this post was submitted on 12 Nov 2023
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LocalLLaMA

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Community to discuss about Llama, the family of large language models created by Meta AI.

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Vectara's Hallucination Evaluation Model and leaderboard was launched last week. I notice Mistral having a hallucination rate of 9.4% compared to 5.6% for Llama2. Any thoughts?

https://preview.redd.it/sj0akn15tszb1.png?width=1118&format=png&auto=webp&s=ca9ec766f592a8748bf95a8ad2ef81483c2270bd

Source: https://github.com/vectara/hallucination-leaderboard

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[โ€“] FullOf_Bad_Ideas@alien.top 1 points 10 months ago (1 children)

I don't think they actually tested base models. Look at the description of their methods - they don't run the models themselves, they only use public apis They say they used mistral-instruct, not Mistral. Those are not the same models, you shouldn't put "Mistral" in the table if you ran tests on "Mistral-Instruct". There is no information what actual model was used for llama test, or the output of the test. I suspect that they used llama-2-chat models which were RHLFed. Mistral Instruct is not RHLFed. It's likely that RHLF can reduce hallucination rate and we are seeing it's effects.

[โ€“] aaronr_90@alien.top 1 points 10 months ago

Noob question: What is the recommended method to interact with a non finetuned/chat model?