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#!/usr/bin/env bash
TOKENIZERS_PARALLELISM=false python3 run_distillation.py \
--model_name_or_path "./first-save" \
--teacher_model_name_or_path "NbAiLab/nb-whisper-large" \
--train_dataset_name "NbAiLab/annotated_ncc_speech_styling_v2_vad3_distil_postLv2" \
--train_dataset_config_name "" \
--train_split_name "train" \
--eval_dataset_name "NbAiLab/ncc_speech_v7" \
--eval_dataset_config_name "" \
--eval_split_name "validation_norwegian_fleurs" \
--eval_steps 500 \
--save_steps 5000 \
--warmup_steps 0 \
--learning_rate 0.0003 \
--lr_scheduler_type "constant_with_warmup" \
--logging_steps 500 \
--save_total_limit 2 \
--max_steps 200000 \
--wer_threshold 10 \
--per_device_train_batch_size 4\
--per_device_eval_batch_size 4 \
--dataloader_num_workers 32 \
--dtype "bfloat16" \
--output_dir "./nb-distil-whisper-large-flax7" \
--do_train \
--do_eval \
--use_scan \
--gradient_checkpointing \
--overwrite_output_dir \
--predict_with_generate \
--freeze_encoder \
--streaming \
--use_auth_token \
--report_to "wandb" \
--wandb_project "nb-distil-whisper-large-fleurseval" \
--wandb_name "flax_experiment2_bs4_v5_1e4_wer10_restart10k" \
--save_code_to_wandb \
--save_train_state \
--hub_model_id "NbAiLab/nb-distil-whisper-large-flax7"\
--push_to_hub
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