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Saving train state of step 50
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#!/usr/bin/env bash
# --assistant_model_name_or_path "patrickvonplaten/whisper-large-v2-32-2" \
# --attn_type "flash2" \
names=("openai/whisper-large-v2" "openai/whisper-medium.en" "openai/whisper-small.en" "openai/whisper-base.en" "openai/whisper-tiny.en" "patrickvonplaten/whisper-large-v2-32-2" "patrickvonplaten/whisper-medium-24-2")
batch_sizes=(1 4 16)
# Double loop
for name in "${names[@]}"; do
for batch_size in "${batch_sizes[@]}"; do
CUDA_VISIBLE_DEVICES="1" python ./run_speed_pt.py \
--dataset_name "google/fleurs+distil-whisper/chime4+distil-whisper/earnings22+kensho/spgispeech" \
--wandb_name "A100-bsz${batch_size}-${name}" \
--model_name_or_path ${name} \
--wandb_project "distil-whisper-speed-bench-256-no-timestamps" \
--dataset_config_name "en_us+1-channel+chunked+test" \
--dataset_split_nam "test+test+test+test" \
--text_column_name "transcription+text+transcription+transcript" \
--samples_per_dataset "256" \
--batch_size ${batch_size}
done
done