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Adding Evaluation Results

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This 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

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  ---
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- base_model:
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- - Qwen/Qwen2.5-14B
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  library_name: transformers
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  tags:
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  - mergekit
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  - merge
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- license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Arcee-SuperNova-Medius
@@ -72,3 +167,17 @@ SuperNova-Medius is available for use under the Apache-2.0 license. For those wh
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  ## Summary
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  Arcee-SuperNova-Medius provides a unique balance of power, efficiency, and versatility. By distilling knowledge from two top-performing teacher models into a single 14B parameter model, SuperNova-Medius achieves results that rival larger models while maintaining a compact size ideal for practical deployment. Whether for customer support, content creation, or technical assistance, SuperNova-Medius is the perfect choice for organizations looking to leverage advanced language model capabilities in a cost-effective and accessible form.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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  - mergekit
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  - merge
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+ base_model:
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+ - Qwen/Qwen2.5-14B
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+ model-index:
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+ - name: SuperNova-Medius
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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: 55.6
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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=arcee-ai/SuperNova-Medius
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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: 49.3
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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=arcee-ai/SuperNova-Medius
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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: 32.48
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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=arcee-ai/SuperNova-Medius
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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: 17.9
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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=arcee-ai/SuperNova-Medius
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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: 19.19
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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=arcee-ai/SuperNova-Medius
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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: 48.83
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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=arcee-ai/SuperNova-Medius
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+ name: Open LLM Leaderboard
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  ---
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  # Arcee-SuperNova-Medius
 
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  ## Summary
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  Arcee-SuperNova-Medius provides a unique balance of power, efficiency, and versatility. By distilling knowledge from two top-performing teacher models into a single 14B parameter model, SuperNova-Medius achieves results that rival larger models while maintaining a compact size ideal for practical deployment. Whether for customer support, content creation, or technical assistance, SuperNova-Medius is the perfect choice for organizations looking to leverage advanced language model capabilities in a cost-effective and accessible form.
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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_arcee-ai__SuperNova-Medius)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |37.22|
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+ |IFEval (0-Shot) |55.60|
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+ |BBH (3-Shot) |49.30|
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+ |MATH Lvl 5 (4-Shot)|32.48|
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+ |GPQA (0-shot) |17.90|
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+ |MuSR (0-shot) |19.19|
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+ |MMLU-PRO (5-shot) |48.83|
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+