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README.md
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license: apache-2.0
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Due to the recent focus of expanding LLM to multilingual, we decided to put in great effort in converting MMLU to different languages.You can refer to all repos
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Spanish: jzhang86/esmmlu_no_train
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German: jzhang86/demmlu_no_train
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French: jzhang86/frmmlu_no_train
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We evaluated different translation methods by comparing among Google translate, translation agent and using Frontier
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The data was also randomly checked by human and native speakers. For the areas where the translation quality are not the best, such as law, we provide professional dictionary to LLM, which resulted in much improved quality.
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we maintain the code structure the same as https://huggingface.co/datasets/hails/mmlu_no_train, and we only translate the data in ./test and ./dev., so it can be easily used by lm-evaluation-harness
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---
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license: apache-2.0
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| 3 |
---
|
| 4 |
+
Due to the recent focus of expanding LLM to multilingual, we decided to put in great effort in converting MMLU to different languages.You can refer to all repos available:
|
| 5 |
+
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| 6 |
Spanish: jzhang86/esmmlu_no_train
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| 7 |
+
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German: jzhang86/demmlu_no_train
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| 9 |
+
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French: jzhang86/frmmlu_no_train
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| 11 |
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+
We evaluated different translation methods by comparing among Google translate, translation agent and using Frontier LLM. We finally decided to use gpt-4o-2024-05-13 for translation, by giving few-shot examples and careful prompting to boost translation quality.
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The data was also randomly checked by human and native speakers. For the areas where the translation quality are not the best, such as law, we provide professional dictionary to LLM, which resulted in much improved quality.
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we maintain the code structure the same as https://huggingface.co/datasets/hails/mmlu_no_train, and we only translate the data in ./test and ./dev., so it can be easily used by lm-evaluation-harness
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