{
    "config": {
        "method": "random",
        "metric": {
            "goal": "minimize",
            "name": "extraction score"
        },
        "parameters": {
            "data_per_class_train": {
                "value": 250
            },
            "extraction_data_amount_per_class": {
                "value": 500
            },
            "extraction_epochs": {
                "value": 50000
            },
            "extraction_evaluate_rate": {
                "value": 1000
            },
            "extraction_init_scale": {
                "distribution": "log_uniform_values",
                "max": 0.1,
                "min": "1e-06"
            },
            "extraction_lr": {
                "distribution": "log_uniform_values",
                "max": 1,
                "min": "1e-05"
            },
            "extraction_min_lambda": {
                "distribution": "uniform",
                "max": 0.5,
                "min": 0.01
            },
            "extraction_model_relu_alpha": {
                "distribution": "uniform",
                "max": 500,
                "min": 10
            },
            "model_hidden_list": {
                "value": "[1000,1000]"
            },
            "model_init_list": {
                "value": "[0.001,0.001]"
            },
            "pretrained_model_path": {
                "value": "weights-cifar10_vehicles_animals_d250_cifar10_vehicles_animals.pth"
            },
            "problem": {
                "value": "cifar10_vehicles_animals"
            },
            "run_mode": {
                "value": "reconstruct"
            },
            "wandb_active": {
                "value": true
            }
        },
        "program": "Main.py"
    },
    "full_name": "cifar10_vehicles_animals_3s9e7mys",
    "id": "3s9e7mys",
    "pretrained_model_path": "weights-cifar10_vehicles_animals_d250_cifar10_vehicles_animals.pth",
    "problem": "cifar10_vehicles_animals"
}