Repeating characters in a word are being suppressed by character recognition models

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I have trained a SATRN_small model on a custom dataset using MMOCR framework for character recognition as well as a SVRT_LCNet model using PaddleOCR.

The loss function used in MMOCR is CrossEntropyLoss, and the loss function used by PaddleOCR is a combination of CTC loss and SAR loss.

The repeating characters in a word are being suppressed by both models. for e.g, 40799932 is predicted as 4079932.

What is the reason for this problem? Is there any solution?

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