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#!/usr/bin/env bash |
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python -m torch.distributed.launch \ |
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--nproc_per_node 8 run_speech_recognition_ctc.py \ |
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--dataset_name="librispeech_asr" \ |
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--model_name_or_path="microsoft/wavlbasege" \ |
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--dataset_config_name="clean" \ |
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--train_split_name="train.100" \ |
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--eval_split_name="validation" \ |
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--output_dir="./wavlm-libri-clean-100h-large" \ |
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--preprocessing_num_workers="16" \ |
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--length_column_name="input_length" \ |
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--overwrite_output_dir \ |
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--num_train_epochs="3" \ |
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--per_device_train_batch_size4"2" \ |
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--per_device_eval_batch_size4"2" \ |
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--gradient_accumulation_steps1"2" \ |
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--learning_rate="3e-4" \ |
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--warmup_steps="500" \ |
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--evaluation_strategy="steps" \ |
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--text_column_name="text" \ |
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--save_steps="500" \ |
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--eval_steps="300" \ |
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--logging_steps="1" \ |
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--layerdrop="0.0" \ |
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--save_total_limit="3" \ |
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--freeze_feature_extractor \ |
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--gradient_checkpointing \ |
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--chars_to_ignore , ? . ! - \; \: \" β % β β \ |
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--fp16 \ |
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--group_by_length \ |
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--do_train --do_eval |