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roberta-base-fake-news-detection
This model is a fine-tuned version of roberta-base on the fake-news-detection-dataset-english dataset. It achieves the following results on the evaluation set:
- Loss: 0.0061
- Accuracy: 0.9992
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0073 | 1.0 | 4490 | 0.0087 | 0.9989 |
| 0.0076 | 2.0 | 8980 | 0.0062 | 0.9992 |
| 0.0094 | 3.0 | 13470 | 0.0061 | 0.9992 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
