Does high accuracy metrics with small (but equally sampled) dataset means a good model?
You can do a crossvalidation to be sure your testing set is not just very easy to classify. 

If it is possible, you could try to augment the size of your training set by doing some rotation, shift, flip ... If you are using Keras, you can read this blog.