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python run_whisper_finetuning.py \ |
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--model_name_or_path="openai/whisper-small" \ |
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--output_dir="../whisper-NST-cons2e5" \ |
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--overwrite_output_dir=True \ |
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--language="Norwegian" \ |
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--task="transcribe" \ |
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--dataset_name="NbAiLab/NST" \ |
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--dataset_config="no-close" \ |
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--do_train=True \ |
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--do_eval=True \ |
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--audio_column_name="audio" \ |
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--text_column_name="text" \ |
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--per_device_train_batch_size=16 \ |
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--per_device_train_batch_size=16 \ |
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--learning_rate=2e-5 \ |
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--lr_scheduler_type="constant_with_warmup" \ |
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--warmup_steps=500 \ |
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--max_steps=10000 \ |
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--gradient_checkpointing=True \ |
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--gradient_accumulation_steps=1 \ |
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--group_by_length=False \ |
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--evaluation_strategy="steps" \ |
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--save_steps=1000 \ |
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--eval_steps=1000 \ |
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--max_eval_samples=100 \ |
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--logging_steps=250 \ |
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--fp16=True \ |
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--load_best_model_at_end=True \ |
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--metric_for_best_model="wer" \ |
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--greater_is_better=False \ |
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--report_to="tensorboard" \ |
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--predict_with_generate=True \ |
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--generation_max_length=225 \ |
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--print_training_arguments=True \ |
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--ignore_data_skip=True \ |
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--push_to_hub=True |
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