jb_whisper_parkinson_model
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: 0.3598
- Accuracy: 1.0
- F1 Macro: 1.0
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 0.5351 | 1.0 | 70 | 0.3526 | 1.0 | 1.0 |
| 0.5046 | 2.0 | 140 | 0.2548 | 1.0 | 1.0 |
| 0.4078 | 3.0 | 210 | 0.2285 | 1.0 | 1.0 |
| 0.4748 | 4.0 | 280 | 0.2205 | 1.0 | 1.0 |
| 0.5464 | 5.0 | 350 | 0.2163 | 1.0 | 1.0 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2