Update README.md

README.md

@@ -47,7 +47,7 @@ pretty_name: Databrick Dolly Instructions Multilingual
 size_categories:
 - 10K<n<100K
 ---
-# Dataset Card for "databricks-dolly-15k-multilingual"
+# Dataset Card for "databricks-dolly-15k-curated-multilingual"
 
 ## Table of Contents
 - [Table of Contents](#table-of-contents)
@@ -84,12 +84,19 @@ size_categories:
 
 ### Dataset Summary
 
-This collection of datasets are machine-translated (and soon curated) versions of the `databricks-dolly-15k` [dataset](https://github.com/databrickslabs/dolly/tree/master/data) originally created by Databricks, Inc. in 2023.
+This dataset collection is a curated and machine-translated version of the `databricks-dolly-15k` [dataset](https://github.com/databrickslabs/dolly/tree/master/data) originally created by Databricks, Inc. in 2023.
 
-The goal is to give practitioners a starting point for training open-source instruction-following models beyond English. However, as the translation quality will not be perfect, we highly recommend dedicating time to curate and fix translation issues. Below we explain how to load the datasets into [Argilla for data curation and fixing](https://github.com/argilla-io/argilla). Additionally, we'll be improving the datasets made available here, with the help of different communities.
+The goal is to give practitioners a starting point for training open-source instruction-following models with better-quality English data and translated data beyond English. However, as the translation quality will not be perfect, we highly recommend dedicating time to curate and fix translation issues. Below we explain how to load the datasets into [Argilla for data curation and fixing](https://github.com/argilla-io/argilla). Additionally, we'll be improving the datasets made available here, with the help of different communities.
 
-**We highly recommend dataset curation beyond proof-of-concept experiments.**
 
+Currently, the original English version has been curated combining automatic processing and collaborative human curation using Argilla (~400 records have been manually edited and fixed). The following graph shows a summary about the number of edited fields.
+
+![Edited records](edited_records.png)
+
+As a result of this curation process the content of the fields have been reduced, counted in number of tokens, especially for the responses:
+
+
+![Edited records](token_diff.png)
 
 If you want to browse and curate your dataset with Argilla, you can:
 
@@ -105,10 +112,10 @@ There's one split per language:
 from datasets import load_dataset
 
 # loads all splits
-load_dataset("argilla/databricks-dolly-15k-multilingual")
+load_dataset("argilla/databricks-dolly-15k-curate-multilingual")
 
 # loads Spanish splits
-load_dataset("argilla/databricks-dolly-15k-multilingual", split="es")
+load_dataset("argilla/databricks-dolly-15k-curated-multilingual", split="es")
 
 ```