| command: | |
| - python3 | |
| - ${program} | |
| - --do_train | |
| - --do_eval | |
| - --use_scan | |
| - --gradient_checkpointing | |
| - --overwrite_output_dir | |
| - --predict_with_generate | |
| - ${args} | |
| method: random | |
| metric: | |
| goal: minimize | |
| name: eval/wer | |
| parameters: | |
| model_name_or_path: | |
| value: distil-whisper/large-32-2 | |
| dataset_name: | |
| value: distil-whisper/librispeech_asr | |
| dataset_config_name: | |
| value: all | |
| train_split_name: | |
| value: train.clean.100+train.clean.360+train.other.500 | |
| eval_split_name: | |
| value: validation.clean | |
| text_column_name: | |
| value: whisper_transcript | |
| cache_dir: | |
| value: /home/sanchitgandhi/cache | |
| dataset_cache_dir: | |
| value: /home/sanchitgandhi/cache | |
| output_dir: | |
| value: ./ | |
| per_device_train_batch_size: | |
| value: 32 | |
| per_device_eval_batch_size: | |
| value: 16 | |
| dtype: | |
| value: bfloat16 | |
| learning_rate: | |
| distribution: log_uniform | |
| max: -6.91 | |
| min: -11.51 | |
| warmup_steps: | |
| value 500 | |
| num_train_epochs: | |
| value: 1 | |
| preprocessing_num_workers: | |
| value: 16 | |
| dataloader_num_workers: | |
| value: 16 | |
| logging_steps: | |
| value: 25 | |
| freeze_encoder: | |
| values: | |
| - True | |
| - False | |
| program: run_finetuning.py | |
| project: distil-whisper | |