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[D] ShuffleNet V2 on MNIST dataset

Few days ago ,I see a article introduceed ShuffleNet V2 .

Based on my curiosity I trained ShuffleNet V2 on MNIST datase, and I got 99.14% accuracy .
( code here : https://github.com/allen108108/Model_on_MNIST/blob/master/MNIST%20-%20ShuffleNetV2.ipynb ).

The result looks good , but I got higher accuracy ( almost 99.5% ) when I trained a typically CNN model on the same dataset
( code here : https://github.com/allen108108/Model_on_MNIST/blob/master/MNIST%20-%20CNN.ipynb).

Is that normal situation ? Did I make some mistakes ?

PS : the ShuffleNet V2 model that I used : https://github.com/opconty/keras-shufflenetV2

submitted by /u/allen108108
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.