Hello @Sarah Cummings , Thanks for using Microsoft Q&A Platform.
As we know the Custom classification models in Azure Document Intelligence are designed to process each page of the input file separately and makes a prediction for each page based on its content and layout.
This is a known behavior, the model classifies each page of the input document to one of the classes in the labeled dataset, and additional pages may introduce noise or irrelevant information that can affect the model's predictions.
In this scenario, the possible workaround could be retraining the model with additional data that includes the extra pages to improve the model's accuracy. Or you can split the documents and posting required page to the classification model.
Also please note that training custom models is always free with Document Intelligence. You are only charged when a model is used to analyze a document means it is billed by number of pages that are analyzed. Please visit here for pricing information: https://azure.microsoft.com/en-us/pricing/details/ai-document-intelligence/
Here is the service limit details for custom models usage: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/service-limits?view=doc-intel-3.1.0#custom-model-usage
I hope this helps.
Regards,
Vasavi
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