Update README.md

README.md

@@ -17,7 +17,7 @@ metrics:
 
 # Model Card for Finetuned NepBertA-NER
 
-This model is a fine-tuned version of the NepBERTa model, specifically trained for Named Entity Recognition (NER) tasks in the Nepali language. It recognizes entities such as persons (PER), organizations (ORG), and locations (LOC) in Nepali text. The model has been trained on a custom dataset and supports token classification for the following entity tags:
+This model is a fine-tuned version of the **NepBERTa** model, specifically trained for Named Entity Recognition (NER) tasks in the Nepali language. It recognizes entities such as persons (PER), organizations (ORG), and locations (LOC) in Nepali text. The model has been trained on a custom dataset and supports token classification for the following entity tags:
 
 - `O` (Other)
 - `B-PER` (Beginning of a person’s name)
@@ -127,6 +127,22 @@ The model was evaluated using the seqeval metric, with the following results on
 - **Precision:** 0.86
 - **Recall:** 0.90
 
+## Citation for the Base Model
+
+If you use this model or the base model in your work, please consider citing **NepBERTa** as follows:
+
+```bibtex
+@misc{adhikari2021nepberta,
+  title={NepBERTa: A Pretrained BERT Model for the Nepali Language},
+  author={Adhikari, Bharat},
+  year={2021},
+  eprint={2109.08654},
+  archivePrefix={arXiv},
+  primaryClass={cs.CL},
+  url={https://arxiv.org/abs/2109.08654}
+}
+```
+
 ## Citation
 
 If you use this model in your research, please consider citing it: