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Introduction to Model Training

Updated on 2022-12-08 GMT+08:00
NOTE:

ModelArts provides model training of both the new and old versions. Training management of the old version is only available for its existing users.

This tutorial applies only to training management of the old version, which will be discontinued soon. Use the tutorial for the new version. For details, see, Introduction to Model Development.

For details about the differences between the old and new versions, see FAQs.

ModelArts provides model training for you to view the training effect, based on which you can adjust your model parameters. You can select resource pools with different instance flavors for model training.

Model Training Features

Table 1 Features

Feature

Description

Reference

Training job management

You can create training jobs, manage training job versions, and view details of training jobs, and evaluation details.

Introduction to Training Jobs

Managing Training Job Versions

Viewing Job Details

Job parameter management

You can save the parameter settings of a training job (including the data source, algorithm source, running parameters, resource pool parameters, and more) as a job parameter, which can be directly used when you create a training job, eliminating the need to set parameters one by one. As such, the configuration efficiency can be greatly improved.

Managing Job Parameters

Model training visualization

TensorBoard and MindInsight effectively display the computational graph of a model in the running process, the trend of all metrics in time, and the data used in the training.

Managing Visualization Jobs

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