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mallikrao2/bert-base-uncased-finetuned
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.5897
- Train End Logits Accuracy: 0.8276
- Train Start Logits Accuracy: 0.7901
- Validation Loss: 1.0614
- Validation End Logits Accuracy: 0.7313
- Validation Start Logits Accuracy: 0.6992
- Epoch: 2
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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 16596, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, '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 |
|---|---|---|---|---|---|---|
| 1.2874 | 0.6616 | 0.6200 | 1.0094 | 0.7239 | 0.6855 | 0 |
| 0.7993 | 0.7755 | 0.7332 | 0.9985 | 0.7323 | 0.7022 | 1 |
| 0.5897 | 0.8276 | 0.7901 | 1.0614 | 0.7313 | 0.6992 | 2 |
Framework versions
- Transformers 4.29.2
- TensorFlow 2.8.0
- Datasets 2.12.0
- Tokenizers 0.13.3
