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Electra Large Synqa
基于ELECTRA-Large架构的两阶段训练问答模型，先在合成对抗数据上训练，再在SQuAD和AdversarialQA数据集上微调
Downloads 24
Release Time : 3/2/2022
Model Overview
该模型专为问答系统设计，能够准确回答基于给定文本的问题，适用于多种问答场景。
Model Features
两阶段训练
先在合成对抗数据上训练，再在人工标注数据上微调，提高模型鲁棒性
高性能
在SQuAD验证集上达到89.42的精确匹配度和94.79的F1分数
对抗性训练
使用对抗性QA数据增强模型应对挑战性问题的能力
Model Capabilities
文本理解
问题回答
上下文分析
Use Cases
教育
阅读理解辅助
帮助学生快速理解文章内容并回答问题
提高学习效率和理解深度
客户服务
自动问答系统
基于知识库自动回答客户问题
减少人工客服压力，提高响应速度
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