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LayoutLMv3 fine-tuned on the Kleister-NDA dataset. Code (including pre-processing) and results are available at the official GitHub repository of my Master Degree thesis .

Results obtained with seqeval in strict mode:

Precision Recall F1-score Variance (F1)
EFFECTIVE_DATE 0.92 0.99 0.95 5e-5
JURISDICTION 0.87 0.88 0.88 8e-6
PARTY 0.92 0.99 0.95 5e-5
TERM 1 1 1 0
Micro avg 0.91 0.96 0.94 2e-5
Macro avg 0.92 0.96 0.94 3e-7
Weighted avg 0.91 0.96 0.94 2e-5

Since I used the same segmentation strategy of the original paper i.e. using the labels to create segments, the scores are not directly comparable with the other LayoutLM versions.

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