README.md

---
library_name: transformers
license: mit
language:
- en
metrics:
- f1
- precision
- recall
base_model:
- Salesforce/codet5p-220m
pipeline_tag: text-classification
---

# CodeT5+ 220m for classifying code comments (multi-label)

This model classifies comments in Python code as 'usage', 'parameters', 'developmentNotes', 'expand' or 'summary'.

- **Developed by:** Fabian C. Peña, Steffen Herbold
- **Finetuned from:** [Salesforce/codet5p-220m](https://huggingface.co/Salesforce/codet5p-220m)
- **Replication kit:** [https://github.com/aieng-lab/senlp-benchmark](https://github.com/aieng-lab/senlp-benchmark)
- **Language:** English
- **License:** MIT

## Citation

```
@misc{pena2025benchmark,
  author    = {Fabian Peña and Steffen Herbold},
  title     = {Evaluating Large Language Models on Non-Code Software Engineering Tasks},
  year      = {2025}
}
```