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whisper_attention_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: 4.1328
- Train Accuracy: 0.0132
- Train Wermet: 1.1476
- Validation Loss: 3.2918
- Validation Accuracy: 0.0129
- Validation Wermet: 1.3463
- 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': 1e-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 |
|---|---|---|---|---|---|---|
| 5.4192 | 0.0107 | 1.9359 | 3.9929 | 0.0112 | 3.4029 | 0 |
| 4.7175 | 0.0116 | 1.3557 | 3.9525 | 0.0113 | 3.2613 | 1 |
| 4.6756 | 0.0117 | 1.4198 | 3.9189 | 0.0113 | 2.6795 | 2 |
| 4.6543 | 0.0117 | 1.3165 | 3.9021 | 0.0114 | 2.2678 | 3 |
| 4.6317 | 0.0118 | 1.2794 | 3.8796 | 0.0114 | 1.8964 | 4 |
| 4.6128 | 0.0118 | 1.2033 | 3.8579 | 0.0115 | 1.6353 | 5 |
| 4.5945 | 0.0118 | 1.1814 | 3.8787 | 0.0114 | 3.6041 | 6 |
| 4.5719 | 0.0119 | 1.1171 | 3.8418 | 0.0116 | 1.1922 | 7 |
| 4.5503 | 0.0120 | 1.1435 | 3.8061 | 0.0117 | 1.8502 | 8 |
| 4.5235 | 0.0121 | 1.0483 | 3.7736 | 0.0118 | 1.4279 | 9 |
| 4.4837 | 0.0122 | 1.0371 | 3.7294 | 0.0119 | 1.6705 | 10 |
| 4.4401 | 0.0123 | 1.0621 | 3.6991 | 0.0118 | 3.1038 | 11 |
| 4.3684 | 0.0125 | 1.0436 | 3.6220 | 0.0121 | 3.1267 | 12 |
| 4.2692 | 0.0128 | 1.1086 | 3.4681 | 0.0124 | 1.1431 | 13 |
| 4.1328 | 0.0132 | 1.1476 | 3.2918 | 0.0129 | 1.3463 | 14 |
Framework versions
- Transformers 4.33.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3
