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thank s for this great tutorial
I want to apply this for a multi label text classification problem. My labels are of this format
tensor([[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
...,
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0]])
I changed the softmax function in the bert model by the sigmoid function but when I tried to train the model I got this error
multi-target not supported at /pytorch/aten/src/THCUNN/generic/ClassNLLCriterion.cu:18
Could u help plz
thank u
The text was updated successfully, but these errors were encountered:
First, thank u for responding. Well, I am confused now because in all tutorials Ive read about multi label classification, they all recommend using sigmoid for this kind of problems. Can u explain more plz
Thank u
Hi,
thank s for this great tutorial
I want to apply this for a multi label text classification problem. My labels are of this format
tensor([[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
...,
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0]])
I changed the softmax function in the bert model by the sigmoid function but when I tried to train the model I got this error
multi-target not supported at /pytorch/aten/src/THCUNN/generic/ClassNLLCriterion.cu:18
Could u help plz
thank u
The text was updated successfully, but these errors were encountered: