Document Understanding
latest
false
- Overview
- Getting Started
- Activities
- Insights Dashboards
- Document Understanding Process
- Quickstart Tutorials
- Framework Components
- ML Packages
- Overview
- Document Understanding - ML Package
- DocumentClassifier - ML Package
- ML Packages With OCR Capabilities
- 1040 - ML Package
- 1040 Schedule C - ML Package
- 1040 Schedule D - ML Package
- 1040 Schedule E - ML Package
- 4506T - ML Package
- 990 - ML Package - Preview
- ACORD125 - ML Package
- ACORD126 - ML Package
- ACORD131 - ML Package
- ACORD140 - ML Package
- ACORD25 - ML Package
- Bank Statements - ML Package
- BillsOfLading - ML Package
- Certificate of Incorporation - ML Package
- Certificate of Origin - ML Package
- Checks - ML Package
- Children Product Certificate - ML Package
- CMS 1500 - ML Package
- EU Declaration of Conformity - ML Package
- Financial Statements - ML Package
- FM1003 - ML Package
- I9 - ML Package
- ID Cards - ML Package
- Invoices - ML Package
- Invoices Australia - ML package
- Invoices China - ML package
- Invoices India - ML package
- Invoices Japan - ML package
- Invoices Shipping - ML Package
- Packing Lists - ML Package
- Payslips - ML Package
- Passports - ML Package
- Purchase Orders - ML Package
- Receipts - ML Package
- RemittanceAdvices - ML Package
- UB04 - ML Package
- Utility Bills - ML Package
- Vehicle Titles - ML Package
- W2 - ML Package
- W9 - ML Package
- Other Out-of-the-box ML Packages
- Public Endpoints
- Traffic limitations
- OCR Configuration
- Pipelines
- OCR Services
- Deep Learning
- Licensing
Document Understanding User Guide
Last updated Apr 26, 2024
Evaluate a Trained Model
Configure the evaluation pipeline as follows:
- In the Pipeline type field, select Evaluation run.
- In the Choose package major version field, select a major version for your package.
- In the Choose package minor version field, select a minor version you want to evaluate.
- In the Choose evaluation dataset field, select a representative evaluation dataset. For more information on dataset structure, check the Dataset Format section.
- In the Enter parameters section, there is one environment variable is relevant for Evaluation pipelines you could use:
eval.redo_ocrwhich, if set to true, allows you to rerun OCR when running the pipeline to assess the impact of OCR on extraction accuracy. This assumes an OCR engine was configured when the ML Package was created.- The Enable GPU slider is disabled by default, in which case the pipeline is runs on CPU. We strongly recommend that Evaluation pipelines run only on CPU.
-
Select one of the options when the pipeline should run: Run now,Time based or Recurring.
- After you configure all the fields, click Create. The pipeline is created.
