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QA Summary and Reasoning

问答摘要与推理 1.1 问题描述(“汽车大师问答摘要与推理”) 使用汽车大师提供的11万条(技师与用户的多轮对话与诊断建议报告数据)建立模型,模型需基于对话文本、用户问题、车型与车系,输出包含摘要与推断的报告文本,综合考验模型的归纳总结与推断能力。该解决方案可以节省大量人工时间,提高用户获取回答和解决方案的效率。 1.2 数据说明 对于每个用户问题"QID",有对应文本形式的文本集合 D = "Brand", "Collection", "Problem", "Conversation",要求阅读理解系统自动对D进行分析,输出相应的报告文本"Report",其中包含摘要与推理。目标是"Report"可以正确、完整、简洁、清晰、连贯地对D中的信息作归纳总结与推理。 训练:所提供的训练集(82943条记录)建立模型,基于汽车品牌、车系、问题内容与问答对话的文本,输出建议报告文本。 输出结果:对所提供的测试集(20000条记录)使用训练好的模型,输出建议报告的结果文件,通过最终测评得到评价分数

本项目使用的模型是seq2seq(GRU)+attention 数据集下载地址:https://aistudio.baidu.com/aistudio/competition/detail/3

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