@ricardoyepez Thanks, According to the fetched documents, it's recommended to create a balanced dataset that represents all the typical variations you would expect to see for the document. If your document has at least 3 different types of structures, you can consider splitting the dataset into folders and train a model for each of the variations. This way, you can train a model for each of the structures and then compose the individual models into a single composed model.
Doubts when training custom model
I am training a custom model in the form recognizer to process PDF files with more than 20 pages each, but in this case the document has at least 3 different types of structures inside it.
My idea to process these documents is to label each of the sheets in at least 5 different documents, but since it is a somewhat extensive task, I want to make sure beforehand that this is the best way or do you recommend another solution?
Thanks in advance.
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