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Datasets:
UMxYTLAILabs
/
MalayMMLU

Tasks:
Question Answering
Languages:
Malay
Size:
10K<n<100K
Tags:
knowledge
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+ ---
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+ task_categories:
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+ - question-answering
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+ language:
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+ - ms
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+ tags:
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+ - knowledge
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+ pretty_name: MalayMMLU
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+ size_categories:
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+ - 10K<n<100K
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+ ---
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+ # MalayMMLU
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+
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+ Released on September 27, 2024
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+
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+ <h4 align="center">
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+ <p>
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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://openreview.net/pdf?id=VAXwQqkp5e" target="_blank" style="margin-right: 15px; margin-left: 10px">Paper</a> •
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+ 🤗 <a href="https://github.com/UMxYTL-AI-Labs/MalayMMLU" target="_blank" style="margin-left: 10px">Github</a>
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+ </p>
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+ </h4>
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+
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+ # Introduction
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+
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+ MalayMMLU is the first multitask language understanding (MLU) for Malay Language. The benchmark comprises 24,213 questions spanning both primary (Year 1-6) and secondary (Form 1-5) education levels in Malaysia, encompassing 5 broad topics that further divide into 22 subjects.
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+ <p align="center">
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+ <img src="imgs/MalayMMLU.png" width="250" >
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+ </p>
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+
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+ | **Category** | **Subjects** |
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+ |----------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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+ | **STEM** | Computer Science (Secondary), Biology (Secondary), Chemistry (Secondary), Computer Literacy (Secondary), Mathematics (Primary, Secondary), Additional Mathematics (Secondary), Design and Technology (Primary, Secondary), Core Science (Primary, Secondary), Information and Communication Technology (Primary), Automotive Technology (Secondary) |
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+ | **Language** | Malay Language (Primary, Secondary) |
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+ | **Social science** | Geography (Secondary), Local Studies (Primary), History (Primary, Secondary) |
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+ | **Others** | Life Skills (Primary, Secondary), Principles of Accounting (Secondary), Economics (Secondary), Business (Secondary), Agriculture (Secondary) |
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+ | **Humanities** | Quran and Sunnah (Secondary), Islam (Primary, Secondary), Sports Science Knowledge (Secondary) |
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+
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+ # Result
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+
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+ ### Zero-shot results of LLMs on MalayMMLU (First token accuracy)
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+
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+ | **Model** | **Language** | **Humanities** | **STEM** | **Social Science** | **Others** | **Average** |
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+ |-------------------------|-------------------|---------------------|---------------|-------------------------|-----------------|------------------|
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+ | Random | 38.01 | 42.09 | 36.31 | 36.01 | 38.07 | 38.02 |
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+ | GPT-4 | **82.90** | **83.91** | **78.80** | **77.29** | **77.33** | **80.11** |
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+ | GPT-3.5 | 69.62 | 71.01 | 67.17 | 66.70 | 63.73 | 67.78 |
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+ | [LLaMA-3 (8B)](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) | 63.93 | 66.21 | 62.26 | 62.97 | 61.38 | 63.46 |
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+ | [LLaMA-2 (13B)](https://huggingface.co/meta-llama/Llama-2-13b-chat-hf) | 45.58 | 50.72 | 44.13 | 44.55 | 40.87 | 45.26 |
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+ | [LLaMA-2 (7B)](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) | 47.47 | 52.74 | 48.71 | 50.72 | 48.19 | 49.61 |
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+ | [Mistral-v0.3 (7B)](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) | 56.97 | 59.29 | 57.14 | 58.28 | 56.56 | 57.71 |
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+ | [Mistral-v0.2 (7B)](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) | 56.23 | 59.86 | 57.10 | 56.65 | 55.22 | 56.92 |
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+ | [Sailor (7B)](https://huggingface.co/sail/Sailor-7B-Chat) | 74.54 | 68.62 | 62.79 | 64.69 | 63.61 | 67.58 |
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+ | [SeaLLM-v2.5 (7B)](https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5) | 69.75 | 67.94 | 65.29 | 62.66 | 63.61 | 65.89 |
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+ | [Phi-3 (14B)](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct) | 60.07 | 58.89 | 60.91 | 58.73 | 55.24 | 58.72 |
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+ | [Phi-3 (3.8B)](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) | 52.24 | 55.52 | 54.81 | 53.70 | 51.74 | 53.43 |
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+ | [GLM-4 (9B)](https://huggingface.co/THUDM/glm-4-9b-chat) | 58.51 | 60.48 | 56.32 | 55.04 | 53.97 | 56.87 |
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+ | [Qwen-1.5 (7B)](https://huggingface.co/Qwen/Qwen1.5-7B-Chat) | 60.13 | 59.14 | 58.62 | 54.26 | 54.67 | 57.18 |
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+ | [Qwen-1.5 (4B)](https://huggingface.co/Qwen/Qwen1.5-4B-Chat) | 48.39 | 52.01 | 51.37 | 50.00 | 49.10 | 49.93 |
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+ | [Qwen-1.5 (1.8B)](https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat) | 42.70 | 43.37 | 43.68 | 43.12 | 44.42 | 43.34 |
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+ | [Gemma (7B)](https://huggingface.co/google/gemma-7b-it) | 45.53 | 50.92 | 46.13 | 47.33 | 46.27 | 47.21 |
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+ | [Gemma (2B)](https://huggingface.co/google/gemma-2b-it) | 46.50 | 51.15 | 49.20 | 48.06 | 48.79 | 48.46 |
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+ | [Baichuan-2 (7B)](https://huggingface.co/baichuan-inc/Baichuan2-7B-Chat) | 40.41 | 47.35 | 44.37 | 46.33 | 43.54 | 44.30 |
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+ | [Komodo (7B)](https://huggingface.co/Yellow-AI-NLP/komodo-7b-base) | 43.62 | 45.53 | 39.34 | 39.75 | 39.48 | 41.72 |
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+ | [MaLLaM-v2 (5B)](https://huggingface.co/mesolitica/mallam-5b-20k-instructions-v2)| 42.56 | 46.42 | 42.16 | 40.81 | 38.81 | 42.07 |