train_config.json

{
    "name": "ResNet152-AutoAugment",
    "n_gpu": 1,

    "arch": {
        "type": "ResNet152",
        "args": {
            "use_pretrained": true,
            "num_classes": 196
        }
    },
    "data_processing": {
        "type": "CarsDataLoader",
        "args":{
            "mode": "train",
            "data_dir": "data_processing/datasets/training/extracted/",
            "metas": "data_processing/datasets/cars_metas/cars_train_annos.mat",
            "resize_width": 299,
            "resize_height": 299,
            "batch_size": 16,
            "shuffle": true,
            "validation_split": 0.15,
            "num_workers": 1,
            "limit": null
        }
    },
    "optimizer": {
        "type": "SGD",
        "args":{
            "lr": 0.1,
            "momentum": 0.9,
            "weight_decay": 0.005,
            "nesterov": true
        }
    },
    "loss": "cross_entropy_loss",
    "metrics": [
        "accuracy", "top_k_accuracy"
    ],
    "lr_scheduler": {
        "type": "CyclicLR",
        "args": {
            "base_lr": 1e-6,
            "max_lr": 1e-5
        }
    },
    "trainer": {
        "epochs": 300,

        "save_dir": "saved/",
        "save_period": 1,
        "verbosity": 2,
        
        "monitor": "max val_accuracy",
        "early_stop": 40,
        
        "tensorboardX": true
    }
}