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#!/usr/bin/env bash |
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CUDA_VISIBLE_DEVICES="1" python run_speech_recognition_ctc.py \ |
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--dataset_name="multilingual_librispeech" \ |
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--model_name_or_path="facebook/wav2vec2-large-xlsr-53" \ |
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--train_split_name="train.9h" \ |
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--dataset_config_name="german" \ |
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--output_dir="./wav2vec2-xlsr-53-300m-mls-german-ft" \ |
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--overwrite_output_dir \ |
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--num_train_epochs="100" \ |
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--per_device_train_batch_size="32" \ |
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--gradient_accumulation_steps="1" \ |
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--learning_rate="1e-4" \ |
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--activation_dropout="0.1" \ |
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--warmup_steps="1000" \ |
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--evaluation_strategy="steps" \ |
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--text_column_name="text" \ |
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--save_steps="1000" \ |
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--eval_steps="500" \ |
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--logging_steps="10" \ |
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--layerdrop="0.1" \ |
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--hidden_dropout="0.0" \ |
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--save_total_limit="1" \ |
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--mask_time_prob="0.75" \ |
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--mask_feature_prob="0.25" \ |
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--mask_feature_length="64" \ |
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--freeze_feature_extractor \ |
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--fp16 \ |
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--group_by_length \ |
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--do_eval \ |
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--gradient_checkpointing \ |
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--use_auth_token \ |
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--do_train --do_eval \ |
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--push_to_hub \ |
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