Evaluating allows you to discover the performance of your model’s Machine Learning part. Thus, evaluating a model is only possible for models expanded with custom training data.
Check out Custom data and Machine Learning best practices page for evaluation best practices.
To evaluate a model:
Navigate to NLU → NLU Models section.
Select a model from the list of available models and click on it.
Select the Evaluate tab and click Evaluate.
The following dialog box opens. Upload the data you want to evaluate your model with and confirm by clicking Evaluate. Supported file formats are TXT, CSV, TSV.
5. The evaluation starts and can take up to several minutes depending on the evaluation data scope. When the evaluation is finished, the high-level metrics of the evaluation report are presented on the screen:
6. To download the report, click the here button. The report includes detailed statistics and is available as a ZIP archive containing three TSV files.
To evaluate a model, avoid using the data that you have used to train your model with. Make sure that your evaluation set includes data that are unseen for the Machine Learning part of your model.