Abstract
This paper presents the different models submitted by the LT@Helsinki team for the SemEval2020 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 dataset. The results show that offensive tweet classification is one of several language-based tasks where BERT can achieve state-of-the-art results.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 14th International Workshop on Semantic Evaluation |
| Publisher | International Committee on Computational Linguistics (ICCL |
| Number of pages | 7 |
| ISBN (Print) | 978-1-952148-31-6 |
| Publication status | Published - 2020 |
| MoE publication type | A4 Conference publication |
| Event | International Workshop on Semantic Evaluation - Barcelona, Spain Duration: 12 Dec 2020 → 13 Dec 2020 http://alt.qcri.org/semeval2020/ |
Workshop
| Workshop | International Workshop on Semantic Evaluation |
|---|---|
| Abbreviated title | SemEval |
| Country/Territory | Spain |
| City | Barcelona |
| Period | 12/12/2020 → 13/12/2020 |
| Other | Collocated with The 28th International Conference on Computational Lingustics (COLING-2020) |
| Internet address |