<!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. -->
bert-finetuned-mrpc
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: 0.1719
- Train Accuracy: 0.9359
- Validation Loss: 0.4050
- Validation Accuracy: 0.8382
- 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': 5e-05, 'decay_steps': 1374, '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-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|---|---|---|---|---|
| 0.5877 | 0.6823 | 0.4665 | 0.8015 | 0 |
| 0.3843 | 0.8201 | 0.4026 | 0.8309 | 1 |
| 0.1719 | 0.9359 | 0.4050 | 0.8382 | 2 |
Framework versions
- Transformers 4.19.1
- TensorFlow 2.8.0
- Datasets 2.2.1
- Tokenizers 0.12.1
