README.md

---
title: MNIST Digit Recognition
emoji: 🎯
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 6.3.0
app_file: app.py
pinned: false
license: mit
---

# 🎯 MNIST Digit Recognition Demo

Draw a digit (0-9) and watch the AI recognize it with **99.6% accuracy**!

## About This Model

This Space demonstrates a Convolutional Neural Network trained on the MNIST dataset, achieving exceptional performance:

- **Test Accuracy:** 99.60%
- **Model Size:** 271K parameters
- **Architecture:** 4-layer CNN with batch normalization
- **Framework:** PyTorch

## How to Use

1. **Draw a digit** in the canvas on the left
2. **Wait a moment** for the prediction
3. **See the result** with confidence scores for all digits

The model was trained using advanced techniques including:
- Data augmentation (rotation, scaling, random erasing)
- OneCycleLR scheduler with warmup
- Dropout and batch normalization
- Early stopping

## Model Repository

Full training code and model weights: [mnist-cnn-classifier](https://huggingface.co/developerPratik/mnist-cnn-classifier)

## Performance

The model achieves near-perfect accuracy across all digits:
- Most digits: 99-100% accuracy
- Balanced performance (no digit is significantly harder)
- Fast inference (~5ms per image on CPU)

Try it out and see if you can draw digits the model gets wrong! 🎨