To reproduce this run, first install Whisper from the Transformers compatible repo patrickvonplaten/whisper:

pip install git+https://github.com/openai/whisper.git

Then execute the command:

#!/usr/bin/env bash
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_whisper.py \
 --model_name_or_path="medium.en" \
 --dataset_name="esb/datasets" \
 --dataset_config_name="voxpopuli" \
 --max_steps="5000" \
 --output_dir="./" \
 --run_name="whisper-voxpopuli" \
 --wandb_project="whisper" \
 --per_device_train_batch_size="64" \
 --per_device_eval_batch_size="16" \
 --logging_steps="25" \
 --learning_rate="1e-4" \
 --warmup_steps="500" \
 --report_to="wandb" \
 --preprocessing_num_workers="16" \
 --evaluation_strategy="steps" \
 --eval_steps="500" \
 --save_strategy="steps" \
 --save_steps="500" \
 --generation_max_length="224" \
 --length_column_name="input_lengths" \
 --gradient_checkpointing \
 --group_by_length \
 --freeze_encoder \
 --fp16 \
 --overwrite_output_dir \
 --do_train \
 --do_eval \
 --do_predict \
 --predict_with_generate \
 --use_auth_token