In the field of AI, evaluation metrics serve as an essential tool to navigate through the quality and performance of language models. These metrics are very useful in gauging how well a language model (ex: Mistral, GPT-4) aligns with human-like understanding for using these models across diverse tasks. Just as tests in school help assess […]
Benchmarks of Large Language Models Building on the foundational topics introduced in the first article, in this article we will look into these LLM benchmarks in detail. Benchmarks such as MMLU, LLMEval, among others, are designed to test language models on various tasks including multi-task language understanding, text summarization and multi-dialogue capabilities. Through these benchmarks, […]
Welcome to the first article in our three-part series titled “Evaluating Large Language Models”. In this inaugural article, we embark on a journey to explore the evolution and significance of benchmarking intelligence, with a special focus on Large Language Models (LLMs). We delve into the history of intelligence benchmarks and how these metrics have been […]