---
title: "Discussion on \"Layer Normalization - Benefits over Batch Norm & How to Tune Its Hyperparameters\" | Hashnode"
description: "Discussion on \"Layer Normalization - Benefits over Batch Norm & How to Tune Its Hyperparameters\". Why do we need layer normalization?\nLayer normalization is crucial in deep learning for several key reasons:\n\nAddressing Internal Covariate Shift: Stabilizes input distributions to each layer as previous layer parameters update during training\nFaster..."
url: "https://hashnode.com/posts/layer-normalization-benefits-over-batch-norm-and-how-to-tune-its-hyperparameters/6879e030b04e845dcd8bb1fe"
---

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# [Layer Normalization - Benefits over Batch Norm & How to Tune Its Hyperparameters](https://huanganni.hashnode.dev/layer-normalization-benefits-over-batch-norm-and-how-to-tune-its-hyperparameters?utm_source=hashnode&utm_medium=feed)

Why do we need layer normalization? Layer normalization is crucial in deep learning for several key reasons: Addressing Internal Covariate Shift: Stabilizes input distributions to each layer as previous layer parameters update during training Faster...

Jul 18, 2025 · 8 min read · huanganni.hashnode.dev  
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-   [#layer-norm](https://hashnode.com/tag/layer-norm)
-   [#batch-normalization](https://hashnode.com/tag/batch-normalization)
-   [#transformers](https://hashnode.com/tag/transformers)
-   [#hyperparameter-tunning](https://hashnode.com/tag/hyperparameter-tunning)

## Written by

[Anni Huang](https://hashnode.com/@HuangAnni)

@HuangAnni · Singapore

  
[View profile](https://hashnode.com/@HuangAnni)

LLM Training Operation Specialist @ ByteDance | Ex-Master of IT in Business (AI track) at SMU

I’m Anni Huang, an AI researcher-in-training currently at ByteDance, specializing in LLM training operations with a coding focus. I bridge the gap between engineering execution and model performance, ensuring the quality, reliability, and timely delivery of large-scale training projects.

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