---
library_name: transformers
base_model: microsoft/graphcodebert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cwe-parent-vulnerability-classification-microsoft-graphcodebert-base
  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. -->

# cwe-parent-vulnerability-classification-microsoft-graphcodebert-base

This model is a fine-tuned version of [microsoft/graphcodebert-base](https://huggingface.co/microsoft/graphcodebert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8233
- Accuracy: 0.6517
- F1 Macro: 0.3050

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 3.255         | 1.0   | 25   | 3.2962          | 0.0225   | 0.0083   |
| 3.1345        | 2.0   | 50   | 3.3120          | 0.2697   | 0.0544   |
| 3.0539        | 3.0   | 75   | 3.3627          | 0.3820   | 0.0582   |
| 2.9349        | 4.0   | 100  | 3.3122          | 0.3596   | 0.0921   |
| 2.9555        | 5.0   | 125  | 3.2926          | 0.4045   | 0.1695   |
| 2.7748        | 6.0   | 150  | 3.3514          | 0.4607   | 0.1757   |
| 2.803         | 7.0   | 175  | 3.3219          | 0.5169   | 0.1884   |
| 2.67          | 8.0   | 200  | 3.2696          | 0.4831   | 0.2198   |
| 2.5684        | 9.0   | 225  | 3.2657          | 0.4944   | 0.2445   |
| 2.4226        | 10.0  | 250  | 3.1999          | 0.3371   | 0.1697   |
| 2.4615        | 11.0  | 275  | 3.1954          | 0.4270   | 0.1996   |
| 2.2738        | 12.0  | 300  | 3.1108          | 0.4157   | 0.1954   |
| 2.2423        | 13.0  | 325  | 3.0714          | 0.3933   | 0.1862   |
| 2.2066        | 14.0  | 350  | 3.0598          | 0.3820   | 0.1975   |
| 1.9919        | 15.0  | 375  | 3.0252          | 0.4382   | 0.1992   |
| 1.9622        | 16.0  | 400  | 2.9873          | 0.3708   | 0.1981   |
| 1.9415        | 17.0  | 425  | 2.9783          | 0.4494   | 0.2166   |
| 1.8459        | 18.0  | 450  | 2.9570          | 0.4831   | 0.2304   |
| 1.7008        | 19.0  | 475  | 2.9116          | 0.4607   | 0.2104   |
| 1.6705        | 20.0  | 500  | 2.9134          | 0.4607   | 0.2152   |
| 1.6422        | 21.0  | 525  | 2.9341          | 0.4607   | 0.2554   |
| 1.4982        | 22.0  | 550  | 2.8852          | 0.5056   | 0.2604   |
| 1.5523        | 23.0  | 575  | 2.9029          | 0.5056   | 0.2555   |
| 1.3784        | 24.0  | 600  | 2.8782          | 0.5393   | 0.2840   |
| 1.4479        | 25.0  | 625  | 2.8525          | 0.5730   | 0.2558   |
| 1.2508        | 26.0  | 650  | 2.9039          | 0.5730   | 0.2563   |
| 1.3662        | 27.0  | 675  | 2.8784          | 0.6067   | 0.3081   |
| 1.2199        | 28.0  | 700  | 2.8704          | 0.6180   | 0.2729   |
| 1.1903        | 29.0  | 725  | 2.8577          | 0.6404   | 0.2811   |
| 1.1881        | 30.0  | 750  | 2.8612          | 0.6404   | 0.2890   |
| 1.1572        | 31.0  | 775  | 2.8371          | 0.6292   | 0.2968   |
| 1.0623        | 32.0  | 800  | 2.8413          | 0.6404   | 0.2969   |
| 1.0405        | 33.0  | 825  | 2.8233          | 0.6517   | 0.3050   |
| 1.1084        | 34.0  | 850  | 2.8323          | 0.6404   | 0.3012   |
| 1.0211        | 35.0  | 875  | 2.8341          | 0.6404   | 0.3042   |
| 1.0215        | 36.0  | 900  | 2.8391          | 0.6404   | 0.3006   |
| 0.9438        | 37.0  | 925  | 2.8321          | 0.6404   | 0.3006   |
| 0.9383        | 38.0  | 950  | 2.8266          | 0.6404   | 0.3012   |
| 1.017         | 39.0  | 975  | 2.8236          | 0.6404   | 0.3037   |
| 0.9262        | 40.0  | 1000 | 2.8264          | 0.6404   | 0.3037   |


### Framework versions

- Transformers 4.55.4
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2