---
title: "TDM for Classification Models"
slug: "tdm-for-classification-models"
description: "Manage your Semi-structured Classification models effectively with TDM, ensuring accurate training data for optimal document processing results."
updated: 2026-10-19T18:06:45Z
published: 2026-10-19T18:06:45Z
canonical: "help.hyperscience.ai/tdm-for-classification-models"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://help.hyperscience.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# TDM for Classification Models

Training Data Management for Classification is where you prepare the data for a Semi-structured Classification model. This model is also called an NLC model. It selects the Semi-structured or Additional layout for each page in a submission. For more information, see [Semi-structured Document Classification](/v44/docs/semi-structured-document-classification).

This article explains the model-version controls in [Model History](/v44/docs/tdm-for-classification-models#model-history-table) and the document controls in the [Training Data tab](/v44/docs/tdm-for-classification-models#training-data-tab).

> [!NOTE]
> **Accessing this feature**
> 
> Your access to the feature described in this article depends on your license package and pricing plan.
> 
> To learn which features are available to your organization and how to add more, contact your Hyperscience representative.

## Before you start

- Make sure that the release contains the correct Semi-structured or Additional layouts.
- Collect different examples of the documents that you expect to process.
- Collect examples that the model must ignore. These are called **Excluded documents**.

> [!NOTE]
> **Use processed submissions as training data**
> 
> Enable **Send documents to Training Data Management** in **Administration** > **System Settings**. This setting is off by default.

## Open TDM for Classification

1. Go to **Models**.
2. Open the **Classification** tab.
3. Select a model name.

![The Classification tab in the Models section, showing the Classification models table](https://cdn.us.document360.io/87894cef-4958-4f3f-be6f-b75a78c82548/Images/Documentation/class.jpg?sv=2026-02-06&spr=https&st=2026-11-04T06%3A57%3A21Z&se=2026-11-04T07%3A57%3A21Z&sr=c&sp=r&sig=WhB9ey5SimWQ6gfcBtIZhG1byHJ%2FSrPwfiB6QUhE8BM%3D)

You can also open a model from its release. Go to **Library** > **Releases**. Open the release, then select **View Model** in the Automatic Document Classification card.

![The Automatic Document Classification card on a release's page, with the View Model button](https://cdn.us.document360.io/87894cef-4958-4f3f-be6f-b75a78c82548/Images/Documentation/tdm_releases.jpg?sv=2026-02-06&spr=https&st=2026-11-04T06%3A57%3A21Z&se=2026-11-04T07%3A57%3A21Z&sr=c&sp=r&sig=WhB9ey5SimWQ6gfcBtIZhG1byHJ%2FSrPwfiB6QUhE8BM%3D)

The Classification models table shows the model name, compatible releases, status, and last deployment date. Use **Filter by release** to show models for one release.

**Importing duplicate Classification models**

Importing a Classification model with a UUID that already exists returns an error instead of creating a duplicate version. The error identifies the UUID and notes that the existing model may be in the Archive view.

## Use TDM for Classification

Follow this order when you prepare and train a Classification model.

| Step | What to do | Result |
| --- | --- | --- |
| **1. Add data** | Add documents for each layout. Add Excluded documents for pages that the model must ignore. | The model has examples of correct and incorrect matches. |
| **2. Review data** | Check each layout assignment. Remove incorrect or duplicate documents. Set usage rules and tags when needed. | The training data is correct and easy to manage. |
| **3. Check the page count** | Check the Training Data Summary and Training Data Health cards. | You know if the model is ready to train. |
| **4. Train and review** | Run training. Review projected automation and any Model Validation Tasks (MVTs). | You have a new model version and its results. |
| **5. Deploy or improve** | Deploy the model version, or update the data and train again. | The selected version becomes the live model. |

### Training data requirements

You manage whole documents in TDM. The model trains and predicts at the page level. Therefore, TDM uses page counts to check if the model is ready.

- **Minimum:** 10 pages for each layout.
- **Recommended:** 120 pages for each layout.
- **Maximum per layout:** 5,000 pages.
- **Maximum per model:** 100,000 pages.

Excluded pages are required when the release has one Semi-structured or Additional layout. They are optional when the release has two or more layouts. Add them when the model must learn to ignore similar pages.

**Do not add the same document more than once.**

## Overview tab

Use the Overview tab to review model performance, model versions, and release compatibility.

### Projected Automation chart

The chart shows projected automation for the live model. A higher target accuracy usually gives lower automation. A lower target accuracy usually gives higher automation. The chart also shows the margin of error.

For more information, see [Accuracy](/v44/docs/accuracy), [Automation](/v44/docs/automation), and [Evaluating Model Training Results](/v44/docs/evaluating-model-training-results).

![The Projected Automation chart in the Overview tab](https://cdn.us.document360.io/87894cef-4958-4f3f-be6f-b75a78c82548/Images/Documentation/classification_proj_auto.jpg?sv=2026-02-06&spr=https&st=2026-11-04T06%3A57%3A21Z&se=2026-11-04T07%3A57%3A21Z&sr=c&sp=r&sig=WhB9ey5SimWQ6gfcBtIZhG1byHJ%2FSrPwfiB6QUhE8BM%3D)

### Model History table

The table shows each model version. It includes the name, UUID, creation date, trainer version, source, projected automation, documents used for training, and last deployment date.

You can search, filter, sort, and choose which columns to show. You can also change the test target accuracy.

The **Actions** menu can include these options:

- **Deploy:** Make this version live.
- **Undeploy:** Stop using the live version.
- **Reject Candidate:** Reject a candidate version.
- **Download:** Download the version for use in another instance.
- **Archive:** Starting in v43.2, move the version from Model History to the Archive view.
- **Rename:** Starting in v44.0.1, change the displayed name of the version. Renaming does not create a new version.

#### Rename a model version

In v44.0.1 and later, you can rename a model version in the Model History table. Renaming changes only the displayed name. It does not create a new version.

To rename a model version:

1. In the **Model History** table, find the version to rename.
2. Hover over the model version’s name.
3. Enter the new name, and confirm.

When you download a renamed model version and import it into another instance, its new name is preserved.

#### Archive and unarchive model versions

In v43.2 and later, archived versions are removed from the active Model History view but remain available in the Archive view. You can archive a version only when it is neither live nor a candidate. Undeploy a live version or reject a candidate version first.

1. In the **Model History** table, find the version to archive.
2. Open its three-dot **Actions** menu and select **Archive**.
3. Confirm the action.

To restore a version, open the table options menu and select **View Archive**. Open the archived version’s three-dot menu and select **Unarchive**. The version returns to Model History as inactive; it is not deployed automatically. Select **View Active** to return to the active view.

**Note:** You can permanently delete an archived version. Deletion cannot be undone.

#### View and copy a model UUID

In v43.2 and later, the **UUID** column is hidden by default. In **Model History**, open the table options menu next to **Filter**, select **Manage columns**, enable **UUID**, and save. The column shows a shortened identifier. Hover over it to view the complete UUID, or select it to copy the complete value to your clipboard.

![The Model History table with filtering, searching, and column management options](https://cdn.us.document360.io/87894cef-4958-4f3f-be6f-b75a78c82548/Images/Documentation/nlc_model_history.jpg?sv=2026-02-06&spr=https&st=2026-11-04T06%3A57%3A21Z&se=2026-11-04T07%3A57%3A21Z&sr=c&sp=r&sig=WhB9ey5SimWQ6gfcBtIZhG1byHJ%2FSrPwfiB6QUhE8BM%3D)

### Model Compatibility table

This table lists the releases that can use the model. It shows each release name, creation date, and status. Select a column heading to sort the table. For release statuses, see [What is a Release?](/v44/docs/what-is-a-release).

## Training Data tab

Use the Training Data tab to check and manage the documents used for training.

### Training Data Summary

This card shows if the training data meets the page requirements.

| Status | Meaning |
| --- | --- |
| **Requirements Not Met** | At least one layout has fewer than 10 pages. You cannot start training. |
| **Not Optimized** | Each layout has at least 10 pages, but one or more layouts have fewer than 120 pages. You can start training. |
| **Ready To Train** | Each layout has at least 120 pages. |

The card shows eligible layouts, page counts, document counts, and Excluded data counts. Excluded pages do not appear in the main page count when they are optional.

![The Training Data Summary card](https://cdn.us.document360.io/87894cef-4958-4f3f-be6f-b75a78c82548/Images/Documentation/summary_nlc.jpg?sv=2026-02-06&spr=https&st=2026-11-04T06%3A57%3A21Z&se=2026-11-04T07%3A57%3A21Z&sr=c&sp=r&sig=WhB9ey5SimWQ6gfcBtIZhG1byHJ%2FSrPwfiB6QUhE8BM%3D)

### Training Data Health

This card shows the page count for each layout. It also shows the required and recommended counts. Select **Add Training Data** to add documents.

![The Training Data Health card, showing per-layout page counts](https://cdn.us.document360.io/87894cef-4958-4f3f-be6f-b75a78c82548/Images/Documentation/tdm_class_training_data.jpg?sv=2026-02-06&spr=https&st=2026-11-04T06%3A57%3A21Z&se=2026-11-04T07%3A57%3A21Z&sr=c&sp=r&sig=WhB9ey5SimWQ6gfcBtIZhG1byHJ%2FSrPwfiB6QUhE8BM%3D)

### Training Data table

This table lists the documents that can be used for training.

![The Training Data table](https://cdn.us.document360.io/87894cef-4958-4f3f-be6f-b75a78c82548/Images/Documentation/image(249).png?sv=2026-02-06&spr=https&st=2026-11-04T06%3A57%3A21Z&se=2026-11-04T07%3A57%3A21Z&sr=c&sp=r&sig=WhB9ey5SimWQ6gfcBtIZhG1byHJ%2FSrPwfiB6QUhE8BM%3D)

**Columns:** Document ID, File Name, Pages, Layout, Usage Rule, Source, Scheduled Deletion, and Tags.

- Point to the preview icon next to a Document ID to preview the document. Select the icon to keep the preview open.
- Older documents can have no file name. Imported older data shows **N/A**.
- **Source** can be Upload, Processing, or QA. QA applies to legacy documents from v37 or earlier.

**Filters:** Layout, Usage Rule, Source, Scheduled Deletion, Has Anomalies, and Tags.

**Actions:** Edit the layout or usage rule, export all or selected rows, or delete selected rows.

#### Edit or delete documents in a filtered table

In v44.0.1 and later, when you filter the Training Data table, the edit and delete actions apply only to the documents that you select in the filtered results. Documents that the filters hide are not changed.

To apply an action to every document that matches the filters:

1. Apply the filters.
2. Select the checkbox in the table header.
3. Select the option to select all documents that match the filters.
4. Open the **Actions** menu, and select the edit or delete action.

#### Export training data as CSV

1. To export a subset, select its rows in the **Training Data** table. To export the entire table, do not select individual rows.
2. Open the table’s **Actions** menu. Under **Export**, select **All training data as CSV** or **Selected rows as CSV**.
3. When the export is ready, use the download link in the **Notifications** menu.

A CSV export option is unavailable if it would include documents that are still loading. **All training data as CSV** is unavailable while any document in that table is loading. **Selected rows as CSV** remains available for loaded rows, even if another document is loading, but is unavailable when the selection includes a loading document. Hover over an unavailable option to see why. Wait for loading to finish or select only ready rows.

The same CSV export behavior applies to the **Excluded Training Data** table.

#### Usage rules

| Value | How the system uses the document |
| --- | --- |
| **Always** | Uses the document in future training. Data-deletion settings do not delete it. |
| **Auto** | Can use the document until data-deletion settings delete it. |
| **Never** | Does not use the document. Data-deletion settings can delete it. Documents from Supervision or QA always use this value. |
| **Loading** | The document is still loading. The value changes to Auto after loading finishes. |

#### Tags

Use tags to group and filter documents. Point to the **Tags** cell, then select **+**. Select an existing tag or create a tag.

- Imported training data keeps its tags.
- Tag names cannot contain spaces or semicolons. The system replaces them with underscores.
- The system deletes tags that are not assigned to a document.
- Starting in v43.1, tag names are not case-sensitive. For example, **Tag** and **tag** are the same tag.
- Starting in v43.2, long tag names use an ellipsis. Point to the tag to see its full name.

![Tags in the Training Data table](https://cdn.us.document360.io/87894cef-4958-4f3f-be6f-b75a78c82548/Images/Documentation/nlc_tags(1).jpg?sv=2026-02-06&spr=https&st=2026-11-04T06%3A57%3A21Z&se=2026-11-04T07%3A57%3A21Z&sr=c&sp=r&sig=WhB9ey5SimWQ6gfcBtIZhG1byHJ%2FSrPwfiB6QUhE8BM%3D)

#### Anomalies

A high-confidence error occurs when the model is confident, but the layout is wrong. TDM marks these documents as anomalies. Complete the related Model Validation Tasks (MVTs) to check and correct them. For more information, see [Model Validation Tasks](/v44/docs/model-validation-tasks).

### Excluded Training Data table

This table contains documents that the model must not match to a layout. It uses the same columns, filters, and actions as the Training Data table.

![The Excluded Training Data table](https://cdn.us.document360.io/87894cef-4958-4f3f-be6f-b75a78c82548/Images/Documentation/excluded.jpg?sv=2026-02-06&spr=https&st=2026-11-04T06%3A57%3A21Z&se=2026-11-04T07%3A57%3A21Z&sr=c&sp=r&sig=WhB9ey5SimWQ6gfcBtIZhG1byHJ%2FSrPwfiB6QUhE8BM%3D)

For CSV export steps, see [Export training data as CSV](/v44/docs/tdm-for-classification-models#export-training-data-as-csv).

A tool used to annotate, manage, import, and export training documents. It is also used to train models by working directly with the training data (“ground truth”) obtained from each document in the training set.

Tasks used to review and correct data predictions made by Hyperscience models. They help evaluate model accuracy and provide feedback that can be used to improve future model performance.