Update README.md

README.md

@@ -14,26 +14,26 @@ widget:
 - text: "Texto de exemplo em português"
 inference: false
 ---
-# PTT5-base Reranker finetuned on both English and Portuguese MS MARCO
+# PTT5-base-msmarco-en-pt-10k-v1 Reranker finetuned on both English and Portuguese MS MARCO
 ## Introduction
-ptt5-base-msmarco-en-pt-10k is a T5-based model pretrained in the BrWac corpus, finetuned on both English and Portuguese translated version of MS MARCO passage dataset. This model was finetuned for 10k steps. 
+ptt5-base-msmarco-en-pt-10k-v1 is a T5-based model pretrained in the BrWac corpus, fine-tuned on both English and Portuguese translated version of MS MARCO passage dataset. In the version v1, the Portuguese dataset was translated using [Helsinki](https://huggingface.co/Helsinki-NLP) NMT model. This model was finetuned for 10k steps. 
 Further information about the dataset or the translation method can be found on our [**mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset**](https://arxiv.org/abs/2108.13897) and [mMARCO](https://github.com/unicamp-dl/mMARCO) repository.
 ## Usage
 ```python
 
 from transformers import T5Tokenizer, T5ForConditionalGeneration
 
-model_name = 'unicamp-dl/ptt5-base-msmarco-en-pt-10k'
+model_name = 'unicamp-dl/ptt5-base-msmarco-en-pt-10k-v1'
 tokenizer  = T5Tokenizer.from_pretrained(model_name)
 model      = T5ForConditionalGeneration.from_pretrained(model_name)
 
 ```
 # Citation
-If you use ptt5-base-msmarco-en-pt-10k, please cite:
+If you use ptt5-base-msmarco-en-pt-10k-v1, please cite:
 
     @misc{bonifacio2021mmarco,
       title={mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset}, 
-      author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
+      author={Luiz Henrique Bonifacio and Vitor Jeronymo and Hugo Queiroz Abonizio and Israel Campiotti and Marzieh Fadaee and  and Roberto Lotufo and Rodrigo Nogueira},
       year={2021},
       eprint={2108.13897},
       archivePrefix={arXiv},