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