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Viiksata/qa_model-davicni_800
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1075
- Train End Logits Accuracy: 0.9630
- Train Start Logits Accuracy: 0.9637
- Validation Loss: 0.5521
- Validation End Logits Accuracy: 0.8889
- Validation Start Logits Accuracy: 0.8925
- Epoch: 7
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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 26320, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 1.5290 | 0.6181 | 0.6265 | 0.7635 | 0.7831 | 0.7819 | 0 |
| 0.6245 | 0.8075 | 0.8159 | 0.5712 | 0.8379 | 0.8301 | 1 |
| 0.4064 | 0.8701 | 0.8721 | 0.5069 | 0.8656 | 0.8663 | 2 |
| 0.2854 | 0.9039 | 0.9096 | 0.4773 | 0.8813 | 0.8810 | 3 |
| 0.2145 | 0.9269 | 0.9287 | 0.4887 | 0.8732 | 0.8820 | 4 |
| 0.1669 | 0.9436 | 0.9462 | 0.4637 | 0.8938 | 0.8925 | 5 |
| 0.1300 | 0.9522 | 0.9563 | 0.5295 | 0.8938 | 0.8960 | 6 |
| 0.1075 | 0.9630 | 0.9637 | 0.5521 | 0.8889 | 0.8925 | 7 |
Framework versions
- Transformers 4.33.0
- TensorFlow 2.12.0
- Datasets 2.1.0
- Tokenizers 0.13.3
