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obeshor/best_param.py

Created February 19, 2021 22:53
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best_param.py
# Get the optimal hyperparameters
best_hps = tuner.get_best_hyperparameters(num_trials = 1)[0]
print(f"""
The hyperparameter search is complete.\n The optimal filter in second Convolutional layer is {best_hps.get('num_filters')}.\n The optimal number of units in the first densely-connected
layer is {best_hps.get('units')}.\n The optimal rate of dropout is {best_hps.get('dropout_1')} And the optimal learning rate for the optimizer is {best_hps.get('learning_rate')}.
""")
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