Why my test error is lower then train error I am trying to train a CNN regression model using the ADAM optimizer, dropout and weight decay.

My test accuracy is better than training accuracy.
But as I know, usually train accuracy is better than test accuracy.

So I wonder how this is happening.
You use dropout during traing to reduce overfitting, but this reduces the training accuracy. The dropout will not be used during testing, therefore the accuracy will be higher.

That's normal behavior if you work with dropout.