updated stats with nlucat

README.md

@@ -7,7 +7,7 @@ language:
 ## Dataset Description
 
 ### Dataset Summary
-InstruCat is a dataset consisting of 223445 instructions in Catalan.
+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.
@@ -18,6 +18,7 @@ InstruCat is a dataset consisting of 223445 instructions in Catalan.
 - 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.
+- NLUCat : The instructions were created in form of phrase generation tasks to express a given intent.
 - 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.
@@ -27,9 +28,9 @@ InstruCat is a dataset consisting of 223445 instructions in Catalan.
 ## Dataset Structure
 
 #### Data Splits
-- train.jsonl: 169025 instructions
-- validation.jsonl: 26695 instructions
-- test.jsonl: 27725 instructions
+- train.jsonl: 178044 instructions
+- validation.jsonl: 28125 instructions
+- test.jsonl: 29149 instructions
 
 ### Data Instances
 
@@ -50,14 +51,15 @@ An example of 'test' looks as follows:
 ### Category Distibution
 | Category | Number of instructions |% |
 |----------------|----------|------ |
-| ner | 59410 | 26.58% |
-| paraphrasis | 34695 | 15.52% |
-| text_classification | 33393 | 14.94% |
-| toxicity | 29809 | 13.34% |
-| qa | 27427 | 12.27% |
-| emotion_detection | 18492 | 8.27% |
-| entailment_generation | 6354 | 2.84% |
-| sentiment_analysis | 5750 | 2.57% |
-| abstractive_summarization | 2999 | 1.34% |
-| extreme_summarization | 2999 | 1.34% |
-| entailment | 2117 | 0.94% |
+| 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% |