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train_from_raw_cv12_true_suppress_syl__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: 0.6496
- Train Accuracy: 0.0312
- Train Wermet: 5.7322
- Validation Loss: 0.8221
- Validation Accuracy: 0.0223
- Validation Wermet: 7.7657
- 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 |
---|---|---|---|---|---|---|
5.0429 | 0.0114 | 9.0587 | 3.8750 | 0.0118 | 5.0498 | 0 |
4.4427 | 0.0127 | 4.5412 | 3.5504 | 0.0125 | 1.0435 | 1 |
4.0670 | 0.0138 | 1.4433 | 3.2998 | 0.0131 | 0.8708 | 2 |
3.8001 | 0.0146 | 1.2315 | 3.1614 | 0.0134 | 0.9290 | 3 |
3.6184 | 0.0152 | 1.1992 | 3.0624 | 0.0137 | 0.8952 | 4 |
3.4663 | 0.0157 | 1.3336 | 3.0000 | 0.0139 | 1.1129 | 5 |
3.3304 | 0.0161 | 1.6150 | 2.9249 | 0.0142 | 0.9842 | 6 |
3.1968 | 0.0167 | 1.6722 | 2.8195 | 0.0145 | 1.0184 | 7 |
3.0193 | 0.0175 | 1.8390 | 2.6745 | 0.0151 | 1.0552 | 8 |
2.7798 | 0.0186 | 2.9387 | 2.3953 | 0.0161 | 1.5900 | 9 |
2.3558 | 0.0208 | 3.8370 | 1.9310 | 0.0178 | 2.0889 | 10 |
1.6793 | 0.0246 | 3.1644 | 1.3969 | 0.0199 | 1.8707 | 11 |
1.1330 | 0.0280 | 3.7080 | 1.0962 | 0.0212 | 3.6178 | 12 |
0.8349 | 0.0299 | 4.2648 | 0.9345 | 0.0218 | 3.0073 | 13 |
0.6496 | 0.0312 | 5.7322 | 0.8221 | 0.0223 | 7.7657 | 14 |
Framework versions
- Transformers 4.33.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3