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eIRC

This repository contains notebooks that replicate the usage of adapters for the task of issue report classification.

Dataset

The data used is available at: NLBSE'24 competition.

Requirements

The Python packages required to run the code are listed in requirements.txt.

The requirements can easily installed via pip install -r requirements.txt.

For saving the model on Huggingface and for experiment tracking on wandb, you need to have your API keys.

Notebooks

The code is simplified and available in several Python Jupyter Notebooks, compatible to run on Google Colab.

Notebook Description
AdaptIRC_unsplit.ipynb This notebook trains adapter per repo and does not split the training data into training and validation.
AdaptIRC_FT.ipynb This notebook utilises full fine-tuning if the RoBERTa model.
AdaptIRC_SA.ipynb This notebook trains a single adapter for all repositories.
eIRC_Demo.ipynb This notebook shows a demo of the eIRC web application.

The work during the NLBSE'24 competition is available on another branch at: AdaptIRC

Adapters

The adapters created ara available on the following link: Adapters

Results

The JSON format results are avaialble on the results directory at Results

Logs on wandb:

All the results and metrics ara available at: IRC wandb

eIRC Web Application

The eIRC web application demonstration is available on HuggingFace on the following link: eIRC

Acknowledgement

This repository used codes of different libraries and other notebooks:

  1. Adapters
  2. Transformers
  3. NLBSE'2024 competition
  4. Gradio
  5. Huggingface

Citation

The work is based on the NLBSE'24 competition.

@inproceedings{kallis2024nlbse,
  title={The NLBSE'24 Tool Competition},
  author={Kallis, Rafael and Colavito, Giuseppe and Al-Kaswan, Ali and Pascarella, Luca and Chaparro, Oscar and Rani, Pooja},
  booktitle={Proceedings of the Third ACM/IEEE International Workshop on NL-based Software Engineering},
  pages={33--40},
  year={2024}
}

It is also an extention of the AdaptIRC model.

@inproceedings{ebrahim2024few,
  title={Few-Shot Issue Report Classification with Adapters},
  author={Ebrahim, Fahad and Joy, Mike},
  booktitle={Proceedings of the Third ACM/IEEE International Workshop on NL-based Software Engineering},
  pages={41--44},
  year={2024}
}

The Journal will be shared later.

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