title: "val_acc" does not change at all
body: <p>I created a CNN for image classification using Keras on Python. I have a rather small data set(approx. 3000 pictures), the main goal is a simple binary classification.</p>
  
  <p>And the issue is that <strong>during the training the "acc" grows, while the "val_acc" doesn't change at all</strong> from the very beginning and stays +- 0.6.</p>
  
  <p>I searched the internet and almost everywhere people say that the main trouble is the small size of my data set, i.e. the net is <strong>overfitting</strong>. 
  But I tried to make it as simple as possible (now it's 2 Conv layers, Flatten and 1 hidden FC layer), i added batch normalization and nothing helps! </p>
  
  <p>Maybe there's something i don't understand and that's why it doesn't work? The longer I'm doing this, the more confused I get about <strong>what's the difference between "acc" and "val_acc"</strong> at all? I would be very grateful for any help!</p>
  
  <p>P.S. I tried to use the code from the <a href="https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html" rel="nofollow noreferrer">Keras blog tutorial</a> about "Cats vs. Dogs" classification, but this didn't help to, the problem stays the same:(</p>