# EfficientNet-B0 Fruit & Vegetable Classifier 🍎🥕🌽

This model classifies images of fruits and vegetables into multiple categories.  
It is trained on the [Fruit and Vegetable Image Recognition dataset](https://www.kaggle.com/datasets/kritikseth/fruit-and-vegetable-image-recognition).

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## 📊 Dataset Statistics
- Training Images: {len(train_dataset)}
- Validation Images: {len(val_dataset)}
- Test Images: {len(test_dataset)}
- Classes: {len(class_names)} → {class_names}

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## 🏆 Results
- Final Training Accuracy: {train_acc:.2f}%
- Final Validation Accuracy: {val_acc:.2f}%
- Final Test Accuracy: {test_acc:.2f}%

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## 🚀 Usage
```python
import torch
from torchvision import models

# Load model
model = models.efficientnet_b0(pretrained=False)
num_features = model.classifier[1].in_features
model.classifier = torch.nn.Sequential(
    torch.nn.Dropout(0.3),
    torch.nn.Linear(num_features, {len(class_names)})
)

# Load weights
model.load_state_dict(torch.load("pytorch_model.bin", map_location="cpu"))
model.eval()