lonePatient / Bert-Multi-Label-Text-Classification

This repo contains a PyTorch implementation of a pretrained BERT model for multi-label text classification.
MIT License
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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. #22

Open w279805299 opened 5 years ago

w279805299 commented 5 years ago

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.

qiu-nian commented 5 years ago

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?

bimhud commented 5 years ago

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

sunxiaowu commented 4 years ago

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

sunxiaowu commented 4 years ago

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 ?

xiaoyichao commented 4 years ago

我也遇到了同样的问题,实际的分类效果非常差

wl915634785 commented 2 years ago

是的,我也遇到了,66个类别,准确率不能反映真实情况