模型:
oliverguhr/fullstop-punctuation-multilingual-base
precision recall f1-score support 0 0.99 0.99 0.99 47903344 . 0.94 0.95 0.95 2798780 , 0.85 0.84 0.85 3451618 ? 0.88 0.85 0.87 88876 - 0.61 0.32 0.42 157863 : 0.72 0.52 0.60 103789 accuracy 0.98 54504270 macro avg 0.83 0.75 0.78 54504270 weighted avg 0.98 0.98 0.98 54504270
@article{guhr-EtAl:2021:fullstop, title={FullStop: Multilingual Deep Models for Punctuation Prediction}, author = {Guhr, Oliver and Schumann, Anne-Kathrin and Bahrmann, Frank and Böhme, Hans Joachim}, booktitle = {Proceedings of the Swiss Text Analytics Conference 2021}, month = {June}, year = {2021}, address = {Winterthur, Switzerland}, publisher = {CEUR Workshop Proceedings}, url = {http://ceur-ws.org/Vol-2957/sepp_paper4.pdf} }
@misc{https://doi.org/10.48550/arxiv.2301.03319, doi = {10.48550/ARXIV.2301.03319}, url = {https://arxiv.org/abs/2301.03319}, author = {Vandeghinste, Vincent and Guhr, Oliver}, keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences, I.2.7}, title = {FullStop:Punctuation and Segmentation Prediction for Dutch with Transformers}, publisher = {arXiv}, year = {2023}, copyright = {Creative Commons Attribution Share Alike 4.0 International} }