Comments (4)
Yes it is normal ! I found that siamese networks need some epoch (sometimes more than 5 or 10 !) to increase their accuracy and this can be explained as follow : they try to separate « same » and « not same » from a scalar value (distance) so they have to find the right threshold before having a better score (before that they always predict either 0 or 1)
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@Ananas120 Hi, are you using python 2.7 or 3.*?
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I re-implemented your model architecture in python 3 in my personal project
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Thank you for your response,
I have just reimplemented train_siamese.py code in python 3 and currently training on google colab.
I'm getting accuracy value == 0.5000 since first training step. Is it normal or I'm missing something.
if it is possible can you share training log?
Thank you.
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