training / flax /pseudo_labelling_scripts /run_librispeech_pseudo_labelling.sh
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Saving train state of step 5000
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#!/usr/bin/env bash
python run_pseudo_labelling.py \
--model_name_or_path "openai/whisper-large-v2" \
--dataset_name "sanchit-gandhi/librispeech_asr_clean" \
--dataset_config_name "clean" \
--data_split_name "train.100" \
--text_column_name "text" \
--cache_dir "/home/sanchitgandhi/cache" \
--dataset_cache_dir "/home/sanchitgandhi/cache" \
--output_dir "./transcriptions-streaming" \
--wandb_dir "/home/sanchitgandhi/.cache" \
--wandb_project "distil-whisper-debug" \
--wandb_name "whisper-large-v2-beam-libri-train.clean.100" \
--per_device_eval_batch_size 16 \
--max_label_length 256 \
--dtype "bfloat16" \
--preprocessing_num_workers 16 \
--report_to "wandb" \
--dataloader_num_workers 16 \
--streaming False \
--generation_num_beams 1