Your question is Best Practices for Model Evaluation. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You are reviewing a model before it is approved for use in a real workflow. The team wants a clear way to judge whether the model is good enough and which metrics matter most.
What are the best practices for model evaluation in machine learning?