qa_model_upgraded

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mmiteva/qa_model_upgraded

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: 0.3087
• Train End Logits Accuracy: 0.8935
• Train Start Logits Accuracy: 0.8884
• Validation Loss: 1.1857
• Validation End Logits Accuracy: 0.7448
• Validation Start Logits Accuracy: 0.7335
• Epoch: 4

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': 5e-05, 'decay_steps': 68700, '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

Framework versions

• Transformers 4.25.1
• TensorFlow 2.10.1
• Datasets 2.7.1
• Tokenizers 0.12.1