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whisper_syl_cv12_pad_lob100_low__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: 3.4649
- Train Accuracy: 0.0157
- Train Wermet: 0.7651
- Validation Loss: 3.0334
- Validation Accuracy: 0.0139
- Validation Wermet: 0.8417
- 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 |
|---|---|---|---|---|---|---|
| 5.2930 | 0.0113 | 2.0658 | 3.9415 | 0.0117 | 0.9401 | 0 |
| 4.6215 | 0.0121 | 0.8917 | 3.7803 | 0.0120 | 0.9294 | 1 |
| 4.4086 | 0.0128 | 0.8403 | 3.6070 | 0.0124 | 0.9223 | 2 |
| 4.1842 | 0.0135 | 0.8337 | 3.4291 | 0.0128 | 0.8867 | 3 |
| 3.9981 | 0.0141 | 0.8182 | 3.3251 | 0.0131 | 0.8750 | 4 |
| 3.8531 | 0.0145 | 0.8058 | 3.2385 | 0.0133 | 0.8699 | 5 |
| 3.7345 | 0.0149 | 0.7925 | 3.1751 | 0.0134 | 0.8665 | 6 |
| 3.6307 | 0.0152 | 0.7851 | 3.1031 | 0.0136 | 0.8507 | 7 |
| 3.5437 | 0.0155 | 0.7717 | 3.0752 | 0.0138 | 0.8286 | 8 |
| 3.4649 | 0.0157 | 0.7651 | 3.0334 | 0.0139 | 0.8417 | 9 |
Framework versions
- Transformers 4.33.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3
