--- 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} }