device: cuda
batch_size: 64
optimizer: Adam (
Parameter Group 0
    amsgrad: False
    betas: (0.9, 0.999)
    capturable: False
    differentiable: False
    eps: 1e-08
    foreach: None
    fused: True
    lr: 0.0001
    maximize: False
    weight_decay: 0
)
loss_function: CrossEntropyLoss()
augment_data: True
model: Sequential(
  (0): Conv2d(1, 32, kernel_size=(3, 3), stride=(1, 1), padding=same, bias=False)
  (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (2): ReLU()
  (3): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=same, bias=False)
  (4): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (5): ReLU()
  (6): MaxPool2d(kernel_size=3, stride=3, padding=1, dilation=1, ceil_mode=False)
  (7): Dropout2d(p=0.1, inplace=False)
  (8): Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=same, bias=False)
  (9): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (10): ReLU()
  (11): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=same, bias=False)
  (12): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (13): ReLU()
  (14): MaxPool2d(kernel_size=3, stride=3, padding=1, dilation=1, ceil_mode=False)
  (15): Dropout2d(p=0.1, inplace=False)
  (16): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=same, bias=False)
  (17): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (18): ReLU()
  (19): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=same, bias=False)
  (20): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (21): ReLU()
  (22): MaxPool2d(kernel_size=3, stride=3, padding=1, dilation=1, ceil_mode=False)
  (23): Flatten(start_dim=1, end_dim=-1)
  (24): Dropout(p=0.25, inplace=False)
  (25): Linear(in_features=2048, out_features=1024, bias=True)
  (26): ReLU()
  (27): Linear(in_features=1024, out_features=512, bias=True)
  (28): ReLU()
  (29): Linear(in_features=512, out_features=20, bias=False)
)