/QASystem

COMP90042 Project - Question Answering System

Primary LanguageJupyter Notebook

QASystem

Introduction

This is the repository for COMP90042 Question and Answering System Project.

Model

image

  • Encode context and question with RNN
  • Use attention find correlation
  • Output the span of the answer

Performance

Metrics

Model Train Loss @ Step Dev Loss @ Step Dev F1-score
RNN 1.25 @ 1000 1.87 @ 1000 0.48
CNN 1.21 @ 1000 1.78 @ 1000 0.41
Rule Based N/A N/A 0.18

Loss

image

Reference

QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension[ICLR 2018]

Zhouhan Lin et al. “A Structured Self-attentive Sentence Embedding”. In:CoRRabs/1703.03130 (2017).arXiv:1703.03130.

Pranav Rajpurkar et al. “SQuAD: 100, 000+ Questions for Machine Comprehension of Text”. In:CoRRabs/1606.05250 (2016). arXiv:1606.05250.

Wenhui Wang et al. “Gated Self-Matching Networks for Reading Comprehension and Question Answering”