Update README.md

README.md

@@ -4,19 +4,29 @@ language:
 license:
 - cc-by-nc-4.0
 size_categories:
-- 10K<n<100K
+- 1M<n<10M
 task_categories:
 - summarization
 tags:
 - textual-simplification
+- DFP
+- french prompts
+annotations_creators:
+- found
+language_creators:
+- found
+multilinguality:
+- monolingual
+source_datasets:
+- bisect
 ---
 
 # bisect_fr_prompt_textual_simplification
 ## Summary
 
-**bisect_fr_prompt_textual_simplification** is a subset of the [**Dataset of French Prompts (DFP)**]().
-It contains **X** rows that can be used for a textual simplification task.
-The original data (without prompts) comes from the dataset [BiSECT](https://huggingface.co/datasets/GEM/BiSECT) by Kim et al. where only the French part has been kept.
+**bisect_fr_prompt_textual_simplification** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).  
+It contains **9,889,420** rows that can be used for a textual simplification task.  
+The original data (without prompts) comes from the dataset [BiSECT](https://huggingface.co/datasets/GEM/BiSECT) by Kim et al. where only the French part has been kept.  
 A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the [xP3](https://huggingface.co/datasets/bigscience/xP3) dataset by Muennighoff et al.
 
 
@@ -57,9 +67,9 @@ targets = bisect['train'][i]['target'].replace(' . ','. ').replace(' .','. ').re
 
 
 # Splits
-- train with X samples
-- dev with Y samples
-- test with Z samples
+- `train` with 9,820,700 samples
+- `valid` with 20,720 samples
+- `test` with 48,000 samples
 
 
 # How to use?
@@ -82,3 +92,6 @@ dataset = load_dataset("CATIE-AQ/bisect_fr_prompt_textual_simplification")
 ## This Dataset
 
 
+
+## License
+cc-by-nc-4.0