Experiment file: train.py
batch_size: 32
dropout_probability: 0.8
eta: 0.0001
filter_size: 19
filter_type: median
initializer: xavier
num_epochs: 50
activation_function: relu
dense_layer_units: 64
drop_probab: 0
input_size: (100, 120, 1)
kernel_initializer: Xavier
kernel_shape: (3, 3)
model: <function wittel at 0x7f8aba543840>
num_kernels: 64
padding: valid
regularization_l2: 0
use_bias: True