This paper presents the different models submitted by the LT@Helsinki team for the SemEval 2020 Shared Task 12. Our team participated in sub-tasks A and C; titled offensive language identification and offense target identification, respectively. In both cases we used the so-called Bidirectional Encoder Representation from Transformer (BERT), a model pre-trained by Google and fine-tuned by us on the OLID and SOLID datasets. The results show that offensive tweet classification is one of several language-based tasks where BERT can achieve state-of-the-art results.
@article{arxiv.2008.00805,
title = {LT@Helsinki at SemEval-2020 Task 12: Multilingual or language-specific BERT?},
author = {Marc Pàmies and Emily Öhman and Kaisla Kajava and Jörg Tiedemann},
journal= {arXiv preprint arXiv:2008.00805},
year = {2020}
}
Comments
Accepted at SemEval-2020 Task 12. Identical to camera-ready version except where adjustments to fit arXiv requirements were necessary