Open lihuikenny opened 3 years ago
weight_CV: tensor([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]],
[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]],
训练自己的数据的时候报错了,weight_cv一直都是NAN 我尝试过以下这些方案解决,结果不行: 1、调整学习率 2、对FC权重和特征进行归一化
我的分类数是3000多类,我看代码weight_cv,是对label的一个onehot转换。按理应该不会出现这种错误才对。 希望作者能指点一下,谢谢
补充一下:不过二分类好像没问题,
weight_CV: tensor([[[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]],
训练自己的数据的时候报错了,weight_cv一直都是NAN 我尝试过以下这些方案解决,结果不行: 1、调整学习率 2、对FC权重和特征进行归一化
我的分类数是3000多类,我看代码weight_cv,是对label的一个onehot转换。按理应该不会出现这种错误才对。 希望作者能指点一下,谢谢