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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-S2-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: 69.45 |
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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-S2-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: 87.15 |
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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-S2-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: 64.98 |
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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-S2-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: 62.18 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/TheTop-5x7B-Instruct-S2-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: 79.64 |
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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-S2-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-S2-v0.1 |
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name: Open LLM Leaderboard |
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--- |
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|
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# MaziyarPanahi/TheTop-5x7B-Instruct-S2-v0.1 |
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Merge of top 7B models with SLERP method. |
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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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> { |
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"all": { |
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"acc": 0.6545868511485138, |
|
"acc_stderr": 0.031980293841566164, |
|
"acc_norm": 0.6542757501692061, |
|
"acc_norm_stderr": 0.03263807517879597, |
|
"mc1": 0.45165238678090575, |
|
"mc1_stderr": 0.017421480300277643, |
|
"mc2": 0.6217500644350165, |
|
"mc2_stderr": 0.015583825644663436 |
|
}, |
|
"harness|arc:challenge|25": { |
|
"acc": 0.6723549488054608, |
|
"acc_stderr": 0.01371584794071934, |
|
"acc_norm": 0.6945392491467577, |
|
"acc_norm_stderr": 0.01346008047800251 |
|
}, |
|
"harness|hellaswag|10": { |
|
"acc": 0.7046405098585939, |
|
"acc_stderr": 0.0045527183605131, |
|
"acc_norm": 0.871539533957379, |
|
"acc_norm_stderr": 0.0033391798350182853 |
|
}, |
|
"harness|hendrycksTest-abstract_algebra|5": { |
|
"acc": 0.37, |
|
"acc_stderr": 0.048523658709391, |
|
"acc_norm": 0.37, |
|
"acc_norm_stderr": 0.048523658709391 |
|
}, |
|
"harness|hendrycksTest-anatomy|5": { |
|
"acc": 0.6148148148148148, |
|
"acc_stderr": 0.04203921040156279, |
|
"acc_norm": 0.6148148148148148, |
|
"acc_norm_stderr": 0.04203921040156279 |
|
}, |
|
"harness|hendrycksTest-astronomy|5": { |
|
"acc": 0.6907894736842105, |
|
"acc_stderr": 0.037610708698674805, |
|
"acc_norm": 0.6907894736842105, |
|
"acc_norm_stderr": 0.037610708698674805 |
|
}, |
|
"harness|hendrycksTest-business_ethics|5": { |
|
"acc": 0.63, |
|
"acc_stderr": 0.04852365870939099, |
|
"acc_norm": 0.63, |
|
"acc_norm_stderr": 0.04852365870939099 |
|
}, |
|
"harness|hendrycksTest-clinical_knowledge|5": { |
|
"acc": 0.7132075471698113, |
|
"acc_stderr": 0.02783491252754407, |
|
"acc_norm": 0.7132075471698113, |
|
"acc_norm_stderr": 0.02783491252754407 |
|
}, |
|
"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": 0.47, |
|
"acc_stderr": 0.050161355804659205, |
|
"acc_norm": 0.47, |
|
"acc_norm_stderr": 0.050161355804659205 |
|
}, |
|
"harness|hendrycksTest-college_computer_science|5": { |
|
"acc": 0.57, |
|
"acc_stderr": 0.04975698519562428, |
|
"acc_norm": 0.57, |
|
"acc_norm_stderr": 0.04975698519562428 |
|
}, |
|
"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": 0.6820809248554913, |
|
"acc_stderr": 0.0355068398916558, |
|
"acc_norm": 0.6820809248554913, |
|
"acc_norm_stderr": 0.0355068398916558 |
|
}, |
|
"harness|hendrycksTest-college_physics|5": { |
|
"acc": 0.4019607843137255, |
|
"acc_stderr": 0.04878608714466996, |
|
"acc_norm": 0.4019607843137255, |
|
"acc_norm_stderr": 0.04878608714466996 |
|
}, |
|
"harness|hendrycksTest-computer_security|5": { |
|
"acc": 0.77, |
|
"acc_stderr": 0.04229525846816506, |
|
"acc_norm": 0.77, |
|
"acc_norm_stderr": 0.04229525846816506 |
|
}, |
|
"harness|hendrycksTest-conceptual_physics|5": { |
|
"acc": 0.5829787234042553, |
|
"acc_stderr": 0.03223276266711712, |
|
"acc_norm": 0.5829787234042553, |
|
"acc_norm_stderr": 0.03223276266711712 |
|
}, |
|
"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": 0.5586206896551724, |
|
"acc_stderr": 0.04137931034482757, |
|
"acc_norm": 0.5586206896551724, |
|
"acc_norm_stderr": 0.04137931034482757 |
|
}, |
|
"harness|hendrycksTest-elementary_mathematics|5": { |
|
"acc": 0.41798941798941797, |
|
"acc_stderr": 0.025402555503260912, |
|
"acc_norm": 0.41798941798941797, |
|
"acc_norm_stderr": 0.025402555503260912 |
|
}, |
|
"harness|hendrycksTest-formal_logic|5": { |
|
"acc": 0.47619047619047616, |
|
"acc_stderr": 0.04467062628403273, |
|
"acc_norm": 0.47619047619047616, |
|
"acc_norm_stderr": 0.04467062628403273 |
|
}, |
|
"harness|hendrycksTest-global_facts|5": { |
|
"acc": 0.34, |
|
"acc_stderr": 0.04760952285695235, |
|
"acc_norm": 0.34, |
|
"acc_norm_stderr": 0.04760952285695235 |
|
}, |
|
"harness|hendrycksTest-high_school_biology|5": { |
|
"acc": 0.7903225806451613, |
|
"acc_stderr": 0.023157879349083522, |
|
"acc_norm": 0.7903225806451613, |
|
"acc_norm_stderr": 0.023157879349083522 |
|
}, |
|
"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": 0.68, |
|
"acc_stderr": 0.04688261722621505, |
|
"acc_norm": 0.68, |
|
"acc_norm_stderr": 0.04688261722621505 |
|
}, |
|
"harness|hendrycksTest-high_school_european_history|5": { |
|
"acc": 0.7696969696969697, |
|
"acc_stderr": 0.0328766675860349, |
|
"acc_norm": 0.7696969696969697, |
|
"acc_norm_stderr": 0.0328766675860349 |
|
}, |
|
"harness|hendrycksTest-high_school_geography|5": { |
|
"acc": 0.7828282828282829, |
|
"acc_stderr": 0.029376616484945633, |
|
"acc_norm": 0.7828282828282829, |
|
"acc_norm_stderr": 0.029376616484945633 |
|
}, |
|
"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": 0.6717948717948717, |
|
"acc_stderr": 0.023807633198657266, |
|
"acc_norm": 0.6717948717948717, |
|
"acc_norm_stderr": 0.023807633198657266 |
|
}, |
|
"harness|hendrycksTest-high_school_mathematics|5": { |
|
"acc": 0.34444444444444444, |
|
"acc_stderr": 0.02897264888484427, |
|
"acc_norm": 0.34444444444444444, |
|
"acc_norm_stderr": 0.02897264888484427 |
|
}, |
|
"harness|hendrycksTest-high_school_microeconomics|5": { |
|
"acc": 0.6638655462184874, |
|
"acc_stderr": 0.030684737115135363, |
|
"acc_norm": 0.6638655462184874, |
|
"acc_norm_stderr": 0.030684737115135363 |
|
}, |
|
"harness|hendrycksTest-high_school_physics|5": { |
|
"acc": 0.304635761589404, |
|
"acc_stderr": 0.03757949922943343, |
|
"acc_norm": 0.304635761589404, |
|
"acc_norm_stderr": 0.03757949922943343 |
|
}, |
|
"harness|hendrycksTest-high_school_psychology|5": { |
|
"acc": 0.8458715596330275, |
|
"acc_stderr": 0.015480826865374303, |
|
"acc_norm": 0.8458715596330275, |
|
"acc_norm_stderr": 0.015480826865374303 |
|
}, |
|
"harness|hendrycksTest-high_school_statistics|5": { |
|
"acc": 0.5185185185185185, |
|
"acc_stderr": 0.03407632093854051, |
|
"acc_norm": 0.5185185185185185, |
|
"acc_norm_stderr": 0.03407632093854051 |
|
}, |
|
"harness|hendrycksTest-high_school_us_history|5": { |
|
"acc": 0.8382352941176471, |
|
"acc_stderr": 0.025845017986926917, |
|
"acc_norm": 0.8382352941176471, |
|
"acc_norm_stderr": 0.025845017986926917 |
|
}, |
|
"harness|hendrycksTest-high_school_world_history|5": { |
|
"acc": 0.810126582278481, |
|
"acc_stderr": 0.02553010046023349, |
|
"acc_norm": 0.810126582278481, |
|
"acc_norm_stderr": 0.02553010046023349 |
|
}, |
|
"harness|hendrycksTest-human_aging|5": { |
|
"acc": 0.6905829596412556, |
|
"acc_stderr": 0.03102441174057221, |
|
"acc_norm": 0.6905829596412556, |
|
"acc_norm_stderr": 0.03102441174057221 |
|
}, |
|
"harness|hendrycksTest-human_sexuality|5": { |
|
"acc": 0.7786259541984732, |
|
"acc_stderr": 0.036412970813137296, |
|
"acc_norm": 0.7786259541984732, |
|
"acc_norm_stderr": 0.036412970813137296 |
|
}, |
|
"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": 0.7685185185185185, |
|
"acc_stderr": 0.04077494709252627, |
|
"acc_norm": 0.7685185185185185, |
|
"acc_norm_stderr": 0.04077494709252627 |
|
}, |
|
"harness|hendrycksTest-logical_fallacies|5": { |
|
"acc": 0.7607361963190185, |
|
"acc_stderr": 0.0335195387952127, |
|
"acc_norm": 0.7607361963190185, |
|
"acc_norm_stderr": 0.0335195387952127 |
|
}, |
|
"harness|hendrycksTest-machine_learning|5": { |
|
"acc": 0.45535714285714285, |
|
"acc_stderr": 0.047268355537191, |
|
"acc_norm": 0.45535714285714285, |
|
"acc_norm_stderr": 0.047268355537191 |
|
}, |
|
"harness|hendrycksTest-management|5": { |
|
"acc": 0.8058252427184466, |
|
"acc_stderr": 0.03916667762822584, |
|
"acc_norm": 0.8058252427184466, |
|
"acc_norm_stderr": 0.03916667762822584 |
|
}, |
|
"harness|hendrycksTest-marketing|5": { |
|
"acc": 0.8675213675213675, |
|
"acc_stderr": 0.022209309073165612, |
|
"acc_norm": 0.8675213675213675, |
|
"acc_norm_stderr": 0.022209309073165612 |
|
}, |
|
"harness|hendrycksTest-medical_genetics|5": { |
|
"acc": 0.71, |
|
"acc_stderr": 0.045604802157206845, |
|
"acc_norm": 0.71, |
|
"acc_norm_stderr": 0.045604802157206845 |
|
}, |
|
"harness|hendrycksTest-miscellaneous|5": { |
|
"acc": 0.8352490421455939, |
|
"acc_stderr": 0.013265346261323788, |
|
"acc_norm": 0.8352490421455939, |
|
"acc_norm_stderr": 0.013265346261323788 |
|
}, |
|
"harness|hendrycksTest-moral_disputes|5": { |
|
"acc": 0.7543352601156069, |
|
"acc_stderr": 0.023176298203992005, |
|
"acc_norm": 0.7543352601156069, |
|
"acc_norm_stderr": 0.023176298203992005 |
|
}, |
|
"harness|hendrycksTest-moral_scenarios|5": { |
|
"acc": 0.4547486033519553, |
|
"acc_stderr": 0.016653875777524006, |
|
"acc_norm": 0.4547486033519553, |
|
"acc_norm_stderr": 0.016653875777524006 |
|
}, |
|
"harness|hendrycksTest-nutrition|5": { |
|
"acc": 0.7483660130718954, |
|
"acc_stderr": 0.0248480182638752, |
|
"acc_norm": 0.7483660130718954, |
|
"acc_norm_stderr": 0.0248480182638752 |
|
}, |
|
"harness|hendrycksTest-philosophy|5": { |
|
"acc": 0.7202572347266881, |
|
"acc_stderr": 0.02549425935069491, |
|
"acc_norm": 0.7202572347266881, |
|
"acc_norm_stderr": 0.02549425935069491 |
|
}, |
|
"harness|hendrycksTest-prehistory|5": { |
|
"acc": 0.7592592592592593, |
|
"acc_stderr": 0.02378858355165854, |
|
"acc_norm": 0.7592592592592593, |
|
"acc_norm_stderr": 0.02378858355165854 |
|
}, |
|
"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": 0.4745762711864407, |
|
"acc_stderr": 0.012753716929101008, |
|
"acc_norm": 0.4745762711864407, |
|
"acc_norm_stderr": 0.012753716929101008 |
|
}, |
|
"harness|hendrycksTest-professional_medicine|5": { |
|
"acc": 0.7095588235294118, |
|
"acc_stderr": 0.027576468622740536, |
|
"acc_norm": 0.7095588235294118, |
|
"acc_norm_stderr": 0.027576468622740536 |
|
}, |
|
"harness|hendrycksTest-professional_psychology|5": { |
|
"acc": 0.6928104575163399, |
|
"acc_stderr": 0.01866335967146367, |
|
"acc_norm": 0.6928104575163399, |
|
"acc_norm_stderr": 0.01866335967146367 |
|
}, |
|
"harness|hendrycksTest-public_relations|5": { |
|
"acc": 0.6727272727272727, |
|
"acc_stderr": 0.0449429086625209, |
|
"acc_norm": 0.6727272727272727, |
|
"acc_norm_stderr": 0.0449429086625209 |
|
}, |
|
"harness|hendrycksTest-security_studies|5": { |
|
"acc": 0.7387755102040816, |
|
"acc_stderr": 0.02812342933514278, |
|
"acc_norm": 0.7387755102040816, |
|
"acc_norm_stderr": 0.02812342933514278 |
|
}, |
|
"harness|hendrycksTest-sociology|5": { |
|
"acc": 0.845771144278607, |
|
"acc_stderr": 0.025538433368578337, |
|
"acc_norm": 0.845771144278607, |
|
"acc_norm_stderr": 0.025538433368578337 |
|
}, |
|
"harness|hendrycksTest-us_foreign_policy|5": { |
|
"acc": 0.86, |
|
"acc_stderr": 0.0348735088019777, |
|
"acc_norm": 0.86, |
|
"acc_norm_stderr": 0.0348735088019777 |
|
}, |
|
"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": 0.45165238678090575, |
|
"mc1_stderr": 0.017421480300277643, |
|
"mc2": 0.6217500644350165, |
|
"mc2_stderr": 0.015583825644663436 |
|
}, |
|
"harness|winogrande|5": { |
|
"acc": 0.7963693764798737, |
|
"acc_stderr": 0.011317798781626913 |
|
}, |
|
"harness|gsm8k|5": { |
|
"acc": 0.7202426080363912, |
|
"acc_stderr": 0.01236438401673532 |
|
} |
|
} |
|
``` |
|
|
|
# [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-S2-v0.1) |
|
|
|
| Metric |Value| |
|
|---------------------------------|----:| |
|
|Avg. |72.57| |
|
|AI2 Reasoning Challenge (25-Shot)|69.45| |
|
|HellaSwag (10-Shot) |87.15| |
|
|MMLU (5-Shot) |64.98| |
|
|TruthfulQA (0-shot) |62.18| |
|
|Winogrande (5-shot) |79.64| |
|
|GSM8k (5-shot) |72.02| |
|
|
|
|
