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#!/usr/bin/env bash
python -m torch.distributed.launch \
--nproc_per_node 8 run_speech_recognition_ctc.py \
--dataset_name="librispeech_asr" \
--model_name_or_path="microsoft/wavlm-base" \
--dataset_config_name="clean" \
--train_split_name="train.100" \
--eval_split_name="validation" \
--output_dir="./wavlm-libri-clean-100h-base" \
--preprocessing_num_workers="16" \
--length_column_name="input_length" \
--overwrite_output_dir \
--num_train_epochs="3" \
--per_device_train_batch_size="4" \
--per_device_eval_batch_size="4" \
--gradient_accumulation_steps="1" \
--learning_rate="3e-4" \
--warmup_steps="500" \
--evaluation_strategy="steps" \
--text_column_name="text" \
--save_steps="500" \
--eval_steps="300" \
--logging_steps="1" \
--layerdrop="0.0" \
--save_total_limit="3" \
--freeze_feature_extractor \
--gradient_checkpointing \
--chars_to_ignore , ? . ! - \; \: \" β€œ % β€˜ ” \
--fp16 \
--group_by_length \
--do_train --do_eval