QASystem

Introduction

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

Model

• 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

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”