Sennodipoi/LayoutLMv3-kleisterNDA

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.