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whisper_syl_cv12_pad_lob100__0010
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: 2.8713
- Train Accuracy: 0.0181
- Train Wermet: 0.6484
- Validation Loss: 2.5226
- Validation Accuracy: 0.0157
- Validation Wermet: 0.7017
- Epoch: 9
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 |
|---|---|---|---|---|---|---|
| 5.0233 | 0.0115 | 1.6383 | 3.8616 | 0.0117 | 0.9516 | 0 |
| 4.4412 | 0.0127 | 0.8560 | 3.5410 | 0.0125 | 0.8971 | 1 |
| 4.0719 | 0.0138 | 0.8366 | 3.2944 | 0.0132 | 0.8706 | 2 |
| 3.8091 | 0.0146 | 0.8133 | 3.1691 | 0.0134 | 0.8487 | 3 |
| 3.6239 | 0.0152 | 0.7866 | 3.0647 | 0.0136 | 0.8282 | 4 |
| 3.4749 | 0.0156 | 0.7589 | 2.9835 | 0.0139 | 0.8049 | 5 |
| 3.3444 | 0.0161 | 0.7359 | 2.9351 | 0.0140 | 0.7979 | 6 |
| 3.2215 | 0.0165 | 0.7138 | 2.8468 | 0.0145 | 0.7589 | 7 |
| 3.0754 | 0.0172 | 0.6873 | 2.7530 | 0.0148 | 0.7413 | 8 |
| 2.8713 | 0.0181 | 0.6484 | 2.5226 | 0.0157 | 0.7017 | 9 |
Framework versions
- Transformers 4.33.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3
