Whisper Small Fr - Radiologie1.1
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: 0.8172
- Wer: 34.6740
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: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0594 | 31.25 | 500 | 0.7913 | 99.4516 |
| 0.0002 | 62.5 | 1000 | 0.7987 | 99.4516 |
| 0.0002 | 93.75 | 1500 | 0.8020 | 41.0116 |
| 0.0001 | 125.0 | 2000 | 0.8071 | 35.1005 |
| 0.0001 | 156.25 | 2500 | 0.8105 | 35.3443 |
| 0.0001 | 187.5 | 3000 | 0.8122 | 34.9787 |
| 0.0001 | 218.75 | 3500 | 0.8153 | 35.1615 |
| 0.0001 | 250.0 | 4000 | 0.8154 | 34.6130 |
| 0.0001 | 281.25 | 4500 | 0.8162 | 34.9787 |
| 0.0001 | 312.5 | 5000 | 0.8172 | 34.6740 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2