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whisper_4_with_init_sun_syl_wd_0_lr_en3_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: 4.1520
- Train Accuracy: 0.0126
- Train Wermet: 1.7418
- Train Wermet Syl: 2.3436
- Validation Loss: 3.2869
- Validation Accuracy: 0.0124
- Validation Wermet: 1.3462
- Validation Wermet Syl: 1.8561
- 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': 0.001, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Train Wermet | Train Wermet Syl | Validation Loss | Validation Accuracy | Validation Wermet | Validation Wermet Syl | Epoch |
|---|---|---|---|---|---|---|---|---|
| 5.0580 | 0.0110 | 1.8635 | 1.7118 | 4.0077 | 0.0112 | 1.0399 | 1.0195 | 0 |
| 4.7330 | 0.0115 | 0.9446 | 0.9262 | 3.9889 | 0.0113 | 0.9757 | 0.9619 | 1 |
| 4.6832 | 0.0116 | 0.8889 | 0.8637 | 3.9832 | 0.0114 | 0.9574 | 0.9276 | 2 |
| 4.6668 | 0.0116 | 0.9362 | 0.9592 | 3.9389 | 0.0113 | 0.9939 | 1.0310 | 3 |
| 4.6252 | 0.0117 | 1.0167 | 1.1679 | 3.9158 | 0.0114 | 0.9633 | 0.9764 | 4 |
| 4.6026 | 0.0117 | 1.0596 | 1.2533 | 3.8896 | 0.0114 | 0.9953 | 1.0541 | 5 |
| 4.5658 | 0.0118 | 1.1222 | 1.3998 | 3.8228 | 0.0116 | 0.9368 | 0.9177 | 6 |
| 4.4715 | 0.0120 | 1.0840 | 1.3327 | 3.7310 | 0.0117 | 0.9284 | 0.9338 | 7 |
| 4.3515 | 0.0122 | 1.5346 | 2.0632 | 3.6182 | 0.0119 | 0.9122 | 0.9112 | 8 |
| 4.1520 | 0.0126 | 1.7418 | 2.3436 | 3.2869 | 0.0124 | 1.3462 | 1.8561 | 9 |
Framework versions
- Transformers 4.34.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3
