About Image Classfication Fine Tune(pre-training)

(Karl Mason) #1

I use Keras VGG16 with the imagenet fine tuned model to classify natural scene images to 5 classes, but now my validation accuracy oscillating at about 85%, cannot be even better unless keep on training to overfit, how can i do to improve the performance, are there any experienced friend can provide some helpful suggestions? The target is up to 90% validation accuracy or more …

I thought some tricks, like lr decay, class weight balance,

My training set contains 12000 pics, and validation contains 3000 pics. I used Adam with lr = 1e-7.

Really appreciate…

:slightly_frowning_face:

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