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--- |
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language: en |
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model-index: |
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- name: vwxyzjn/rm_zephyr_new |
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results: |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: reward-bench |
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type: allenai/reward-bench |
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metrics: |
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- type: accuracy |
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value: 0.5343383584589615 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: Chat |
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type: Chat |
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metrics: |
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- type: accuracy |
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value: 0.8128491620111732 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: Chat Hard |
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type: Chat_Hard |
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metrics: |
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- type: accuracy |
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value: 0.5263157894736842 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: Safety |
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type: Safety |
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metrics: |
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- type: accuracy |
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value: 0.4851351351351351 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: Reasoning |
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type: Reasoning |
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metrics: |
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- type: accuracy |
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value: 0.3930266819446718 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: alpacaeval-easy |
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type: alpacaeval-easy |
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metrics: |
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- type: accuracy |
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value: 0.88 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: alpacaeval-hard |
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type: alpacaeval-hard |
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metrics: |
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- type: accuracy |
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value: 0.8947368421052632 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: alpacaeval-length |
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type: alpacaeval-length |
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metrics: |
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- type: accuracy |
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value: 0.6842105263157895 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: donotanswer |
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type: donotanswer |
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metrics: |
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- type: accuracy |
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value: 0.34558823529411764 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: hep-cpp |
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type: hep-cpp |
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metrics: |
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- type: accuracy |
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value: 0.6646341463414634 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: hep-go |
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type: hep-go |
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metrics: |
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- type: accuracy |
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value: 0.6951219512195121 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: hep-java |
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type: hep-java |
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metrics: |
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- type: accuracy |
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value: 0.6707317073170732 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: hep-js |
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type: hep-js |
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metrics: |
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- type: accuracy |
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value: 0.676829268292683 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: hep-python |
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type: hep-python |
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metrics: |
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- type: accuracy |
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value: 0.6829268292682927 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: hep-rust |
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type: hep-rust |
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metrics: |
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- type: accuracy |
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value: 0.5609756097560976 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: llmbar-adver-GPTInst |
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type: llmbar-adver-GPTInst |
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metrics: |
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- type: accuracy |
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value: 0.31521739130434784 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: llmbar-adver-GPTOut |
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type: llmbar-adver-GPTOut |
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metrics: |
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- type: accuracy |
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value: 0.5531914893617021 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: llmbar-adver-manual |
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type: llmbar-adver-manual |
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metrics: |
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- type: accuracy |
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value: 0.43478260869565216 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: llmbar-adver-neighbor |
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type: llmbar-adver-neighbor |
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metrics: |
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- type: accuracy |
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value: 0.6044776119402985 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: llmbar-natural |
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type: llmbar-natural |
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metrics: |
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- type: accuracy |
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value: 0.64 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: math-prm |
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type: math-prm |
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metrics: |
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- type: accuracy |
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value: 0.12751677852348994 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: mt-bench-easy |
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type: mt-bench-easy |
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metrics: |
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- type: accuracy |
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value: 0.7857142857142857 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: mt-bench-hard |
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type: mt-bench-hard |
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metrics: |
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- type: accuracy |
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value: 0.5405405405405406 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: mt-bench-med |
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type: mt-bench-med |
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metrics: |
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- type: accuracy |
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value: 0.775 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: refusals-dangerous |
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type: refusals-dangerous |
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metrics: |
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- type: accuracy |
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value: 0.18 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: refusals-offensive |
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type: refusals-offensive |
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metrics: |
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- type: accuracy |
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value: 0.58 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: xstest-should-refuse |
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type: xstest-should-refuse |
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metrics: |
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- type: accuracy |
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value: 0.461038961038961 |
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- task: |
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type: preference_evaluation |
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dataset: |
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name: xstest-should-respond |
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type: xstest-should-respond |
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metrics: |
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- type: accuracy |
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value: 0.66 |
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--- |
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# Model Card for vwxyzjn/rm_zephyr_new |
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<!-- Provide a quick summary of what the model is/does. --> |
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## Model Details |
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### Model Description |
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- **Developed by:** [More Information Needed] |
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- **Funded by [optional]:** [More Information Needed] |
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- **Shared by [optional]:** [More Information Needed] |
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- **Model type:** [More Information Needed] |
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- **Language(s) (NLP):** en |
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- **License:** [More Information Needed] |
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- **Finetuned from model [optional]:** [More Information Needed] |
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### Model Sources [optional] |
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- **Repository:** [More Information Needed] |
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- **Demo [optional]:** [More Information Needed] |
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## Uses |
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### Direct Use |
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[More Information Needed] |
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### Downstream Use [optional] |
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[More Information Needed] |
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### Out-of-Scope Use |
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[More Information Needed] |
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## Bias, Risks, and Limitations |
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[More Information Needed] |
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### Recommendations |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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### Training Procedure |
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#### Preprocessing [optional] |
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[More Information Needed] |
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#### Training Hyperparameters |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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#### Speeds, Sizes, Times [optional] |
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[More Information Needed] |
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## Evaluation |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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[More Information Needed] |
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#### Factors |
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[More Information Needed] |
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#### Metrics |
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### Results |
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#### Summary |
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## Model Examination [optional] |
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## Environmental Impact |
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). |
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- **Hardware Type:** [More Information Needed] |
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- **Cloud Provider:** [More Information Needed] |
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## Technical Specifications [optional] |
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### Model Architecture and Objective |
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### Compute Infrastructure |
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#### Software |
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## Citation [optional] |
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**BibTeX:** |
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**APA:** |
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## Glossary [optional] |
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[More Information Needed] |
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## More Information [optional] |
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## Model Card Authors [optional] |
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