Key-Point-Analysis-and-Explanations-for-Quantitative-Text-Analysis

The following files in the repository contain the final code of our work:

1. FineTuningSentenceBert: Contains Unsupervised Finetuning TSDAE, SimCSE, CT
2. SiameseNNContrastiveLossclean: Contains the development of our models
3. Explainability_LeaveOneOutLIMEShap: Contains the LeaveOneOut, LIME and SHAP and their visualizations
4. bertviz_visualization_of_BERT_internals: Contains a visualizations of the attentions layers in the transformer models

In order to get the code running, download the original data from the KPA Shared task 2021 and store all files (dev,train,test) in one data folder.

The final report and presentation are located inside the final_docs_submission directory:

• Final Report: key-point-analysis-and-explanations-for-quantitative-text-analysis.pdf
• Final Presentation: Final_presentation.pptx