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Haloo
I used your dropout version of Convnet for Food classification.
I have 8 batches :
1-6 : train, 7 validation and 8 for test
I followed the methodology https://code.google.com/p/cuda-convnet/wiki/Methodology
I started the training : --train-range=1-6 --test-range=7 --epochs=200
an so on like the methodology...
The error rates for each batches is Good ( around 0.11)
but when I test it ( last method) with batch 8 . its 63% (final result).
I dont know what caused this. I assume that Foods share almost the same colors, shape, etc, mayble those are the cause.
What do you suggest ?
Thanks
The text was updated successfully, but these errors were encountered:
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Haloo
I used your dropout version of Convnet for Food classification.
I have 8 batches :
1-6 : train, 7 validation
and 8 for test
I followed the methodology https://code.google.com/p/cuda-convnet/wiki/Methodology
I started the training :
--train-range=1-6 --test-range=7 --epochs=200
an so on like the methodology...
The error rates for each batches is Good ( around 0.11)
but when I test it ( last method) with batch 8 . its 63% (final result).
I dont know what caused this. I assume that Foods share almost the same colors, shape, etc, mayble those are the cause.
What do you suggest ?
Thanks
The text was updated successfully, but these errors were encountered: