---
library_name: pytorch
datasets:
- ylecun/mnist
tags:
- gan
- conditional-gan
- mnist
- pytorch
---

# Conditional MNIST GAN

Label-conditioned generator for 28x28 MNIST digits.

This repository contains **generator weights only**, as required by the assignment. The model uses a 100-dimensional standard-normal latent vector. See `model.py` for the exact architecture and `training-metrics.json` for the complete loss history.

## Training

- Dataset: `ylecun/mnist`
- Epochs: 25
- Batch size: 256
- Seed: 42
- Fixed-sample pixel standard deviation: 0.6101

## Conditional evaluation

- Independent classifier accuracy on real MNIST test data: 98.51%
- Requested-label agreement on 2000 generated samples: 99.55%


Weights are stored in `safetensors` format. The model generates synthetic images and can produce malformed or ambiguous samples; it is intended for coursework and experimentation.