# LogFormer

**Repository Path**: ywl-1993/LogFormer

## Basic Information

- **Project Name**: LogFormer
- **Description**: AAAI 2024 论文代码
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-07-05
- **Last Updated**: 2024-07-05

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# LogFormer
[AAAI 2024] LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection

# Data
Training data can be download from [LogHub](https://github.com/logpai/loghub)


# Updates
01/23. We release the base code version for LogFormer, which is a strong baseline for log anomaly detection.

# Data processing
1. Downloading data into log_data/
2. parse_log.py
3. preprocess_xxx.py

# Run
1. First run train_transformer.py
2. Then run tune_transformer.py


# Citation
If you feel helpful, please cite our paper.

```
@inproceedings{guo2024logformer,
  title={Logformer: A pre-train and tuning pipeline for log anomaly detection},
  author={Guo, Hongcheng and Yang, Jian and Liu, Jiaheng and Bai, Jiaqi and Wang, Boyang and Li, Zhoujun and Zheng, Tieqiao and Zhang, Bo and Peng, Junran and Tian, Qi},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  number={1},
  pages={135--143},
  year={2024}
}
```