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whisper_4_with_init_sun_syl_wd_0_lr_7en5_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: 1.0044
- Train Accuracy: 0.0268
- Train Wermet: 0.2703
- Train Wermet Syl: 0.3518
- Validation Loss: 1.0470
- Validation Accuracy: 0.0205
- Validation Wermet: 0.3204
- Validation Wermet Syl: 0.2976
- 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': 7e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Train Wermet | Train Wermet Syl | Validation Loss | Validation Accuracy | Validation Wermet | Validation Wermet Syl | Epoch |
|---|---|---|---|---|---|---|---|---|
| 4.9248 | 0.0113 | 1.1777 | 1.1068 | 3.9252 | 0.0115 | 0.9215 | 0.8812 | 0 |
| 4.6658 | 0.0117 | 0.8497 | 0.8066 | 3.9186 | 0.0113 | 0.9766 | 0.9699 | 1 |
| 4.6144 | 0.0118 | 0.8224 | 0.7735 | 3.8791 | 0.0115 | 0.9336 | 0.9042 | 2 |
| 4.5388 | 0.0120 | 0.7917 | 0.7466 | 3.6581 | 0.0120 | 0.8508 | 0.8073 | 3 |
| 4.0826 | 0.0133 | 0.7361 | 0.6973 | 2.7406 | 0.0139 | 0.7479 | 0.7097 | 4 |
| 3.0292 | 0.0166 | 0.6273 | 0.6290 | 1.8185 | 0.0170 | 0.5529 | 0.5186 | 5 |
| 2.1435 | 0.0203 | 0.4839 | 0.5224 | 1.6075 | 0.0176 | 0.4395 | 0.4097 | 6 |
| 1.6289 | 0.0228 | 0.3883 | 0.4416 | 1.1774 | 0.0197 | 0.3770 | 0.3490 | 7 |
| 1.2619 | 0.0250 | 0.3256 | 0.3991 | 1.1074 | 0.0201 | 0.3404 | 0.3137 | 8 |
| 1.0044 | 0.0268 | 0.2703 | 0.3518 | 1.0470 | 0.0205 | 0.3204 | 0.2976 | 9 |
Framework versions
- Transformers 4.34.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3
