From 645337abfe8f6c8e8e4be945383d8dab97b10bf8 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 7 Dec 2022 13:00:19 -0600
Subject: [PATCH] snapshot..
---
modules/deeplearning/icing_fcn.py | 8 ++++----
1 file changed, 4 insertions(+), 4 deletions(-)
diff --git a/modules/deeplearning/icing_fcn.py b/modules/deeplearning/icing_fcn.py
index 21204c88..00900f84 100644
--- a/modules/deeplearning/icing_fcn.py
+++ b/modules/deeplearning/icing_fcn.py
@@ -20,8 +20,8 @@ if NumClasses == 2:
else:
NumLogits = NumClasses
-BATCH_SIZE = 64
-NUM_EPOCHS = 80
+BATCH_SIZE = 128
+NUM_EPOCHS = 60
TRACK_MOVING_AVERAGE = False
EARLY_STOP = True
@@ -583,7 +583,7 @@ class IcingIntensityFCN:
self.get_evaluate_dataset(idxs)
- def build_cnn(self, do_drop_out=False, do_batch_norm=True, drop_rate=0.5):
+ def build_cnn(self, do_drop_out=True, do_batch_norm=True, drop_rate=0.5):
print('build_cnn')
# padding = "VALID"
padding = "SAME"
@@ -731,7 +731,7 @@ class IcingIntensityFCN:
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 = 0.0006
+ initial_learning_rate = 0.0005
decay_rate = 0.95
steps_per_epoch = int(self.num_data_samples/BATCH_SIZE) # one epoch
decay_steps = int(steps_per_epoch)
--
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