openai/whisper-base
This model is a fine-tuned version of openai/whisper-base on the pphuc25/FrenchMed dataset. It achieves the following results on the evaluation set:
- Loss: 1.6240
- Wer: 47.8006
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 |
|---|---|---|---|---|
| 1.2466 | 1.0 | 215 | 1.2507 | 115.8358 |
| 0.7568 | 2.0 | 430 | 1.2524 | 86.4370 |
| 0.4229 | 3.0 | 645 | 1.3556 | 72.1408 |
| 0.2402 | 4.0 | 860 | 1.4000 | 52.4927 |
| 0.1544 | 5.0 | 1075 | 1.4770 | 47.1408 |
| 0.1127 | 6.0 | 1290 | 1.5115 | 56.7449 |
| 0.0674 | 7.0 | 1505 | 1.5317 | 56.8182 |
| 0.0526 | 8.0 | 1720 | 1.5979 | 51.1730 |
| 0.0442 | 9.0 | 1935 | 1.5844 | 50.5865 |
| 0.038 | 10.0 | 2150 | 1.5793 | 55.4252 |
| 0.0193 | 11.0 | 2365 | 1.6582 | 50.3666 |
| 0.0138 | 12.0 | 2580 | 1.6064 | 56.8182 |
| 0.0144 | 13.0 | 2795 | 1.5930 | 48.3138 |
| 0.0125 | 14.0 | 3010 | 1.6400 | 53.4457 |
| 0.0061 | 15.0 | 3225 | 1.6139 | 48.9003 |
| 0.0024 | 16.0 | 3440 | 1.6124 | 46.1877 |
| 0.0017 | 17.0 | 3655 | 1.6168 | 50.2933 |
| 0.0015 | 18.0 | 3870 | 1.6247 | 45.5279 |
| 0.0004 | 19.0 | 4085 | 1.6212 | 45.8211 |
| 0.0005 | 20.0 | 4300 | 1.6240 | 47.8006 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1