Grad_CAM_Siamese/config.yml at main · InTheFuture7/Grad_CAM_Siamese · GitHub

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data_path: 'Data/Flowers'
number_of_iterations: 1
# Model name
backbone_model: 'ResNet50' # MobileNet, ResNet50
pretrained: True
checkpoints_path: 'checkpoints/Flowers'
test_size: 0.1
valid_size: 0.1
# Image processing
image:
    size: [320, 320] # [600, 400] # [320, 320] # [1200, 800]
    normalization:
        mean: [0.485, 0.456, 0.406]
        std: [0.229, 0.224, 0.225]
    Channels: 3
    HorizontalFlip: 0.5 # Probability
    VerticalFlip: 0.5 # Probability
    RandomRotationDegrees: 45 # Degrees
    brightness: 0.0
    contrast: 0.0
    saturation: 0.0
    hue: 0.0
# Training model hyperparameters
hyperparameters:
    epochs: 100
    verbose: True
    batch_size: 4
    num_workers: 0
    optimizer: 'Adam' # Choices: SGD, Adam, AdamW
    learning_rate: 5e-6
    weight_decay: 0.01
    momentum: 0.9
    nesterov: False
    max_norm: 1.0
early_stopping:
    patience: 25
    min_delta: 0.00000001
LRScheduler:
    patience: 15
    min_lr:  0.00000001
    factor: 0.5
    verbose: True
# Other parameters
seed: 42
cuda: True
gpu: 0