I use "LIBSVM" library for classification.
If my first class is the same as the second class, for accuracy I will get 50% or 0%.
What does it mean to get 30% or 20% of precision?
A SVM is a binary classifier. That means, you can distinguish only 2 classes.
If both classes are the same, classification doesn't make sense.
If you have more then 2 classes you need to use different classification methods, such as k-means or neural networks. However, multi-class classification with SVM can still be done by reducing the multi-class decision problem to multiple binary classifications.