[Docs] Add documentation for show_metrics(), stream_logs(), and job notification setup#6065
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mujtaba1747 merged 3 commits intoJul 21, 2026
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amazeAmazing
approved these changes
Jul 20, 2026
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| # After a kernel restart, use the standalone function with job name | ||
| from sagemaker.train import plot_training_metrics | ||
| plot_training_metrics("my-sft-job-20260101195119") |
Contributor
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nit: maybe a more basic job name e.g. my-sft-job
mujtaba1747
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Jul 20, 2026
| df = trainer.show_metrics(metrics=["training_loss", "lr"]) | ||
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| # Filter by step range | ||
| df = trainer.show_metrics(starting_step=20, ending_step=100) |
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is show_metrics supported in serverless?
mujtaba1747
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Jul 20, 2026
| job = trainer.train(wait=False) | ||
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| # Stream logs directly to the terminal (blocking) | ||
| trainer.stream_logs() |
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And is stream_logs() supported in serverless?
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They are both supported for serverless, but we don't have an equivalent finetuning_serverless.rst. Syncing offline to figure out the best place to put this information.
mujtaba1747
approved these changes
Jul 21, 2026
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Issue #, if available: N/A
Summary
Adds documentation for
show_metrics(),stream_logs(), and job notifications to the existing Sphinx RST pages under model customization.Changes
docs/model_customization/model_customization.rstdocs/model_customization/finetuning_serverful.rstshow_metrics()andstream_logs()examples for SMTJ computedocs/model_customization/finetuning_hyperpod.rstshow_metrics()andstream_logs()examples for HyperPod compute, including Ctrl+C behavior noteTesting
make htmlindocs/builds without errorsBy submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.