nlbse25_pharo

Pharo comment classifier

This is a SetFit model that can be used for Pharo code comment classification.

The model has been trained using few-shot learning that involves:

1. Fine-tuning a Sentence Transformer with contrastive learning.
2. Training a classification head with features from the fine-tuned model.

Model Description

• Model Type: SetFit
• Classification head: RandomForestClassifier

Sources

• Repository: GitHub
• Paper: Evaluating the Performance and Efficiency of Sentence-BERT for Code Comment Classification
• Dataset: HF Dataset

How to use it

First, install the depencies:

pip install setfit scikit-learn

Then, load the model and run inferences:

from setfit import SetFitModel

# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("fabiancpl/nlbse25_pharo")
# Run inference
preds = model("This function sorts a list of numbers.")

Cite as

@inproceedings{11029440,
  author={Peña, Fabian C. and Herbold, Steffen},
  booktitle={2025 IEEE/ACM International Workshop on Natural Language-Based Software Engineering (NLBSE)}, 
  title={Evaluating the Performance and Efficiency of Sentence-BERT for Code Comment Classification}, 
  year={2025},
  pages={21-24},
  doi={10.1109/NLBSE66842.2025.00010}}