Update README.md

README.md

@@ -26,19 +26,46 @@ It achieves the following results on the evaluation set:
 - Model Preparation Time: 0.0034
 - Accuracy: 0.9998
 
-## Model description
+# 🍎 Fruits vs. Junkfood Classifier – Vision Transformer (gutkia01)
 
-More information needed
+This model is a fine-tuned version of [`google/vit-base-patch16-224`](https://huggingface.co/google/vit-base-patch16-224), trained on a custom binary dataset to distinguish between **healthy fruits** and **unhealthy fast food**.
 
-## Intended uses & limitations
+## 🧠 Model Description
 
-More information needed
+- **Architecture:** Vision Transformer (ViT)
+- **Base model:** `google/vit-base-patch16-224`
+- **Task:** Binary image classification: `Fruit` vs. `Junkfood`
+- **Framework:** Hugging Face Transformers Trainer
+- **Input format:** RGB images, 224×224, loaded via `imagefolder`
 
-## Training and evaluation data
+## ✅ Intended Use & Limitations
 
-More information needed
+### Appropriate Use Cases
 
-## Training procedure
+- Food classification in nutrition, health, or educational applications
+- Interactive demos comparing healthy vs. unhealthy food
+- Computer vision use cases with simple binary class structures
+
+### Limitations
+
+- Only supports binary classification (no subclass differentiation)
+- Cannot recognize new or abstract dishes (e.g. salad, sushi)
+- Cannot evaluate ingredients, calories, or portion sizes
+
+## 📊 Training and Evaluation Data
+
+The model was trained on a binary dataset composed of:
+
+- **Fruits360 Dataset**: 137,000+ structured fruit images in a controlled studio setup ([Kaggle link](https://www.kaggle.com/datasets/moltean/fruits))
+- **Fast Food Classification Dataset v2**: 20,000 fast food images, 10 categories (e.g., burger, pizza, fries) ([Kaggle link](https://www.kaggle.com/datasets/utkarshsaxenadn/fast-food-classification-dataset))
+- 
+
+### Dataset Composition
+
+The dataset is a combination of:
+
+- **Fruits360 Dataset** ([Kaggle](https://www.kaggle.com/datasets/moltean/fruits))  
+- **Fast Food Classification Dataset v2** ([Kaggle](https://www.kaggle.com/datasets/utkarshsaxenadn/fast-food-classification-dataset))
 
 ### Training hyperparameters
 
@@ -53,7 +80,19 @@ The following hyperparameters were used during training:
 
 ### Training results
 
+### Training results
 
+| Epoch | Training Loss | Validation Loss | Accuracy |
+|-------|---------------|------------------|----------|
+| 1     | 0.0000        | 0.0215           | 0.9975   |
+| 2     | 0.0000        | 0.00004          | 1.0000   |
+| 3     | 0.0000        | 0.00008          | 1.0000   |
+| 4     | 0.0000        | 0.00011          | 1.0000   |
+| 5     | 0.0000        | 0.00011          | 1.0000   |
+| 6     | 0.0000        | 0.00008          | 1.0000   |
+
+Final training loss: **0.00047**  
+Evaluation accuracy: **0.9998**
 
 ### Framework versions