Whisper Small FR - Radiologie
This model is a fine-tuned version of StephaneBah/whisper-small-rad-FR1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7650
- Wer: 33.3943
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 | 0.7386 | 29.1895 |
| No log | 12.5 | 200 | 0.7423 | 33.2115 |
| No log | 18.75 | 300 | 0.7461 | 33.5771 |
| No log | 25.0 | 400 | 0.7524 | 30.8349 |
| 0.0005 | 31.25 | 500 | 0.7564 | 33.6990 |
| 0.0005 | 37.5 | 600 | 0.7596 | 33.8818 |
| 0.0005 | 43.75 | 700 | 0.7628 | 33.6380 |
| 0.0005 | 50.0 | 800 | 0.7629 | 33.0286 |
| 0.0005 | 56.25 | 900 | 0.7645 | 33.4552 |
| 0.0002 | 62.5 | 1000 | 0.7650 | 33.3943 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2