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#!/usr/bin/env bash
python run_finetuning.py \
--model_name_or_path "openai/whisper-large-v2" \
--dataset_name "sanchit-gandhi/librispeech-data" \
--dataset_config_name "all" \
--train_split_name "train.clean.100+train.clean.360+train.other.500" \
--eval_split_name "validation.clean" \
--text_column_name "text" \
--cache_dir "/home/sanchitgandhi/cache" \
--dataset_cache_dir "/home/sanchitgandhi/cache" \
--output_dir "./" \
--wandb_name "large-v2-ft-ls" \
--wandb_dir "/home/sanchitgandhi/cache" \
--wandb_project "flax-whisper-librispeech" \
--per_device_train_batch_size 4 \
--per_device_eval_batch_size 16 \
--dtype "bfloat16" \
--optim "adafactor" \
--learning_rate 1e-4 \
--warmup_steps 500 \
--do_train \
--do_eval \
--num_train_epochs 10 \
--preprocessing_num_workers 16 \
--dataloader_num_workers 64 \
--logging_steps 25 \
--use_scan \
--gradient_checkpointing \
--overwrite_output_dir \
--predict_with_generate \
--push_to_hub
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