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#!/usr/bin/env bash
python run_eval.py \
--model_name_or_path "openai/whisper-tiny.en" \
--dataset_name "librispeech_asr+librispeech_asr+common_voice_13_0+voxpopuli+ami-ihm+ami-sdm+peoples_speech-clean+tedlium+switchboard-data+gigaspeech-l+spgispeech+chime4+google/fleurs+sanchit-gandhi/earnings22_split_resampled" \
--dataset_config_name "all+all+en+en+ihm+sdm+clean+release3+all+l+L+1-channel+en_us+default" \
--dataset_split_name "validation.clean+validation.other+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation" \
--text_column_name "text+text+text+text+text+text+text+text+text+text+text+text+transcription+sentence" \
--cache_dir "/home/sanchitgandhi/.cache" \
--dataset_cache_dir "/home/sanchitgandhi/.cache" \
--output_dir "./" \
--wandb_dir "/home/sanchitgandhi/.cache" \
--wandb_project "distil-whisper-eval" \
--wandb_name "tiny.en" \
--per_device_eval_batch_size 32 \
--dtype "bfloat16" \
--dataloader_num_workers 0 \
--report_to "wandb" \
--streaming \
--predict_with_generate
python run_eval.py \
--model_name_or_path "openai/whisper-base.en" \
--dataset_name "librispeech_asr+librispeech_asr+common_voice_13_0+voxpopuli+ami-ihm+ami-sdm+peoples_speech-clean+tedlium+switchboard-data+gigaspeech-l+spgispeech+chime4+google/fleurs+sanchit-gandhi/earnings22_split_resampled" \
--dataset_config_name "all+all+en+en+ihm+sdm+clean+release3+all+l+L+1-channel+en_us+default" \
--dataset_split_name "validation.clean+validation.other+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation" \
--text_column_name "text+text+text+text+text+text+text+text+text+text+text+text+transcription+sentence" \
--cache_dir "/home/sanchitgandhi/.cache" \
--dataset_cache_dir "/home/sanchitgandhi/.cache" \
--output_dir "./" \
--wandb_dir "/home/sanchitgandhi/.cache" \
--wandb_project "distil-whisper-eval" \
--wandb_name "base.en" \
--per_device_eval_batch_size 32 \
--dtype "bfloat16" \
--dataloader_num_workers 0 \
--report_to "wandb" \
--streaming \
--predict_with_generate
python run_eval.py \
--model_name_or_path "openai/whisper-small.en" \
--dataset_name "librispeech_asr+librispeech_asr+common_voice_13_0+voxpopuli+ami-ihm+ami-sdm+peoples_speech-clean+tedlium+switchboard-data+gigaspeech-l+spgispeech+chime4+google/fleurs+sanchit-gandhi/earnings22_split_resampled" \
--dataset_config_name "all+all+en+en+ihm+sdm+clean+release3+all+l+L+1-channel+en_us+default" \
--dataset_split_name "validation.clean+validation.other+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation" \
--text_column_name "text+text+text+text+text+text+text+text+text+text+text+text+transcription+sentence" \
--cache_dir "/home/sanchitgandhi/.cache" \
--dataset_cache_dir "/home/sanchitgandhi/.cache" \
--output_dir "./" \
--wandb_dir "/home/sanchitgandhi/.cache" \
--wandb_project "distil-whisper-eval" \
--wandb_name "small.en" \
--per_device_eval_batch_size 32 \
--dtype "bfloat16" \
--dataloader_num_workers 0 \
--report_to "wandb" \
--streaming \
--predict_with_generate
python run_eval.py \
--model_name_or_path "openai/whisper-medium.en" \
--dataset_name "librispeech_asr+librispeech_asr+common_voice_13_0+voxpopuli+ami-ihm+ami-sdm+peoples_speech-clean+tedlium+switchboard-data+gigaspeech-l+spgispeech+chime4+google/fleurs+sanchit-gandhi/earnings22_split_resampled" \
--dataset_config_name "all+all+en+en+ihm+sdm+clean+release3+all+l+L+1-channel+en_us+default" \
--dataset_split_name "validation.clean+validation.other+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation" \
--text_column_name "text+text+text+text+text+text+text+text+text+text+text+text+transcription+sentence" \
--cache_dir "/home/sanchitgandhi/.cache" \
--dataset_cache_dir "/home/sanchitgandhi/.cache" \
--output_dir "./" \
--wandb_dir "/home/sanchitgandhi/.cache" \
--wandb_project "distil-whisper-eval" \
--wandb_name "medium.en" \
--per_device_eval_batch_size 32 \
--dtype "bfloat16" \
--dataloader_num_workers 0 \
--report_to "wandb" \
--streaming \
--predict_with_generate
python run_eval.py \
--model_name_or_path "openai/whisper-large-v2" \
--dataset_name "librispeech_asr+librispeech_asr+common_voice_13_0+voxpopuli+ami-ihm+ami-sdm+peoples_speech-clean+tedlium+switchboard-data+gigaspeech-l+spgispeech+chime4+google/fleurs+sanchit-gandhi/earnings22_split_resampled" \
--dataset_config_name "all+all+en+en+ihm+sdm+clean+release3+all+l+L+1-channel+en_us+default" \
--dataset_split_name "validation.clean+validation.other+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation+validation" \
--text_column_name "text+text+text+text+text+text+text+text+text+text+text+text+transcription+sentence" \
--cache_dir "/home/sanchitgandhi/.cache" \
--dataset_cache_dir "/home/sanchitgandhi/.cache" \
--output_dir "./" \
--wandb_dir "/home/sanchitgandhi/.cache" \
--wandb_project "distil-whisper-eval" \
--wandb_name "large-v2" \
--per_device_eval_batch_size 16 \
--dtype "bfloat16" \
--dataloader_num_workers 0 \
--report_to "wandb" \
--streaming \
--predict_with_generate |