Update README.md

README.md

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 ---
 license: mit
+base_model: google/efficientnet-b0
+tags:
+- medical
+- mri
+- brain-tumor-detection
+- computer-vision
+- image-classification
+- tensorflow
+- keras
+pipeline_tag: image-classification
+library_name: keras
+---
+
+# 🧠 Brain Tumor MRI Classification Model (Fine-Tuned EfficientNetB0)
+
+This model is a fine-tuned version of **EfficientNetB0** trained to classify Brain Tumor types from MRI images into 4 distinct classes.
+
+## 📋 Model Overview
+
+- **Base Architecture:** EfficientNetB0 (Pre-trained on ImageNet)
+- **Task:** Multi-class Image Classification (4 Classes)
+- **Input Image Size:** 224 x 224 x 3
+- **Framework:** TensorFlow 2.x / Keras
+
+## 🏷️ Target Classes
+
+1. **Glioma Tumor**
+2. **Meningioma Tumor**
+3. **No Tumor**
+4. **Pituitary Tumor**
+
+## ⚙️ Training Details & Hyperparameters
+
+- **Optimizer:** Adam (Learning Rate = `1e-4`)
+- **Loss Function:** Categorical Crossentropy
+- **Batch Size:** 16
+- **Data Augmentation:**
+  - Rotation Range: 15°
+  - Width & Height Shift: 10%
+  - Zoom Range: 15%
+  - Horizontal Flip: True
+- **Fine-Tuning Strategy:** Unfroze top 40 layers of EfficientNetB0 for fine-tuning.
+
+## 📊 Model Architecture Summary
+
+```text
+Input (224, 224, 3) 
+  ↳ EfficientNetB0 Base (Top 40 layers unfrozen)
+  ↳ GlobalAveragePooling2D
+  ↳ BatchNormalization
+  ↳ Dense(256, activation='relu')
+  ↳ Dropout(0.4)
+  ↳ Dense(4, activation='softmax')
 ---