distilroberta-base-finetuned-fakeNews
This model is a fine-tuned version of distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0355
- Accuracy: 0.9910
Training and evaluation data
All of the process to train this model is available in this repository: https://github.com/G0nz4lo-4lvarez-H3rv4s/FakeNewsDetection
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0301 | 1.0 | 1523 | 0.0322 | 0.9868 |
| 0.0165 | 2.0 | 3046 | 0.0292 | 0.9892 |
| 0.0088 | 3.0 | 4569 | 0.0355 | 0.9910 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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