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whisper_4_with_init_sun_syl_wd_0_lr_en4_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: 1.0272
- Train Accuracy: 0.0266
- Train Wermet: 0.2339
- Train Wermet Syl: 0.2620
- Validation Loss: 1.0518
- Validation Accuracy: 0.0206
- Validation Wermet: 0.3258
- Validation Wermet Syl: 0.2928
- 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-04, '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 |
---|---|---|---|---|---|---|---|---|
4.9733 | 0.0111 | 1.5643 | 1.4238 | 3.9610 | 0.0114 | 0.9612 | 0.9404 | 0 |
4.6745 | 0.0116 | 0.8628 | 0.8245 | 3.8859 | 0.0115 | 0.9258 | 0.8928 | 1 |
4.6271 | 0.0117 | 0.8456 | 0.8063 | 3.8727 | 0.0114 | 0.9561 | 0.9364 | 2 |
4.5738 | 0.0119 | 0.8242 | 0.8004 | 3.7410 | 0.0117 | 0.8760 | 0.8375 | 3 |
4.1772 | 0.0130 | 0.7540 | 0.7249 | 2.8900 | 0.0136 | 0.7575 | 0.7119 | 4 |
3.1940 | 0.0159 | 0.6535 | 0.6496 | 2.2086 | 0.0152 | 0.6192 | 0.5859 | 5 |
2.3103 | 0.0193 | 0.5146 | 0.5379 | 1.4923 | 0.0182 | 0.4666 | 0.4350 | 6 |
1.6683 | 0.0226 | 0.3900 | 0.4225 | 1.2258 | 0.0195 | 0.3874 | 0.3520 | 7 |
1.2915 | 0.0248 | 0.2991 | 0.3266 | 1.1613 | 0.0198 | 0.3557 | 0.3195 | 8 |
1.0272 | 0.0266 | 0.2339 | 0.2620 | 1.0518 | 0.0206 | 0.3258 | 0.2928 | 9 |
Framework versions
- Transformers 4.34.0.dev0
- TensorFlow 2.13.0
- Tokenizers 0.13.3