IRLab@IITBHU at WNUT-2020 Task 2: Identification of informative COVID-19 English Tweets using BERT

Supriya Chanda, Eshita Nandy, Sukomal Pal
November, 2020
PDF Cite Slides DOI
Image credit: Unsplash

Abstract

This paper reports our submission to the shared Task 2 Identification of informative COVID-19 English tweets at W-NUT 2020. We attempted a few techniques, and we briefly explain here two models that showed promising results in tweet classification tasks DistilBERT and FastText. DistilBERT achieves a F1 score of 0.7508 on the test set, which is the best of our submissions.

Type
Preprint
Publication
Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)
Click the Cite button above to demo the feature to enable visitors to import publication metadata into their reference management software.
Create your slides in Markdown - click the Slides button to check out the example.

#Supplementary notes can be added here, including code, math, and images.

covid-19
Supriya Chanda
Supriya Chanda
Research Scholar (2018-2024)

Supriya Chanda (pronounced as Supriyo), completed his Ph.D in the Department of Computer Science and Engineering, IIT (BHU), Varanasi. He did his research under the guidance of Dr. Sukomal Pal at the Information retrieval lab.