首页> 外文会议>Social Media Mining for Health Workshop and Shared Tasks;Annual Conference of the North American Chapter of the Association for Compuational Linguistics >Classification of Tweets Self-reporting Adverse Pregnancy Outcomes and Potential COVID-19 Cases Using RoBERTa Transformers
【24h】

Classification of Tweets Self-reporting Adverse Pregnancy Outcomes and Potential COVID-19 Cases Using RoBERTa Transformers

机译:使用罗伯塔变换2019冠状病毒疾病报告的不良妊娠结局和潜在的COVID-19病例分类

获取原文

摘要

This study describes our proposed model design for SMM4H 2021 shared tasks. We fine-tune the language model of RoBERTa transformers and their connecting classifier to complete the classification tasks of tweets for adverse pregnancy outcomes (Task 4) and potential COVID-19 cases (Task 5). The evaluation metric is F1 -score of the positive class for both tasks. For Task 4, our best score of 0.93 exceeded the median score of 0.925. For Task 5, our best of 0.75 exceeded the median score of 0.745.
机译:本研究描述了我们所提出的SMM4H 2021共享任务的模型设计。我们对罗伯塔2019冠状病毒疾病的语言模型和它们的连接分类器进行微调,完成妊娠不良妊娠结局的任务分类(任务4)和潜在的COVID-19病例(任务5)。评估指标是F1——两项任务的积极等级分数。对于任务4,我们的最佳得分为0.93,超过了中位数0.925。对于任务5,我们的最佳成绩为0.75,超过了中位数0.745。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号