Ensemble Model for Image Classification on CIFAR-10

This repository implements image classification on the CIFAR-10 dataset using an ensemble of ResNet18 models. The model is built with PyTorch and leverages timm for efficient training.

🛠️ Setup & Requirements

The following dependencies were used:

• Python 3.9
• PyTorch 1.10.1 + CUDA 11.3
• Torchvision 0.11.2 + CUDA 11.3
• timm 0.9.2

To install the required packages, run:

pip install -r requirements.txt

📊 Performance

The ensemble model achieved a testing accuracy of 97.26% on the CIFAR-10 dataset.

🚀 Training the Model

To train the model, run:

python train.py

🎯 Testing the Model

To evaluate the model on test data, run:

python test.py

📂 Project Structure

ResNet-Ensemble-Model-CIFAR10/
│── train.py          # Training script
│── test.py           # Testing script
│── README.md         # Project documentation

📬 Contact

For any questions or contributions, feel free to open an issue or reach out.

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