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#!/usr/bin/env bash
TCMALLOC_LARGE_ALLOC_REPORT_THRESHOLD=10000000000 python3 run_distillation.py \
--model_name_or_path "distil-whisper/large-32-2" \
--teacher_model_name_or_path "openai/whisper-large-v2" \
--train_dataset_config_name "all+all+all+l" \
--train_dataset_samples "100+360+500+2500" \
--train_dataset_name "librispeech_asr-token-ids+librispeech_asr-token-ids+librispeech_asr-token-ids+gigaspeech-l-token-ids" \
--train_split_name "train.clean.100+train.clean.360+train.other.500+train" \
--eval_dataset_name "librispeech_asr+librispeech_asr+gigaspeech-l" \
--eval_dataset_config_name "all+all+l" \
--eval_split_name "validation.clean+validation.other+validation" \
--eval_text_column_name "text+text+text" \
--eval_steps 5000 \
--save_steps 5000 \
--warmup_steps 50 \
--learning_rate 0.0001 \
--lr_scheduler_type "constant_with_warmup" \
--logging_steps 25 \
--save_total_limit 1 \
--max_steps 10000 \
--wer_threshold 10 \
--per_device_train_batch_size 64 \
--per_device_eval_batch_size 64 \
--dataloader_num_workers 16 \
--cache_dir "/home/sanchitgandhi/.cache" \
--dataset_cache_dir "/home/sanchitgandhi/.cache" \
--dtype "bfloat16" \
--output_dir "./" \
--wandb_name "large-32-2-ls-gs-token-ids" \
--wandb_dir "/home/sanchitgandhi/.cache" \
--wandb_project "distil-whisper" \
--do_train \
--do_eval \
--use_scan \
--gradient_checkpointing \
--overwrite_output_dir \
--predict_with_generate \
--freeze_encoder \
--streaming \
--use_auth_token \
--push_to_hub
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