Human In The Loop
Human in the loop(HITL) is a way to speed up the labeling process and improve model quality.
When you have a lot of documents to label, and analyze a lot of testing files to improve model quality, it's a long process. HITL can help you here.
- Train a model with 5 labeled documents
- Pick a up local file and analyze it, if you find there are incorrect fields, you could add the document to training set then adjust the labels if necessary.
- Train a new model with new labeling data.
- Repeat step 2 - 3 until the model is good enough.
- Upload lots of documents into your Azure blob storage, train a model with at least 5 labeled documents.
- Click auto-label, FoTT will automatically pick up other files in the blob storage and analyze them, then return the analyze results as label files. (note: there will be cost associated with using Form Recognizer Analyze API, please be aware).
- Users can revise the labels of those files if necessary, notice the icons of the document are changed, indicating it’s been revised and ready to be used for training.
- You could start a new training session with newly revised files.
- Repeat step 2 - 4 until the model is good enough.