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whisper_input_decoder_equal_labels_no_force__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: 0.0004
- Train Accuracy: 0.0362
- Train Wermet: 16.8461
- Validation Loss: 0.0004
- Validation Accuracy: 0.0266
- Validation Wermet: 34.1220
- 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 |
|---|---|---|---|---|---|---|
| 0.7688 | 0.0332 | 32.0424 | 0.0164 | 0.0265 | 57.8712 | 0 |
| 0.0114 | 0.0362 | 31.1067 | 0.0062 | 0.0266 | 54.8371 | 1 |
| 0.0048 | 0.0362 | 27.0610 | 0.0030 | 0.0266 | 50.1428 | 2 |
| 0.0027 | 0.0362 | 24.9672 | 0.0018 | 0.0266 | 48.0741 | 3 |
| 0.0018 | 0.0362 | 23.1500 | 0.0013 | 0.0266 | 44.9304 | 4 |
| 0.0013 | 0.0362 | 21.5445 | 0.0010 | 0.0266 | 42.3508 | 5 |
| 0.0009 | 0.0362 | 20.2775 | 0.0008 | 0.0266 | 40.4061 | 6 |
| 0.0007 | 0.0362 | 19.5082 | 0.0006 | 0.0266 | 38.2329 | 7 |
| 0.0005 | 0.0362 | 17.9967 | 0.0005 | 0.0266 | 35.9761 | 8 |
| 0.0004 | 0.0362 | 16.8461 | 0.0004 | 0.0266 | 34.1220 | 9 |
Framework versions
- Transformers 4.33.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3
