Unstable results when I train a CNN I'm currently training a CNN to do a binary classification.
I'm getting fairly good results, but unfortunately the training is very unstable.
Just by changing the seed the relative error changes by 20-30%.

What can be the cause of this and how can I prevent it?

Other info:


The amount of data is rather small.
I'm starting from imagenet snapshot.
Understand a data
Find the most suitable metrics
handle missing values
normalize, scale etc your variables
feature selecting
use cross validation(kfold for example)
try oversampling or undersampling 
trying other models