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--- |
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license: apache-2.0 |
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library_name: transformers |
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tags: |
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- merge |
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pipeline_tag: text-generation |
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model-index: |
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- name: TheTop-5x7B-Instruct-S3-v0.1 |
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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: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 70.9 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S3-v0.1 |
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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: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 88.0 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S3-v0.1 |
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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 (5-Shot) |
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type: cais/mmlu |
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config: all |
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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: 65.13 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S3-v0.1 |
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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: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 64.47 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S3-v0.1 |
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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: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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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: 83.66 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S3-v0.1 |
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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: GSM8k (5-shot) |
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type: gsm8k |
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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: 72.02 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S3-v0.1 |
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name: Open LLM Leaderboard |
|
--- |
|
|
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Merge of top 7B models and the SLERP of other 7B models |
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|
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> mergekit is a toolkit for merging pre-trained language models. mergekit uses an out-of-core approach to perform unreasonably elaborate merges in resource-constrained situations. Merges can be run entirely on CPU or accelerated with as little as 8 GB of VRAM. Many merging algorithms are supported, with more coming as they catch my attention. |
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> |
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> ## Eval |
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> ```python |
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> { |
|
"all": { |
|
"acc": 0.6571641282160704, |
|
"acc_stderr": 0.031918970852064334, |
|
"acc_norm": 0.6561506230894164, |
|
"acc_norm_stderr": 0.03258982989656136, |
|
"mc1": 0.4834761321909425, |
|
"mc1_stderr": 0.017493940190057723, |
|
"mc2": 0.6447306680251751, |
|
"mc2_stderr": 0.015519245883344577 |
|
}, |
|
"harness|arc:challenge|25": { |
|
"acc": 0.689419795221843, |
|
"acc_stderr": 0.01352229209805306, |
|
"acc_norm": 0.7090443686006825, |
|
"acc_norm_stderr": 0.013273077865907595 |
|
}, |
|
"harness|hellaswag|10": { |
|
"acc": 0.7168890659231228, |
|
"acc_stderr": 0.004495891440519419, |
|
"acc_norm": 0.8800039832702649, |
|
"acc_norm_stderr": 0.0032429275808698544 |
|
}, |
|
"harness|hendrycksTest-abstract_algebra|5": { |
|
"acc": 0.33, |
|
"acc_stderr": 0.047258156262526045, |
|
"acc_norm": 0.33, |
|
"acc_norm_stderr": 0.047258156262526045 |
|
}, |
|
"harness|hendrycksTest-anatomy|5": { |
|
"acc": 0.6370370370370371, |
|
"acc_stderr": 0.04153948404742398, |
|
"acc_norm": 0.6370370370370371, |
|
"acc_norm_stderr": 0.04153948404742398 |
|
}, |
|
"harness|hendrycksTest-astronomy|5": { |
|
"acc": 0.7105263157894737, |
|
"acc_stderr": 0.03690677986137283, |
|
"acc_norm": 0.7105263157894737, |
|
"acc_norm_stderr": 0.03690677986137283 |
|
}, |
|
"harness|hendrycksTest-business_ethics|5": { |
|
"acc": 0.65, |
|
"acc_stderr": 0.0479372485441102, |
|
"acc_norm": 0.65, |
|
"acc_norm_stderr": 0.0479372485441102 |
|
}, |
|
"harness|hendrycksTest-clinical_knowledge|5": { |
|
"acc": 0.6981132075471698, |
|
"acc_stderr": 0.02825420034443866, |
|
"acc_norm": 0.6981132075471698, |
|
"acc_norm_stderr": 0.02825420034443866 |
|
}, |
|
"harness|hendrycksTest-college_biology|5": { |
|
"acc": 0.7638888888888888, |
|
"acc_stderr": 0.03551446610810826, |
|
"acc_norm": 0.7638888888888888, |
|
"acc_norm_stderr": 0.03551446610810826 |
|
}, |
|
"harness|hendrycksTest-college_chemistry|5": { |
|
"acc": 0.48, |
|
"acc_stderr": 0.050211673156867795, |
|
"acc_norm": 0.48, |
|
"acc_norm_stderr": 0.050211673156867795 |
|
}, |
|
"harness|hendrycksTest-college_computer_science|5": { |
|
"acc": 0.56, |
|
"acc_stderr": 0.049888765156985884, |
|
"acc_norm": 0.56, |
|
"acc_norm_stderr": 0.049888765156985884 |
|
}, |
|
"harness|hendrycksTest-college_mathematics|5": { |
|
"acc": 0.27, |
|
"acc_stderr": 0.0446196043338474, |
|
"acc_norm": 0.27, |
|
"acc_norm_stderr": 0.0446196043338474 |
|
}, |
|
"harness|hendrycksTest-college_medicine|5": { |
|
"acc": 0.6589595375722543, |
|
"acc_stderr": 0.03614665424180826, |
|
"acc_norm": 0.6589595375722543, |
|
"acc_norm_stderr": 0.03614665424180826 |
|
}, |
|
"harness|hendrycksTest-college_physics|5": { |
|
"acc": 0.4117647058823529, |
|
"acc_stderr": 0.048971049527263666, |
|
"acc_norm": 0.4117647058823529, |
|
"acc_norm_stderr": 0.048971049527263666 |
|
}, |
|
"harness|hendrycksTest-computer_security|5": { |
|
"acc": 0.75, |
|
"acc_stderr": 0.04351941398892446, |
|
"acc_norm": 0.75, |
|
"acc_norm_stderr": 0.04351941398892446 |
|
}, |
|
"harness|hendrycksTest-conceptual_physics|5": { |
|
"acc": 0.5787234042553191, |
|
"acc_stderr": 0.03227834510146268, |
|
"acc_norm": 0.5787234042553191, |
|
"acc_norm_stderr": 0.03227834510146268 |
|
}, |
|
"harness|hendrycksTest-econometrics|5": { |
|
"acc": 0.5175438596491229, |
|
"acc_stderr": 0.04700708033551038, |
|
"acc_norm": 0.5175438596491229, |
|
"acc_norm_stderr": 0.04700708033551038 |
|
}, |
|
"harness|hendrycksTest-electrical_engineering|5": { |
|
"acc": 0.5655172413793104, |
|
"acc_stderr": 0.04130740879555497, |
|
"acc_norm": 0.5655172413793104, |
|
"acc_norm_stderr": 0.04130740879555497 |
|
}, |
|
"harness|hendrycksTest-elementary_mathematics|5": { |
|
"acc": 0.4312169312169312, |
|
"acc_stderr": 0.02550648169813821, |
|
"acc_norm": 0.4312169312169312, |
|
"acc_norm_stderr": 0.02550648169813821 |
|
}, |
|
"harness|hendrycksTest-formal_logic|5": { |
|
"acc": 0.48412698412698413, |
|
"acc_stderr": 0.04469881854072606, |
|
"acc_norm": 0.48412698412698413, |
|
"acc_norm_stderr": 0.04469881854072606 |
|
}, |
|
"harness|hendrycksTest-global_facts|5": { |
|
"acc": 0.33, |
|
"acc_stderr": 0.04725815626252604, |
|
"acc_norm": 0.33, |
|
"acc_norm_stderr": 0.04725815626252604 |
|
}, |
|
"harness|hendrycksTest-high_school_biology|5": { |
|
"acc": 0.7838709677419354, |
|
"acc_stderr": 0.02341529343356853, |
|
"acc_norm": 0.7838709677419354, |
|
"acc_norm_stderr": 0.02341529343356853 |
|
}, |
|
"harness|hendrycksTest-high_school_chemistry|5": { |
|
"acc": 0.4975369458128079, |
|
"acc_stderr": 0.03517945038691063, |
|
"acc_norm": 0.4975369458128079, |
|
"acc_norm_stderr": 0.03517945038691063 |
|
}, |
|
"harness|hendrycksTest-high_school_computer_science|5": { |
|
"acc": 0.67, |
|
"acc_stderr": 0.04725815626252607, |
|
"acc_norm": 0.67, |
|
"acc_norm_stderr": 0.04725815626252607 |
|
}, |
|
"harness|hendrycksTest-high_school_european_history|5": { |
|
"acc": 0.7878787878787878, |
|
"acc_stderr": 0.031922715695483, |
|
"acc_norm": 0.7878787878787878, |
|
"acc_norm_stderr": 0.031922715695483 |
|
}, |
|
"harness|hendrycksTest-high_school_geography|5": { |
|
"acc": 0.7929292929292929, |
|
"acc_stderr": 0.028869778460267045, |
|
"acc_norm": 0.7929292929292929, |
|
"acc_norm_stderr": 0.028869778460267045 |
|
}, |
|
"harness|hendrycksTest-high_school_government_and_politics|5": { |
|
"acc": 0.9015544041450777, |
|
"acc_stderr": 0.021500249576033456, |
|
"acc_norm": 0.9015544041450777, |
|
"acc_norm_stderr": 0.021500249576033456 |
|
}, |
|
"harness|hendrycksTest-high_school_macroeconomics|5": { |
|
"acc": 0.6666666666666666, |
|
"acc_stderr": 0.023901157979402534, |
|
"acc_norm": 0.6666666666666666, |
|
"acc_norm_stderr": 0.023901157979402534 |
|
}, |
|
"harness|hendrycksTest-high_school_mathematics|5": { |
|
"acc": 0.34814814814814815, |
|
"acc_stderr": 0.029045600290616255, |
|
"acc_norm": 0.34814814814814815, |
|
"acc_norm_stderr": 0.029045600290616255 |
|
}, |
|
"harness|hendrycksTest-high_school_microeconomics|5": { |
|
"acc": 0.680672268907563, |
|
"acc_stderr": 0.030283995525884396, |
|
"acc_norm": 0.680672268907563, |
|
"acc_norm_stderr": 0.030283995525884396 |
|
}, |
|
"harness|hendrycksTest-high_school_physics|5": { |
|
"acc": 0.33112582781456956, |
|
"acc_stderr": 0.038425817186598696, |
|
"acc_norm": 0.33112582781456956, |
|
"acc_norm_stderr": 0.038425817186598696 |
|
}, |
|
"harness|hendrycksTest-high_school_psychology|5": { |
|
"acc": 0.8385321100917431, |
|
"acc_stderr": 0.015776239256163224, |
|
"acc_norm": 0.8385321100917431, |
|
"acc_norm_stderr": 0.015776239256163224 |
|
}, |
|
"harness|hendrycksTest-high_school_statistics|5": { |
|
"acc": 0.5138888888888888, |
|
"acc_stderr": 0.03408655867977749, |
|
"acc_norm": 0.5138888888888888, |
|
"acc_norm_stderr": 0.03408655867977749 |
|
}, |
|
"harness|hendrycksTest-high_school_us_history|5": { |
|
"acc": 0.8578431372549019, |
|
"acc_stderr": 0.024509803921568603, |
|
"acc_norm": 0.8578431372549019, |
|
"acc_norm_stderr": 0.024509803921568603 |
|
}, |
|
"harness|hendrycksTest-high_school_world_history|5": { |
|
"acc": 0.8143459915611815, |
|
"acc_stderr": 0.025310495376944856, |
|
"acc_norm": 0.8143459915611815, |
|
"acc_norm_stderr": 0.025310495376944856 |
|
}, |
|
"harness|hendrycksTest-human_aging|5": { |
|
"acc": 0.6860986547085202, |
|
"acc_stderr": 0.031146796482972465, |
|
"acc_norm": 0.6860986547085202, |
|
"acc_norm_stderr": 0.031146796482972465 |
|
}, |
|
"harness|hendrycksTest-human_sexuality|5": { |
|
"acc": 0.7862595419847328, |
|
"acc_stderr": 0.0359546161177469, |
|
"acc_norm": 0.7862595419847328, |
|
"acc_norm_stderr": 0.0359546161177469 |
|
}, |
|
"harness|hendrycksTest-international_law|5": { |
|
"acc": 0.8099173553719008, |
|
"acc_stderr": 0.03581796951709282, |
|
"acc_norm": 0.8099173553719008, |
|
"acc_norm_stderr": 0.03581796951709282 |
|
}, |
|
"harness|hendrycksTest-jurisprudence|5": { |
|
"acc": 0.7962962962962963, |
|
"acc_stderr": 0.03893542518824847, |
|
"acc_norm": 0.7962962962962963, |
|
"acc_norm_stderr": 0.03893542518824847 |
|
}, |
|
"harness|hendrycksTest-logical_fallacies|5": { |
|
"acc": 0.7730061349693251, |
|
"acc_stderr": 0.03291099578615769, |
|
"acc_norm": 0.7730061349693251, |
|
"acc_norm_stderr": 0.03291099578615769 |
|
}, |
|
"harness|hendrycksTest-machine_learning|5": { |
|
"acc": 0.5, |
|
"acc_stderr": 0.04745789978762494, |
|
"acc_norm": 0.5, |
|
"acc_norm_stderr": 0.04745789978762494 |
|
}, |
|
"harness|hendrycksTest-management|5": { |
|
"acc": 0.7961165048543689, |
|
"acc_stderr": 0.03989139859531771, |
|
"acc_norm": 0.7961165048543689, |
|
"acc_norm_stderr": 0.03989139859531771 |
|
}, |
|
"harness|hendrycksTest-marketing|5": { |
|
"acc": 0.8760683760683761, |
|
"acc_stderr": 0.02158649400128137, |
|
"acc_norm": 0.8760683760683761, |
|
"acc_norm_stderr": 0.02158649400128137 |
|
}, |
|
"harness|hendrycksTest-medical_genetics|5": { |
|
"acc": 0.73, |
|
"acc_stderr": 0.0446196043338474, |
|
"acc_norm": 0.73, |
|
"acc_norm_stderr": 0.0446196043338474 |
|
}, |
|
"harness|hendrycksTest-miscellaneous|5": { |
|
"acc": 0.8288633461047255, |
|
"acc_stderr": 0.013468201614066307, |
|
"acc_norm": 0.8288633461047255, |
|
"acc_norm_stderr": 0.013468201614066307 |
|
}, |
|
"harness|hendrycksTest-moral_disputes|5": { |
|
"acc": 0.7514450867052023, |
|
"acc_stderr": 0.023267528432100174, |
|
"acc_norm": 0.7514450867052023, |
|
"acc_norm_stderr": 0.023267528432100174 |
|
}, |
|
"harness|hendrycksTest-moral_scenarios|5": { |
|
"acc": 0.4480446927374302, |
|
"acc_stderr": 0.016631976628930595, |
|
"acc_norm": 0.4480446927374302, |
|
"acc_norm_stderr": 0.016631976628930595 |
|
}, |
|
"harness|hendrycksTest-nutrition|5": { |
|
"acc": 0.7320261437908496, |
|
"acc_stderr": 0.025360603796242553, |
|
"acc_norm": 0.7320261437908496, |
|
"acc_norm_stderr": 0.025360603796242553 |
|
}, |
|
"harness|hendrycksTest-philosophy|5": { |
|
"acc": 0.707395498392283, |
|
"acc_stderr": 0.02583989833487798, |
|
"acc_norm": 0.707395498392283, |
|
"acc_norm_stderr": 0.02583989833487798 |
|
}, |
|
"harness|hendrycksTest-prehistory|5": { |
|
"acc": 0.7530864197530864, |
|
"acc_stderr": 0.023993501709042107, |
|
"acc_norm": 0.7530864197530864, |
|
"acc_norm_stderr": 0.023993501709042107 |
|
}, |
|
"harness|hendrycksTest-professional_accounting|5": { |
|
"acc": 0.4787234042553192, |
|
"acc_stderr": 0.029800481645628693, |
|
"acc_norm": 0.4787234042553192, |
|
"acc_norm_stderr": 0.029800481645628693 |
|
}, |
|
"harness|hendrycksTest-professional_law|5": { |
|
"acc": 0.4791395045632334, |
|
"acc_stderr": 0.012759117066518015, |
|
"acc_norm": 0.4791395045632334, |
|
"acc_norm_stderr": 0.012759117066518015 |
|
}, |
|
"harness|hendrycksTest-professional_medicine|5": { |
|
"acc": 0.7058823529411765, |
|
"acc_stderr": 0.02767846864214472, |
|
"acc_norm": 0.7058823529411765, |
|
"acc_norm_stderr": 0.02767846864214472 |
|
}, |
|
"harness|hendrycksTest-professional_psychology|5": { |
|
"acc": 0.6862745098039216, |
|
"acc_stderr": 0.018771683893528176, |
|
"acc_norm": 0.6862745098039216, |
|
"acc_norm_stderr": 0.018771683893528176 |
|
}, |
|
"harness|hendrycksTest-public_relations|5": { |
|
"acc": 0.6818181818181818, |
|
"acc_stderr": 0.04461272175910509, |
|
"acc_norm": 0.6818181818181818, |
|
"acc_norm_stderr": 0.04461272175910509 |
|
}, |
|
"harness|hendrycksTest-security_studies|5": { |
|
"acc": 0.7346938775510204, |
|
"acc_stderr": 0.028263889943784603, |
|
"acc_norm": 0.7346938775510204, |
|
"acc_norm_stderr": 0.028263889943784603 |
|
}, |
|
"harness|hendrycksTest-sociology|5": { |
|
"acc": 0.835820895522388, |
|
"acc_stderr": 0.026193923544454115, |
|
"acc_norm": 0.835820895522388, |
|
"acc_norm_stderr": 0.026193923544454115 |
|
}, |
|
"harness|hendrycksTest-us_foreign_policy|5": { |
|
"acc": 0.85, |
|
"acc_stderr": 0.03588702812826371, |
|
"acc_norm": 0.85, |
|
"acc_norm_stderr": 0.03588702812826371 |
|
}, |
|
"harness|hendrycksTest-virology|5": { |
|
"acc": 0.5481927710843374, |
|
"acc_stderr": 0.03874371556587953, |
|
"acc_norm": 0.5481927710843374, |
|
"acc_norm_stderr": 0.03874371556587953 |
|
}, |
|
"harness|hendrycksTest-world_religions|5": { |
|
"acc": 0.8362573099415205, |
|
"acc_stderr": 0.028380919596145866, |
|
"acc_norm": 0.8362573099415205, |
|
"acc_norm_stderr": 0.028380919596145866 |
|
}, |
|
"harness|truthfulqa:mc|0": { |
|
"mc1": 0.4834761321909425, |
|
"mc1_stderr": 0.017493940190057723, |
|
"mc2": 0.6447306680251751, |
|
"mc2_stderr": 0.015519245883344577 |
|
}, |
|
"harness|winogrande|5": { |
|
"acc": 0.8366219415943172, |
|
"acc_stderr": 0.010390695970273764 |
|
}, |
|
"harness|gsm8k|5": { |
|
"acc": 0.7202426080363912, |
|
"acc_stderr": 0.012364384016735319 |
|
} |
|
} |
|
|
|
``` |
|
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
|
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_MaziyarPanahi__TheTop-5x7B-Instruct-S3-v0.1) |
|
|
|
| Metric |Value| |
|
|---------------------------------|----:| |
|
|Avg. |74.03| |
|
|AI2 Reasoning Challenge (25-Shot)|70.90| |
|
|HellaSwag (10-Shot) |88.00| |
|
|MMLU (5-Shot) |65.13| |
|
|TruthfulQA (0-shot) |64.47| |
|
|Winogrande (5-shot) |83.66| |
|
|GSM8k (5-shot) |72.02| |
|
|
|
|
