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- f1
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- accuracy
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model-index:
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- name:
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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#
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This model is a fine-tuned version of [jackaduma/SecBERT](https://huggingface.co/jackaduma/SecBERT) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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- f1
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- accuracy
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model-index:
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- name: Cyber-ThreaD/SecBERT-AttackER
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Cyber-ThreaD/SecBERT-AttackER
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This model is a fine-tuned version of [jackaduma/SecBERT](https://huggingface.co/jackaduma/SecBERT) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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### Citing & Authors
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If you use the model kindly cite the following work
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```
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@inproceedings{deka2024attacker,
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title={AttackER: Towards Enhancing Cyber-Attack Attribution with a Named Entity Recognition Dataset},
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author={Deka, Pritam and Rajapaksha, Sampath and Rani, Ruby and Almutairi, Amirah and Karafili, Erisa},
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booktitle={International Conference on Web Information Systems Engineering},
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pages={255--270},
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year={2024},
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organization={Springer}
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}
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```
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