@hackproduct9: Most people learn about LLM evaluation backwards. They memorize BLEU, ROUGE, F1, BERTScore, and Perplexity without understanding when each metric actually matters. The truth? There is no single “best” metric. 📊 Training a model? → Watch Perplexity 🎯 Classification tasks? → Accuracy & F1 📝 Summarization? → ROUGE 🌍 Translation? → BLEU 🧠 Semantic similarity? → BERTScore 🤖 AI applications? → LLM-as-a-Judge 👨‍⚖️ Production systems? → Human Evaluation still wins One of the biggest mistakes AI engineers make is optimizing for a metric instead of optimizing for the user. A model can score 95% on a benchmark and still deliver a terrible user experience. Metrics are indicators. Users are the truth. Save this cheat sheet for your next AI interview, LLM project, RAG system, or agent evaluation framework. Follow @hackproduct for practical AI engineering breakdowns. #AIEngineering #LLM #MachineLearning #ArtificialIntelligence #GenerativeAI

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Saturday 06 June 2026 01:13:13 GMT