This guide shows you how to train the AI for your custom requirements.
When you create a custom model, you can teach the AI to recognise and label any piece of information from any document.
- You have a custom document type (e.g. German identity cards, Utility Bills etc)
- You need to extract custom fields (that our pre-trained model was not trained on)
Begin with a simple approach and gradually expand. Break down your use case into smaller experiments for prototyping, then gradually incorporate more complexity over time.
Click through the prototype below for a step-by-step walk-through on how to build a custom model.
To start building your own model, keep the following ready:
Here are the broad steps we will follow:
- 1.Create a custom model
- 2.Upload sample documents
- 3.Add label (fields) to extract
- 4.Annotate examples
- 5.Train the Model
Check that each label name you have added has a minimum of 10 examples marked. Don't have enough examples for a label on your files? Delete that label and Train the model without that label.
Take a break—your model will take around 10 to 45 minutes to train depending on how many files you labelled. We'll send you an email on your registered account when it's ready to auto-extract your data.
Why do I need to mark 10 examples?
AI learns from examples. When you mark data on your images and assign a label, the AI uses this information to learn to recognise that data on a new file.
If you add more examples, the AI will have more data to learn from and you will see higher accuracy in how it is able to auto-extract data after Training.
- Click on All Files on the top left corner of this page > you will be taken to the page with the list of files you added (shown above).
- Under Model details > check the Examples column under the Labels section.
- You can also locate a file with fewer labels marked from the Marked labels column on the file list.