update README

README.md

@@ -30,3 +30,13 @@ There are two key aspects to note here
 ### ResNetBuilder factory
 - Use ResNetBuilder [build](https://github.com/raghakot/keras-resnet/blob/master/resnet.py#L135-L153) methods to build standard ResNet architectures with your own input shape. It will auto calculate paddings and final pooling layer filters for you.
 - Use the generic [build](https://github.com/raghakot/keras-resnet/blob/master/resnet.py#L99) method to setup your own architecture.
+
+### Cifar10 Example
+
+Includes cifar10 training example. Achieves ~86% accuracy using Resnet18 model.
+
+![cifar10_convergence](images/convergence.png?raw=true "Convergence on cifar10")
+
+Note that ResNet18 as implemented doesn't really seem appropriate for CIFAR-10 as the last two residual stages end up 
+as all 1x1 convolutions from downsampling (stride). This is worse for deeper versions. A smaller, modified ResNet-like 
+architecture achieves ~92% accuracy (see [gist](https://gist.github.com/JefferyRPrice/c1ecc3d67068c8d9b3120475baba1d7e)).