albert-base-technical-debt-code-tesoro

Improving the detection of technical debt in Java source code with an enriched dataset

Model Details

Model Description

This model is the part of Tesoro project, used for detecting technical debt in source code. More information can be found at Tesoro HomePage.

• Developed by: Nam Hai Le
• Model type: Encoder-based PLMs
• Language(s): Java
• Finetuned from model: ALBERT

Model Sources

• Repository: Tesoro
• Paper: [To be update]

How to Get Started with the Model

Use the code below to get started with the model.

from transformers import AutoModelForSequenceClassification, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("NamCyan/albert-base-technical-debt-code-tesoro")
model = AutoModelForSequenceClassification.from_pretrained("NamCyan/albert-base-technical-debt-code-tesoro")

Training Details

• Training Data: The model is finetuned using tesoro-code

• Infrastructure: Training process is conducted on two NVIDIA A100 GPUs with 80GB of VRAM.

Leaderboard

Citing us

@article{nam2024tesoro,
  title={Improving the detection of technical debt in Java source code with an enriched dataset},
  author={Hai, Nam Le and Bui, Anh M. T. Bui and Nguyen, Phuong T. and Ruscio, Davide Di and Kazman, Rick},
  journal={},
  year={2024}
}