training / flax /run_orig_longform.sh
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#!/usr/bin/env bash
names=("openai/whisper-large-v2" "openai/whisper-medium.en" "openai/whisper-small.en" "openai/whisper-base.en" "openai/whisper-tiny.en")
names=("openai/whisper-small.en" "openai/whisper-base.en" "openai/whisper-tiny.en")
# names=("patrickvonplaten/whisper-large-v2-32-2" "patrickvonplaten/whisper-medium-24-2")
# chunk_lengths=("15.0" "30.0")
# --return_timestamps \
# --assistant_model_name_or_path "patrickvonplaten/whisper-large-v2-32-2" \
# --attn_type "flash2" \
# Double loop
for name in "${names[@]}"; do
CUDA_VISIBLE_DEVICES="1" python ./run_speed_pt.py \
--dataset_name "distil-whisper/earnings21+distil-whisper/earnings22+distil-whisper/meanwhile+distil-whisper/rev16" \
--wandb_name "A100-${name}-Longform-Orig" \
--model_name_or_path ${name} \
--wandb_project "distil-whisper-speed-bench-long-form-orig-32" \
--dataset_config_name "full+full+default+whisper_subset" \
--dataset_split_name "test+test+test+test" \
--text_column_name "transcription+transcription+text+transcription" \
--use_orig_whisper \
--max_label_length "1000000" \
--samples_per_dataset "32" \
--batch_size "1"
done