---
license: mit
language:
- as
base_model:
- google/muril-large-cased
pipeline_tag: token-classification
tags:
- NER
- Named_Entity_Recognition
pretty_name: CLASSER Assamese MuRIL
datasets:
- prachuryyaIITG/CLASSER
metrics:
- f1
- precision
- recall
---
**MuRIL is fine-tuned on Assamese [CLASSER](https://huggingface.co/datasets/prachuryyaIITG/CLASSER) dataset for Fine-grained Named Entity Recognition.**
The tagset of [MultiCoNER2](https://huggingface.co/datasets/MultiCoNER/multiconer_v2) is a fine-grained tagset. The fine to coarse level mapping of the tags are 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: 74.88
Recall: 75.62
**F1: 75.25**
## Training Parameters:
Epochs: 6
Optimizer: AdamW
Learning Rate: 5e-5
Weight Decay: 0.01
Batch Size: 64
## Citation
If you use this model, please cite the following papers:
```bibtex
@inproceedings{kaushik2025classer,
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},
year = {2025},
publisher = {Association for Computational Linguistics},
note = {Main conference paper}
}
@inproceedings{kaushik2026sampurner,
title={SampurNER: Fine-grained Named Entity Recognition Dataset for 22 Indian Languages},
author={Kaushik, Prachuryya and Anand, Ashish},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={40},
year={2026}
}
@inproceedings{fetahu2023multiconer,
title={MultiCoNER v2: a Large Multilingual dataset for Fine-grained and Noisy Named Entity Recognition},
author={Fetahu, Besnik and Chen, Zhiyu and Kar, Sudipta and Rokhlenko, Oleg and Malmasi, Shervin},
booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
pages={2027--2051},
year={2023}
}