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Modelcards

Word Segmentation

#TODO

Part-of-Speech Tagging

#TODO

Chunking

Language Dataset Backbone Method AdaSeq F1 Best published Modelcard & Demo Config
English conll2000 xlm-roberta-large Bert-CRF 97.18 97.3 (Wang et al., 2020) ModelScope

Named Entity Recognition

Language Dataset Backbone Method AdaSeq F1 Best published Modelcard & Demo Config
Chinese msra structbert-base Bert-CRF 96.69 96.72 (Li et al., 2020) ModelScope
Chinese ontonotes 4.0 structbert-base Bert-CRF 83.04 84.47 (Li et al., 2020) ModelScope
Chinese resume structbert-base Bert-CRF 96.87 96.79 (Xuan et al., 2020) ModelScope
Chinese weibo structbert-base Bert-CRF 72.77 72.66 (Zhu et al., 2022) ModelScope
English conll03 xlm-roberta-large Bert-CRF 93.35 94.6 (Wang et al., 2021) ModelScope
English conllpp xlm-roberta-large Bert-CRF 94.71 95.88 (Zhou et al., 2021) ModelScope
English wnut16 xlm-roberta-large Bert-CRF 57.23 58.98 (Wang et al., 2021) -
English wnut17 xlm-roberta-large Bert-CRF 59.69 60.45 (Wang et al., 2021) ModelScope
English ai xlm-roberta-large BERT-CRF 70.22 66.03 (Tang et al., 2022) ModelScope
English literature xlm-roberta-large BERT-CRF 72.64 68.59 (Tang et al., 2022) ModelScope
English music xlm-roberta-large BERT-CRF 80.41 73.10 (Tang et al., 2022) ModelScope
English politics xlm-roberta-large BERT-CRF 76.56 75.52 (Tang et al., 2022) ModelScope
English science xlm-roberta-large BERT-CRF 75.96 71.69 (Tang et al., 2022) ModelScope
English multiconer2022-en xlm-roberta-large RaNER 96.59 (dev) 95.82 (dev macro) (Wang et al., 2022) ModelScope
Bangla multiconer2022-bn xlm-roberta-large RaNER 85.11 (dev) 86.40 (dev macro) (Chen et al., 2022) ModelScope
German multiconer2022-de xlm-roberta-large RaNER 95.00 (dev) 94.62 (dev macro) (Wang et al., 2022) ModelScope
Spanish multiconer2022-es xlm-roberta-large RaNER 94.64 (dev) 94.44 (dev macro) (Wang et al., 2022) ModelScope
Farsi multiconer2022-fa xlm-roberta-large RaNER 95.97 (dev) 95.93 (dev macro) (Wang et al., 2022) ModelScope
Hindi multiconer2022-hi xlm-roberta-large RaNER 85.28 (dev) 86.43 (dev macro) (Wang et al., 2022) ModelScope
Korean multiconer2022-ko xlm-roberta-large RaNER 95.49 (dev) 96.34 (dev macro) (Wang et al., 2022) ModelScope
Dutch multiconer2022-nl xlm-roberta-large RaNER 97.28 (dev) 97.53 (dev macro) (Wang et al., 2022) ModelScope
Russian multiconer2022-ru xlm-roberta-large RaNER 95.14 (dev) 95.59 (dev macro) (Wang et al., 2022) ModelScope
Turkish multiconer2022-tr xlm-roberta-large RaNER 97.83 (dev) 97.40 (dev macro) (Wang et al., 2022) ModelScope
Chinese multiconer2022-zh xlm-roberta-large RaNER 91.44 (dev) 92.20 (dev macro) (Chen et al., 2022) ModelScope
Multilingual multiconer2022-multi xlm-roberta-large RaNER 94.05 (dev) 93.60 (dev macro) (Wang et al., 2022) ModelScope
English wiki-diverse xlm-roberta-large BERT-CRF 75.80 76.01 (Wang et al., 2022 ModelScope
Chinese ecom-cn-50cls structbert-base BERT-CRF 74.18 - ModelScope
Chinese ecom-cn structbert-base BERT-CRF 81.36 - ModelScope
Chinese book structbert-base BERT-CRF 81.96 - ModelScope
Chinese game structbert-base BERT-CRF 79.89 - ModelScope
Chinese finance structbert-base BERT-CRF 81.34 - ModelScope
Chinese bank structbert-base BERT-CRF 85.90 - ModelScope
Chinese cmeee structbert-base BERT-CRF 68.97 - (TBD) ModelScope
English ecom-en xlm-roberta-large BERT-CRF 83.18 - ModelScope
Spanish ecom-es xlm-roberta-large BERT-CRF 90.94 - ModelScope
Russian ecom-ru xlm-roberta-large BERT-CRF 86.25 - ModelScope
French ecom-fr xlm-roberta-large BERT-CRF 87.18 - ModelScope
English ecom-title-en xlm-roberta-base BERT-CRF 77.30 - ModelScope
Vietnamese ecom-title-vie xlm-roberta-base BERT-CRF 77.80 - ModelScope
Thai ecom-title-th xlm-roberta-base BERT-CRF 85.10 - ModelScope
Indonesian ecom-title-id xlm-roberta-base BERT-CRF 85.80 - ModelScope
English ecom-query-en xlm-roberta-base BERT-CRF 75.70 - ModelScope
Vietnamese ecom-query-vie xlm-roberta-base BERT-CRF 75.70 - ModelScope
Thai ecom-query-th xlm-roberta-base BERT-CRF 82.70 - ModelScope
Indonesian ecom-query-id xlm-roberta-base BERT-CRF 75.50 - ModelScope