run_librispeech.sh

#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=1 python run_speech_recognition_seq2seq.py \
	--dataset_name="librispeech_asr" \
	--model_name_or_path="./" \
	--tokenizer_name="./" \
	--dataset_config_name="clean" \
	--train_split_name="train.100" \
	--eval_split_name="validation" \
	--output_dir="./" \
	--preprocessing_num_workers="1" \
	--length_column_name="input_length" \
	--overwrite_output_dir \
	--num_train_epochs="3" \
	--per_device_train_batch_size="14" \
	--per_device_eval_batch_size="14" \
	--gradient_accumulation_steps="8" \
	--generation_max_length="40" \
	--generation_num_beams="1" \
	--learning_rate="1e-3" \
	--warmup_steps="500" \
	--evaluation_strategy="steps" \
	--text_column_name="text" \
	--save_steps="500" \
	--eval_steps="500" \
	--logging_steps="1" \
	--save_total_limit="1" \
	--freeze_feature_encoder \
	--gradient_checkpointing \
	--fp16 \
	--group_by_length \
	--predict_with_generate \
	--do_lower_case \
	--do_eval --do_train \
	--push_to_hub \
	--use_auth_token