title: how to calculate the average of training accuracy in Keras?
body: <p>i am trying to calculate the average of the training accuracy in y model which is written with KERAS, i have 200 epochs. So in the end i want to sum each training accuracy in each epoch with the previous one and divided them by 200..</p>
  
  <p>here is my code </p>
  
  <pre><code>num = 200
  total_sum = 0
  for n in range(num):
      avg_train=np.array(model.fit(x_train,y_train, epochs=200, batch_size=64, verbose=2))
      total_sum = avg_train + total_sum
  avg = total_sum/num
  
  score=model.evaluate(x_test, y_test, verbose=2)
  print(score)
  print('the average is',avg)
  </code></pre>
  
  <p>i am trying to store each accuracy in a numpy array to be able using it in the summation operation but it gives me the following error</p>
  
  <pre><code>Traceback (most recent call last):
    File "G:\Master Implementation\MLPADAM.py", line 87, in &lt;module&gt;
      total_sum = avg_train + total_sum
  TypeError: unsupported operand type(s) for +: 'History' and 'int' 
  </code></pre>