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whisper_wermet_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: 0.5820
- Train Accuracy: 0.0305
- Train Wermet: 1.5323
- Validation Loss: 0.6980
- Validation Accuracy: 0.0305
- Validation Wermet: 1.1238
- 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 |
|---|---|---|---|---|---|---|
| 5.0795 | 0.0116 | 43.8776 | 4.4395 | 0.0122 | 35.4119 | 0 |
| 4.3059 | 0.0131 | 29.7976 | 4.0311 | 0.0143 | 26.0070 | 1 |
| 3.8871 | 0.0148 | 19.3999 | 3.6500 | 0.0158 | 19.2186 | 2 |
| 3.0943 | 0.0184 | 18.3704 | 2.3327 | 0.0226 | 22.5034 | 3 |
| 1.8954 | 0.0240 | 16.2471 | 1.4889 | 0.0266 | 14.2782 | 4 |
| 1.2781 | 0.0269 | 8.4169 | 1.1273 | 0.0283 | 7.4581 | 5 |
| 0.9797 | 0.0283 | 4.8739 | 0.9481 | 0.0292 | 3.9451 | 6 |
| 0.8006 | 0.0293 | 2.7433 | 0.8371 | 0.0297 | 2.3065 | 7 |
| 0.6764 | 0.0299 | 2.1646 | 0.7554 | 0.0301 | 1.3005 | 8 |
| 0.5820 | 0.0305 | 1.5323 | 0.6980 | 0.0305 | 1.1238 | 9 |
Framework versions
- Transformers 4.25.0.dev0
- TensorFlow 2.9.2
- Datasets 2.6.1
- Tokenizers 0.13.2
