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README.md

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+# CNN with CIFAR-10
+
+A PyTorch implementation of a Convolutional Neural Network (CNN) for image classification on the CIFAR-10 dataset, achieving **81.45% test accuracy**.
+
+## Architecture
+
+![CNN Architecture](benchmarks/architecture.png)
+
+The CNN model consists of
+### Convolutional Layers:
+- **Conv1**: 3 → 32 channels, 3x3 kernel, padding=1
+- **Conv2**: 32 → 64 channels, 3x3 kernel, padding=1  
+- **Conv3**: 64 → 128 channels, 3x3 kernel, padding=1
+
+### Others
+- **Batch Normalization** after each convolutional layer
+- **MaxPooling2D** (2x2) for downsampling
+- **ReLU** activation functions
+- **Fully Connected Layers**: 2048 → 512 → 10
+- **Dropout** (50%) for regularization
+
+
+## Getting Started
+
+### Prerequisites
+- Python 3.12+
+- PyTorch 2.7.1+
+- torchvision 0.22.1+
+
+> [!TIP]
+> This project was developed with `uv`, so it is best to use `uv` for project management.
+
+### Installation
+
+1. **Clone the repository:**
+   ```bash
+   git clone https://github.com/rahuletto/cnn
+   cd CNN
+   ```
+
+2. **Create virtual environment:**
+   ```bash
+   python -m venv .venv
+   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
+   ```
+
+3. **Install dependencies:**
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+
+## Training Configuration
+
+- **Optimizer**: Adam (lr=0.001)
+- **Batch Size**: 64
+- **Epochs**: 50
+
+> Best model checkpoint was saved at epoch 49 with validation loss of 0.6553.
+
+
+## Performance
+
+![Training Loss](benchmarks/loss.png)
+Reaching 0.7227 in Train loss and 0.6557 in Validation loss at epoch 50
+
+
+### Accuracy:
+
+Total Accuracy: `81.45%`
+- **Airplane**: `84.60%`
+- **Automobile**: `93.20%`
+- **Bird**: `76.90%`
+- **Cat**: `69.70%`
+- **Deer**: `77.20%`
+- **Dog**: `64.00%`
+- **Frog**: `89.30%`
+- **Horse**: `82.10%`
+- **Ship**: `89.60%`
+- **Truck**: `87.90%`
+
+![Accuracy Benchmark](benchmarks/accuracy.png)
+
+---
+
+## References
+
+- [CIFAR-10 Dataset](https://www.cs.toronto.edu/~kriz/cifar.html)
+- [PyTorch Documentation](https://pytorch.org/docs/)
+- [Convolutional Neural Networks for Visual Recognition (CS231n)](http://cs231n.stanford.edu/)
+- [Deep Learning Book - Ian Goodfellow](https://www.deeplearningbook.org/)
+
+## License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.