title: Training keras model; why mae decreases while mse increases?
body: <p>I am training a model using keras on a regression problem. When I investigate the loss and metrics during training, sometimes <code>mean absolute error (mae)</code> decreases at the end of an epoch, while <code>mean square error (mse)</code> increases. I set <code>mae</code> as loss and <code>mse</code> as metric.</p>
  
  <p>Is it OK? Or is there any problem with the setting?
  Thanks</p>