title: The loss plot and the criteria for determining whether it converges
body: <p>I have been running a keras u-net implementation with tensorflow as backend. In the experiment, I run 60 epochs. The loss plot is shown as following, can I assume that the program has converged? Looks to me that the loss does not change significantly.</p>
  
  <p>This is the code related to defining optimizer and launching the training process.</p>
  
  <pre><code>  optimizer = SGD(lr=0.001, momentum=0.9, decay=0.0005, nesterov=False)
    autoencoder.compile(loss=customized_loss, optimizer=optimizer, metrics=   [customized_dice])
     nb_epoch = 60
     batch_size = 32
     model.fit(imgs_train, imgs_mask_train, batch_size=batch_size, nb_epoch=nb_epoch, verbose=1,callbacks=[model_checkpoint])
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/npIn6.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/npIn6.jpg" alt="enter image description here"></a></p>