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GPT2SP Replication Package


GPT2SP

A web-based Agile story point estimator
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Table of Contents
  1. How to replicate
  2. Acknowledgements
  3. License

How to replicate

About the Datasets

All of the datasets for 16 different projects are available in the marked_data folder Each dataset has the following 5 columns:

  1. issuekey: Issue ID
  2. title: Issue Title
  3. description: Issue Description
  4. storypoint: Assigned Story Point of the Issue
  5. split_mark: Represent whether the row was used as training, validation, or testing
issuekey title description storypoint split_mark
... ... ... ... ...

About the Models

Model Naming Convention

All of the models on HuggingFace Model Hub and Google Drive has the same naming convention as described in the following table:

Model ID Model Specification Experiment Scenario
#0 BPE GPT2 Tokenizer + Custom Pre-trained GPT-2 (GPT2SP) Within-Project
#00 BPE GPT2 Tokenizer + Custom Pre-trained GPT-2 (GPT2SP) Within-Repository
#000 BPE GPT2 Tokenizer + Custom Pre-trained GPT-2 (GPT2SP) Cross-Repository
#2 Word-levelSP Tokenizer + Custom Pretrained GPT-2 Within-Project
#22 Word-levelSP Tokenizer + Custom Pretrained GPT-2 Within-Repository
#222 Word-levelSP Tokenizer + Custom Pretrained GPT-2 Cross-Repository
#6 WordPieceSP Tokenizer + Custom Pretrained GPT-2 Within-Project
#66 WordPieceSP Tokenizer + Custom Pretrained GPT-2 Within-Repository
#666 WordPieceSP Tokenizer + Custom Pretrained GPT-2 Cross-Repository
#7 SentencePieceSP Tokenizer + Custom Pretrained GPT-2 Within-Project
#77 SentencePieceSP Tokenizer + Custom Pretrained GPT-2 Within-Repository
#777 SentencePieceSP Tokenizer + Custom Pretrained GPT-2 Cross-Repository

How to access the models

About the Model Training Process

About the GPT2SP Web App

  • Access the GPT2SP web app here to interact with our GPT2SP model and navigate the datasets

Acknowledgements

  • Special thanks to DeepSE's developers for providing the datasets and the replication package.
  • Special thanks to developers from PyTorch, HuggingFace, Streamlit, Transformers Interpret for providing amazing frameworks for the community

License

MIT License

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