From e08037fa2700e5c33989f3124a0c6ea06841cdbd Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Thu, 11 Nov 2021 09:51:30 -0600
Subject: [PATCH] adjust learning rate parameters
---
modules/deeplearning/icing_cnn.py | 5 ++---
1 file changed, 2 insertions(+), 3 deletions(-)
diff --git a/modules/deeplearning/icing_cnn.py b/modules/deeplearning/icing_cnn.py
index cd8b8634..e9cbd3a8 100644
--- a/modules/deeplearning/icing_cnn.py
+++ b/modules/deeplearning/icing_cnn.py
@@ -638,11 +638,10 @@ class IcingIntensityNN:
self.loss = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=False) # For multi-class
# decayed_learning_rate = learning_rate * decay_rate ^ (global_step / decay_steps)
- initial_learning_rate = 0.002
+ initial_learning_rate = 0.006
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 = 8 * steps_per_epoch
+ decay_steps = int(steps_per_epoch / 2)
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)
--
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