Reinforcement learning (q-learning) evaluation

Question

I am new to reinforcement learning, and currently I am working on a small q-learning project but I am a little confused? 1- what is the testing phase of a q-learning model, and how do we make a prediction (try it on single, unseen data) with it? at this point I have created the needed function for choosing action and getting reward ...etc, and I was able to run a 10000 episodes, but I believe this is the training phase. 2- what are the metrics that we use to say that our model has learned and performed well or not? something like accuracy in classification scheme for example.

Thank you.