| Título |
NLP-CIC at HASOC 2020: Multilingual offensive language detection using all-in-one model |
| Tipo |
Congreso |
| Sub-tipo |
Memoria |
| Descripción |
12th Forum for Information Retrieval Evaluation, FIRE-WN 2020 |
| Resumen |
We describe our deep learning model submitted to the HASOC 2020 shared task on detection of offensive language in social media in three Indo-European languages: English, German, and Hindi. We fine-tune a pre-trained multilingual encoder on the combination of data provided for the competition. Our submission received a competitive macro- average F1 score of 0.4980 on the English Subtask A as well as comparatively strong performance on the German data. |
| Observaciones |
CEUR Workshop Proceedings |
| Lugar |
Hyderabad |
| País |
India |
| No. de páginas |
331-335 |
| Vol. / Cap. |
v. 2826 |
| Inicio |
2020-12-16 |
| Fin |
2020-12-20 |
| ISBN/ISSN |
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