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command: |
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- python3 |
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- ${program} |
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- --overwrite_output_dir |
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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_train |
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- --do_eval |
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- ${args} |
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method: random |
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metric: |
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goal: minimize |
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name: eval/wer |
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parameters: |
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dataset_cache_dir: |
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value: /home/sanchitgandhi/cache/huggingface/datasets |
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dataset_config_name: |
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value: clean |
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dataset_name: |
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value: librispeech_asr |
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eval_split_name: |
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value: validation |
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eval_steps: |
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value: 500 |
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generation_max_length: |
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value: 40 |
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generation_num_beams: |
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value: 1 |
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gradient_accumulation_steps: |
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value: 1 |
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gradient_checkpointing: |
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value: True |
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learning_rate: |
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distribution: log_uniform |
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max: -6.9 |
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min: -9.2 |
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length_column_name: |
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value: input_length |
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logging_steps: |
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value: 25 |
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max_duration_in_seconds: |
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value: 20 |
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max_target_length: |
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value: 128 |
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model_name_or_path: |
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value: ./ |
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num_train_epochs: |
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value: 3 |
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output_dir: |
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value: ./output_dir |
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per_device_eval_batch_size: |
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value: 2 |
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per_device_train_batch_size: |
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value: 1 |
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preprocessing_num_workers: |
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value: 16 |
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text_column_name: |
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value: text |
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train_split_name: |
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value: train.100 |
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warmup_steps: |
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value: 500 |
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program: run_flax_speech_recognition_seq2seq.py |
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project: flax-wav2vec2-2-bart-large-checkpointing-scan |
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