Abstract
We present the system description of our team Zhegu in SemEval-2023 Task 9 Multilingual Tweet Intimacy Analysis. We propose \textbf{EPM} (\textbf{E}xponential \textbf{P}enalty \textbf{M}ean Squared Loss) for the purpose of enhancing the ability of learning difficult samples during the training process. Meanwhile, we also apply several methods (frozen Tuning \& contrastive learning based on Language) on the XLM-R multilingual language model for fine-tuning and model ensemble. The results in our experiments provide strong faithful evidence of the effectiveness of our methods. Eventually, we achieved a Pearson score of 0.567 on the test set.- Anthology ID:
- 2023.semeval-1.43
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 318–323
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.43
- DOI:
- 10.18653/v1/2023.semeval-1.43
- Cite (ACL):
- Pan He and Yanru Zhang. 2023. Zhegu at SemEval-2023 Task 9: Exponential Penalty Mean Squared Loss for Multilingual Tweet Intimacy Analysis. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 318–323, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Zhegu at SemEval-2023 Task 9: Exponential Penalty Mean Squared Loss for Multilingual Tweet Intimacy Analysis (He & Zhang, SemEval 2023)
- PDF:
- https://preview.aclanthology.org/rocling-reingestion-23/2023.semeval-1.43.pdf