Whisper Small Ha v10 - Eldad Akhaumere
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:
- Loss: 2.3326
- Wer Ortho: 81.6211
- Wer: 79.5746
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- num_epochs: 90.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0914 | 3.1847 | 500 | 1.7962 | 85.2344 | 83.1194 |
| 0.0298 | 6.3694 | 1000 | 1.9290 | 82.9492 | 80.9734 |
| 0.022 | 9.5541 | 1500 | 2.0141 | 84.1797 | 82.4104 |
| 0.021 | 12.7389 | 2000 | 2.1154 | 80.8984 | 78.8848 |
| 0.0141 | 15.9236 | 2500 | 2.1146 | 83.8086 | 81.9506 |
| 0.0101 | 19.1083 | 3000 | 2.2107 | 79.2383 | 77.5628 |
| 0.0072 | 22.2930 | 3500 | 2.2648 | 82.5391 | 80.9925 |
| 0.0084 | 25.4777 | 4000 | 2.3229 | 81.3477 | 79.0190 |
| 0.0116 | 28.6624 | 4500 | 2.3326 | 81.6211 | 79.5746 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0