How do I save model metrics from a Deep AR model training step to S3?

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I have a sagemaker pipeline that trains a Deep-AR algorithm. The model metrics are displayed as "Output" in the sagemaker DAG, but I want to persist these metrics in a JSON file so I can baseline the model.

Is there any way to save the Deep-AR model's train and test evaluation metrics as a JSON on S3?

Casey
demandé il y a 8 mois185 vues
2 réponses
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Hi,

If you speak about the metrics mentioned on this page ( https://docs.aws.amazon.com/sagemaker/latest/dg/training-metrics.html ), they are in CloudWatch,

CloudWatch has a generic way to export CW metrics to CSV: see https://docs.aws.amazon.com/prescriptive-guidance/latest/patterns/publish-amazon-cloudwatch-metrics-to-a-csv-file.html

Best,

Didier

profile pictureAWS
EXPERT
répondu il y a 8 mois
0

If you are interested in baselining the model and comparing its performance against other models, you may want to consider using SageMaker experiments so that you can create, manage, analyze, and compare your machine learning experiments. SageMaker Experiments automatically tracks the inputs, parameters, configurations, and results of your iterations as runs. You can assign, group, and organize these runs into experiments. SageMaker Experiments is integrated with Amazon SageMaker Studio, providing a visual interface to browse your active and past experiments, compare runs on key performance metrics, and identify the best performing models.

https://docs.aws.amazon.com/sagemaker/latest/dg/experiments.html

It's specifically designed to address the usecase you're describing, and the cost is driven by the volume of metrics that are ingested, stored, and queried.

https://aws.amazon.com/sagemaker/pricing/

Cheers, David

AWS
répondu il y a 8 mois

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