---
library_name: transformers
base_model: microsoft/graphcodebert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: vuln-patch-cwe-guesser-model-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. -->

# vuln-patch-cwe-guesser-model-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: 4.8276
- Accuracy: 0.35
- F1: 0.1264

## 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: 3e-05
- train_batch_size: 40
- eval_batch_size: 40
- 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: 5
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 1    | 5.1591          | 0.0      | 0.0    |
| No log        | 2.0   | 2    | 5.0441          | 0.3      | 0.0985 |
| No log        | 3.0   | 3    | 4.9430          | 0.45     | 0.1833 |
| No log        | 4.0   | 4    | 4.8677          | 0.35     | 0.1264 |
| No log        | 5.0   | 5    | 4.8276          | 0.35     | 0.1264 |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2