From e9532cff6a4f1fd5be147cde1fa4cac94d386a90 Mon Sep 17 00:00:00 2001 From: Michael Pilosov Date: Mon, 15 Jan 2024 03:46:19 +0000 Subject: [PATCH] bigger alpha needed --- main.py | 2 +- out/index.html | 2 +- search.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/main.py b/main.py index 6383278..93f1767 100644 --- a/main.py +++ b/main.py @@ -47,7 +47,7 @@ if __name__ == "__main__": early_stop_callback = EarlyStopping( monitor="hp_metric", # Metric to monitor min_delta=1e-5, # Minimum change in the monitored quantity to qualify as an improvement - patience=12, # Number of epochs with no improvement after which training will be stopped + patience=24, # Number of epochs with no improvement after which training will be stopped mode="min", # Mode can be either 'min' for minimizing the monitored quantity or 'max' for maximizing it. verbose=True, ) diff --git a/out/index.html b/out/index.html index d9ad3af..fbc1891 100644 --- a/out/index.html +++ b/out/index.html @@ -53,7 +53,7 @@
-

Image Gallery

+
diff --git a/search.py b/search.py index 5a3adf6..881a017 100644 --- a/search.py +++ b/search.py @@ -18,7 +18,7 @@ job_plugin = studio.installed_plugins["jobs"] # do a sweep over learning rates # Define the ranges or sets of values for each hyperparameter -alpha_values = list(np.round(np.linspace(0, 4, 41), 4)) +alpha_values = list(np.round(np.linspace(2, 6, 41), 4)) # learning_rate_values = list(np.round(np.logspace(-5, -3, 41), 5)) learning_rate_values = [5e-4] batch_size_values = [64, 128]