---
license: apache-2.0
base_model: neuralsentry/distilbert-git-commits-mlm
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: vulnfixClassification-DistilBERT-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-DistilBERT-DCMB

This model is a fine-tuned version of [neuralsentry/distilbert-git-commits-mlm](https://huggingface.co/neuralsentry/distilbert-git-commits-mlm) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1769
- Accuracy: 0.9713
- Precision: 0.9778
- Recall: 0.9667
- F1: 0.9722
- Roc Auc: 0.9715

## 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: 256
- eval_batch_size: 256
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 0.2594        | 1.0   | 110  | 0.1452          | 0.9520   | 0.9672    | 0.9395 | 0.9532 | 0.9525  |
| 0.0966        | 2.0   | 220  | 0.1103          | 0.9644   | 0.9714    | 0.9599 | 0.9656 | 0.9646  |
| 0.0499        | 3.0   | 330  | 0.1193          | 0.9640   | 0.9679    | 0.9626 | 0.9653 | 0.9641  |
| 0.0251        | 4.0   | 440  | 0.1289          | 0.9623   | 0.9577    | 0.9703 | 0.9640 | 0.9619  |
| 0.0132        | 5.0   | 550  | 0.1495          | 0.9660   | 0.9660    | 0.9687 | 0.9673 | 0.9659  |
| 0.0086        | 6.0   | 660  | 0.1759          | 0.9684   | 0.9830    | 0.9558 | 0.9692 | 0.9689  |
| 0.0054        | 7.0   | 770  | 0.1568          | 0.9700   | 0.9788    | 0.9632 | 0.9709 | 0.9703  |
| 0.0023        | 8.0   | 880  | 0.1775          | 0.9707   | 0.9754    | 0.9681 | 0.9717 | 0.9708  |
| 0.0023        | 9.0   | 990  | 0.1752          | 0.9710   | 0.9794    | 0.9646 | 0.9719 | 0.9713  |
| 0.0011        | 10.0  | 1100 | 0.1769          | 0.9713   | 0.9778    | 0.9667 | 0.9722 | 0.9715  |


### Framework versions

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