leaderboard-pr-bot
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Adding Evaluation Results
Browse filesThis is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr
The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.
If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions
README.md
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---
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language:
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- en
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- fr
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- ro
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- de
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- multilingual
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tags:
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- text2text-generation
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widget:
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- text: "Translate to German: My name is Arthur"
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example_title: "Translation"
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- text: "Please answer to the following question. Who is going to be the next Ballon d'or?"
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example_title: "Question Answering"
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- text: "Q: Can Geoffrey Hinton have a conversation with George Washington? Give the rationale before answering."
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example_title: "Logical reasoning"
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- text: "Please answer the following question. What is the boiling point of Nitrogen?"
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example_title: "Scientific knowledge"
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- text: "Answer the following yes/no question. Can you write a whole Haiku in a single tweet?"
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example_title: "Yes/no question"
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- text: "Answer the following yes/no question by reasoning step-by-step. Can you write a whole Haiku in a single tweet?"
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example_title: "Reasoning task"
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- text: "Q: ( False or not False or False ) is? A: Let's think step by step"
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example_title: "Boolean Expressions"
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- text: "The square root of x is the cube root of y. What is y to the power of 2, if x = 4?"
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example_title: "Math reasoning"
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- text: "Premise: At my age you will probably have learnt one lesson. Hypothesis: It's not certain how many lessons you'll learn by your thirties. Does the premise entail the hypothesis?"
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example_title: "Premise and hypothesis"
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datasets:
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- svakulenk0/qrecc
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- taskmaster2
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- esnli
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- quasc
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- qed
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---
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# Model Card for FLAN-T5 small
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copyright = {Creative Commons Attribution 4.0 International}
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}
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```
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---
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language:
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- en
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- fr
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- ro
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- de
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- multilingual
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license: apache-2.0
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tags:
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- text2text-generation
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datasets:
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- svakulenk0/qrecc
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- taskmaster2
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- esnli
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- quasc
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- qed
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widget:
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- text: 'Translate to German: My name is Arthur'
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example_title: Translation
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- text: Please answer to the following question. Who is going to be the next Ballon
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d'or?
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example_title: Question Answering
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- text: 'Q: Can Geoffrey Hinton have a conversation with George Washington? Give the
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rationale before answering.'
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example_title: Logical reasoning
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- text: Please answer the following question. What is the boiling point of Nitrogen?
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example_title: Scientific knowledge
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- text: Answer the following yes/no question. Can you write a whole Haiku in a single
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tweet?
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example_title: Yes/no question
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- text: Answer the following yes/no question by reasoning step-by-step. Can you write
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a whole Haiku in a single tweet?
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example_title: Reasoning task
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- text: 'Q: ( False or not False or False ) is? A: Let''s think step by step'
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example_title: Boolean Expressions
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- text: The square root of x is the cube root of y. What is y to the power of 2, if
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x = 4?
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example_title: Math reasoning
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- text: 'Premise: At my age you will probably have learnt one lesson. Hypothesis: It''s
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not certain how many lessons you''ll learn by your thirties. Does the premise
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entail the hypothesis?'
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example_title: Premise and hypothesis
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model-index:
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- name: flan-t5-small
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 15.24
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name: strict accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-t5-small
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 6.36
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-t5-small
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 0.0
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name: exact match
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-t5-small
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 1.45
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-t5-small
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 10.37
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-t5-small
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 2.59
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=google/flan-t5-small
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name: Open LLM Leaderboard
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---
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# Model Card for FLAN-T5 small
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copyright = {Creative Commons Attribution 4.0 International}
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}
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_google__flan-t5-small)
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| Metric |Value|
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|-------------------|----:|
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|Avg. | 6.00|
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|IFEval (0-Shot) |15.24|
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|BBH (3-Shot) | 6.36|
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|MATH Lvl 5 (4-Shot)| 0.00|
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|GPQA (0-shot) | 1.45|
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|MuSR (0-shot) |10.37|
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|MMLU-PRO (5-shot) | 2.59|
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