Stay organized with collections
Save and categorize content based on your preferences.
As a data scientist experimenting with large models, you need a way to run
experiments on a scalable training service to log parameters and metrics.
This enables reproducibility.
With Vertex AI training and experiments autologging integration,
you can run your ML experiments at scale and autolog their parameters and
metrics by using the enable_autolog argument.
Notebook: Vertex AI Experiments: Custom training autologging - Local script
This tutorial uses the following Google Cloud ML services and resources:
Vertex AI Experiments
Vertex AI training
The steps performed include:
Formalize model experiment in a script.
Run model training using local script on Vertex AI training.
Check out ML experiment parameters and metrics in
Vertex AI Experiments.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-02-14 UTC."],[],[]]