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authorDavid Doan <daviddoan@davids-mbp-3.devices.brown.edu>2022-05-09 00:25:39 -0400
committerDavid Doan <daviddoan@davids-mbp-3.devices.brown.edu>2022-05-09 00:25:39 -0400
commita0870ac3f1f84278c5b9fe7f78f6b1af1d1f33e9 (patch)
tree440f9c17f23042e32c7c495c49d36bb838fcd73a /hyperparameters.py
parent18f1f7bddcb63502120581f3fa24b980559ffa9f (diff)
clean and refactor code for submission
Diffstat (limited to 'hyperparameters.py')
-rw-r--r--hyperparameters.py12
1 files changed, 7 insertions, 5 deletions
diff --git a/hyperparameters.py b/hyperparameters.py
index ac2beda8..180eaf85 100644
--- a/hyperparameters.py
+++ b/hyperparameters.py
@@ -9,19 +9,21 @@ Number of epochs. If you experiment with more complex networks you
might need to increase this. Likewise if you add regularization that
slows training.
"""
-num_epochs = 200
+num_epochs = 500
"""
A critical parameter that can dramatically affect whether training
succeeds or fails. The value for this depends significantly on which
optimizer is used. Refer to the default learning rate parameter
"""
-learning_rate = 1e2
+learning_rate = .002
+
+beta_1 = .99
+
+epsilon = 1e-1
momentum = 0.01
alpha = .05
-beta = 5
-# alpha = 1e-5
-# beta = 1e-2
+beta = 5