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: 0.3107
- Wer: 12.0213
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: 40000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1577 | 0.06 | 2500 | 0.4077 | 16.2349 |
| 0.2244 | 0.12 | 5000 | 0.3698 | 14.7325 |
| 0.3231 | 0.19 | 7500 | 0.3434 | 13.7448 |
| 0.2536 | 0.25 | 10000 | 0.3406 | 13.4981 |
| 0.2234 | 0.31 | 12500 | 0.3510 | 14.1304 |
| 0.1989 | 0.38 | 15000 | 0.3388 | 13.6394 |
| 0.2449 | 0.44 | 17500 | 0.3394 | 13.4293 |
| 0.2302 | 0.5 | 20000 | 0.3198 | 12.5020 |
| 0.213 | 0.56 | 22500 | 0.3167 | 12.4904 |
| 0.2395 | 0.62 | 25000 | 0.3145 | 12.7533 |
| 0.1152 | 0.69 | 27500 | 0.3181 | 12.6087 |
| 0.0901 | 1.01 | 30000 | 0.3134 | 12.3240 |
| 0.1595 | 1.07 | 32500 | 0.3107 | 12.0213 |
| 0.1249 | 1.13 | 35000 | 0.3131 | 12.0869 |
| 0.1404 | 1.2 | 37500 | 0.3117 | 12.4635 |
| 0.1812 | 1.26 | 40000 | 0.3104 | 12.1415 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2