finetune_base_100.sh
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	#!/usr/bin/env bash
	python run_asr.py \
	--output_dir="./wav2vec2-base-100h" \
	--num_train_epochs="30" \
	--per_device_train_batch_size="32" \
	--per_device_eval_batch_size="32" \
	--evaluation_strategy="steps" \
	--save_total_limit="3" \
	--save_steps="500" \
	--eval_steps="100" \
	--logging_steps="50" \
	--learning_rate="5e-4" \
	--warmup_steps="3000" \
	--model_name_or_path="facebook/wav2vec2-base" \
	--fp16 \
	--dataset_name="librispeech_asr" \
	--dataset_config_name="clean" \
	--train_split_name="train.100" \
	--preprocessing_num_workers="32" \
	--group_by_length \
	--freeze_feature_extractor