Cyber-ThreaD/SecureBERT-DNRTI

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Cyber-ThreaD/SecureBERT-DNRTI

This model is a fine-tuned version of ehsanaghaei/SecureBERT on the DNRTI dataset. It achieves the following results on the evaluation set:

• —Loss: 0.2427
• —Precision: 0.7694
• —Recall: 0.7854
• —F1: 0.7773
• —Accuracy: 0.9382

It achieves the following results on the prediction set:

• —Precision: 0.8346
• —Recall: 0.8403
• —F1: 0.8374
• —Accuracy: 0.9554

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:

• —learning_rate: 2e-05
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 10.0

Training results

Framework versions

• —Transformers 4.36.0.dev0
• —Pytorch 2.1.0+cu118
• —Datasets 2.14.6
• —Tokenizers 0.14.1

Citing & Authors

If you use the model kindly cite the following work

@inproceedings{deka2024attacker,
  title={AttackER: Towards Enhancing Cyber-Attack Attribution with a Named Entity Recognition Dataset},
  author={Deka, Pritam and Rajapaksha, Sampath and Rani, Ruby and Almutairi, Amirah and Karafili, Erisa},
  booktitle={International Conference on Web Information Systems Engineering},
  pages={255--270},
  year={2024},
  organization={Springer}
}