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#!/usr/bin/env bash |
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python run_flax_speech_recognition_seq2seq.py \ |
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--dataset_name="librispeech_asr" \ |
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--model_name_or_path="./" \ |
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--dataset_config_name="clean" \ |
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--train_split_name="train.100[:5%]" \ |
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--eval_split_name="validation[:5%]" \ |
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--dataset_cache_dir="~/cache/huggingface/datasets" \ |
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--output_dir="./output_dir" \ |
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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="10" \ |
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--per_device_train_batch_size="4" \ |
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--per_device_eval_batch_size="4" \ |
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--gradient_accumulation_steps="1" \ |
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--logging_steps="25" \ |
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--max_duration_in_seconds="10" \ |
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--max_target_length="64" \ |
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--generation_max_length="40" \ |
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--generation_num_beams="1" \ |
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--learning_rate="3e-4" \ |
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--warmup_steps="500" \ |
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--text_column_name="text" \ |
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--save_total_limit="1" \ |
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--freeze_feature_encoder \ |
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--predict_with_generate \ |
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--do_lower_case \ |
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--do_eval \ |
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--do_train \ |
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--push_to_hub \ |
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--use_auth_token \ |
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--wandb_project="flax-wav2vec2-2-bart-debug" |
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