--- title: Test and publish your model description: Assess the performance of your NLU model to identify areas for improvement. Then publish your model to make it available to other applications such as Virtual Agent. locale: en-US canonical_url: https://www.servicenow.com/docs/r/australia/intelligent-experiences/nlu-service/testing-your-model.html release: australia product: NLU Service classification: nlu-service topic_type: concept last_updated: "2026-03-12" reading_time_minutes: 4 breadcrumb: [Model management, Natural Language Understanding, Enable AI experiences] --- # Test and publish your model Assess the performance of your NLU model to identify areas for improvement. Then publish your model to make it available to other applications such as Virtual Agent. ## Summary usage Test your Virtual Agent or AI Search model against its default test set to see how the model responds. Test results provide information you can use to improve your model. **Note:** Testing your model requires the Multi-model Batch Testing feature, available with the NLU Workbench - Advanced Features application from ServiceNow® Store. For more information, see [Install NLU Workbench - Advanced Features](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/nlu-service/install-nlu-workbench-adv-features.md). To test your model, navigate to **NLU Workbench** > **Models**. Select the tab for your model's application, then select the name of the model. In the **Test and publish your model** card, select **View phase.** \[Omitted image "testing-your-model001.png"\] Alt text: Test and publish your model phase card ## Overview of testing and publishing your model The **Test and publish your model** phase opens in the **Overview** page by default. Buttons for **Run new test** and **Publish model** are located here. \[Omitted image "testing-your-model002.png"\] Alt text: Test and publish your model overview page **Overview** provides information about a previous test run, with bar charts summarizing the test results. If you have earlier test runs, you can view those by selecting from the **Test run date** list. \[Omitted image "testing-your-model003.png"\] Alt text: Test run date pulldown To drill down into the test results table, select the **Detailed results** tab. Each test utterance is listed in **Detailed results**, with its prediction. ## Understanding test results The test results show how your model responded to the utterances in the test set. \[Omitted image "testing-your-model02.png"\] Alt text: Test results for a model test in the NLU Workbench. The bar chart shows the prediction percentages for correct, correct among multiple, missed, and incorrect:
| Percentage | Description |
|---|---|
| Correct | The percentage of utterances for which your model correctly predicted the intent. When the model predicts no intent for utterances marked as `Not relevant`, that result is counted as Correct. |
| Correct among multiple | For utterances that had more than one intent predicted. The percentage of utterances for which the model correctly predicted the intent or intents, but also predicted intents that did not belong to the utterance. |
| Missed | The percentage of utterances for which your model did not predict an intent, even though there was an expected intent. |
| Incorrect | The percentage of utterances for which your model predicted an intent that was not correct. |