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LLMonitor Benchmarks

Oct 09, 2023 - news.bensbites.co
The article discusses a unique experiment that addresses the limitations of traditional Language Learning Models (LLMs) benchmarks. The experiment involves a dynamic dataset that changes weekly and consists of crowdsourced real-world prompts. GPT-4 is used to grade each model's response against a set of rubrics, with the data stored in a Postgres database and displayed on a webpage.

The leaderboard shows the performance of various models, with GPT 4 03/14 (Legacy) ranking first with a score of 93. Other models like GPT 4, GPT 3.5 Turbo Instruct, and GPT 3.5 Turbo follow closely. The scores range from a high of 93 to a low of 7, indicating a wide variation in the performance of different models.

Key takeaways:

  • The leaderboard is an experiment to address the drawbacks of traditional LLMs benchmarks, which quickly become part of training datasets and are hard to relate to real-world use-cases.
  • The dataset used here is dynamic, changes every week, and is composed of crowdsourced real-world prompts.
  • GPT-4 is used to grade each model's response against a set of rubrics, with more details available on the about page.
  • All the data is stored in a Postgres database and the page shows the raw results, with GPT 4 03/14 (Legacy) currently leading the leaderboard.
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