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whisper_wermet_nosup_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: 0.4694
- Train Accuracy: 0.0303
- Train Wermet: 4.3895
- Validation Loss: 0.6038
- Validation Accuracy: 0.0304
- Validation Wermet: 2.8294
- 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': 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 |
|---|---|---|---|---|---|---|
| 5.0729 | 0.0113 | 42.1824 | 4.4421 | 0.0120 | 27.3059 | 0 |
| 4.3249 | 0.0126 | 23.9224 | 4.0443 | 0.0141 | 18.2054 | 1 |
| 3.8845 | 0.0144 | 12.7780 | 3.4577 | 0.0169 | 10.3356 | 2 |
| 2.7411 | 0.0198 | 15.0018 | 1.8774 | 0.0244 | 14.5666 | 3 |
| 1.5621 | 0.0250 | 9.7248 | 1.2443 | 0.0273 | 5.4731 | 4 |
| 1.0745 | 0.0272 | 7.1512 | 0.9802 | 0.0285 | 4.4745 | 5 |
| 0.8261 | 0.0284 | 6.2358 | 0.8209 | 0.0293 | 5.6600 | 6 |
| 0.6673 | 0.0292 | 5.8338 | 0.7182 | 0.0298 | 4.0874 | 7 |
| 0.5548 | 0.0298 | 5.0555 | 0.6489 | 0.0301 | 4.4537 | 8 |
| 0.4694 | 0.0303 | 4.3895 | 0.6038 | 0.0304 | 2.8294 | 9 |
Framework versions
- Transformers 4.27.0.dev0
- TensorFlow 2.11.0
- Datasets 2.10.0
- Tokenizers 0.13.2
