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README.md
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---
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base_model: neuralsentry/starencoder-git-commits-mlm
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: starencoder-vulnfix-classification
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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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# starencoder-vulnfix-classification
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This model is a fine-tuned version of [neuralsentry/starencoder-git-commits-mlm](https://huggingface.co/neuralsentry/starencoder-git-commits-mlm) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1191
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- Accuracy: 0.9703
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- Precision: 0.9769
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- Recall: 0.96
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- F1: 0.9684
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- Roc Auc: 0.9698
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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: 0.0001
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 420
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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: 3.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
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| 0.3716 | 0.33 | 66 | 0.2018 | 0.9296 | 0.9368 | 0.9133 | 0.9249 | 0.9288 |
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| 0.1745 | 0.67 | 132 | 0.1468 | 0.9533 | 0.9711 | 0.9293 | 0.9498 | 0.9522 |
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| 0.1346 | 1.0 | 198 | 0.1091 | 0.9657 | 0.9761 | 0.951 | 0.9634 | 0.9650 |
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| 0.0917 | 1.33 | 264 | 0.1294 | 0.9647 | 0.9790 | 0.946 | 0.9622 | 0.9638 |
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| 0.0877 | 1.67 | 330 | 0.1090 | 0.9668 | 0.9619 | 0.9683 | 0.9651 | 0.9669 |
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| 0.0731 | 2.0 | 396 | 0.1042 | 0.9688 | 0.9746 | 0.9593 | 0.9669 | 0.9684 |
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| 0.0342 | 2.33 | 462 | 0.1291 | 0.9692 | 0.9686 | 0.9663 | 0.9675 | 0.9690 |
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| 0.0375 | 2.67 | 528 | 0.1202 | 0.9706 | 0.9753 | 0.9623 | 0.9688 | 0.9702 |
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| 0.0342 | 3.0 | 594 | 0.1191 | 0.9703 | 0.9769 | 0.96 | 0.9684 | 0.9698 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.0
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- Tokenizers 0.13.3
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