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Diffstat (limited to 'hyperparameters.py')
| -rw-r--r-- | hyperparameters.py | 36 |
1 files changed, 1 insertions, 35 deletions
diff --git a/hyperparameters.py b/hyperparameters.py index 487023f3..f59b9747 100644 --- a/hyperparameters.py +++ b/hyperparameters.py @@ -9,7 +9,7 @@ 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 = 50 +num_epochs = 100 """ A critical parameter that can dramatically affect whether training @@ -18,38 +18,4 @@ optimizer is used. Refer to the default learning rate parameter """ learning_rate = 1e-4 -""" -Momentum on the gradient (if you use a momentum-based optimizer) -""" momentum = 0.01 - -""" -Resize image size for task 1. Task 3 must have an image size of 224, -so that is hard-coded elsewhere. -""" -img_size = 224 - -""" -Sample size for calculating the mean and standard deviation of the -training data. This many images will be randomly seleted to be read -into memory temporarily. -""" -preprocess_sample_size = 400 - -""" -Maximum number of weight files to save to checkpoint directory. If -set to a number <= 0, then all weight files of every epoch will be -saved. Otherwise, only the weights with highest accuracy will be saved. -""" -max_num_weights = 5 - -""" -Defines the number of training examples per batch. -You don't need to modify this. -""" -batch_size = 10 - -""" -The number of image scene classes. Don't change this. -""" -num_classes = 15 |