aws / aws/amazon-sagemaker-examples

[Example Request] PyTorch 1.11 with SM Training Compiler - Tuning Hyperparameters

Open
#3,571 0 comments 0 reactions 0 assignees View on GitHub
Dominant language
Jupyter Notebook
Stars
11k
Forks
7k
Avg merge
8h 29m
Merged PRs (30d)
8

Description

**Describe the use case example you want to see**

A notebook example describing how to tune hyper-parameters while training with SM Training Compiler on PyTorch 1.11. This particular example will explore how to effectively use SM Training Compiler by tuning the hyper-parameters.

**How would this example be used? Please describe.**

Onboarding new customers to advanced use-cases with SM Training Compiler

**Describe which SageMaker services are involved**

1. SageMaker Training
2. SageMaker Training Compiler
3. SageMaker Model Tuner

**Describe what other services (other than SageMaker) are involved***

None

**Describe which dataset could be used. Provide its location in s3://sagemaker-sample-files or another source.**

Contributor guide

Open the contributing guide

Assessment

This issue has not been assessed yet.

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.