The Science of LLM Benchmarks: Methods, Metrics, and Meanings πŸš€

The Science of LLM Benchmarks: Methods, Metrics, and Meanings πŸš€

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https://www.linkedin.com/events/7144928717054672896/

Register here: https://www.linkedin.com/events/7144928717054672896/

Date & Time:Β January 9th, 2024 | 8.30 AM PST | 5.30 PM CET

The upcoming LLMOps.space event is about "The Science of LLM Benchmarks: Methods, Metrics, and Meanings". πŸš€

In this session, Jonathan from Shujin AI will talk about LLM benchmarks and their performance evaluation metrics. He will address intriguing questions such as whether Gemini truly outperformed GPT4-v. Learn how to review benchmarks effectively and understand popular benchmarks like ARC, HellSwag, MMLU, and more.

Topics that will be covered:

🧠 Did Gemini really beat GPT4-v?

The performance showdown between Gemini and GPT 4, based on objective and detailed benchmark results.

πŸ” What exactly are ARC, HellSwag, MMLU, etc.?

Gain insights into some of the most popular benchmarks in the LLM arena, such as ARC, HellSwag, and MMLU.

πŸ’ͺ How to review benchmarks and what to look out for?

Jonathan will guide you through a step-by-step process to assess these benchmarks critically, helping you understand the strengths and limitations of different models.