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A Tensorflow implementation of Resnet, with test accuracy 91.97% on cifar10.

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checkpoint
checkpoint
 
 
cifar-10-batches-py
cifar-10-batches-py
 
 
summary
summary
 
 
testresults
testresults
 
 
README.md
README.md
 
 
input_data.py
input_data.py
 
 
predict.py
predict.py
 
 
resnet.py
resnet.py
 
 
resnet_cifar10.py
resnet_cifar10.py
 
 
train.py
train.py
 
 

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About

A Tensorflow implementation of Resnet,Resnetv2 trained on cifar10. The tese accuracy is 91.97%(93.03% in paper).

  • layer: 56

Train

python train.py

Test

python predict.py

Results

accuracy

learning rte

loss

test results

on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.940000
on batch size: 100, test accuracy: 0.900000
on batch size: 100, test accuracy: 0.900000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.970000
on batch size: 100, test accuracy: 0.900000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.970000
on batch size: 100, test accuracy: 0.940000
on batch size: 100, test accuracy: 0.880000
on batch size: 100, test accuracy: 0.950000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.900000
on batch size: 100, test accuracy: 0.970000
on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.880000
on batch size: 100, test accuracy: 0.940000
on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.950000
on batch size: 100, test accuracy: 0.850000
on batch size: 100, test accuracy: 0.950000
on batch size: 100, test accuracy: 0.950000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.960000
on batch size: 100, test accuracy: 0.880000
on batch size: 100, test accuracy: 0.870000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.830000
on batch size: 100, test accuracy: 0.890000
on batch size: 100, test accuracy: 0.900000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.890000
on batch size: 100, test accuracy: 0.900000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.950000
on batch size: 100, test accuracy: 0.980000
on batch size: 100, test accuracy: 0.950000
on batch size: 100, test accuracy: 0.940000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.880000
on batch size: 100, test accuracy: 0.940000
on batch size: 100, test accuracy: 0.880000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.950000
on batch size: 100, test accuracy: 0.970000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.950000
on batch size: 100, test accuracy: 0.940000
on batch size: 100, test accuracy: 0.960000
on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.950000
on batch size: 100, test accuracy: 0.950000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.870000
on batch size: 100, test accuracy: 0.960000
on batch size: 100, test accuracy: 0.900000
on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.900000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.940000
on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.880000
on batch size: 100, test accuracy: 0.940000
on batch size: 100, test accuracy: 0.940000
on batch size: 100, test accuracy: 0.910000
on batch size: 100, test accuracy: 0.890000
on batch size: 100, test accuracy: 0.880000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.870000
on batch size: 100, test accuracy: 0.940000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.890000
on batch size: 100, test accuracy: 0.940000
on batch size: 100, test accuracy: 0.890000
on batch size: 100, test accuracy: 0.920000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.900000
on batch size: 100, test accuracy: 0.930000
on batch size: 100, test accuracy: 0.890000
The test set number is 10000, the average accuracy is 0.919700

About

A Tensorflow implementation of Resnet, with test accuracy 91.97% on cifar10.

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resnet cifar10

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