{
  "model_type": "ResidualConvAutoencoder",
  "architecture": "autoencoder",
  "latent_dim": 512,
  "image_size": 128,
  "input_channels": 3,
  "dropout": 0.1,
  "num_epochs_trained": 30,
  "best_epoch": 29,
  "batch_size": 1024,
  "learning_rate": 0.0001,
  "weight_decay": 1e-05,
  "gradient_clip": 1.0,
  "datasets": [
    "CIFAR-10",
    "CIFAR-100",
    "STL-10-train",
    "STL-10-unlabeled"
  ],
  "best_val_loss": 0.00797,
  "training_time_minutes": 21.4,
  "framework": "pytorch",
  "task": "image-reconstruction",
  "separation_ratio": 19.18,
  "description": "Residual Convolutional Autoencoder trained on CIFAR-10, CIFAR-100, and STL-10 for deepfake detection via reconstruction error"
}