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transformers-question-answer
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 1.4951
- Validation Loss: 1.1651
- Epoch: 0
Model description
This is a sample transformer trained for question-answer use case. I have used a pre-trained BERT model and then finetuned it using the hugging-face transformer library.
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': 5e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: mixed_float16
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 1.4951 | 1.1651 | 0 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.11.0
- Datasets 2.14.2
- Tokenizers 0.13.3
