Classical Metrics BLEU, ROUGE-L, F1, exact-match, accuracy. Five metrics that still account for most published LLM eval numbers. Implement each from first principles so you know what the number means.
Prerequisites: Phase 19 Track B foundations, lesson 70
# Learning objectives
Implement token-level exact-match, F1, and accuracy with explicit tokenisation rules.
Implement BLEU-4 from the ground up: modified n-gram precision, geometric mean over n equals 1 through 4, brevity penalty.
Implement ROUGE-L using longest common subsequence, with F-beta combination of precision and recall.
Dispatch on the metric_name field from lesson 70 so the runner stays metric-agnostic.
Pin the behaviour with reference vectors drawn from worked examples, not from a third-party library.
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The text and code of this lesson are based on AI Engineering from Scratch by Rohit Ghumare, MIT licensed.