Adding paper details to model card

README.md

@@ -1,37 +1,32 @@
 ---
 library_name: transformers
-tags: []
+tags: [software engineering, software traceability]
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
+# Model Card for nl-bert
 
+Provides TAPT (Task Adaptive Pretraining) model from "Enhancing Automated Software Traceability by 
+Transfer Learning from Open-World Data".
 
 ## Model Details
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+This model was trained to predict trace links between issue and commits on GitHub data from 2016-21.
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Developed by:** Jinfeng Lin, University of Notre Dame
+- **Shared by [optional]:** Alberto Rodriguez, University of Notre Dame
+- **Model type:** BertForSequenceClassification
+- **Language(s) (NLP):** EN
+- **License:** MIT
 
 ### Model Sources [optional]
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** https://github.com/thearod5/se-models
+- **Paper:** https://arxiv.org/abs/2207.01084
 
 ## Uses
 
@@ -67,133 +62,51 @@ This is the model card of a 🤗 transformers model that has been pushed on the
 
 Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
 
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
 
 ## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
+Please see cite paper for full training details.
 
 ## Evaluation
 
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
+Please see cited paper for full evaluation.
 
 ### Results
 
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
+The model achieved a MAP score improvement of over 20% compared to baseline models. See cited paper for full details.
 
 ## Environmental Impact
 
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
+- **Hardware Type:** Distributed machine pool
+- **Hours used:** 72 hours
 
-[More Information Needed]
-
-#### Software
+# Technical Specifications [optional]
+# Model Architecture and Objective
+The model uses a Single-BERT architecture from the TBERT framework, which performs well on traceability tasks by encoding concatenated source and target artifacts.
 
-[More Information Needed]
+# Compute Infrastructure
+Hardware
+300 servers in a distributed machine pool
 
-## Citation [optional]
+# Software
+- Transformers library
+- PyTorch
+- HTCondor for distributed computation
 
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+## Citation
 
 **BibTeX:**
 
-[More Information Needed]
+@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}
+}
 
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
+## Model Card Authors
+Alberto Rodriguez
 
 ## Model Card Contact
-
-[More Information Needed]
+Alberto Rodriguez ([email protected])