{
    "architecture": {
        "base_model": "MobileNetV2",
        "input_shape": [
            224,
            224,
            3
        ]
    },
    "custom_layers": [
        {
            "type": "GlobalAveragePooling2D"
        },
        {
            "type": "Dense",
            "units": 128,
            "activation": "relu"
        },
        {
            "type": "Dropout",
            "rate": 0.5
        },
        {
            "type": "Dense",
            "units": 1,
            "activation": "sigmoid"
        }
    ],
    "training": {
        "optimizer": "Adam",
        "learning_rate": 0.001,
        "loss": "binary_crossentropy",
        "metrics": [
            "accuracy"
        ]
    },
    "fine_tuning": {
        "unfreeze_from_layer": 100,
        "fine_tune_learning_rate": 0.0001
    }
}