snapshot...

modules/deeplearning/icing.py

@@ -381,7 +381,7 @@ class IcingIntensityNN:
         decay_rate = 0.95
         steps_per_epoch = int(self.num_data_samples/BATCH_SIZE)  # one epoch
         # decay_steps = int(steps_per_epoch / 2)
-        decay_steps = 2 * steps_per_epoch
+        decay_steps = 4 * steps_per_epoch
         print('initial rate, decay rate, steps/epoch, decay steps: ', initial_learning_rate, decay_rate, steps_per_epoch, decay_steps)
 
         self.learningRateSchedule = tf.keras.optimizers.schedules.ExponentialDecay(initial_learning_rate, decay_steps, decay_rate)