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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: mit
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+ language:
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+ - en
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+ base_model:
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+ - google/muril-large-cased
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+ pipeline_tag: token-classification
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+ tags:
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+ - NER
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+ - Named_Entity_Recognition
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+ pretty_name: FewNERD EnglishBishnupriya MuRIL
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+ datasets:
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+ - DFKI-SLT/few-nerd
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+ metrics:
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+ - f1
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+ - precision
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+ - recall
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+ ---
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+
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+ **MuRIL is fine-tuned on English [Few-NERD](https://huggingface.co/datasets/DFKI-SLT/few-nerd) dataset.** <br>
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+
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+ Read the papers: [FewNERD in ACL](https://aclanthology.org/2021.acl-long.248.pdf) , [SampurNER in AAAI-2026](https://github.com/PrachuryyaKaushik/SampurNER/blob/main/SampurNER_AAAI_extended.pdf)
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+
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+
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+ The tagset of [Few-NERD](https://aclanthology.org/2021.acl-long.248.pdf) is a fine-grained tagset. The fine to coarse level mapping of the tags are as follows:
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+
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+ * Location : GPE, Body of Water, Island, Mountain, Park, Road/Transit, Other
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+ * Person : Actor, Artist/Author, Athlete, Director, Politician, Scholar, Soldier, Other
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+ * ORG : Company, Education, Government, Media, Political Party, Religion, Sports League, Show Organization, Other
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+ * Building : Airport, Hospital, Hotel, Library, Restaurant, Sports Facility, Theater, Other
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+ * Art : Music, Film, Written Art, Broadcast, Painting, Other
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+ * Product : Airplane, Car, Food, Game, Ship, Software, Train, Weapon, Other
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+ * Event : Attack, Election, Natural Disaster, Protest, Sports Event, Other
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+ * Misc : Astronomy, Award, Biology, Chemistry, Currency, Disease, Educational Degree, God, Language, Law, Living Thing, Medical
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+
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+
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+ ## Model performance:
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+ Precision: 66.21 <br>
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+ Recall: 69.98 <br>
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+ **F1: 68.04** <br>
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+
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+ ## Training Parameters:
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+ Epochs: 6 <br>
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+ Optimizer: AdamW <br>
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+ Learning Rate: 5e-5 <br>
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+ Weight Decay: 0.01 <br>
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+ Batch Size: 64 <br>
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+
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+
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+ ## Citation
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+
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+ If you use this model, please cite the following papers:
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+
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+ ```bibtex
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+ @inproceedings{ding-etal-2021-nerd,
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+ title = "Few-{NERD}: A Few-shot Named Entity Recognition Dataset",
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+ author = "Ding, Ning and Xu, Guangwei and Chen, Yulin and Wang, Xiaobin and Han, Xu and Xie, Pengjun and Zheng, Haitao and Liu, Zhiyuan",
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+ booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
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+ month = aug,
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+ year = "2021",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/2021.acl-long.248",
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+ doi = "10.18653/v1/2021.acl-long.248",
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+ pages = "3198--3213",
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+ }
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+
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+ @inproceedings{kaushik2026sampurner,
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+ title={SampurNER: Fine-grained Named Entity Recognition Dataset for 22 Indian Languages},
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+ author={Kaushik, Prachuryya and Anand, Ashish},
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+ booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
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+ volume={40},
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+ year={2026}
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+ }