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STACC: a set of SentenceTransformer Assisted Comment Classifiers

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STACC: a set of SentenceTransformer Assisted Comment Classifiers πŸ“š

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This repository contains our notebooks for the train, test and use STACC, our submission to the NLBSE'23 Code Comment Classification tool competition.

Quickstart Guide

Install SetFit with the Optuna backend:

pip install setfit[optuna]

Now you're ready to roll

Notebook Descriptions:

  • 1-Model_selection.ipynb outlines how we selected the base model and tuned the hyperparameters
  • 2-Creating_classifiers.ipynb shows how we created the 19 classifiers that make up STACC πŸ“š
  • 3-Inference.ipynb shows how you can put STACC to good use by loading a classifier and start predicting.

Google Colab

If you wish to run the notebooks in Google Colab we provide the following ready-to-go notebooks:

Huggingface Space

We also integrated STACC πŸ“š in a Huggingface space.

image

Citation

@software{STACC_2023,
  author = {Al-Kaswan, Ali and Izadi, Maliheh and van Deursen, Arie},
  year = {2023},
  title = {STACC: a set of SentenceTransformer Assisted Comment Classifiers},
  url = {https://github.com/AISE-TUDelft/STACC},
  version = {1.0}

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