I am training a classification network (efficientnet_b0) on a dataset where I have unbalanced images.
Does each minibatch have equal number of examples from each class of data? Are there any config options for how the data is loaded or how sampling is handled?
Sorry, each minibatch has equal number of examples from each class of data.
I misunderstood your question. What I mentioned earlier is that for training images, it is not needed to set equal number of examples for each class.