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2020 EMNLP EMNLP 2020

SU-NLP at WNUT-2020 Task 2: The Ensemble Models

Abstract

AbstractIn this paper, we address the problem of identifying informative tweets related to COVID-19 in the form of a binary classification task as part of our submission for W-NUT 2020 Task 2. Specifically, we focus on ensembling methods to boost the classification performance of classification models such as BERT and CNN. We show that ensembling can reduce the variance in performance, specifically for BERT base models.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing

🐣 Hot Topic Early Bird - covid-19 detection

Authors

Kenan Fayoumi, Reyyan Yeniterzi

Topics

Artificial Intelligence > Core AI > Foundation Models Machine Learning > Core Methods > Classification Machine Learning > Application Areas > Model Merging Deep Learning > Architectures > Transformers Natural Language Processing > Applications > Text Classification Machine Learning > Core Methods > Ensemble Methods Deep Learning > Learning Types > Deep Learning Deep Learning > Learning Types > Ensemble Learning

Keywords

ensemble learning text classification bert model convolutional neural network ensemble method bidirectional encoder covid-19 detection transformer model cnn model

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