Update README.md

README.md

@@ -28,8 +28,10 @@ task_ids:
 
 ## Dataset Description
 
-- **Homepage:** [Projecte AINA](https://projecteaina.cat/)
+- **Homepage:** [Projecte AINA](https://huggingface.co/projecte-aina)
+- **Repository**: [HuggingFace](https://huggingface.co/datasets/projecte-aina/CATalog)
 - **Paper:** ["A CURATEd CATalog: Rethinking the Extraction of Pretraining Corpora for Mid-Resourced Languages"]()
+- **Leaderboard**: N/A
 - **Point of Contact:** [Language Technologies Unit at Barcelona Supercomputing Center (BSC)]([email protected])
 
 ### Dataset Summary
@@ -40,7 +42,7 @@ CATalog is a diverse, open-source Catalan corpus for language modelling. It cons
 
 - `Fill-Mask`
 - `Text Generation`
-- `other:Language-Modelling`: The dataset is suitable for training a model in Language Modelling, predicting the next word in a given context. Success is measured by achieving a low [Perplexity](https://huggingface.co/spaces/evaluate-metric/perplexity)score, indicating the model's proficiency in accurately predicting subsequent words.
+- `other:Language-Modelling`: The dataset is suitable for training a model in Language Modelling, predicting the next word in a given context. Success is measured by achieving a low [Perplexity](https://huggingface.co/spaces/evaluate-metric/perplexity) score, indicating the model's proficiency in accurately predicting subsequent words.
 - `other:Masked-Language-Modelling`: The dataset is designed for training models in Masked Language Modelling. This task involves predicting masked or hidden words within a sentence. Success is typically measured by achieving a high performance score, such as accuracy or [F1](https://huggingface.co/spaces/evaluate-metric/f1) score, on correctly predicting the masked tokens.
 
 ### Languages