whishper
This model is a fine-tuned version of openai/whisper-small on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5474
- Wer: 72.2488
- Cer: 29.9605
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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 0.5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.2442 | 0.0333 | 5 | 0.8071 | 140.3509 | 157.0811 |
| 0.2386 | 0.0667 | 10 | 0.7964 | 146.2520 | 136.7877 |
| 0.3848 | 0.1 | 15 | 0.7687 | 146.8900 | 111.5479 |
| 0.3015 | 0.1333 | 20 | 0.7213 | 157.0973 | 126.8761 |
| 0.2178 | 0.1667 | 25 | 0.6916 | 159.1707 | 144.8561 |
| 0.2314 | 0.2 | 30 | 0.6551 | 149.6013 | 125.3526 |
| 0.2112 | 0.2333 | 35 | 0.6239 | 99.3620 | 64.2844 |
| 0.1571 | 0.2667 | 40 | 0.5794 | 76.5550 | 35.1514 |
| 0.1934 | 0.3 | 45 | 0.5547 | 73.0463 | 33.7596 |
| 0.3231 | 0.3333 | 50 | 0.5474 | 72.2488 | 29.9605 |
| 0.1035 | 0.3667 | 55 | 0.5434 | 72.5678 | 32.3491 |
| 0.1991 | 0.4 | 60 | 0.5454 | 74.0032 | 31.4275 |
| 0.196 | 0.4333 | 65 | 0.5495 | 73.5247 | 36.0166 |
| 0.4541 | 0.4667 | 70 | 0.5448 | 73.3652 | 38.5556 |
| 0.2166 | 0.5 | 75 | 0.5418 | 73.3652 | 39.3455 |
Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0