Abstract
We present our works on SemEval-2021 Task 5 about Toxic Spans Detection. This task aims to build a model for identifying toxic words in whole posts. We use the BiLSTM-CRF model combining with ToxicBERT Classification to train the detection model for identifying toxic words in posts. Our model achieves 62.23% by F1-score on the Toxic Spans Detection task.- Anthology ID:
- 2021.semeval-1.113
- Volume:
- Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 846–851
- Language:
- URL:
- https://aclanthology.org/2021.semeval-1.113
- DOI:
- 10.18653/v1/2021.semeval-1.113
- Cite (ACL):
- Son T. Luu and Ngan Nguyen. 2021. UIT-ISE-NLP at SemEval-2021 Task 5: Toxic Spans Detection with BiLSTM-CRF and ToxicBERT Comment Classification. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 846–851, Online. Association for Computational Linguistics.
- Cite (Informal):
- UIT-ISE-NLP at SemEval-2021 Task 5: Toxic Spans Detection with BiLSTM-CRF and ToxicBERT Comment Classification (Luu & Nguyen, SemEval 2021)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/2021.semeval-1.113.pdf
- Code
- sonlam1102/toxic-spans-detection-bilstm_crf