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Normalize model config image_augmentations to structured dictionaries
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{
"model": "ResNet-50 (RadImageNet)",
"loss_function": "CE",
"must_include": true,
"learning_rate": 1e-05,
"batch_size": 16,
"weight_decay": 0.0001,
"optimizer": "AdamW",
"scheduler": "CosineAnnealing",
"image_augmentations": {
"rotation": 15,
"horizontal_flip": true,
"random_crop": true,
"color_jitter": true,
"brightness": 0.2,
"contrast": 0.2,
"imagenet_norm": true
},
"dropout": 0.2,
"loss_specific_params": "class_weights=inverse_frequency",
"multi_target_strategy": "Shared backbone + task-specific heads",
"single_target_strategy": null,
"pretrained_weights": "RadImageNet",
"fine_tuning_strategy": "Full fine-tuning",
"expected_gpu_memory": "6-8GB",
"architectural_family": "Medical CNN",
"class_weighting": "inverse_frequency",
"sampling_strategy": "balanced_batch",
"threshold_selection": "F1_optimal",
"experiment_name": "ResNet-50_RadImageNet_lr1e-05_bs16"
}