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train_from_raw_cv12_true_suppress_syl__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: 2.7798
- Train Accuracy: 0.0186
- Train Wermet: 2.9387
- Validation Loss: 2.3953
- Validation Accuracy: 0.0161
- Validation Wermet: 1.5900
- 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 |
|---|---|---|---|---|---|---|
| 5.0429 | 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 |
Framework versions
- Transformers 4.33.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3
