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jborras18/qa_bert_catalan
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: 1.4159
- Train End Logits Accuracy: 0.6381
- Train Start Logits Accuracy: 0.5826
- Validation Loss: 1.5331
- Validation End Logits Accuracy: 0.6169
- Validation Start Logits Accuracy: 0.5583
- 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2140, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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 |
|---|---|---|---|---|---|---|
| 2.3671 | 0.4386 | 0.3832 | 1.6448 | 0.5845 | 0.5326 | 0 |
| 1.5667 | 0.6029 | 0.5472 | 1.5331 | 0.6169 | 0.5583 | 1 |
| 1.4159 | 0.6381 | 0.5826 | 1.5331 | 0.6169 | 0.5583 | 2 |
Framework versions
- Transformers 4.26.1
- TensorFlow 2.11.0
- Datasets 2.10.0
- Tokenizers 0.13.2
