Junior interview questionAsked at ByteDance · interview write-up
You're evaluating three agents with different error costs. How do you decide whether precision, recall or F1 is the right metric for each?
Model answer
Ask which mistake costs more. Precision when a false alarm is expensive, like an agent that issues refunds or bans accounts. Recall when a miss is expensive, like a safety agent that must catch harmful content. F1 when both matter and positives are rare, so accuracy misleads. With known costs, weight errors directly.
Practise the rest
11 Benchmarking questions, 492 in all, each with a model answer. Free.
More from ByteDance interview questions.
More Benchmarking interview questions
- What does a fair inference benchmark hold fixed?
- An upgrade makes your 960-token prefill 5% faster in one before-and-after run. Do you ship it?
- A vendor says their GPU is twice as fast as your CPU. How would you judge what it buys your workload?
- A provider's status page shows a p50 TTFT of 180 ms. You need 300 ms for 9 in 10 of your users. What do you do before signing up?
- In the capstone, continuous batching with at most 8 seats gives a p90 first token of 122 ms against a 300 ms target, yet the planner marks it failing. Why, how do you fix it, and what would you measure first on the real system?
- What does perplexity measure, how do tokenizers distort it, and where does it break down as a quality metric?