Whisper Small FR - Radiologie
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7673
- Wer: 32.0536
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: 8
- eval_batch_size: 6
- seed: 3407
- optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 6.25 | 100 | 0.7878 | 100.0 |
| No log | 12.5 | 200 | 0.7400 | 39.0006 |
| No log | 18.75 | 300 | 0.7597 | 33.4552 |
| No log | 25.0 | 400 | 0.7574 | 32.6630 |
| 0.0558 | 31.25 | 500 | 0.7604 | 32.6630 |
| 0.0558 | 37.5 | 600 | 0.7635 | 32.7239 |
| 0.0558 | 43.75 | 700 | 0.7639 | 32.5411 |
| 0.0558 | 50.0 | 800 | 0.7660 | 32.6021 |
| 0.0558 | 56.25 | 900 | 0.7668 | 32.7239 |
| 0.0003 | 62.5 | 1000 | 0.7673 | 32.0536 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2