prachuryyaIITG/CLASSER_Bodo_MuRIL
016
MuRIL is fine-tuned on Bodo [CLASSER](https://huggingface.co/datasets/prachuryyaIITG/CLASSER) dataset for Fine-grained Named Entity Recognition.
Tagset Mapping
The model uses the fine-grained tagset from MultiCoNER2. The mapping from fine to coarse level tags is as follows:
- Location (LOC) : Facility, OtherLOC, HumanSettlement, Station
- Creative Work (CW) : VisualWork, MusicalWork, WrittenWork, ArtWork, Software
- Group (GRP) : MusicalGRP, PublicCORP, PrivateCORP, AerospaceManufacturer, SportsGRP, CarManufacturer, ORG
- Person (PER) : Scientist, Artist, Athlete, Politician, Cleric, SportsManager, OtherPER
- Product (PROD) : Clothing, Vehicle, Food, Drink, OtherPROD
- Medical (MED) : Medication/Vaccine, MedicalProcedure, AnatomicalStructure, Symptom, Disease
Model Performance
- Precision: 73.83
- Recall: 76.37
- F1 Score: 75.08
Training Parameters
- Epochs: 6
- Optimizer: AdamW
- Learning Rate: 5e-5
- Weight Decay: 0.01
- Batch Size: 64
Contributors
Prachuryya Kaushik and 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="अमिताभ बच्चनआ सासे मुंदांखा फावखुंगुर।",
language="Bodo"
)
print(result)Citation
If you use this model, please cite the following papers:
@inproceedings{kaushik-anand-2025-classer,
title = "{CLASSER}: Cross-lingual Annotation Projection enhancement through Script Similarity for Fine-grained Named Entity Recognition",
author = "Kaushik, Prachuryya and
Anand, Ashish",
booktitle = "Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics",
month = dec,
year = "2025",
address = "Mumbai, India",
publisher = "The Asian Federation of Natural Language Processing and The Association for Computational Linguistics",
url = "https://aclanthology.org/2025.ijcnlp-long.94/",
pages = "1745--1760",
ISBN = "979-8-89176-298-5",
}
@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{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}
}