update readme

README.md

@@ -5,10 +5,19 @@ language_creators:
   - crowdsourced
 language:
   - en
+  - es
+  - fr
+  - de
+  - ru
+  - zh
+  - ja
+  - th
+  - sw
+  - bn
 license:
   - cc-by-sa-4.0
 multilinguality:
-  - monolingual
+  - multilingua
 size_categories:
   - 1K<n<10K
 source_datasets:
@@ -16,41 +25,10 @@ source_datasets:
 task_categories:
   - text2text-generation
 task_ids: []
-paperswithcode_id: gsm8k
-pretty_name: Grade School Math 8K
+paperswithcode_id: multi-task-language-understanding-on-mgsm
+pretty_name: Multilingual Grade School Math Benchmark (MGSM)
 tags:
   - math-word-problems
-dataset_info:
-  - config_name: main
-    features:
-      - name: question
-        dtype: string
-      - name: answer
-        dtype: string
-    splits:
-      - name: train
-        num_bytes: 3963202
-        num_examples: 7473
-      - name: test
-        num_bytes: 713732
-        num_examples: 1319
-    download_size: 4915944
-    dataset_size: 4676934
-  - config_name: socratic
-    features:
-      - name: question
-        dtype: string
-      - name: answer
-        dtype: string
-    splits:
-      - name: train
-        num_bytes: 5198108
-        num_examples: 7473
-      - name: test
-        num_bytes: 936859
-        num_examples: 1319
-    download_size: 6374717
-    dataset_size: 6134967
 ---
 
 # Dataset Card for MGSM
@@ -261,22 +239,4 @@ The GSM8K dataset is licensed under the [MIT License](https://opensource.org/lic
 
 ### Contributions
 
-Thanks to [@juletx](https://github.com/juletx) for adding this dataset.
-# Multilingual Grade School Math Benchmark (MGSM)
-
-MGSM is a benchmark of grade-school math problems, proposed in the paper [Language models are multilingual chain-of-thought reasoners](http://arxiv.org/abs/2210.03057).
-
-The same 250 problems from [GSM8K](https://arxiv.org/abs/2110.14168) are each translated via human annotators in 10 languages. The 10 languages are:
-- Spanish
-- French
-- German
-- Russian
-- Chinese
-- Japanese
-- Thai
-- Swahili
-- Bengali
-- Telugu
-
-You can find the input and targets for each of the ten languages (and English) as `.tsv` files.
-We also include few-shot exemplars that are also manually translated from each language in `exemplars.py`.
+Thanks to [@juletx](https://github.com/juletx) for adding this dataset.