adding some descriptions

README.md

@@ -2,13 +2,30 @@
 language:
 - ca
 ---
-# Dataset Card for Instrucat_v2
+# Dataset Card for Instrucat
 
 ## Dataset Description
 
 ### Dataset Summary
 InstruCat is a dataset consisting of 223445 instructions in Catalan.
 
+### Dataset contains data converted to instructions format from the following datasets:
+- caBreu : The instructions were created in form of summarization tasks. There are 2 types of summarization categories in the dataset: extreme and abstractive. The extreme one summarizes text into one sentence and the abstractive into shorter texts around 3-5 sentences.
+- CaSERa : The instructions were created in form of multilabel classification tasks, where the labels are a given set of emotions present or absent in the texts.
+- CatalanQA : The instructions correspond to questions in CatalanQA.
+- CaWikiTC : The instructions were created in 2 different ways of text classification tasks with the distribution 70% - 30%. The first way is to define a category of a given text. The second way is to answer where a given text belongs to a certain category in a form of alternative question.
+- ceil : The instructions were created in 2 different ways of Named Entity Recognition tasks with the distribution 70% - 30%. The first way is to list all the found Named Entities. The second way is to list only Named Entities of a particular category.  
+- CoqCat : The instructions correspond to the first questions of CoqCat conversations. 
+- GuiaCat : The instructions were created in form of sentiment analysis tasks.
+- IntoxiCat : The instructions were created in form of binary classification tasks. The task is to define wether a given text is toxic or no.
+- Parafraseja : The instructions were created in form of text generation tasks. The task is to generate a text equivalent by meaning to a given text.
+- PAWS-ca : The instructions were created in form of text generation tasks. The task is to generate a text equivalent by meaning to a given text.
+- sts-ca : The instructions were created in form of text generation tasks. The task is to generate a text equivalent by meaning to a given text.
+- teca : The instructions were created in 2 different ways with the distribution 70% - 30%. The first way is in form of entailment generation tasks. The second way is to define whether one given text is an entailment of another given text. 
+- WikiCat : The instructions were created in 2 different ways of text classification tasks with the distribution 70% - 30%. The first way is to define a category of a given text. The second way is to answer where a given text belongs to a certain category in a form of alternative question.
+
+## Dataset Structure
+
 #### Data Splits
 - train.jsonl: 169025 instructions
 - validation.jsonl: 26695 instructions
@@ -30,24 +47,7 @@ An example of 'test' looks as follows:
 }
 ```
 
-#### Dataset contains data converted to instructions format from the following datasets:
-- caBreu
-- CatalanQA
-- CoqCat
-- GuiaCat
-- IntoxiCat
-- Parafraseja
-- PAWS-ca
-- sts-ca
-- WikiCat
-- CaWikiTC
-- teca
-- CaSERa
-- ceil
-
-
-
-#### Category Distibution
+### Category Distibution
 | Category | Number of instructions |% |
 |----------------|----------|------ |
 | ner | 59410 | 26.58% |