Fayoumi, Kenan and Yeniterzi, Reyyan (2020) SU-NLP at WNUT-2020 task 2: the ensemble models. In: The Sixth Workshop on Noisy User-generated Text (W-NUT 2020), Online
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2020.wnut-1.61.pdf
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Official URL: http://dx.doi.org/10.18653/v1/2020.wnut-1.61
Abstract
In 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.
Item Type: | Papers in Conference Proceedings |
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Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng. Faculty of Engineering and Natural Sciences |
Depositing User: | Reyyan Yeniterzi |
Date Deposited: | 27 Aug 2021 19:45 |
Last Modified: | 26 Apr 2022 09:38 |
URI: | https://research.sabanciuniv.edu/id/eprint/41676 |