Update README.md

README.md

@@ -4,7 +4,6 @@ language:
 license: apache-2.0
 tags:
 - "catalan"
-- "bne"
 - "qa"
 datasets:
 - "xquad-ca"
@@ -17,18 +16,18 @@ metrics:
 
 # Catalan RoBERTa-base (BERTa) finetuned for Question Answering on the viquiquad dataset.
 
-The roberta-base-ca-cased-qa is a Question Answering (QA) 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).
+The **roberta-base-ca-cased-qa** is a Question Answering (QA) 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).
 
-## Dataset
-The dataset used is a QA dataset in Catalan called [viquiquad](https://huggingface.co/datasets/projecte-aina/viquiquad). 
-
-## Fine-tuning
-TODO
+## Datasets
+We used the QA dataset in Catalan called [ViquiQuAD](https://huggingface.co/datasets/projecte-aina/viquiquad) for training and evaluation, and the [XQuAD-ca](https://huggingface.co/datasets/projecte-aina/xquad-ca) test set for evaluation.
 
 ## Evaluation and results
-TODO
 
-For the fine-tuning and evaluation details visit the official [GitHub repository]().
+| Task        | QA (ViquiQuAD) (F1/EM)  | QA (XQuAD-ca) (F1/EM) | 
+| ------------|:------|:----|
+| BERTa       | **86.99/73.25** | **67.81/49.43** |
+
+For more details, check the fine-tuning and evaluation scripts in the official [GitHub repository](https://github.com/projecte-aina/berta).
 
 
 ## Citing 
@@ -63,7 +62,7 @@ TODO
 
 The models published in this repository are intended for a generalist purpose and are available to third parties. These models may have bias and/or any other undesirable distortions.
 
-When third  parties, deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of artificial intelligence.
+When third parties, deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of artificial intelligence.
 
 In no event shall the owner of the models (SEDIA – State Secretariat for digitalization and artificial intelligence) nor the creator (BSC – Barcelona Supercomputing Center) be liable for any results arising from the use made by third parties of these models.