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the pre-training loss #9

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jancylee opened this issue May 10, 2021 · 10 comments
Open

the pre-training loss #9

jancylee opened this issue May 10, 2021 · 10 comments

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@jancylee
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The pre-training losses are always negative (like -199.03), is that normal?

@merlinarer
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The pre-training losses are always negative (like -199.03), is that normal?

I got the negative loss also, have you solve it?

@jancylee
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Not yet.

@yinjunbo
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yinjunbo commented Jun 30, 2021

Have you worked it out? What should be the correct loss?

@jxhuang0508
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Anyone reproduced the results or solved the negative loss issue?

@jianglianEin
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Anyone konw something about the negative loss? Is that right?

@impiga
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impiga commented Oct 13, 2021

Hi, do you mean the value of loss is negative?

If this is the point, this is right for PixPro. You may check the implementation of this line https://github.com/zdaxie/PixPro/blob/main/contrast/models/PixPro.py#L204 .

@xiao7199
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Hi,
If I understand correctly, this regreission loss only includes the pushing force with aligning spatial corresponding pixel. So where is the repulsing force as in Eqn2?

@ZHEGG
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ZHEGG commented Mar 7, 2022

why negative loss?

@shiyongde
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same question.

@douyimin
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douyimin commented Oct 7, 2022

I carefully studied the code. The loss of this implementation seems different from the paper. It does not apply constractive loss.

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