학술논문

Shayona@SMM4H23: COVID-19 Self diagnosis classification using BERT and LightGBM models
Document Type
Working Paper
Source
Subject
Computer Science - Computation and Language
Computer Science - Artificial Intelligence
Language
Abstract
This paper describes approaches and results for shared Task 1 and 4 of SMMH4-23 by Team Shayona. Shared Task-1 was binary classification of english tweets self-reporting a COVID-19 diagnosis, and Shared Task-4 was Binary classification of English Reddit posts self-reporting a social anxiety disorder diagnosis. Our team has achieved the highest f1-score 0.94 in Task-1 among all participants. We have leveraged the Transformer model (BERT) in combination with the LightGBM model for both tasks.