What this tutorial covers
Start training and follow each epoch through the live integrated log.
Before you start：You need access to the product and should ideally follow the tutorial using your own real parameters or data. The screenshots below were manually rematched to avoid the image/topic mismatches seen in the previous version.
Step-by-step workflow
1Open the module
Make sure the model and data are ready, then switch to Train. Confirm that the visible page really matches the tutorial topic before changing any settings.
2Configure the input
Prepare and check training controls, dataset splits and the compute device.
3Run and watch the status
Start training and keep watching the log, loss and accuracy updates. Watch the visible status, plot or log area while the workflow is running.
4Inspect the result
Pay special attention to training progress, live logs and intermediate metrics.
5Verify and iterate
The live log is often the fastest way to spot training failures, unstable settings or dataset-loading issues. Change one meaningful parameter and rerun so you can verify whether the output changes in the expected direction.
How to read the result
- The main output of this workflow is training progress, live logs and intermediate metrics.
- Read the result together with the exact inputs used for the run; a screenshot alone rarely tells the whole story.
- The live log is often the fastest way to spot training failures, unstable settings or dataset-loading issues.
Troubleshooting & practical tips
- If nothing changes, first confirm that the correct module is open.
- If the output looks unrealistic, check units, field mapping and input scale first.
- For comparisons, change one key parameter at a time whenever possible.