Update README.md

README.md

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 ## Model Details 🧠
-- **Architecture**: Fine-tuned **ResNet101**.
-- **Optimizer**: Adam with learning rate scheduling.
-- **Loss Function**: Cross-Entropy Loss.
+- **Architecture**: Architecture:
+The model has a multi-input architecture with two branches:
+Image input branch:
+Input shape: (150, 150, 3)
+Three Conv2D layers with ReLU activation and MaxPooling2D layers
+Flattening layer at the end
+Numerical input branch:
+Input shape: (5,) (for 5 numerical features)
+One Dense layer with 64 units and ReLU activation
+The branches are then combined using concatenation, followed by:
+Dense layer with 128 units and ReLU activation
+Output Dense layer with 1 unit and sigmoid activation
+
+- **Optimizer**: Adam optimizer.
+- **Loss Function**: Binary crossentropy
 
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