title: Training doesn't generalize to predict validation and test set well, how to improve generalization?
body: <p>I have built a 1D CNN regression model using features from the embedding layer by <code>keras</code>, to predict a score of some sequences.</p>
  <p>Typical performance of my model after training is like:</p>
  <p><a href="https://i.stack.imgur.com/xfu0G.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/xfu0G.png" alt="enter image description here" /></a></p>
  <p><a href="https://i.stack.imgur.com/27hrr.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/27hrr.png" alt="enter image description here" /></a></p>
  <p>As you can see, the performance of predicting training data is very good but seems the performance doesn't generalize to predicting validation and testing data.</p>
  <p>Do you have any recommendations on <strong>how to improve validation/ test set prediction performance, possibly by trading in the prediction performance on training data?</strong> (Is this possible?)</p>
  <p>Thanks!</p>