Document Understanding Modern Projects User Guide

DELIVERY:

Last updated Dec 9, 2025

Retrain extractors

You can use documents that were validated in Validation Station to further improve the performance of your models.

You can retrain documents that were processed using the following activities:

UiPath.DocumentUnderstanding.Activities: all documents that were processed using this activity package and were validated in Validated Station are collected automatically and can be used for retraining.
UiPath.IntelligentOCR.Activities (starting with version 6.25.0-preview): to retrain documents processed using this activity package, use the Document Understanding Project Extractor Trainer activity in your workflow. This allows documents to be collected for retraining purposes.

The Exceptions for review button is now always visible for the corresponding document type within the Build section. If no documents have been collected, the button remains available and displays a count of 0.

Note: Collected documents are not automatically included in the training set. You need to review the documents and confirm their addition in the training set to retrain your model.

Exceptions for review

Follow the steps from this procedure to fine-tune your model using documents from Validation Station.

Note: Documents collected for exceptions are stored for a period of 90, after which they are automatically deleted.

Documents are not collected for validation tasks with a duration greater than 7 days.

Select the Exceptions for review button.
Check the exception documents from the Exceptions for fine-tuning menu.
The following information is available for each document:
- File name: the file name of the document containing an exception.
- Status: the status of the document.
- Pages: the number of pages that the document contains.
- Project version: the project version that contains the document.
- Processed date: the date when the document was processed.
- No of extracted fields: the number of extracted fields for the document containing an exception.
- No of corrected fields: the number of modified fields during validation step.
- Validator name: the username of the person who validated the document.
Note: The Exceptions for fine-tunning list may include documents imported from other Document Understanding projects or environments.
Select the document you want to use for fine-tuning from the list.
The following information is available for each document:
- All extracted fields are displayed, along with their model confidence. If the confidence value is N/A, this indicates that the field was not automatically extracted and was instead manually added by the validator.
- Corrected fields are marked with a yellow point next to extracted field name.
- The following information is available for all corrected fields:
  - Predicted value: the value predicted by the model.
  - Corrected value: if changed manually, the value after validation. If the document type was not changed after validation, the value will be N/A.
  - Reference: the original value that is highlighted on the document. This value is used for annotation if you decide to use the document for fine-tuning.
- You can easily sort by confidences to check fields with low confidences without corrections.
- You can filter by corrected fields to only focus on them.
Choose Annotate if you want to further annotate this document or choose Use for fine-tuning if you want to use this document to retrain your model.
- Use for fine-tuning:
  - Choose this when the document is a good example for the model fine-tuning and all fields are correctly referenced within the document.
  - The document is imported in the training with the Exception tag and all annotations confirmed. The document will be used for fine-tuning.
- Annotate:
  - Choose this if the document is a good example for the model fine-tuning, but there are some validation errors, for example not all fields are correctly referenced wihtin the document and further corrections are needed.
  - The document is imported in the training set with the Exception tag and all annotations unconfirmed. Annotations must be confirmed in the Build section in order for the document to be used to fine-tune the model.
  - If you choose to further annotate your document, check the Annotate documents page for more information on how to annotate documents.
- Exclude:
  - Choose this when the document is not a good example and you want to remove it from the list of exceptions for review and you do not need to review it in future review sessions.
  - You can change the status of the document to revert the changes.
Figure 1. Selected document used for fine-tuning or annotation

Once you selected all your documents for fine-tuning, your model is retrained using the new data from Validation Station.

You can create a new project version and use the Compare model feature from the Measure section to compare the performance of your model.

[Preview] Exporting and importing retraining candidates

Document Understanding allows you to export retraining candidates from one environment and import them into another.

This setup is commonly used in scenarios where you maintain a development–test–production environment structure, and your process involves creating a copy of the development Document Understanding project in higher environments, such as test, UAT, or production. In this arrangement, retraining documents are gathered within the production project, and the export–import feature allows you to bring the documents back into the development environment for model retraining, before promoting the updates back to the higher environments.

Exporting retraining candidates

You can export retraining candidates directly from the Exceptions for review page by selecting the Export button. Select View exports to access the list of exported files.

You may choose to export all collected documents or only a selected subset, depending on how you prefer to manage the review process, as explained in the following examples:

You can export all collected documents and triage them in the environment where you plan to import them and retrain the model.
You can complete the review in the current environment and export only the specific documents you want to use for retraining.

Importing retraining candidates

Importing is done from the Exceptions for review page. Imported documents are displayed in a similar manner to documents automatically collected from the Validation Station, with the To review status.

Imported documents are added as retraining candidates. For model fine-tuning, simply follow the same steps as for documents collected directly in a project. Remember to review and confirm the retraining candidates before adding them to the training set.

On this page

Exceptions for review
[Preview] Exporting and importing retraining candidates
Exporting retraining candidates
Importing retraining candidates

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