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FYP2022
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.6016
- Train Sparse Categorical Accuracy: 0.7503
- Train Sparse Top 3 Categorical Accuracy: 0.9901
- Epoch: 5
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', 'clipnorm': 1.0, 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Sparse Categorical Accuracy | Train Sparse Top 3 Categorical Accuracy | Epoch |
|---|---|---|---|
| 0.9433 | 0.5975 | 0.9523 | 0 |
| 0.8257 | 0.6498 | 0.9704 | 1 |
| 0.7625 | 0.6765 | 0.9778 | 2 |
| 0.7062 | 0.7014 | 0.9832 | 3 |
| 0.6526 | 0.7263 | 0.9872 | 4 |
| 0.6016 | 0.7503 | 0.9901 | 5 |
Framework versions
- Transformers 4.19.2
- TensorFlow 2.8.0
- Tokenizers 0.12.1
