model_config.json

{
  "model_type": "phone_detection_cnn",
  "architecture": "MobileNetV2_with_custom_head",
  "input_shape": [
    224,
    224,
    3
  ],
  "num_classes": 1,
  "task": "binary_classification",
  "classes": {
    "0": "negative",
    "1": "positive"
  },
  "training_parameters": {
    "batch_size": 32,
    "learning_rate": 0.001,
    "optimizer": "Adam",
    "loss_function": "binary_crossentropy",
    "metrics": [
      "accuracy"
    ],
    "epochs": 50
  },
  "data_augmentation": {
    "rotation_range": 20,
    "width_shift_range": 0.2,
    "height_shift_range": 0.2,
    "horizontal_flip": true,
    "zoom_range": 0.2,
    "shear_range": 0.2,
    "fill_mode": "nearest"
  },
  "model_layers": {
    "base_model": "MobileNetV2",
    "base_model_trainable": false,
    "custom_layers": [
      "GlobalAveragePooling2D",
      "Dense_128_relu",
      "Dropout_0.3",
      "Dense_64_relu",
      "Dropout_0.2",
      "Dense_1_sigmoid"
    ]
  },
  "performance": {
    "validation_accuracy": 0.8079096078872681,
    "validation_loss": 0.4199891686439514
  },
  "dataset_info": {
    "total_images": 888,
    "training_samples": 711,
    "validation_samples": 177,
    "class_distribution": {
      "positive": 540,
      "negative": 348
    }
  }
}