Ddaow/distilbert-base-uncased-finetuned-squad
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: 0.9692
- Train End Logits Accuracy: 0.7314
- Train Start Logits Accuracy: 0.6923
- Validation Loss: 1.1071
- Validation End Logits Accuracy: 0.7008
- Validation Start Logits Accuracy: 0.6691
- Epoch: 1
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': 11064, '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 |
|---|---|---|---|---|---|---|
| 1.5125 | 0.6064 | 0.5677 | 1.1969 | 0.6799 | 0.6471 | 0 |
| 0.9692 | 0.7314 | 0.6923 | 1.1071 | 0.7008 | 0.6691 | 1 |
Framework versions
- Transformers 4.23.1
- TensorFlow 2.9.2
- Datasets 2.5.2
- Tokenizers 0.13.1