Update README.md

README.md

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----
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: label
-    dtype: string
-  - name: prompts
-    list:
-    - name: text
-      dtype: string
-  - name: prompt_templates
-    sequence: string
-  - name: metadata
-    struct:
-    - name: language
-      dtype: string
-    - name: url
-      dtype: string
-    - name: title
-      dtype: string
-  splits:
-  - name: id
-    num_bytes: 322112
-    num_examples: 100
-  - name: id_fewshot
-    num_bytes: 5963
-    num_examples: 5
-  - name: ta
-    num_bytes: 1075514
-    num_examples: 100
-  - name: ta_fewshot
-    num_bytes: 10198
-    num_examples: 5
-  - name: th
-    num_bytes: 1201794
-    num_examples: 100
-  - name: th_fewshot
-    num_bytes: 8735
-    num_examples: 5
-  - name: vi
-    num_bytes: 395697
-    num_examples: 100
-  - name: vi_fewshot
-    num_bytes: 9092
-    num_examples: 5
-  download_size: 1258846
-  dataset_size: 3029105
-configs:
-- config_name: default
-  data_files:
-  - split: id
-    path: data/id-*
-  - split: id_fewshot
-    path: data/id_fewshot-*
-  - split: ta
-    path: data/ta-*
-  - split: ta_fewshot
-    path: data/ta_fewshot-*
-  - split: th
-    path: data/th-*
-  - split: th_fewshot
-    path: data/th_fewshot-*
-  - split: vi
-    path: data/vi-*
-  - split: vi_fewshot
-    path: data/vi_fewshot-*
----
+---
+pretty_name: SEA Abstractive Summarization
+license:
+- cc-by-nc-sa-4.0
+task_categories:
+- text-generation
+language:
+- id
+- ta
+- th
+- vi
+dataset_info:
+  features:
+  - name: id
+    dtype: string
+  - name: label
+    dtype: string
+  - name: prompts
+    list:
+    - name: text
+      dtype: string
+  - name: prompt_templates
+    sequence: string
+  - name: metadata
+    struct:
+    - name: language
+      dtype: string
+    - name: url
+      dtype: string
+    - name: title
+      dtype: string
+  splits:
+  - name: id
+    num_bytes: 322112
+    num_examples: 100
+    num_tokens_gpt_4o: 61628
+    num_tokens_gemma_2: 55485
+    num_tokens_llama_3: 77016
+  - name: id_fewshot
+    num_bytes: 5963
+    num_examples: 5
+    num_tokens_gpt_4o: 1124
+    num_tokens_gemma_2: 1050
+    num_tokens_llama_3: 1430
+  - name: ta
+    num_bytes: 1075514
+    num_examples: 100
+    num_tokens_gpt_4o: 114275
+    num_tokens_gemma_2: 156476
+    num_tokens_llama_3: 457559
+  - name: ta_fewshot
+    num_bytes: 10198
+    num_examples: 5
+    num_tokens_gpt_4o: 964
+    num_tokens_gemma_2: 1339
+    num_tokens_llama_3: 3905
+  - name: th
+    num_bytes: 1201794
+    num_examples: 100
+    num_tokens_gpt_4o: 155203
+    num_tokens_gemma_2: 151988
+    num_tokens_llama_3: 176985
+  - name: th_fewshot
+    num_bytes: 8735
+    num_examples: 5
+    num_tokens_gpt_4o: 925
+    num_tokens_gemma_2: 869
+    num_tokens_llama_3: 1062
+  - name: vi
+    num_bytes: 395697
+    num_examples: 100
+    num_tokens_gpt_4o: 86305
+    num_tokens_gemma_2: 78285
+    num_tokens_llama_3: 82269
+  - name: vi_fewshot
+    num_bytes: 9092
+    num_examples: 5
+    num_tokens_gpt_4o: 2396
+    num_tokens_gemma_2: 2170
+    num_tokens_llama_3: 2282
+  download_size: 1258846
+  dataset_size: 3029105
+  total_tokens_gpt_4o: 422820
+  total_tokens_gemma_2: 447662
+  total_tokens_llama_3: 802508
+configs:
+- config_name: default
+  data_files:
+  - split: id
+    path: data/id-*
+  - split: id_fewshot
+    path: data/id_fewshot-*
+  - split: ta
+    path: data/ta-*
+  - split: ta_fewshot
+    path: data/ta_fewshot-*
+  - split: th
+    path: data/th-*
+  - split: th_fewshot
+    path: data/th_fewshot-*
+  - split: vi
+    path: data/vi-*
+  - split: vi_fewshot
+    path: data/vi_fewshot-*
+size_categories:
+- n<1K
+---
+
+# SEA Abstractive Summarization
+
+SEA Abstractive Summarization evaluates a model's ability to read a document, identify the key points within, and summarize them into a coherent and fluent text while paraphrasing the document. It is sampled from [XL-Sum](https://aclanthology.org/2021.findings-acl.413/) for Indonesian, Tamil, Thai, and Vietnamese.
+
+### Supported Tasks and Leaderboards
+
+SEA Abstractive Summarization is designed for evaluating chat or instruction-tuned large language models (LLMs). It is part of the [SEA-HELM](https://leaderboard.sea-lion.ai/) leaderboard from [AI Singapore](https://aisingapore.org/).
+
+### Languages
+- Indonesian (id)
+- Tamil (ta)
+- Thai (th)
+- Vietnamese (vi)
+
+### Dataset Details
+SEA Abstractive Summarization is split by language, with additional splits containing fewshot examples. Below are the statistics for this dataset. The number of tokens only refer to the strings of text found within the `prompts` column.
+
+| Split | # of examples | # of GPT-4o tokens | # of Gemma 2 tokens | # of Llama 3 tokens |
+|-|:-|:-|:-|:-|
+| id | 100 | 61628 | 55485 | 77016 |
+| ta | 100 | 114275 | 156476 | 457559 |
+| th | 100 | 155203 | 151988 | 176985 |
+| vi | 100 | 86305 | 78285 | 82269 |
+| id_fewshot | 5 | 1124 | 1050 | 1430 |
+| ta_fewshot | 5 | 964 | 1339 | 3905 |
+| th_fewshot | 5 | 925 | 869 | 1062 |
+| vi_fewshot | 5 | 2396 | 2170 | 2282 |
+| **total** | 420 | 422820 | 447662 | 802508 |
+
+### Data Sources
+
+| Data Source | License | Language/s | Split/s
+|-|:-|:-| :-|
+| [XL-Sum](https://huggingface.co/datasets/csebuetnlp/xlsum) | [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) | Indonesian, Tamil, Thai, Vietnamese | id, id_fewshot, ta, ta_fewshot, th, th_fewshot, vi, vi_fewshot
+
+### License
+
+For the license/s of the dataset/s, please refer to the data sources table above.
+
+We endeavor to ensure data used is permissible and have chosen datasets from creators who have processes to exclude copyrighted or disputed data. 
+
+
+### References
+
+```bibtex
+@inproceedings{hasan-etal-2021-xl,
+    title = "{XL}-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages",
+    author = "Hasan, Tahmid  and
+      Bhattacharjee, Abhik  and
+      Islam, Md. Saiful  and
+      Mubasshir, Kazi  and
+      Li, Yuan-Fang  and
+      Kang, Yong-Bin  and
+      Rahman, M. Sohel  and
+      Shahriyar, Rifat",
+    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
+    month = aug,
+    year = "2021",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2021.findings-acl.413",
+    pages = "4693--4703",
+}
+
+@misc{leong2023bhasaholisticsoutheastasian,
+      title={BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models}, 
+      author={Wei Qi Leong and Jian Gang Ngui and Yosephine Susanto and Hamsawardhini Rengarajan and Kengatharaiyer Sarveswaran and William Chandra Tjhi},
+      year={2023},
+      eprint={2309.06085},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2309.06085}, 
+}
+```