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What is hp-tuning?

ddutta/hp-tuning — explained in plain English

Analysis updated 2026-07-18 · repo last pushed 2018-04-10

JavaScriptAudience · researcherComplexity · 4/5DormantSetup · hard

In one sentence

Katib automatically tests different machine learning model settings in parallel on Kubernetes to find the combination that gives the best results.

Mindmap

mindmap
  root((repo))
    What it does
      Auto tune ML settings
      Parallel training runs
      Picks best combo
    Tech stack
      Kubernetes
      TensorFlow
      PyTorch
      MXNet
    Use cases
      Tune learning rate
      Fine tune translation model
      Visualize trial results
    Audience
      Data scientists
      ML engineers
      Kubernetes teams

Code map

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What do people build with it?

USE CASE 1

Automatically search for the best learning rate and batch size instead of tuning by hand.

USE CASE 2

Run dozens of training variations in parallel to fine-tune a neural machine translation model.

USE CASE 3

Visualize which parameter combination performed best using the built-in web interface and TensorBoard.

USE CASE 4

Tune models across teams already running ML workloads on a Kubernetes cluster.

What is it built with?

JavaScriptKubernetesTensorFlowPyTorch

How does it compare?

ddutta/hp-tuning3rd-eden/ircb.ioa15n/a15n
LanguageJavaScriptJavaScriptJavaScript
Last pushed2018-04-102016-11-162019-04-07
MaintenanceDormantDormantDormant
Setup difficultyhardeasyeasy
Complexity4/52/52/5
Audienceresearcherdevelopergeneral

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1day+

Requires a Kubernetes cluster to run trials, not just a local install.

No license information is provided in the explanation.

Copy-paste prompts

Prompt 1
Explain how I would define a Katib Study to tune learning rate and dropout for my model.
Prompt 2
Show me how Katib's hyperband algorithm decides which parameter combination to try next.
Prompt 3
Help me set up a Katib Trial that runs my TensorFlow training job on Kubernetes.
Prompt 4
Compare Katib's random search, grid search, and hyperband options for my use case.
Prompt 5
Walk me through connecting Katib's results to TensorBoard so I can visualize trial performance.

Frequently asked questions

What is hp-tuning?

Katib automatically tests different machine learning model settings in parallel on Kubernetes to find the combination that gives the best results.

What language is hp-tuning written in?

Mainly JavaScript. The stack also includes JavaScript, Kubernetes, TensorFlow.

Is hp-tuning actively maintained?

Dormant — no commits in 2+ years (last push 2018-04-10).

What license does hp-tuning use?

No license information is provided in the explanation.

How hard is hp-tuning to set up?

Setup difficulty is rated hard, with roughly 1day+ to a first successful run.

Who is hp-tuning for?

Mainly researcher.

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