| --- |
| base_model: |
| - google/muril-large-cased |
| datasets: |
| - DFKI-SLT/few-nerd |
| language: |
| - en |
| license: mit |
| metrics: |
| - f1 |
| - precision |
| - recall |
| pipeline_tag: other |
| tags: |
| - NER |
| - Named_Entity_Recognition |
| pretty_name: FewNERD English MuRIL |
| library_name: transformers |
| --- |
| |
| This model is an expert detector for Fine-grained Named Entity Recognition (FgNER) within the **AWED-FiNER** project. It is a fine-tuned version of `google/muril-large-cased` on the English [Few-NERD](https://huggingface.co/datasets/DFKI-SLT/few-nerd) dataset. |
|
|
| **AWED-FiNER** is presented in the paper: [AWED-FiNER: Agents, Web applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers](https://huggingface.co/papers/2601.10161). |
|
|
| Read the papers: [FewNERD in ACL-2021](https://aclanthology.org/2021.acl-long.248.pdf) , [SampurNER in AAAI-2026](https://github.com/PrachuryyaKaushik/SampurNER/blob/main/SampurNER_AAAI_extended.pdf) |
|
|
| 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: |
|
|
| * 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: 66.21 <br> |
| Recall: 69.98 <br> |
| **F1: 68.04** <br> |
|
|
| ## Training Parameters: |
| Epochs: 6 <br> |
| Optimizer: AdamW <br> |
| Learning Rate: 5e-5 <br> |
| Weight Decay: 0.01 <br> |
| Batch Size: 64 <br> |
|
|
| [**AWED-FiNER collection**](https://huggingface.co/collections/prachuryyaIITG/awed-finer) | [**Paper**](https://huggingface.co/papers/2601.10161) | [**Agentic Tool**](https://github.com/PrachuryyaKaushik/AWED-FiNER) | [**Interactive Demo**](https://huggingface.co/spaces/prachuryyaIITG/AWED-FiNER) |
|
|
| ## Sample Usage of Agentic Tool |
|
|
| The AWED-FiNER agentic tool can be used to interact with expert models trained using this framework. Below is an example: |
| ```bash |
| pip install smolagents gradio_client |
| ``` |
| ```python |
| from 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: |
|
|
| ```bibtex |
| @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", |
| } |
| |
| @misc{kaushik2026awedfiner, |
| title = {AWED-FiNER: Agents, Web Applications, and Expert Detectors for Fine-grained Named Entity Recognition across 36 Languages for 6.6 Billion Speakers}, |
| author = {Kaushik, Prachuryya and Anand, Ashish}, |
| year = {2026}, |
| note = {arXiv preprint, submitted}, |
| archivePrefix= {arXiv}, |
| eprint = {2601.10161}, |
| url = {https://arxiv.org/abs/2601.10161} |
| } |
| |
| @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} |
| } |
| ``` |
