normalize weights for default training as well

toolkit.py

@@ -828,7 +828,7 @@ class ClassificationProject(object):
                                validation_split = self.validation_split,
                                # we have to multiply by class weight since keras ignores class weight if sample weight is given
                                # see https://github.com/keras-team/keras/issues/497
-                               sample_weight=self.w_train*np.array(self.class_weight)[self.y_train.astype(int)],
+                               sample_weight=self.w_train*np.array(self.class_weight)[self.y_train.astype(int)]/self.mean_train_weight,
                                shuffle=True,
                                batch_size=self.batch_size,
                                callbacks=self.callbacks_list)