Update README.md

README.md

@@ -20,7 +20,6 @@ dataset_info:
   dataset_size: 2042850034
 task_categories:
 - summarization
-- question-answering
 language:
 - en
 - de
@@ -28,18 +27,27 @@ language:
 - it
 - es
 size_categories:
-- 1M<n<10M
+- 100K<n<1M
+license: apache-2.0
+tags:
+- chemistry
+- biology
 ---
-# Dataset Card for "sumstew-16k"
+# Dataset Card for "sumstew"
+
+## TL;DR: 
+
+Sumstew is a abstractive, multilingual Dataset, with a balanced number of samples from a diverse set of summarization Datasets. The input sizes range up to 8192 tokens.
+Filtered using a diverse set of heuristics to encourage high coverage, accuracy and factual consistency. Code to reproduce Dataset available at *TODO*
 
 ## Dataset Description
 
 - **Dataset Identifier**: sumstew
-- **Dataset Summary**: "SumStew" is a rich multilingual dataset for text summarization and question answering tasks. It incorporates diverse data sources such as cnn_dailymail, samsum, mlsum (de, fr, es, it), klexikon, xlsum (fr, en, es), govreport, sciqa, piqa, pumbed_qa, multinews, laysum, booksum, dialogsum, fanpage (it), ilpost (it). This data has been curated by filtering based on n-gram overlap between the source and target documents and normalized to prevent undue bias. Every instance in this dataset is prefixed by an instruction (title, summary, or qa).
+- **Dataset Summary**: "SumStew" is a rich multilingual dataset for text summarization. It incorporates diverse data sources such as cnn_dailymail, samsum, mlsum (de, fr, es, it), klexikon, xlsum (fr, en, es), govreport, sciqa, piqa, pumbed_qa, multinews, laysum, booksum, dialogsum, fanpage (it), ilpost (it). This data has been curated by filtering based on n-gram overlap between the source and target documents and normalized to prevent undue bias. Every instance in this dataset is prefixed by an instruction (title, summary, or qa).
 
 ## Task Information
 
-- **Task Categories**: The tasks covered by this dataset are primarily summarization and question-answering tasks.
+- **Task Categories**: The tasks covered by this dataset are primarily summarization tasks.
 - **Languages**: This dataset supports multiple languages including English (en), German (de), French (fr), Italian (it), and Spanish (es).
 
 ## Dataset Structure
@@ -47,19 +55,15 @@ size_categories:
 - **Data Instances**: Each data instance in the dataset comprises five fields - 'prompt', 'target', 'task', 'subset', and 'language'.
     - 'prompt': The input text for the task. (dtype: string)
     - 'target': The expected output for the task. (dtype: string)
-    - 'task': The type of task to be performed. (dtype: string)
     - 'subset': The subset of the dataset the instance belongs to. (dtype: string)
     - 'language': The language of the instance. (dtype: string)
 
 - **Data Splits**: The dataset is split into two subsets:
-    - 'Train' set: 1,278,891 examples (5,017,100,271 bytes)
-    - 'Validation' set: 78,903 examples (328,807,241 bytes)
+    - 'Train' set: 314114 examples
+    - 'Validation' set: 11143 examples
 
 ## Dataset Statistics
 
-- **Dataset Size Categories**: The total dataset size falls in the range of 1M<n<10M.
-- **Download Size**: 3,460,794,602 bytes
-- **Total Dataset Size**: 5,345,907,512 bytes
 - **Max Document Length**: The maximum document length is 8192 mlong-t5 tokens.
 - **Max Output Length**: The maximum output length is 1024 mlong-t5 tokens.