<!-- 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. -->
ademola277/bert-base-uncased-finetuned-squad
This model is a fine-tuned version of bert-base-uncased on FEVER dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0000
- Train End Logits Accuracy: 1.0
- Train Start Logits Accuracy: 1.0
- Validation Loss: 0.0011
- Validation End Logits Accuracy: 0.9995
- Validation Start Logits Accuracy: 1.0
- 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', '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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 13587, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: mixed_float16
Training results
| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 0.0302 | 0.9944 | 0.9963 | 0.0024 | 0.9988 | 1.0 | 0 |
| 0.0002 | 0.9999 | 1.0000 | 0.0009 | 0.9998 | 1.0 | 1 |
| 0.0000 | 1.0 | 1.0 | 0.0011 | 0.9995 | 1.0 | 2 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.13.0
- Datasets 2.12.0
- Tokenizers 0.13.2
