Winning solution of competition held by Bridgei2i under InterIIT Tech Meet 2021 [video, slides]

We provide well-commented code for your reference. The overall directory structure is as follows:

Outputs for the evaluation data is located at ./predictions/

High level directory overview

├── text-cls
│   ├── phoneme.py # code conversion to phonemes
│   └── train_cls.py # training classification model
├── summarization
│   ├── train.py # fine mbart model on dataset (refer to training_utils/args.py)
│   └── evaluate.py
├── ner
|   └── run.py # run NER + sentiment
├── assets
|   └── ppt.pdf # brief solution description
├── preprocess.py # preprocessing script
└── README.md

Running the app for theme classification and summarization

streamlit run app.py

Running the app for NER (only for tweets because of dependency issues)

streamlit run app_ner.py

IMPORTANT

• To run the NER code (./ner/run.py) and corresponding app (./app_ner.py), please install transformer==2.5
• To run summarization (./summarization/train.py) and corresponding app (./app.py) please use transformers==4.4