Fine tuning LayoutLMv2 For Token Classification on CORD dataset
I use this colab:colab.research.google.comGoogle Colaboratoryto Fine tuning LayoutLMv2ForTokenClassification on CORD datasethere is the result:huggingface.codoc2txt/layoutlmv2-finetuned-cord · Hugging FaceWe’re on a journey to advance and democratize artificial intelligence through open source and open science.F1: 0.9665and indeed the result are pretty amazing when running on the test sethow ever, when running on any other receipt (printed or pdf) the result are completely offSo from some reason the model is overfitting, to the cord dataset, even though I use similar images for testing.I don’t think that there is aData leakageunless the cord DS is not clean (which I assume it is clean)What could be the reason for this?Is it some inherent property of LayoutLM?The LayoutLM models are somewhat old, and it seems deserted…I don’t have much experience so I would appreciate any infoThanks