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Configurable-Hermes-2-Pro-Llama-3-8B

Text Generation
Transformers
Safetensors
llama
safety
conversational
Eval Results
text-generation-inference
Inference Endpoints
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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.

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  1. README.md +110 -1
README.md CHANGED
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  ---
 
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  library_name: transformers
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  tags:
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  - safety
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- license: apache-2.0
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  base_model: NousResearch/Hermes-2-Pro-Llama-3-8B
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  datasets:
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  - vicgalle/configurable-system-prompt-multitask
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Configurable-LLama-3-8B
@@ -94,3 +189,17 @@ If you find this work, data and/or models useful for your research, please consi
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  primaryClass={cs.CL}
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  }
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  ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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  - safety
 
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  base_model: NousResearch/Hermes-2-Pro-Llama-3-8B
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  datasets:
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  - vicgalle/configurable-system-prompt-multitask
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+ model-index:
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+ - name: Configurable-Hermes-2-Pro-Llama-3-8B
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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: 57.63
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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=vicgalle/Configurable-Hermes-2-Pro-Llama-3-8B
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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: 30.51
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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=vicgalle/Configurable-Hermes-2-Pro-Llama-3-8B
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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: 5.97
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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=vicgalle/Configurable-Hermes-2-Pro-Llama-3-8B
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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: 6.26
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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=vicgalle/Configurable-Hermes-2-Pro-Llama-3-8B
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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: 10.06
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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=vicgalle/Configurable-Hermes-2-Pro-Llama-3-8B
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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: 23.31
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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=vicgalle/Configurable-Hermes-2-Pro-Llama-3-8B
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+ name: Open LLM Leaderboard
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  ---
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  # Configurable-LLama-3-8B
 
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  primaryClass={cs.CL}
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  }
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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_vicgalle__Configurable-Hermes-2-Pro-Llama-3-8B)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |22.29|
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+ |IFEval (0-Shot) |57.63|
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+ |BBH (3-Shot) |30.51|
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+ |MATH Lvl 5 (4-Shot)| 5.97|
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+ |GPQA (0-shot) | 6.26|
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+ |MuSR (0-shot) |10.06|
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+ |MMLU-PRO (5-shot) |23.31|
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+