Update README.md

README.md

@@ -1,3 +1,73 @@
 ---
-license: other
+annotations_creators:
+- no-annotation
+language:
+- pt
+license:
+- other
+multilinguality:
+- monolingual
+pretty_name: ParlamentoPT
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text-generation
+- fill-mask
+task_ids:
+- language-modeling
+- masked-language-modeling
+tags:
+- parlamentopt
+- parlamento
+- albertina-pt*
+- albertina-ptpt
+- albertina-ptbr
+- fill-mask
+- bert
+- deberta
+- portuguese
+- encoder
+- foundation model
 ---
+
+# Dataset Card for ParlamentoPT
+
+### Dataset Summary
+
+The ParlamentoPT data set was obtained by collecting publicly available documents containing transcriptions of debates in the Portuguese Parliament.
+The data was collected from the Portuguese Parliament portal in accordance with its [open data policy](https://www.parlamento.pt/Cidadania/Paginas/DadosAbertos.aspx).
+
+
+This dataset was collected with the purpose of creating the [Albertina-PT*](https://huggingface.co/PORTULAN/albertina-ptpt) language model, and it serves as training data for model development. 
+The development of the model is a collaborative effort between the University of Lisbon and the University of Porto in Portugal
+
+</br>
+
+# Citation
+
+When using or citing this data set, kindly cite the following publication:
+
+``` latex
+@misc{albertina-pt,
+      title={Advancing Neural Encoding of Portuguese
+             with Transformer Albertina PT-*}, 
+      author={João Rodrigues and Luís Gomes and João Silva and
+              António Branco and Rodrigo Santos and
+              Henrique Lopes Cardoso and Tomás Osório},
+      year={2023},
+      eprint={?},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+<br>
+
+# Acknowledgments
+
+The research reported here was partially supported by: PORTULAN CLARIN—Research Infrastructure for the Science and Technology of Language,
+funded by Lisboa 2020, Alentejo 2020 and FCT—Fundação para a Ciência e Tecnologia under the
+grant PINFRA/22117/2016; research project ALBERTINA - Foundation Encoder Model for Portuguese and AI, funded by FCT—Fundação para a Ciência e Tecnologia under the
+grant CPCA-IAC/AV/478394/2022; innovation project ACCELERAT.AI - Multilingual Intelligent Contact Centers, funded by IAPMEI, I.P. - Agência para a Competitividade e Inovação under the grant C625734525-00462629, of Plano de Recuperação e Resiliência, call RE-C05-i01.01 – Agendas/Alianças Mobilizadoras para a Reindustrialização; and LIACC - Laboratory for AI and Computer Science, funded by FCT—Fundação para a Ciência e Tecnologia under the grant FCT/UID/CEC/0027/2020.