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license: cc-by-2.0 |
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# IndoMMLU |
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[](https://github.com/internLM/OpenCompass/) [](https://github.com/EleutherAI/lm-evaluation-harness) |
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--> |
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<p align="center"> <img src="https://raw.githubusercontent.com/fajri91/eval_picts/master/IndoMMLU-Bar.png" style="width: 100%;" id="title-icon"> |
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</p> |
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<p align="center"> <a href="http://www.fajrikoto.com" target="_blank">Fajri Koto</a>, <a href="https://www.linkedin.com/in/nuaisyah/" target="_blank">Nurul Aisyah</a>, <a href="https://haonan-li.github.io/" target="_blank">Haonan Li</a>, <a href="https://people.eng.unimelb.edu.au/tbaldwin/" target="_blank">Timothy Baldwin</a> </p> |
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<h4 align="center"> |
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<p align="center" style="display: flex; flex-direction: row; justify-content: center; align-items: center"> |
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📄 <a href="https://arxiv.org/abs/2310.04928" target="_blank" style="margin-right: 15px; margin-left: 10px">Paper</a> • |
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🏆 <a href="https://github.com/fajri91/IndoMMLU/blob/main/README_EN.md#evaluation" target="_blank" style="margin-left: 10px">Leaderboard</a> • |
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🤗 <a href="https://huggingface.co/datasets/indolem/indommlu" target="_blank" style="margin-left: 10px">Dataset</a> |
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## Introduction |
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We introduce IndoMMLU, the first multi-task language understanding benchmark for Indonesian culture and languages, |
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which consists of questions from primary school to university entrance exams in Indonesia. By employing professional teachers, |
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we obtain 14,906 questions across 63 tasks and education levels, with 46\% of the questions focusing on assessing proficiency |
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in the Indonesian language and knowledge of nine local languages and cultures in Indonesia. |
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<p align="left"> <img src="https://github.com/fajri91/eval_picts/blob/master/IndoMMLU-dist.png?raw=true" style="width: 500px;" id="title-icon"> </p> |
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## Subjects |
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| Level | Subjects | |
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| SD (Primary School) | Science, Social science, Civics, Indonesian Language, Balinese, Makassarese, Banjarese, Lampungic, Madurese, Sundanese, Javanese, Dayak Ngaju, Minangkabau culture, Art, Sports, Islam religion, Christian religion, Hindu religion | |
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| SMP (Junior High School) | Science, Social science, Civics, Indonesian Language, Balinese, Makassarese, Banjarese, Lampungic, Madurese, Sundanese, Javanese, Minangkabau culture, Art, Sports, Islam religion, Christian religion, Hindu religion | |
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| SMA (Senior High School) | Physics, Chemistry, Biology, Geography, Sociology, Economics, History, Civics, Indonesian Language, Balinese, Makassarese, Banjarese, Lampungic, Madurese, Sundanese, Javanese, Art, Sports, Islam religion, Christian religion, Hindu religion | |
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University Entrance Test | Chemistry, Biology, Geography, Sociology, Economics, History, Indonesian Language | |
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We categorize the collected questions into different subject areas, including: (1) STEM (Science, Technology, Engineering, and Mathematics); (2) Social Science; (3) Humanities; (4) Indonesian Language; and (5) Local Languages and Cultures. |
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## Examples |
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These questions are written in Indonesian. For local language subjects, some are written in the local languages. The English version is for illustrative purposes only. |
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<p align="left"> |
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<img src="https://github.com/fajri91/eval_picts/blob/master/min_example.png?raw=true" style="width: 400px;" id="title-icon"> |
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</p> |
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## Evaluation |
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We evaluate 24 multilingual LLMs of different sizes in zero-shot and few-shot settings. This includes [GPT-3.5 (ChatGPT)](https://chat.openai.com/), [XGLM](https://arxiv.org/abs/2112.10668), [Falcon](https://falconllm.tii.ae/), [BLOOMZ](https://huggingface.co/bigscience/bloomz), [mT0](https://huggingface.co/bigscience/bloomz), [LLaMA](https://arxiv.org/abs/2302.13971), and [Bactrian-X](https://github.com/mbzuai-nlp/bactrian-x). Prior to the question and multiple-choice options, we add a simple prompt in the Indonesian language: |
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``` |
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Ini adalah soal [subject] untuk [level]. Pilihlah salah satu jawaban yang dianggap benar! |
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English Translation: This is a [subject] question for [level]. Please choose the correct answer! |
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``` |
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#### Zero-shot Evaluation |
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| Model (#param) | STEM | Social Science | Humanities | Indonesian Lang. | Local L. Culture | Average | |
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|---------------------|------|----------|-------------|---------|----------|---------| |
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| Random | 21.9 | 23.4 | 23.5 | 24.4 | 26.6 | 24.4 | |
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| [GPT-3.5 (175B)](https://chat.openai.com/) | **54.3** | **62.5** | **64.0** | **62.2** | 39.3 | **53.2** | |
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| [XGLM (564M)](https://huggingface.co/facebook/xglm-564M) | 22.1 | 23.0 | 25.6 | 25.6 | 27.5 | 25.2 | |
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| [XGLM (1.7B)](https://huggingface.co/facebook/xglm-1.7B) | 20.9 | 23.0 | 24.6 | 24.8 | 26.6 | 24.4 | |
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| [XGLM (2.9B)](https://huggingface.co/facebook/xglm-2.9B) | 22.9 | 23.2 | 25.4 | 26.3 | 27.2 | 25.2 | |
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| [XGLM (4.5B)](https://huggingface.co/facebook/xglm-4.5B) | 21.8 | 23.1 | 25.6 | 25.8 | 27.1 | 25.0 | |
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| [XGLM (7.5B)](https://huggingface.co/facebook/xglm-7.5B) | 22.7 | 21.7 | 23.6 | 24.5 | 27.5 | 24.5 | |
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| [Falcon (7B)](https://huggingface.co/tiiuae/falcon-7b) | 22.1 | 22.9 | 25.5 | 25.7 | 27.5 | 25.1 | |
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| [Falcon (40B)](https://huggingface.co/tiiuae/falcon-40b) | 30.2 | 34.8 | 34.8 | 34.9 | 29.2 | 32.1 | |
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| [BLOOMZ (560M)](https://huggingface.co/bigscience/bloomz-560m) | 22.9 | 23.6 | 23.2 | 24.2 | 25.1 | 24.0 | |
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| [BLOOMZ (1.1B)](https://huggingface.co/bigscience/bloomz-1b1) | 20.4 | 21.4 | 21.1 | 23.5 | 24.7 | 22.4 | |
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| [BLOOMZ (1.7B)](https://huggingface.co/bigscience/bloomz-1b7) | 31.5 | 39.3 | 38.3 | 42.8 | 29.4 | 34.4 | |
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| [BLOOMZ (3B)](https://huggingface.co/bigscience/bloomz-3b) | 33.5 | 44.5 | 39.7 | 46.7 | 29.8 | 36.4 | |
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| [BLOOMZ (7.1B)](https://huggingface.co/bigscience/bloomz-7b1) | 37.1 | 46.7 | 44.0 | 49.1 | 28.2 | 38.0 | |
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| [mT0<sub>small</sub> (300M)](https://huggingface.co/bigscience/mt0-small) | 21.8 | 21.4 | 25.7 | 25.1 | 27.6 | 24.9 | |
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| [mT0<sub>base</sub> (580M)](https://huggingface.co/bigscience/mt0-base) | 22.6 | 22.6 | 25.7 | 25.6 | 26.9 | 25.0 | |
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| [mT0<sub>large</sub> (1.2B)](https://huggingface.co/bigscience/mt0-large) | 22.0 | 23.4 | 25.1 | 27.3 | 27.6 | 25.2 | |
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| [mT0<sub>xl</sub> (3.7B)](https://huggingface.co/bigscience/mt0-xl) | 31.4 | 42.9 | 41.0 | 47.8 | 35.7 | 38.2 | |
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| [mT0<sub>xxl</sub> (13B)](https://huggingface.co/bigscience/mt0-xxl) | 33.5 | 46.2 | 47.9 | 52.6 | **39.6** | 42.5 | |
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| [LLaMA (7B)](https://arxiv.org/abs/2302.13971) | 22.8 | 23.1 | 25.1 | 26.7 | 27.6 | 25.3 | |
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| [LLaMA (13B)](https://arxiv.org/abs/2302.13971) | 24.1 | 23.0 | 24.4 | 29.5 | 26.7 | 25.3 | |
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| [LLaMA (30B)](https://arxiv.org/abs/2302.13971) | 25.4 | 23.5 | 25.9 | 28.4 | 28.7 | 26.5 | |
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| [LLaMA (65B)](https://arxiv.org/abs/2302.13971) | 33.0 | 37.7 | 40.8 | 41.4 | 32.1 | 35.8 | |
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| [Bactrian-X-LLaMA (7B)](https://github.com/mbzuai-nlp/bactrian-x) | 23.3 | 24.0 | 26.0 | 26.1 | 27.5 | 25.7 | |
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| [Bactrian-X-LLaMA (13B)](https://github.com/mbzuai-nlp/bactrian-x) | 28.3 | 29.9 | 32.8 | 35.2 | 29.2 | 30.3 | |
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#### GPT-3.5 performance (% accuracy) across different education levels |
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<p align="left"> |
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<img src="https://github.com/fajri91/eval_picts/blob/master/IndoMMLU-result.png?raw=true" style="width: 370px;" id="title-icon"> |
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</p> |
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Red indicates that the score is below the minimum passing threshold of 65, while green signifies a score at or above this minimum. We can observe that ChatGPT mostly passes a score of 65 in Indonesian primary school exams. |
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#### Few-shot Evaluation |
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<p align="left"> |
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<img src="https://github.com/fajri91/eval_picts/blob/master/plot_fewshot.png?raw=true" style="width: 380px;" id="title-icon"> |
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</p> |
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## Data |
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Each question in the dataset is a multiple-choice question with up to 5 choices and only one choice as the correct answer. |
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We provide our dataset according to each subject in [data](data) folder. You can also access our dataset via [Hugging Face](https://huggingface.co/datasets/indolem/indommlu). |
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<!-- |
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#### Quick Use |
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Our dataset has been added to [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) and [OpenCompass](https://github.com/InternLM/opencompass), you can evaluate your model via these open-source tools. |
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--> |
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#### Evaluation |
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The code for the evaluation of each model we used is in `evaluate.py`, and the code to run them is listed in `run.sh`. |
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## Citation |
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``` |
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@inproceedings{koto-etal-2023-indommlu, |
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title = "Large Language Models Only Pass Primary School Exams in {I}ndonesia: A Comprehensive Test on {I}ndo{MMLU}", |
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author = "Fajri Koto and Nurul Aisyah and Haonan Li and Timothy Baldwin", |
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booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP)", |
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month = December, |
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year = "2023", |
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address = "Singapore", |
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publisher = "Association for Computational Linguistics", |
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} |
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``` |
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## License |
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The IndoMMLU dataset is licensed under a |
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[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-nc-sa/4.0/). |
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