config.json

{
  "model_name": "ELIAS-epiblepharon",
  "model_type": "resnet18",
  "architecture": "ResNet-18 (frozen ImageNet backbone + task-specific head)",
  "task": "binary-image-classification",
  "disease": "epiblepharon",
  "num_classes": 2,
  "id2label": {
    "0": "control",
    "1": "epiblepharon"
  },
  "label2id": {
    "control": 0,
    "epiblepharon": 1
  },
  "image_size": 224,
  "input_channels": 3,
  "preprocessing": {
    "resize": [224, 224],
    "grayscale_to_3ch": true,
    "normalize_mean": [0.485, 0.456, 0.406],
    "normalize_std": [0.229, 0.224, 0.225]
  },
  "training": {
    "backbone_frozen": true,
    "optimizer": "Adam",
    "learning_rate": 0.001,
    "epochs": 20,
    "batch_size": 32,
    "loss": "CrossEntropyLoss",
    "validation": "StratifiedKFold(n_splits=5, random_state=42)"
  },
  "performance": {
    "auc": 0.93,
    "validation_strategy": "5-fold cross-validation",
    "note": "No fold collapse observed"
  },
  "deployment": {
    "ios_coreml": true,
    "inference_latency_ms": "<1000",
    "device": "iPhone 12+ (A14+ Neural Engine)",
    "model_size_mb": "<50"
  },
  "framework": "pytorch",
  "torch_version": ">=2.0.0"
}