Datasets:

projecte-aina
/

InstruCAT

@@ -7,11 +7,10 @@ language:
 ## Dataset Description
 ### Dataset Summary
-InstruCat is a dataset consisting of 235318 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.
@@ -28,9 +27,9 @@ InstruCat is a dataset consisting of 235318 instructions in Catalan.
 ## Dataset Structure
 #### Data Splits
-- train.jsonl: 178044 instructions
-- validation.jsonl: 28125 instructions
-- test.jsonl: 29149 instructions
 ### Data Instances
@@ -51,15 +50,14 @@ An example of 'test' looks as follows:
 ### Category Distibution
 | Category | Number of instructions |% |
 |----------------|----------|------ |
-| ner | 59410 | 25.24% |
-| paraphrasis | 34695 | 14.74% |
-| text_classification | 33393 | 14.19% |
-| toxicity | 29809 | 12.66% |
-| qa | 27427 | 11.65% |
-| emotion_detection | 18492 | 7.85% |
-| phrase_generation | 11873 | 5.04% |
-| entailment_generation | 6354 | 2.70% |
-| sentiment_analysis | 5750 | 2.44% |
-| abstractive_summarization | 2999 | 1.27% |
-| extreme_summarization | 2999 | 1.27% |
-| entailment | 2117 | 0.89% |

 ## Dataset Description
 ### Dataset Summary
+InstruCat is a dataset consisting of 216826 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.
 - 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.
 ## Dataset Structure
 #### Data Splits
+- train.jsonl: 165100 instructions
+- validation.jsonl: 25351 instructions
+- test.jsonl: 26375 instructions
 ### Data Instances
 ### Category Distibution
 | Category | Number of instructions |% |
 |----------------|----------|------ |
+| ner | 59410 | 27.39% |
+| paraphrasis | 34695 | 16.00% |
+| text_classification | 33393 | 15.40% |
+| toxicity | 29809 | 13.74% |
+| qa | 27427 | 12.64% |
+| phrase_generation | 11873 | 5.47% |
+| entailment_generation | 6354 | 2.93% |
+| sentiment_analysis | 5750 | 2.65% |
+| abstractive_summarization | 2999 | 1.38% |
+| extreme_summarization | 2999 | 1.38% |
+| entailment | 2117 | 0.97% |