openai/whisper-small
This model is a fine-tuned version of openai/whisper-small on the pphuc25/FrenchMed dataset. It achieves the following results on the evaluation set:
- Loss: 1.6120
- Wer: 44.5015
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 |
|---|---|---|---|---|
| 1.2076 | 1.0 | 215 | 1.2220 | 65.9091 |
| 0.7142 | 2.0 | 430 | 1.3108 | 57.4047 |
| 0.3943 | 3.0 | 645 | 1.3278 | 56.9648 |
| 0.227 | 4.0 | 860 | 1.4398 | 46.9208 |
| 0.1701 | 5.0 | 1075 | 1.4437 | 46.3343 |
| 0.1137 | 6.0 | 1290 | 1.5016 | 48.8270 |
| 0.0942 | 7.0 | 1505 | 1.6104 | 47.0674 |
| 0.0627 | 8.0 | 1720 | 1.5725 | 48.1672 |
| 0.0484 | 9.0 | 1935 | 1.6233 | 45.5279 |
| 0.0454 | 10.0 | 2150 | 1.6325 | 49.7801 |
| 0.0276 | 11.0 | 2365 | 1.6426 | 45.7478 |
| 0.0246 | 12.0 | 2580 | 1.6756 | 44.7214 |
| 0.0189 | 13.0 | 2795 | 1.6642 | 46.1144 |
| 0.0135 | 14.0 | 3010 | 1.6463 | 43.1818 |
| 0.0036 | 15.0 | 3225 | 1.6292 | 44.3548 |
| 0.0066 | 16.0 | 3440 | 1.6133 | 45.0147 |
| 0.0022 | 17.0 | 3655 | 1.6154 | 45.8211 |
| 0.0015 | 18.0 | 3870 | 1.6086 | 45.5279 |
| 0.0002 | 19.0 | 4085 | 1.6105 | 45.2346 |
| 0.0005 | 20.0 | 4300 | 1.6120 | 44.5015 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1