prachuryyaIITG/SampurNER_Bodo_IndicBERTv2
IndicBERTv2 is fine-tuned on Bodo [SampurNER](https://huggingface.co/datasets/prachuryyaIITG/SampurNER) dataset for Fine-grained Named Entity Recognition. It is created using the [EaMaTa](https://ojs.aaai.org/index.php/AAAI/article/view/40405) framework, utilizing the [Few-NERD](https://huggingface.co/datasets/DFKI-SLT/few-nerd) dataset. <br>
Read the paper: SampurNER in AAAI-2026
SampurNER Dataset: datasets/prachuryyaIITG/SampurNER
The tagset of Few-NERD is a fine-grained tagset. The fine to coarse level mapping of the tags are as follows:
- Location : GPE, Body of Water, Island, Mountain, Park, Road/Transit, Other
- Person : Actor, Artist/Author, Athlete, Director, Politician, Scholar, Soldier, Other
- ORG : Company, Education, Government, Media, Political Party, Religion, Sports League, Show Organization, Other
- Building : Airport, Hospital, Hotel, Library, Restaurant, Sports Facility, Theater, Other
- Art : Music, Film, Written Art, Broadcast, Painting, Other
- Product : Airplane, Car, Food, Game, Ship, Software, Train, Weapon, Other
- Event : Attack, Election, Natural Disaster, Protest, Sports Event, Other
- Misc : Astronomy, Award, Biology, Chemistry, Currency, Disease, Educational Degree, God, Language, Law, Living Thing, Medical
Model performance:
Precision: 64.17 <br> Recall: 67.14 <br> F1: 65.62 <br>
Training Parameters:
Epochs: 6 <br> Optimizer: AdamW <br> Learning Rate: 5e-5 <br> Weight Decay: 0.01 <br> Batch Size: 64 <br>
Contributors
Prachuryya Kaushik <br> Prof. Ashish Anand
It is part of the AWED-PIPER ecosystem: **Paper** | **Agent for FgNER** | **Web App for FgNER** | **Agent for PII Protection** | **Web App for PII Protection**
Sample Usage
The AWED-FiNER agentic tool can be used to interact with expert models trained using this framework. Below is an example:
pip install smolagents gradio_clientfrom tool import AWEDFiNERTool
tool = AWEDFiNERTool(
space_id="prachuryyaIITG/AWED-FiNER"
)
result = tool.forward(
text="Jude Bellingham joined Real Madrid in 2023.",
language="English"
)
print(result)Citation
If you use this model, please cite the following papers:
@inproceedings{kaushik2026sampurner,
title={SampurNER: Fine-Grained Named Entity Recognition Dataset for 22 Indian Languages},
volume={40},
url={https://ojs.aaai.org/index.php/AAAI/article/view/40405},
DOI={10.1609/aaai.v40i37.40405},
number={37},
journal={Proceedings of the AAAI Conference on Artificial Intelligence},
author={Kaushik, Prachuryya and Anand, Ashish},
year={2026},
month={Mar.},
pages={31410-31418}
}
@misc{kaushik2026awedpiperagentswebapplications,
title={AWED-PIPER: Agents, Web Applications & Expert Detectors for Personally Identifiable Information Protection & Fine-grained Named Entity Recognition across 36 languages for 6.6 Billion Speakers},
author={Prachuryya Kaushik and Ashish Anand},
year={2026},
eprint={2601.10161},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2601.10161},
}
@inproceedings{ding-etal-2021-nerd,
title = "Few-{NERD}: A Few-shot Named Entity Recognition Dataset",
author = "Ding, Ning and Xu, Guangwei and Chen, Yulin and Wang, Xiaobin and Han, Xu and Xie, Pengjun and Zheng, Haitao and Liu, Zhiyuan",
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)",
month = aug,
year = "2021",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.acl-long.248",
doi = "10.18653/v1/2021.acl-long.248",
pages = "3198--3213",
}