openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the pphuc25/FranceMed dataset. It achieves the following results on the evaluation set:
- Loss: 1.5876
- Wer: 35.7771
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.0291 | 1.0 | 215 | 1.0037 | 44.2815 |
| 0.6067 | 2.0 | 430 | 1.1008 | 35.7038 |
| 0.3327 | 3.0 | 645 | 1.1870 | 37.0235 |
| 0.1727 | 4.0 | 860 | 1.2912 | 37.5367 |
| 0.1213 | 5.0 | 1075 | 1.4015 | 36.7302 |
| 0.1029 | 6.0 | 1290 | 1.4085 | 42.7419 |
| 0.054 | 7.0 | 1505 | 1.5070 | 37.2434 |
| 0.0438 | 8.0 | 1720 | 1.5635 | 37.2434 |
| 0.0465 | 9.0 | 1935 | 1.5192 | 51.5396 |
| 0.0329 | 10.0 | 2150 | 1.5806 | 39.0029 |
| 0.0211 | 11.0 | 2365 | 1.5379 | 34.8974 |
| 0.0165 | 12.0 | 2580 | 1.5379 | 40.1026 |
| 0.0157 | 13.0 | 2795 | 1.5596 | 37.1701 |
| 0.0115 | 14.0 | 3010 | 1.5608 | 36.5836 |
| 0.0048 | 15.0 | 3225 | 1.5498 | 35.9238 |
| 0.0045 | 16.0 | 3440 | 1.5764 | 36.5836 |
| 0.0019 | 17.0 | 3655 | 1.5668 | 35.7771 |
| 0.0004 | 18.0 | 3870 | 1.5774 | 35.8504 |
| 0.0004 | 19.0 | 4085 | 1.5845 | 35.8504 |
| 0.0003 | 20.0 | 4300 | 1.5876 | 35.7771 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1