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Shayona@SMM4H23: COVID-19 Self diagnosis classification using BERT and LightGBM models

Computation and Language 2024-01-05 v1 Artificial Intelligence

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.

Keywords

Cite

@article{arxiv.2401.02158,
  title  = {Shayona@SMM4H23: COVID-19 Self diagnosis classification using BERT and LightGBM models},
  author = {Rushi Chavda and Darshan Makwana and Vraj Patel and Anupam Shukla},
  journal= {arXiv preprint arXiv:2401.02158},
  year   = {2024}
}