Keras early stopping callback error, val_loss metric not available : <p>I am training a Keras (Tensorflow backend, Python, on MacBook) and am getting an error in the early stopping callback in fit_generator function.  The error is as follows:</p>

<pre><code>RuntimeWarning: Early stopping conditioned on metric `val_loss` which is not available. Available metrics are:
  (self.monitor, ','.join(list(logs.keys()))),
RuntimeWarning: Can save best model only with val_acc available, skipping.

'skipping.' % (self.monitor), RuntimeWarning
[local-dir]/lib/python3.6/site-packages/keras/callbacks.py:497: RuntimeWarning: Early stopping conditioned on metric `val_loss` which is not available. Available metrics are:
  (self.monitor, ','.join(list(logs.keys()))), RuntimeWarning
[local-dir]/lib/python3.6/site-packages/keras/callbacks.py:406: RuntimeWarning: Can save best model only with val_acc available, skipping.
  'skipping.' % (self.monitor), RuntimeWarning)
Traceback (most recent call last):
  :
  [my-code]
  :
  File "[local-dir]/lib/python3.6/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
  File "[local-dir]/lib/python3.6/site-packages/keras/engine/training.py", line 2213, in fit_generator
callbacks.on_epoch_end(epoch, epoch_logs)
  File "[local-dir]/lib/python3.6/site-packages/keras/callbacks.py", line 76, in on_epoch_end
callback.on_epoch_end(epoch, logs)
  File "[local-dir]/lib/python3.6/site-packages/keras/callbacks.py", line 310, in on_epoch_end
self.progbar.update(self.seen, self.log_values, force=True)
AttributeError: 'ProgbarLogger' object has no attribute 'log_values'
</code></pre>

<p>My code is as follows (which looks OK):</p>

<pre><code>:
ES = EarlyStopping(monitor="val_loss", min_delta=0.001, patience=3, mode="min", verbose=1)
:
self.model.fit_generator(
        generator        = train_batch,
        validation_data  = valid_batch,
        validation_steps = validation_steps,
        steps_per_epoch  = steps_per_epoch,
        epochs           = epochs,
        callbacks        = [ES],
        verbose          = 1,
        workers          = 3,
        max_queue_size   = 8)
</code></pre>

<p>The error message appears to relate to the early stopping callback but the callback looks OK.  Also the error states that the val_loss is not appropriate, but I am not sure why... one more unusual thing about this is that the error only occurs when I use smaller data sets.</p>

<p>Any help is appreciated.</p>
