| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: ft-bert-cybersecurity-for-binary-search |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # ft-bert-cybersecurity-for-binary-search |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the https://www.kaggle.com/datasets/skywardai/network-vulnerability-fixed dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0009 |
|
|
| ## 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: |
| - learning_rate: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
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| ### Training results |
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| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 0.0142 | 1.0 | 50 | 0.0062 | |
| | 0.0019 | 2.0 | 100 | 0.0012 | |
| | 0.0015 | 3.0 | 150 | 0.0009 | |
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| ### Framework versions |
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| - Transformers 4.46.2 |
| - Pytorch 2.2.2 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
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