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whisper_input_decoder_shift_r_labels_with_force__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: 3.3218
- Train Accuracy: 0.0148
- Train Wermet: 0.6946
- Validation Loss: 3.1357
- Validation Accuracy: 0.0122
- Validation Wermet: 0.7760
- 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 |
|---|---|---|---|---|---|---|
| 5.6249 | 0.0091 | 1.7162 | 4.2965 | 0.0094 | 0.9447 | 0 |
| 4.9223 | 0.0099 | 0.9041 | 4.1562 | 0.0097 | 0.9327 | 1 |
| 4.6814 | 0.0107 | 0.8376 | 3.9245 | 0.0103 | 0.8927 | 2 |
| 4.4407 | 0.0114 | 0.8311 | 3.7252 | 0.0107 | 0.8775 | 3 |
| 4.2445 | 0.0119 | 0.8228 | 3.6283 | 0.0108 | 0.8695 | 4 |
| 4.0889 | 0.0123 | 0.8067 | 3.5310 | 0.0110 | 0.8916 | 5 |
| 3.9575 | 0.0127 | 0.7908 | 3.4478 | 0.0113 | 0.8407 | 6 |
| 3.8547 | 0.0130 | 0.7781 | 3.4227 | 0.0113 | 0.8670 | 7 |
| 3.7599 | 0.0133 | 0.7654 | 3.3519 | 0.0115 | 0.8375 | 8 |
| 3.6763 | 0.0136 | 0.7543 | 3.3183 | 0.0116 | 0.8678 | 9 |
| 3.6006 | 0.0138 | 0.7421 | 3.2581 | 0.0117 | 0.8120 | 10 |
| 3.5300 | 0.0140 | 0.7296 | 3.2415 | 0.0118 | 0.8257 | 11 |
| 3.4554 | 0.0143 | 0.7179 | 3.2163 | 0.0119 | 0.8078 | 12 |
| 3.3930 | 0.0145 | 0.7057 | 3.1612 | 0.0121 | 0.7758 | 13 |
| 3.3218 | 0.0148 | 0.6946 | 3.1357 | 0.0122 | 0.7760 | 14 |
Framework versions
- Transformers 4.34.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3
