---
base_model: neuralsentry/starencoder-git-commits-mlm
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: starencoder-vulnfix-classification
  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. -->

# starencoder-vulnfix-classification

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.
It achieves the following results on the evaluation set:
- Loss: 0.1191
- Accuracy: 0.9703
- Precision: 0.9769
- Recall: 0.96
- F1: 0.9684
- Roc Auc: 0.9698

## 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 420
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 0.3716        | 0.33  | 66   | 0.2018          | 0.9296   | 0.9368    | 0.9133 | 0.9249 | 0.9288  |
| 0.1745        | 0.67  | 132  | 0.1468          | 0.9533   | 0.9711    | 0.9293 | 0.9498 | 0.9522  |
| 0.1346        | 1.0   | 198  | 0.1091          | 0.9657   | 0.9761    | 0.951  | 0.9634 | 0.9650  |
| 0.0917        | 1.33  | 264  | 0.1294          | 0.9647   | 0.9790    | 0.946  | 0.9622 | 0.9638  |
| 0.0877        | 1.67  | 330  | 0.1090          | 0.9668   | 0.9619    | 0.9683 | 0.9651 | 0.9669  |
| 0.0731        | 2.0   | 396  | 0.1042          | 0.9688   | 0.9746    | 0.9593 | 0.9669 | 0.9684  |
| 0.0342        | 2.33  | 462  | 0.1291          | 0.9692   | 0.9686    | 0.9663 | 0.9675 | 0.9690  |
| 0.0375        | 2.67  | 528  | 0.1202          | 0.9706   | 0.9753    | 0.9623 | 0.9688 | 0.9702  |
| 0.0342        | 3.0   | 594  | 0.1191          | 0.9703   | 0.9769    | 0.96   | 0.9684 | 0.9698  |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3