YNU-HPCC at SemEval-2024 Task 5: Regularized Legal-BERT for Legal Argument Reasoning Task in Civil Procedure

被引：0

作者：

Shi, Peng ^{[1
]}

Wang, Jin ^{[1
]}

Zhang, Xuejie ^{[1
]}

机构：

[1] Yunnan Univ, Sch Informat Sci & Engn, Kunming, Yunnan, Peoples R China

来源：

PROCEEDINGS OF THE 18TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2024 | 2024年

基金：

中国国家自然科学基金;

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes the submission of team YNU-HPCC to SemEval-2024 for Task 5: The Legal Argument Reasoning Task in Civil Procedure. The task asks candidates the topic, questions, and answers, classifying whether a given candidate's answer is correct (True) or incorrect (False). To make a sound judgment, we propose a system. This system is based on fine-tuning the Legal-BERT model that specializes in solving legal problems. Meanwhile, Regularized Dropout (R-Drop) and focal Loss were used in the model. R-Drop is used for data augmentation, and focal loss addresses data imbalances. Our system achieved relatively good results on the competition's official leaderboard. The code of this paper is available at https://github.com/YNU-PengShi/SemEval-2024-Task5.

引用

页码：757 / 762

页数：6

共 22 条

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PROCEEDINGS OF THE 18TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2024, 2024, : 1309 - 1314
[22] nicolay-r at SemEval-2024 Task 3: Using Flan-T5 for Reasoning Emotion Cause in Conversations with Chain-of-Thought on Emotion States
Rusnachenko, Nicolay
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PROCEEDINGS OF THE 18TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2024, 2024, : 22 - 27

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