---
title: "Logit"
description: "A Logit refers to the raw, unnormalized output values produced by a classification model. These values are
typically transformed through a function like the softmax function to produce probabilities.
The term \"logit\" comes from logistic regression, where it refers to the log-odds of a probability.
In deep learning, logits have a significant role in various loss functions and layers."
canonical_url: "https://promptmetheus.com/resources/llm-knowledge-base/logit"
---

> Index of every page on this site: [llms.txt](https://promptmetheus.com/llms.txt)

A Logit refers to the raw, unnormalized output values produced by a classification model. These values are
typically transformed through a function like the softmax function to produce probabilities.
The term "logit" comes from logistic regression, where it refers to the log-odds of a probability.
In deep learning, logits have a significant role in various loss functions and layers.

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