Leaderboards for Evaluating Language Models
Leaderboards test a models' ability to perform across diverse tasks, including factual accuracy, general knowledge, reasoning, and ethical alignment. YouTube Benchmarks explainer - bycloud They incorporate benchmarks like MMLU (Massive Multitask Language Understanding measures general academic and professional knowledge), TruthfulQA (tests the truthfulness of responses), and HellaSwag (testing commonsense reasoning and natural language inference) to test different aspects of model performance. * Stanford Holistic Evaluation of Language Models (HELM) Leaderboard - A reproducible and transparent framework for evaluating foundation models. These leaderboards cover many scenarios, metrics, and models with support for multimodality and model-graded evaluation. * Artificial Analysis provides benchmarking and related information to support people & organizations in choosing the right model for their use-case and which provider to use for that model. * Ch...