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WANDB_PROJECT=whisper-medium-eu \ |
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python run_speech_recognition_seq2seq_streaming.py \ |
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--model_name_or_path="openai/whisper-medium" \ |
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--dataset_name="mozilla-foundation/common_voice_17_0" \ |
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--dataset_config_name="eu" \ |
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--language="basque" \ |
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--train_split_name="train+validation" \ |
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--eval_split_name="test" \ |
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--model_index_name="Whisper Medium Basque" \ |
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--max_steps="8000" \ |
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--output_dir="./" \ |
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--per_device_train_batch_size="4" \ |
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--per_device_eval_batch_size="8" \ |
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--gradient_accumulation_steps="1" \ |
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--logging_steps="25" \ |
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--learning_rate="1e-5" \ |
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--warmup_steps="500" \ |
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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="225" \ |
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--length_column_name="input_length" \ |
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--max_duration_in_seconds="30" \ |
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--text_column_name="sentence" \ |
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--freeze_feature_encoder="False" \ |
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--report_to="tensorboard" \ |
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--metric_for_best_model="wer" \ |
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--greater_is_better="False" \ |
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--load_best_model_at_end \ |
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--gradient_checkpointing \ |
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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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--predict_with_generate \ |
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--do_normalize_eval \ |
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--streaming \ |
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--push_to_hub \ |
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--report_to "wandb" \ |
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--run_name "whisper-medium-eu" |
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