What this tutorial covers
Configure epochs, batch size, learning rate and other training parameters.
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
Inspect the training controls before starting the run. Confirm that the visible page really matches the tutorial topic before changing any settings.
2Configure the input
Prepare and check epochs, batch size, learning rate, seed and the dataset splits.
3Run and watch the status
Adjust the training controls and confirm that the run is ready to start. Watch the visible status, plot or log area while the workflow is running.
4Inspect the result
Pay special attention to a complete set of training hyperparameters.
5Verify and iterate
A short pilot run often helps before committing to a larger epoch count. 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 a complete set of training hyperparameters.
- Read the result together with the exact inputs used for the run; a screenshot alone rarely tells the whole story.
- A short pilot run often helps before committing to a larger epoch count.
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.