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This repository contains various methods such as FlowQA, GraphFlow and BERT based models for conversational Q&A system

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Conversational Question Answering System

This repo contains various methods explored for Conversational Q&A System on CoQA Dataset

Methods

  • FlowQA: Implemented LSTM and GRU-based Flow-QA architecture
  • GraphFlow: a GNN based architecture with various embeddings
  • Transformer: BERT base and BERT large architectures

In total we performed 13 different experiments and found Transformer based architecture gives the best F1 score on the validation set.

The Presentation explaining the methods and results can be found here

Note: To run individual methods check the ReadMe for each methods and install requiremenets from requirement.txt files. Python version used for all the experiments: Python 3.8

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This repository contains various methods such as FlowQA, GraphFlow and BERT based models for conversational Q&A system

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