config.txt

[DATA]
# training and validation are pointers to the files used for learning
training=./DATA/train_small.csv
validation=./DATA/validate_small.csv

[MODEL]
# layers is a comma-separated list of integers telling us how many nodes in each
# hidden layer. Special case: If the value is only one element in the list, and
# its value is 0, you should generate a net without a hidden layer
layers = 24, 24

# activations is a comma-separated list of key-words. It will have as many
# elements as there are elements in the layers-list. Each keyword is a
# non-linearity function, and legal values are relu, linear, and tanh.
activations = relu, relu

# loss_type chooses between L2 loss (for regression) and
# cross_entropy (for classification).
loss_type = cross_entropy

[HYPER]
# Learning rate to use
learning_rate=5.e-4

# Number of epochs before finalizing
no_epochs=500

# What L2-regularization to use to avoid overfitting.
L2_regularization=0