I have train almost 80thousand examples within 2000 labels,valid acc almost 92%,but test result all example prob is blew 0.01.
w279805299 opened this issue · comments
I have trained almost 80thousand examples within 2000 labels,valid acc almost 92%,but test result all example prob is blew 0.01.
I have tried tranning examples to predict.
I have trained almost 80thousand examples within 2000 labels,valid acc almost 92%,but test result all example prob is blew 0.01.
I have tried tranning examples to predict.
hello, have you solved this problem?
When having a large number of labels and the number of actual labels for each sample is small, the loss function needs to be re-considered, otherwise the accuracy is unreliable
I have trained almost 80thousand examples within 2000 labels,valid acc almost 92%,but test result all example prob is blew 0.01.
I have tried tranning examples to predict.
hello have you solved this problem? I meet this problem too
When having a large number of labels and the number of actual labels for each sample is small, the loss function needs to be re-considered, otherwise the accuracy is unreliable
so I should change the loss function? should I modify the method of accuracy ?
我也遇到了同样的问题,实际的分类效果非常差
是的,我也遇到了,66个类别,准确率不能反映真实情况