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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
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Dataset used to train mohammadjavadpirhadi/roberta-base-fake-news-detection