Experiment file: train_both.py
batch_size: 32
dropout_probability: 0.5
eta: 0.0001
filter_size: 1
filter_type: median
initializer: Xavier
memory_size: 10
num_epochs: 75
activation_function: relu
dense_layer_units: 64
drop_probab: 0.5
input_size: (350, 350, 10)
kernel_initializer: Xavier
kernel_shape: (3, 3)
model: <function wittel at 0x7ff524b4e2f0>
num_kernels: 64
output_shape: 2
padding: same
regularization_l2: 0.0
use_bias: True
training_time: 1754.4534485340118
test_error_pitch_power: -36.30038216183645
test_error_power: -23.223233207919574
test_error_yaw_power: -23.442507129364294
val_error_pitch_power: -37.57347033800852
val_error_power: -21.984248946566467
val_error_yaw_power: -22.105847359555355
train_error_pitch_power: -31.602607738464286
train_error_power: -18.452034893088676
train_error_yaw_power: -18.6675400810823