc.append(history[1])\n",
" \n",
" for i in range(nb_sets):\n",
" history = model.evaluate(x_list[i], y_list[i])\n",
" accuracy_list[i].append(history[1])\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"5647427\n",
"989\n",
"990\n",
"990\n",
"990\n"
]
}
],
"source": [
"print(len(data))\n",
"print(len(id_list[:-1]))\n",
"print(len(id_list))\n",
"print(len(accuracy_list[0]))\n",
"print(len(train_acc))"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"1\n",
"2\n",
"3\n",
"4\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"for i in range(nb_sets):\n",
" print(i)\n",
" plt.plot(id_list[:len(accuracy_list[i])], accuracy_list[i])\n",
"plt.plot(id_list, train_acc)\n",
"plt.plot(id_list, test_acc)\n",
"plt.title('model evolution')\n",
"plt.ylabel('accuracy')\n",
"plt.xlabel('start_id_training')\n",
"plt.legend(['0', '1', '2', '3', '4', 'train', 'test'], loc='upper left')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def from_one_hot(pred, mode=\"proba\"):\n",
" return [from_one_hot_single(li, mode) for li in pred[:]]\n",
"\n",
"def from_one_hot_single(single_pred, mode=\"proba\"):\n",
" if mode == \"max\":\n",
" letter_num = np.argmax(single_pred)\n",
" elif \"proba\" in mode:\n",
" if mode == \"probaLim\":\n",
" prenorm = np.sum(single_pred)\n",
" single_pred[single_pred < 0.05*prenorm] = 0\n",
" norm = np.sum(single_pred)\n",
" rand = random.uniform(0, norm)\n",
" # print(rand)\n",
" lim = single_pred[0]\n",
" letter_num = 0\n",
" \n",
" while lim < rand:\n",
" letter_num += 1\n",
" lim += single_pred[letter_num]\n",
" \n",
" if norm < 0.1:\n",
" letter_num = 0\n",
" \n",
" print(single_pred[letter_num])\n",
" \n",
" return int_to_char[letter_num]\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def generate_word():\n",
" start_seq = np.zeros((1,x_train.shape[1],27))\n",
" # set every where spaces\n",
" start_seq[:, 0] = 1\n",
" gen_name = \"\"\n",
" \n",
" # do while\n",
" while True:\n",
" gen_vec = model.predict(start_seq)\n",
" gen_letter = from_one_hot(gen_vec, \"probaLim\")\n",
" \n",
" if gen_letter[0] == \" \":\n",
" break\n",
"\n",
" gen_name += gen_letter[0]\n",
" print(gen_name)\n",
" \n",
" if len(gen_name) > 10:\n",
" break\n",
" \n",
" one_hot_gen = to_one_hot([gen_name])\n",
"\n",
" x_gen, y_gen = to_sequence(one_hot_gen)\n",
" \n",
" shift = len(gen_name)\n",
" if shift > x_gen.shape[1]:\n",
" pos = -1\n",
" else:\n",
" pos = shift-(x_gen.shape[1]+1)\n",
" start_seq = x_gen[pos]\n",
" start_seq = np.expand_dims(start_seq, axis=0)\n",
" # print(start_seq) \n",
" \n",
"for _ in range(10):\n",
" generate_word()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"start_seq = np.zeros((1,x_train.shape[1],27))\n",
"# set every where spaces\n",
"start_seq[:, 0] = 1\n",
"gen_name = \"\"\n",
"\n",
"gen_vec = model.predict(start_seq)\n",
"print(gen_vec)\n",
"print(gen_vec.shape)\n",
"gen_letter = from_one_hot(gen_vec, \"max\")\n",
"print(gen_letter)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"start_seq = np.zeros((1,x_train.shape[1],27))\n",
"y_pred = model.predict(start_seq)\n",
"print(from_one_hot(y_pred, \"proba\"))\n",
"print(y_pred)\n",
"print(start_seq.shape)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"y_pred = model.predict(x_test[0:1])\n",
"print(y_pred.shape)\n",
"print(x_test.shape)\n",
"print(x_test[0:1].shape)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# y_pred = model.predict(x_test)\n",
"print(y_pred.shape)\n",
"print(y_pred[1,:])\n",
"print(np.argmax(y_pred[1,1:]))\n",
"print([np.argmax(li[:]) for li in y_pred[:]])\n",
"print([np.argmax(li[:]) for li in y_data[:]])\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## convert one-hot-coded vectors back to string"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pred_num_letter = [np.argmax(li[:]) for li in y_pred[:]]\n",
"pred_letter = [int_to_char[num_letter] for num_letter in pred_num_letter]\n",
"\n",
"print(pred_letter)\n",
"\n",
"pred_num_letter = [np.argmax(li[:]) for li in y_data[:]]\n",
"pred_letter = [int_to_char[num_letter] for num_letter in pred_num_letter]\n",
"\n",
"print(pred_letter)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n",
"tf.linalg.matmul(embedded_vector,tf.linalg.pinv(embedding_layer.weights[0]))\n",
"\n",
"# https://stackoverflow.com/questions/45773660/reverse-word-embeddings-in-keras-python"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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