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whisper_input_decoder_no_lob__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: 4.5219
- Train Accuracy: 0.0121
- Train Wermet: 0.7591
- Validation Loss: 3.7734
- Validation Accuracy: 0.0118
- Validation Wermet: 0.8383
- 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 |
|---|---|---|---|---|---|---|
| 5.4122 | 0.0107 | 0.9328 | 3.9759 | 0.0114 | 0.9606 | 0 |
| 4.7176 | 0.0116 | 0.8683 | 3.9404 | 0.0114 | 0.9334 | 1 |
| 4.6750 | 0.0117 | 0.8478 | 3.9211 | 0.0115 | 0.9237 | 2 |
| 4.6511 | 0.0117 | 0.8413 | 3.8864 | 0.0115 | 0.9331 | 3 |
| 4.6294 | 0.0118 | 0.8270 | 3.8729 | 0.0115 | 0.9228 | 4 |
| 4.6134 | 0.0118 | 0.8199 | 3.8690 | 0.0114 | 0.9451 | 5 |
| 4.5980 | 0.0118 | 0.8102 | 3.8491 | 0.0115 | 0.9152 | 6 |
| 4.5759 | 0.0119 | 0.7890 | 3.8366 | 0.0116 | 0.8691 | 7 |
| 4.5518 | 0.0120 | 0.7694 | 3.8081 | 0.0116 | 0.9013 | 8 |
| 4.5219 | 0.0121 | 0.7591 | 3.7734 | 0.0118 | 0.8383 | 9 |
Framework versions
- Transformers 4.33.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3
