Update README.md

README.md

@@ -4,13 +4,13 @@ language:
 
 - ca
 
-license: 
+license: ???
 
 tags:
 
 - "catalan"
 
-- "part of speech"
+- "part of speech tagging"
 
 - "pos"
 
@@ -20,20 +20,76 @@ tags:
 
 datasets:
 
-- "projecte-aina/???"  
+- "universal_dependencies"  
 
 metrics:
 
-- "???"
+- f1
+
+model-index:
+- name: roberta-base-ca-cased-pos
+  results:
+  - task: 
+      type: token-classification 
+    dataset:
+      type:   universal_dependencies
+      name: ancora-ca-pos
+    metrics:
+      - type: f1
+        value: 0.9893832385244624
 
 widget:
 
-- text: "El gat menja peix." 
+- text: "Em dic Lluïsa i visc a Santa Maria del Camí." 
 
-- text: "Plou i fa sol, les bruixes es pentinen."
+- text: "L'Aina, la Berta i la Norma són molt amigues."
 
-- text: "El tren pinxo de Banyoles és el més bonic que hi ha."
+- text: "El Martí llegeix el Cavall Fort."
 
 ---
 
-# Catalan RoBERTa-base trained on Catalan Textual Corpus fine-tuned for Part-of-speech tagging.
+# Catalan BERTa (RoBERTa-base) finetuned for Named Entity Recognition.
+
+The **roberta-base-ca-cased-pos** is a Named Entity Recognition (NER) model for the Catalan language fine-tuned from the [BERTa](https://huggingface.co/PlanTL-GOB-ES/roberta-base-ca) model, a [RoBERTa](https://arxiv.org/abs/1907.11692) base model pre-trained on a medium-size corpus collected from publicly available corpora and crawlers (check the BERTa model card for more details).
+
+## Datasets
+We used the POS dataset in Catalan from the [Universal Dependencies Treebank](https://huggingface.co/datasets/universal_dependencies) we refer to _Ancora-ca-pos_ for training and evaluation.
+
+## Evaluation and results
+We evaluated the _roberta-base-ca-cased-tc_ on the Ancora-ca-ner test set against standard multilingual and monolingual baselines:
+
+| Model        | Ancora-ca-pos (F1)   | 
+| ------------|:-------------|
+| roberta-base-ca-cased-pos |**98.93** |
+| mBERT       | 98.82 |
+| XLM-RoBERTa | 98.89 | 
+| WikiBERT-ca | 97.60 | 
+
+For more details, check the fine-tuning and evaluation scripts in the official [GitHub repository](https://github.com/projecte-aina/berta).
+## Citing 
+If you use any of these resources (datasets or models) in your work, please cite our latest paper:
+```bibtex
+@inproceedings{armengol-estape-etal-2021-multilingual,
+    title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
+    author = "Armengol-Estap{\'e}, Jordi  and
+      Carrino, Casimiro Pio  and
+      Rodriguez-Penagos, Carlos  and
+      de Gibert Bonet, Ona  and
+      Armentano-Oller, Carme  and
+      Gonzalez-Agirre, Aitor  and
+      Melero, Maite  and
+      Villegas, Marta",
+    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
+    month = aug,
+    year = "2021",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2021.findings-acl.437",
+    doi = "10.18653/v1/2021.findings-acl.437",
+    pages = "4933--4946",
+}
+```
+## Funding
+TODO
+## Disclaimer
+TODO