Authors: Applica.ai research team
Description: Following the same evaluation rules as others, the OCR mismatch errors are excluded in the submission.
Additionally, we have manually fixed annotation discrepancies in "total" entity in the test set.
1. We submitted the best solution out of 100 fine-tuned models
2. In this task there is an annotation discrepancy in "total" entity which caused unfair comparison between models (In train/test sets "total" entity was randomly prefixed by "RM"). Number of errors in the top solutions caused by this kind of annotation error:
Applica.ai Lambert 2.0 + Excluding OCR Errors + Fixing total entity = 0
LayoutLM 2.0 (single model) = 3 (example: 275)
Applica.ai Lambert 2.0 + Excluding OCR Mismatch = 8 (example: 77)
Tencent Youtu = 8 (example: 120)
VIE = 0
HIK_OCR_Exclude_ocr_mismatch = 0
LayoutLM + Excluding OCR Mismatch = 9 (example: 121)