config.json

{
  "model_type": "vgg16-transfer-learning",
  "architecture": "VGG16 + GlobalAveragePooling2D + BatchNorm + Dense(512,256)",
  "framework": "tensorflow",
  "library_name": "keras",
  "input_shape": [224, 224, 3],
  "num_classes": 5,
  "class_labels": ["angry", "normal", "rested", "sad", "surprised"],
  "preprocessing": {
    "resize": [224, 224],
    "rescale": 0.00392156862,
    "color_mode": "rgb"
  },
  "training": {
    "base_model": "VGG16",
    "base_weights": "imagenet",
    "unfrozen_layers": 8,
    "optimizer": "adam",
    "loss": "categorical_crossentropy",
    "phase1_lr": 1e-4,
    "phase2_lr": 1e-5,
    "batch_size": 32,
    "class_weights": true
  },
  "head": {
    "layers": [
      "GlobalAveragePooling2D",
      "BatchNormalization",
      "Dense(512, relu)",
      "Dropout(0.5)",
      "BatchNormalization",
      "Dense(256, relu)",
      "Dropout(0.3)",
      "Dense(5, softmax)"
    ]
  },
  "performance": {
    "v1_accuracy": 0.8118,
    "v2_accuracy": 0.8219,
    "improvement": 0.0101
  },
  "dataset": {
    "train_samples": 11513,
    "val_samples": 2880,
    "source": "https://www.kaggle.com/datasets/bilalmahmoud/cats-data-set"
  }
}