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

# vulnfixClassification-StarEncoder-DCMB

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: 0.1797
- Accuracy: 0.9770
- Precision: 0.9841
- Recall: 0.9714
- F1: 0.9777
- Roc Auc: 0.9772

## 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: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 0.2106        | 1.0   | 219  | 0.1196          | 0.9640   | 0.9654    | 0.9654 | 0.9654 | 0.9639  |
| 0.086         | 2.0   | 438  | 0.0883          | 0.9736   | 0.9859    | 0.9629 | 0.9743 | 0.9740  |
| 0.0477        | 3.0   | 657  | 0.0944          | 0.9729   | 0.9776    | 0.9700 | 0.9738 | 0.9730  |
| 0.0269        | 4.0   | 876  | 0.1215          | 0.9723   | 0.9705    | 0.9764 | 0.9734 | 0.9721  |
| 0.0146        | 5.0   | 1095 | 0.1299          | 0.9743   | 0.9854    | 0.9648 | 0.9750 | 0.9747  |
| 0.0069        | 6.0   | 1314 | 0.1504          | 0.9750   | 0.9814    | 0.9703 | 0.9758 | 0.9752  |
| 0.0044        | 7.0   | 1533 | 0.1653          | 0.9743   | 0.9779    | 0.9725 | 0.9752 | 0.9744  |
| 0.0019        | 8.0   | 1752 | 0.1804          | 0.9756   | 0.9817    | 0.9711 | 0.9764 | 0.9758  |
| 0.0008        | 9.0   | 1971 | 0.1827          | 0.9767   | 0.9839    | 0.9711 | 0.9775 | 0.9769  |
| 0.0008        | 10.0  | 2190 | 0.1797          | 0.9770   | 0.9841    | 0.9714 | 0.9777 | 0.9772  |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3