---
library_name: transformers
base_model: huggingface/CodeBERTa-small-v1
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: v1
  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. -->

# v1

This model is a fine-tuned version of [huggingface/CodeBERTa-small-v1](https://huggingface.co/huggingface/CodeBERTa-small-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6553
- Accuracy: 0.6354
- F1 Weighted: 0.6336
- F1 Vuln: 0.5847
- Precision: 0.6339
- Recall: 0.6354

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted | F1 Vuln | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-------:|:---------:|:------:|
| 0.6492        | 1.0   | 682  | 0.6336          | 0.6032   | 0.6045      | 0.559   | 0.6068    | 0.6032 |
| 0.5907        | 2.0   | 1364 | 0.6094          | 0.6296   | 0.631       | 0.5942  | 0.6348    | 0.6296 |
| 0.5385        | 3.0   | 2046 | 0.6289          | 0.6442   | 0.6426      | 0.577   | 0.642     | 0.6442 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2