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--- |
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license: bigscience-openrail-m |
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base_model: ehsanaghaei/SecureBERT |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: Cyber-ThreaD/SecureBERT-CyNER |
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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/SecureBERT-CyNER |
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This model is a fine-tuned version of [ehsanaghaei/SecureBERT](https://huggingface.co/ehsanaghaei/SecureBERT) on the [CyNER](https://github.com/aiforsec/CyNER) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0685 |
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- Precision: 0.7334 |
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- Recall: 0.8046 |
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- F1: 0.7674 |
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- Accuracy: 0.9836 |
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It achieves the following results on the prediction set: |
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- Loss: 0.0993 |
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- Precision: 0.7181 |
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- Recall: 0.7564 |
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- F1: 0.7367 |
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- Accuracy: 0.9761 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.1929 | 1.42 | 500 | 0.0685 | 0.7334 | 0.8046 | 0.7674 | 0.9836 | |
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| 0.048 | 2.84 | 1000 | 0.0745 | 0.8054 | 0.7931 | 0.7992 | 0.9837 | |
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| 0.0299 | 4.26 | 1500 | 0.0720 | 0.7936 | 0.8493 | 0.8205 | 0.9857 | |
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| 0.0199 | 5.68 | 2000 | 0.0846 | 0.8049 | 0.8327 | 0.8186 | 0.9848 | |
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| 0.014 | 7.1 | 2500 | 0.0878 | 0.7909 | 0.8455 | 0.8173 | 0.9847 | |
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| 0.0098 | 8.52 | 3000 | 0.0907 | 0.7830 | 0.8250 | 0.8035 | 0.9845 | |
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| 0.0073 | 9.94 | 3500 | 0.0917 | 0.7946 | 0.8301 | 0.8120 | 0.9852 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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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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