Update README.md

README.md

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 - "f1"
 
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+
+# Spanish RoBERTa-base trained on BNE finetuned for CAPITEL Named Entity Recognition (NER) dataset.
+RoBERTa-large-bne is a transformer-based masked language model for the Spanish language. It is based on the [RoBERTa](https://arxiv.org/abs/1907.11692) large model and has been pre-trained using the largest Spanish corpus known to date, with a total of 570GB of clean and deduplicated text processed for this work, compiled from the web crawlings performed by the  [National Library of Spain (Biblioteca Nacional de España)](http://www.bne.es/en/Inicio/index.html) from 2009 to 2019.
+
+Original pre-trained model can be found here: https://huggingface.co/BSC-TeMU/roberta-base-bne
+
+## Dataset
+The dataset used is the one from the [CAPITEL competition at IberLEF 2020](https://sites.google.com/view/capitel2020) (sub-task 1).
+
+## Evaluation and results
+F1 Score: 0.8998
+
+For evaluation details visit our [GitHub repository](https://github.com/PlanTL-SANIDAD/lm-spanish).
+
+## Citing 
+Check out our paper for all the details: https://arxiv.org/abs/2107.07253
+```
+@misc{gutierrezfandino2021spanish,
+      title={Spanish Language Models}, 
+      author={Asier Gutiérrez-Fandiño and Jordi Armengol-Estapé and Marc Pàmies and Joan Llop-Palao and Joaquín Silveira-Ocampo and Casimiro Pio Carrino and Aitor Gonzalez-Agirre and Carme Armentano-Oller and Carlos Rodriguez-Penagos and Marta Villegas},
+      year={2021},
+      eprint={2107.07253},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```