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whisper_train_on_validated_cv_model__0015
This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0815
- Train Accuracy: 0.0804
- Train Wermet: 3.8567
- Validation Loss: 0.3806
- Validation Accuracy: 0.0717
- Validation Wermet: 6.1506
- Epoch: 14
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Train Wermet | Validation Loss | Validation Accuracy | Validation Wermet | Epoch |
|---|---|---|---|---|---|---|
| 2.2992 | 0.0331 | 6.3187 | 1.9677 | 0.0372 | 7.2782 | 0 |
| 1.7447 | 0.0431 | 5.6345 | 1.7865 | 0.0408 | 6.3969 | 1 |
| 1.5036 | 0.0480 | 5.6512 | 1.4821 | 0.0468 | 5.1810 | 2 |
| 1.0955 | 0.0567 | 4.4606 | 1.0492 | 0.0557 | 3.7886 | 3 |
| 0.7076 | 0.0654 | 4.9157 | 0.7312 | 0.0627 | 4.2416 | 4 |
| 0.4703 | 0.0710 | 4.9749 | 0.5668 | 0.0664 | 4.8883 | 5 |
| 0.3552 | 0.0737 | 5.1823 | 0.4725 | 0.0685 | 4.8141 | 6 |
| 0.2865 | 0.0754 | 4.1024 | 0.4358 | 0.0694 | 3.8550 | 7 |
| 0.2380 | 0.0765 | 3.3689 | 0.3947 | 0.0704 | 2.2953 | 8 |
| 0.1998 | 0.0775 | 2.6219 | 0.3848 | 0.0707 | 3.0529 | 9 |
| 0.1687 | 0.0782 | 2.2111 | 0.3689 | 0.0711 | 1.8146 | 10 |
| 0.1417 | 0.0789 | 2.5284 | 0.3709 | 0.0713 | 1.9439 | 11 |
| 0.1190 | 0.0795 | 2.8048 | 0.3631 | 0.0716 | 3.0845 | 12 |
| 0.0983 | 0.0800 | 3.2668 | 0.3657 | 0.0717 | 3.6423 | 13 |
| 0.0815 | 0.0804 | 3.8567 | 0.3806 | 0.0717 | 6.1506 | 14 |
Framework versions
- Transformers 4.32.0.dev0
- TensorFlow 2.12.0
- Tokenizers 0.13.3
