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MarcoLYH/distilbert-base-uncased-finetuned-v3
This model is a fine-tuned version of distilbert-base-uncased-distilled-squad on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.9895
- Train End Logits Accuracy: 0.7708
- Train Start Logits Accuracy: 0.7292
- Validation Loss: 0.7644
- Validation End Logits Accuracy: 0.8000
- Validation Start Logits Accuracy: 0.8000
- Epoch: 9
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': 'WarmUp', 'config': {'initial_learning_rate': 1e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 27, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 3, 'power': 1.0, '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 |
|---|---|---|---|---|---|---|
| 2.1849 | 0.4583 | 0.5625 | 1.4084 | 0.6000 | 0.7000 | 0 |
| 1.7525 | 0.4583 | 0.625 | 1.1174 | 0.6000 | 0.7000 | 1 |
| 1.4231 | 0.5625 | 0.6458 | 0.9771 | 0.7000 | 0.75 | 2 |
| 1.2974 | 0.6042 | 0.6667 | 0.8995 | 0.7000 | 0.8000 | 3 |
| 1.0907 | 0.6875 | 0.6875 | 0.8517 | 0.7000 | 0.8000 | 4 |
| 0.9871 | 0.7292 | 0.7292 | 0.8189 | 0.7000 | 0.8000 | 5 |
| 1.0101 | 0.7292 | 0.75 | 0.7987 | 0.8000 | 0.8000 | 6 |
| 0.9208 | 0.7083 | 0.7708 | 0.7801 | 0.8000 | 0.8000 | 7 |
| 0.9486 | 0.7083 | 0.7292 | 0.7692 | 0.8000 | 0.8000 | 8 |
| 0.9895 | 0.7708 | 0.7292 | 0.7644 | 0.8000 | 0.8000 | 9 |
Framework versions
- Transformers 4.30.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3
