people_relation_extract:结合BERT+GRU+ATT模型,对自己收集的人物关系数据进行模型训练,用于人物关系抽取-源码

上传者: 42134338 | 上传时间: 2021-09-03 20:56:57 | 文件大小: 690KB | 文件类型: ZIP
运行该项目的模型训练和模型预测脚本需要准备BERT中文版的模型数据,下载网址为: 。   利用笔者自己收集的3881个样本,对人物关系抽取进行尝试。人物关系共分为14类,如下: { "unknown": 0, "夫妻": 1, "父母": 2, "兄弟姐妹": 3, "上下级": 4, "师生": 5, "好友": 6, "同学": 7, "合作": 8, "同人": 9, "情侣": 10, "祖孙": 11, "同门": 12, "亲戚": 13 }   人物关系类别频数分布条形图如下:   模型结构: BERT + 双向GRU + Attention + FC   模型训练效果: # 训练集(train), loss: 0.0260, acc: 0.9941 # 最终测试集(test), loss: 0.9505, acc:

文件下载

资源详情

[{"title":"( 32 个子文件 690KB ) people_relation_extract:结合BERT+GRU+ATT模型,对自己收集的人物关系数据进行模型训练,用于人物关系抽取-源码","children":[{"title":"people_relation_extract-master","children":[{"title":".gitignore <span style='color:#111;'> 83B </span>","children":null,"spread":false},{"title":"bert","children":[{"title":"args.py <span style='color:#111;'> 1.54KB </span>","children":null,"spread":false},{"title":"tokenization.py <span style='color:#111;'> 10.31KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 616B </span>","children":null,"spread":false},{"title":"optimization.py <span style='color:#111;'> 5.90KB </span>","children":null,"spread":false},{"title":"modeling.py <span style='color:#111;'> 37.19KB </span>","children":null,"spread":false},{"title":"graph.py <span style='color:#111;'> 6.86KB </span>","children":null,"spread":false},{"title":"extract_feature.py <span style='color:#111;'> 13.67KB </span>","children":null,"spread":false}],"spread":true},{"title":"requirements.txt <span style='color:#111;'> 96B </span>","children":null,"spread":false},{"title":"sent.txt <span style='color:#111;'> 1B </span>","children":null,"spread":false},{"title":"data","children":[{"title":"bar_chart.png <span style='color:#111;'> 33.19KB </span>","children":null,"spread":false},{"title":"test.txt <span style='color:#111;'> 113.94KB </span>","children":null,"spread":false},{"title":"data_into_train_test.py <span style='color:#111;'> 1.27KB </span>","children":null,"spread":false},{"title":"relation_bar_chart.py <span style='color:#111;'> 1.04KB </span>","children":null,"spread":false},{"title":"rel_dict.json <span style='color:#111;'> 226B </span>","children":null,"spread":false},{"title":"train.txt <span style='color:#111;'> 455.11KB </span>","children":null,"spread":false},{"title":"人物关系表.xlsx <span style='color:#111;'> 289.93KB </span>","children":null,"spread":false}],"spread":true},{"title":"load_data.py <span style='color:#111;'> 1.02KB </span>","children":null,"spread":false},{"title":"att.py <span style='color:#111;'> 2.20KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 5.45KB </span>","children":null,"spread":false},{"title":".idea","children":[{"title":"bert_document_classify.iml <span style='color:#111;'> 428B </span>","children":null,"spread":false},{"title":"misc.xml <span style='color:#111;'> 185B </span>","children":null,"spread":false},{"title":"encodings.xml <span style='color:#111;'> 135B </span>","children":null,"spread":false},{"title":"vcs.xml <span style='color:#111;'> 180B </span>","children":null,"spread":false},{"title":"codeStyles","children":[{"title":"Project.xml <span style='color:#111;'> 2.20KB </span>","children":null,"spread":false}],"spread":false},{"title":"dbnavigator.xml <span style='color:#111;'> 22.08KB </span>","children":null,"spread":false},{"title":"inspectionProfiles","children":[{"title":"Project_Default.xml <span style='color:#111;'> 809B </span>","children":null,"spread":false}],"spread":false},{"title":"modules.xml <span style='color:#111;'> 296B </span>","children":null,"spread":false}],"spread":true},{"title":"model_train.py <span style='color:#111;'> 3.49KB </span>","children":null,"spread":false},{"title":"model.png <span style='color:#111;'> 41.59KB </span>","children":null,"spread":false},{"title":"loss_acc.png <span style='color:#111;'> 30.21KB </span>","children":null,"spread":false},{"title":"model_predict.py <span style='color:#111;'> 3.74KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明