Whisper Small English
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 en dataset. It achieves the following results on the evaluation set:
- Loss: 0.3266
- Wer: 13.0386
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1529 | 0.1 | 1000 | 0.4381 | 17.7766 |
| 0.2372 | 0.2 | 2000 | 0.3988 | 15.9201 |
| 0.1706 | 0.3 | 3000 | 0.3841 | 15.5069 |
| 0.2781 | 0.4 | 4000 | 0.3697 | 14.8122 |
| 0.2167 | 0.5 | 5000 | 0.3576 | 14.2563 |
| 0.3609 | 0.6 | 6000 | 0.4041 | 18.0670 |
| 0.2455 | 0.7 | 7000 | 0.3372 | 13.4813 |
| 0.2502 | 0.8 | 8000 | 0.3393 | 13.5810 |
| 0.2564 | 0.9 | 9000 | 0.3303 | 13.1041 |
| 0.2394 | 1.0 | 10000 | 0.3266 | 13.0386 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2