Model Card for se-bert
Provides Generic Software Engineering LM from "Enhancing Automated Software Traceability by Transfer Learning from Open-World Data"
Model Details
The following language models is trained on the Git Corpus and Git Links from 2016 to 2021. The data contains 4 types of records including Comments, Issues, Pull Requests, and Commits.
Uses
This model is intended to be a good set of starting weights for various software engineering tasks including:
- requirements classification
- traceability link prediction
- retrieval / search
Training, Evaluation, and Results
Please see cited paper for complete details on training method.
Technical Specifications
Model Architecture and Objective
MLM model trained on SE Corpus (See Above).
Hardware
1 GPU with CUDA 10.2 or 11.1
Software
Python >= 3.7 pytorch/1.1.0
Citation [optional]
BibTeX:
@misc{lin2022enhancing, title={Enhancing Automated Software Traceability by Transfer Learning from Open-World Data}, author={Jinfeng Lin and Amrit Poudel and Wenhao Yu and Qingkai Zeng and Meng Jiang and Jane Cleland-Huang}, year={2022}, eprint={2207.01084}, archivePrefix={arXiv}, primaryClass={cs.SE} }
Model Card Authors [optional]
Jinfeng Lin, Amrit Poudel, Wenhao Yu, Qingkai Zeng, Jane Cleland-Huang
Model Card Contact
Alberto Rodriguez (arodri39@nd.edu)