Skip to content
4 of 6 · Pipelines

Run, monitor, and compare pipelines

Start one pipeline run, follow preparation and queue state, respond to GPU guidance, and compare compatible completed work.

Model Pipelines list with a synthetic image-classification pipeline in Pending state and the Train New Model action
The list summarizes each pipeline’s current state, live metric, and update time before you open its detail page.

Start and monitor a run#

  1. Select Run once

    Start the reviewed pipeline a single time. A preparation, planning, pending, or queued state means work was accepted; do not submit a duplicate.

  2. Follow data preparation

    Wait while samples, splits, and task inputs are prepared. Read the visible message history when preparation reports a problem.

  3. Watch queue and progress

    Use the queue state, progress indicator, current message, and message history to distinguish waiting from active training or evaluation.

  4. Refresh from durable state

    If the live display disconnects, refresh the page and use the persisted status and history before deciding whether intervention is needed.

  5. Interrupt only when intended

    Interrupt requests a controlled stop. Wait through Interrupting until the pipeline reaches Interrupted or another terminal state.

Respond to GPU memory guidance#

  1. Read the estimate

    Compare required memory, available or free memory, the current batch size, and the recommended batch size shown by the dialog.

  2. Apply the recommended batch size

    Use the suggested lower batch size when offered, then save the configuration.

  3. Check again

    Run the preflight check again after changing the configuration. Retry the pipeline only when the check permits it.

Compare compatible pipelines#

  1. Open Compare Pipelines

    Start from a completed pipeline with results.

  2. Choose compatible completed pipelines

    Search for pipelines that evaluate the same task and comparable target. Incompatible or incomplete pipelines are not useful comparison candidates.

  3. Compare like with like

    Check dataset, split, model version, metric definition, threshold or operating point, and result status before interpreting differences.

  4. Open the detailed results

    Use the comparison as navigation, then inspect each pipeline result and model report for the evidence behind the headline metric.