language: | |
- en | |
tags: | |
- esc | |
datasets: | |
- common_voice | |
To reproduce this run, execute: | |
```python | |
#!/usr/bin/env bash | |
CUDA_VISIBLE_DEVICES=0 python run_speech_recognition_whisper.py \ | |
--model_name_or_path="medium.en" \ | |
--dataset_name="esc-benchmark/esc-datasets" \ | |
--dataset_config_name="common_voice" \ | |
--max_steps="5000" \ | |
--output_dir="./" \ | |
--run_name="whisper-common-voice" \ | |
--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="1000" \ | |
--save_strategy="steps" \ | |
--save_steps="1000" \ | |
--generation_max_length="224" \ | |
--length_column_name="input_lengths" \ | |
--max_eval_duration_in_seconds="20" \ | |
--gradient_checkpointing \ | |
--group_by_length \ | |
--freeze_encoder \ | |
--fp16 \ | |
--overwrite_output_dir \ | |
--do_train \ | |
--do_eval \ | |
--do_predict \ | |
--predict_with_generate \ | |
--use_auth_token | |
``` | |