Adding Evaluation Results

#5
by mkurman - opened
Files changed (1) hide show
  1. README.md +109 -0
README.md CHANGED
@@ -14,6 +14,101 @@ datasets:
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  - WizardLMTeam/WizardLM_evol_instruct_V2_196k
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  - ProlificAI/social-reasoning-rlhf
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  pipeline_tag: text-generation
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # MedIT SUN 2.5B
@@ -52,3 +147,17 @@ As the model is still in training, performance and capabilities may vary. Users
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  **Disclaimer and Safety Considerations**
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  The Model is designed to be used as a smart assistant but not as a knowledge source within your applications, systems, or environments. It is not intended to provide 100% accurate answers, especially in scenarios where high precision and accuracy are
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - WizardLMTeam/WizardLM_evol_instruct_V2_196k
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  - ProlificAI/social-reasoning-rlhf
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  pipeline_tag: text-generation
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+ model-index:
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+ - name: Llama-3.2-SUN-2.5B-chat
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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: 55.37
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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=meditsolutions/Llama-3.2-SUN-2.5B-chat
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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: 7.17
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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=meditsolutions/Llama-3.2-SUN-2.5B-chat
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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: 1.28
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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=meditsolutions/Llama-3.2-SUN-2.5B-chat
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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: 0.45
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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=meditsolutions/Llama-3.2-SUN-2.5B-chat
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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: 0.13
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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=meditsolutions/Llama-3.2-SUN-2.5B-chat
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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: 7.17
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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=meditsolutions/Llama-3.2-SUN-2.5B-chat
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+ name: Open LLM Leaderboard
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  ---
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  # MedIT SUN 2.5B
 
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  **Disclaimer and Safety Considerations**
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  The Model is designed to be used as a smart assistant but not as a knowledge source within your applications, systems, or environments. It is not intended to provide 100% accurate answers, especially in scenarios where high precision and accuracy are
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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_meditsolutions__Llama-3.2-SUN-2.5B-chat)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |11.93|
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+ |IFEval (0-Shot) |55.37|
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+ |BBH (3-Shot) | 7.17|
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+ |MATH Lvl 5 (4-Shot)| 1.28|
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+ |GPQA (0-shot) | 0.45|
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+ |MuSR (0-shot) | 0.13|
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+ |MMLU-PRO (5-shot) | 7.17|
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+