---
title: "Why You Should Not Use Numeric Evals For LLM As a Judge"
url: https://daily.dev/posts/why-you-should-not-use-numeric-evals-for-llm-as-a-judge-wggkjaplr
source_url: https://towardsdatascience.com/why-you-should-not-use-numeric-evals-for-llm-as-a-judge-bf22424f5379
type: article
source: "Towards Data Science"
published: 2024-03-08T16:15:23.965Z
updated: 2024-05-09T09:28:05.588Z
tags: ["nlp", "llm", "text-generation", "llmops"]
reading_time: 7
upvotes: 0
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Why You Should Not Use Numeric Evals For LLM As a Judge

**[Towards Data Science](https://daily.dev/sources/tds)** · 7 min read · 0 upvotes · 0 comments

## Summary

Using LLMs to conduct numeric evaluations is finicky and unreliable. Small changes in prompt templates and switching between models can lead to vastly different results. LLMs are often inconsistent in their responses, making it hard to rely on them as reliable arbiters of numeric evaluation criteria.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdatascience.com/why-you-should-not-use-numeric-evals-for-llm-as-a-judge-bf22424f5379>

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---

Tags: [#nlp](https://daily.dev/tags/nlp), [#llm](https://daily.dev/tags/llm), [#text-generation](https://daily.dev/tags/text-generation), [#llmops](https://daily.dev/tags/llmops)

[View this post on daily.dev](https://daily.dev/posts/why-you-should-not-use-numeric-evals-for-llm-as-a-judge-wggkjaplr)