Tianchi-Multi-Task-Learning:第一名克莱登大学二队方案分享-源码

上传者: 42169971 | 上传时间: 2021-09-04 22:31:20 | 文件大小: 85KB | 文件类型: ZIP
实验环境 CUDA版本:11.0驱动程序版本:450.80.02 GPU:TITAN XP Python:3.7.9 pytorch:1.7.0操作系统:ubuntu 20.04 安装依赖包 pip install -r requirements.txt 解决方案及算法说明 数据预处理:数据清洗(剔除中文,非英文,非数字符号) 文本截断:通过对各任务句子长度的分析,选择句子长度256作为截断标准,不足补0 数据输入 由于任务二和任务三存在轴向的类别不均衡问题,因此训练集和验证集的划分采用分层的KFold交叉验证。由于需要多任务学习,因此模型的输入增加了任务标识dataset_ids。因此模型的输入其中任务一由于是句子对任务,token = [cls +句子1 + sep +句子2],其余两个任务token = [cls +句子+ sep]表示为(token_ids,segment_id,

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