lonePatient / Bert-Multi-Label-Text-Classification

This repo contains a PyTorch implementation of a pretrained BERT model for multi-label text classification.

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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