> For the complete documentation index, see [llms.txt](https://docs.docbits.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.docbits.com/administration-and-setup/settings/global-settings/document-types/model-training.md).

# Model Training

<figure><img src="/files/CPSnyqzvK7tBP4UmVvA4" alt=""><figcaption></figcaption></figure>

#### Overview

Model Training allows administrators to oversee and manage the training of machine learning models specific to each document type. By providing a structured interface for importing sample data, training models, and testing their performance, Docbits ensures that its data extraction capabilities continuously improve over time.

#### Key Features and Options

1. **Metrics Overview**:
   * **Sample**: Number of sample documents used for training.
   * **Exported**: Number of documents that have been successfully exported after processing.
   * **Company Σ**: Total number of company-specific documents processed.
   * **Overall Σ**: Total number of documents processed across all categories.
2. **Training and Testing Options**:
   * **Import**: Allows administrators to import new training data sets which are typically structured samples of documents that should be recognized by the system.
   * **Train Model**: Starts the training process using the imported data to enhance the recognition and extraction capabilities of the system.
   * **Test Classification**: Enables testing of the model to evaluate its performance on classifying and extracting data from new or unseen documents.
3. **Action Buttons**:
   * **Create Field**: Add new data fields that the model should recognize and extract.
   * **Actions**: This dropdown can include options such as view details, edit configurations, or delete training data.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.docbits.com/administration-and-setup/settings/global-settings/document-types/model-training.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.