config.json

{
  "model_type": "deep-svdd",
  "task": "anomaly-detection",
  "architecture": "resnet-encoder",
  "latent_dim": 512,
  "image_size": 128,
  "input_channels": 3,
  "training_datasets": [
    "cifar10",
    "cifar100",
    "stl10"
  ],
  "normalization": {
    "mean": [
      0.485,
      0.456,
      0.406
    ],
    "std": [
      0.229,
      0.224,
      0.225
    ]
  },
  "thresholds": {
    "optimal_f1": 0.001618,
    "95th_percentile": 0.008500736206769943,
    "99th_percentile": 0.015921616926789284,
    "recommended": 0.001618
  },
  "performance": {
    "threshold": 0.001618,
    "accuracy": 0.87,
    "precision": 0.8033,
    "recall": 0.98,
    "f1": 0.8829
  },
  "framework": "pytorch",
  "pytorch_version": "2.9.1+cu128",
  "license": "apache-2.0"
}