Update README.md

README.md

@@ -175,4 +175,82 @@ language:
 pretty_name: CrawlPT (deduplicated)
 size_categories:
 - 10M<n<100M
----
+---
+
+# CrawlPT (deduplicated)
+
+CrawlPT is a generic Portuguese corpus extracted from various web pages.
+
+## Dataset Details
+
+Dataset is composed by three corpora:
+[brWaC](https://aclanthology.org/L18-1686/), [C100-PT](https://arxiv.org/abs/1911.02116), [OSCAR-2301](http://arxiv.org/abs/2201.06642).
+
+- **brWaC**: a web corpus for Brazilian Portuguese from 120,000 different websites.
+- **C100-PT**: Portuguese subset from CC-100. C100 was created for training the multilingual Transformer XLM-R, containing two terabytes of cleaned data from 2018 snapshots of the [Common Crawl project](\url{https://commoncrawl.org/about/) in 100 languages.  We use the , which contains 49.1 GiB of text.
+- **OSCAR-2301-PT**: curation from OSCAR-2301 in the Portuguese language.
+
+  ### Dataset Description
+
+- **Curated by:** [More Information Needed]
+- **Funded by:** [More Information Needed]
+- **Language(s) (NLP):** Brazilian Portuguese (pt-BR)
+- **License:** [Creative Commons Attribution 4.0 International Public License](https://creativecommons.org/licenses/by/4.0/deed.en)
+
+### Dataset Sources
+
+- **Repository:** https://github.com/eduagarcia/roberta-legal-portuguese
+- **Paper:** [More Information Needed]
+
+## Dataset Structure
+
+<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+
+[More Information Needed]
+
+## Data Collection and Processing
+
+Raw corpora sizes in terms of billions of tokens and file size in GiB:
+
+| Corpus          |  Domain | Tokens (B) | Size (GiB) |
+|-----------------|:-------:|:----------:|:----------:|
+| brWaC           | General |     2.7    |    16.3    |
+| CC100 (PT)      | General |     8.4    |    49.1    |
+| OSCAR-2301 (PT) | General |    18.1    |    97.8    |
+
+
+CrawlPT is deduplicated using [MinHash algorithm](https://dl.acm.org/doi/abs/10.5555/647819.736184) and [Locality Sensitive Hashing](https://dspace.mit.edu/bitstream/handle/1721.1/134231/v008a014.pdf?sequence=2&isAllowed=y), following the approach of [Lee et al. (2022)](http://arxiv.org/abs/2107.06499).
+
+We used 5-grams and a signature of size 256, considering two documents to be identical if their Jaccard Similarity exceeded 0.7.
+Deduplicate rate found by the Minhash-LSH algorithm  for the CrawlPT corpus:
+
+| Corpus                 |  Documents | Docs. after deduplicatio} | Duplicates (%) |
+|------------------------|:----------:|:-------------------------:|:--------------:|
+| brWaC                  |  3,530,796 |         3,513,588         |      0.49      |
+| OSCAR-2301 (PT Subset) | 18,031,400 |         10,888,966        |      39.61     |
+| CC100 (PT Subset)      | 38,999,388 |         38,059,979        |      2.41      |
+| Total (CrawlPT)        | 60,561,584 |         52,462,533        |      13.37     |
+
+
+## Citation
+
+```bibtex
+@InProceedings{garcia2024_roberlexpt,
+    author="Garcia, Eduardo A. S.
+    and Silva, N{\'a}dia F. F.
+    and Siqueira, Felipe
+    and Gomes, Juliana R. S.
+    and Albuqueruqe, Hidelberg O.
+    and Souza, Ellen
+    and Lima, Eliomar
+    and De Carvalho, André",
+    title="RoBERTaLexPT: A Legal RoBERTa Model pretrained with deduplication for Portuguese",
+    booktitle="Computational Processing of the Portuguese Language",
+    year="2024",
+    publisher="Association for Computational Linguistics"
+}
+```
+
+## Acknowledgment
+
+This work has been supported by the AI Center of Excellence (Centro de Excelência em Inteligência Artificial – CEIA) of the Institute of Informatics at the Federal University of Goiás (INF-UFG).