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#!/usr/bin/env bash |
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accelerate launch run_distillation.py \ |
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--model_name_or_path "./checkpoint-33000-epoch-1-val-wer-10.871" \ |
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--teacher_model_name_or_path "NbAiLab/nb-whisper-large" \ |
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--train_dataset_name "NbAiLab/annotated_distil_raw_ncc_speech_v7_large" \ |
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--train_dataset_config_name "" \ |
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--train_split_name "train" \ |
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--eval_dataset_name "NbAiLab/ncc_speech_v7" \ |
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--eval_dataset_config_name "" \ |
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--eval_split_name "validation_norwegian_fleurs" \ |
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--eval_steps 500 \ |
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--save_steps 1000 \ |
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--warmup_steps 1000 \ |
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--learning_rate 0.0003 \ |
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--lr_scheduler_type "constant_with_warmup" \ |
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--timestamp_probability 0.2 \ |
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--condition_on_prev_probability 0.2 \ |
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--language "no" \ |
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--task "transcribe" \ |
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--logging_steps 200 \ |
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--save_total_limit 1 \ |
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--max_steps 100000 \ |
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--wer_threshold 10 \ |
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--per_device_train_batch_size 32 \ |
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--per_device_eval_batch_size 32 \ |
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--dataloader_num_workers 8 \ |
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--preprocessing_num_workers 8 \ |
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--ddp_timeout 7200 \ |
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--dtype "bfloat16" \ |
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--attn_implementation "sdpa" \ |
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--output_dir "./" \ |
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--do_train \ |
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--do_eval \ |
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--gradient_checkpointing \ |
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--overwrite_output_dir \ |
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--predict_with_generate \ |
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--freeze_encoder \ |
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--freeze_embed_positions \ |
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--streaming True \ |
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--wandb_project "nb-distil-whisper-large-fleurseval" \ |
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--wandb_name "pytorch_lr3e4_wer10" \ |
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--hub_model_id "NbAiLab/nb-distil-whisper-large-pytorch-wer1-recover33k" \ |
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--push_to_hub |
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