vrx2/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: 0.9741
- Train End Logits Accuracy: 0.7291
- Train Start Logits Accuracy: 0.6924
- Validation Loss: 1.1179
- Validation End Logits Accuracy: 0.6960
- Validation Start Logits Accuracy: 0.6616
- Epoch: 1
Model description
just a bench test of my laptop's capabilities
Intended uses & limitations
testing purposes
Training and evaluation data
trained on squad v2
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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 11064, '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: float32
Training results
| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 1.5188 | 0.6049 | 0.5697 | 1.1433 | 0.6878 | 0.6498 | 0 |
| 0.9741 | 0.7291 | 0.6924 | 1.1179 | 0.6960 | 0.6616 | 1 |
Framework versions
- Transformers 4.34.0
- TensorFlow 2.14.0
- Datasets 2.14.5
- Tokenizers 0.14.1
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