My model which I have trained on a set of 29K images for 36 classes and validated on 7K images. The model has a training accuracy of 94.59% and validation accuracy of 95.72% It has been created for OCR on digits and characters. I know the amount of images for training on 36 classes might not be sufficient. I'm not certain what to infer from these results.

Question: Is this a good result? Should the testing accuracy always be greater than training accuracy? Is my model overfitting?

Question: How would I know if my model was overfitting? I'm assuming a very high training accuracy and very low testing accuracy would indicate that?

1. 95% is rather good for 36 classes. If your validation accuracy is higher than training accuracy, you are underfitting. You can run some more epochs, until your training accuracy is a bit higher than validation accuracy.
2. Exactly, if training accuracy is much higher, you are overfitting.