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#!/usr/bin/env bash |
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CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_whisper.py \ |
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--model_name_or_path="medium.en" \ |
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--dataset_name="esb/datasets" \ |
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--dataset_config_name="ami" \ |
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--max_steps="2500" \ |
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--output_dir="./" \ |
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--run_name="whisper-ami" \ |
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--dropout_rate="0.1" \ |
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--wandb_project="whisper" \ |
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--per_device_train_batch_size="64" \ |
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--per_device_eval_batch_size="16" \ |
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--logging_steps="25" \ |
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--learning_rate="1e-4" \ |
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--warmup_steps="500" \ |
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--report_to="wandb" \ |
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--preprocessing_num_workers="16" \ |
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--evaluation_strategy="steps" \ |
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--eval_steps="500" \ |
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--save_strategy="steps" \ |
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--save_steps="500" \ |
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--generation_max_length="224" \ |
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--length_column_name="input_lengths" \ |
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--gradient_checkpointing \ |
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--group_by_length \ |
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--freeze_encoder \ |
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--fp16 \ |
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--overwrite_output_dir \ |
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--do_train \ |
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--do_eval \ |
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--do_predict \ |
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--predict_with_generate \ |
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--use_auth_token |
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