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whisper_char_cv12_pad_lob100_low__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: 0.1182
- Train Accuracy: 0.1075
- Train Wermet: 3.1399
- Validation Loss: 0.3076
- Validation Accuracy: 0.0636
- Validation Wermet: 9.9836
- 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 |
|---|---|---|---|---|---|---|
| 0.3330 | 0.0999 | 1.7359 | 0.3779 | 0.0615 | 4.7471 | 0 |
| 0.3093 | 0.1007 | 2.0563 | 0.3652 | 0.0618 | 7.2181 | 1 |
| 0.2869 | 0.1015 | 2.0654 | 0.3539 | 0.0620 | 8.6857 | 2 |
| 0.2672 | 0.1022 | 2.1925 | 0.3443 | 0.0623 | 8.0906 | 3 |
| 0.2488 | 0.1028 | 2.3286 | 0.3305 | 0.0626 | 9.1756 | 4 |
| 0.2316 | 0.1034 | 2.4212 | 0.3300 | 0.0626 | 8.1427 | 5 |
| 0.2163 | 0.1039 | 2.5012 | 0.3183 | 0.0629 | 8.3043 | 6 |
| 0.2018 | 0.1045 | 2.7267 | 0.3109 | 0.0631 | 9.5329 | 7 |
| 0.1878 | 0.1050 | 2.7034 | 0.3053 | 0.0632 | 7.9014 | 8 |
| 0.1749 | 0.1054 | 2.8719 | 0.3063 | 0.0632 | 9.0257 | 9 |
| 0.1628 | 0.1058 | 2.8764 | 0.3033 | 0.0634 | 9.1336 | 10 |
| 0.1510 | 0.1063 | 2.8441 | 0.3046 | 0.0634 | 8.6064 | 11 |
| 0.1391 | 0.1067 | 2.9377 | 0.3030 | 0.0635 | 9.1326 | 12 |
| 0.1280 | 0.1071 | 2.9433 | 0.3025 | 0.0636 | 9.4533 | 13 |
| 0.1182 | 0.1075 | 3.1399 | 0.3076 | 0.0636 | 9.9836 | 14 |
Framework versions
- Transformers 4.33.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3
