LCARS_TOP_SCORE / README.md
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Adding Evaluation Results
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metadata
language:
  - en
license: openrail
library_name: transformers
tags:
  - chemistry
  - biology
  - music
  - code
  - climate
  - text-generation-inference
  - finance
  - legal
  - medical
base_model:
  - chihoonlee10/T3Q-Mistral-Orca-Math-DPO
  - yam-peleg/Experiment26-7B
  - liminerity/M7-7b
  - LeroyDyer/Mixtral_AI_Cyber_3.1_SFT
model-index:
  - name: LCARS_TOP_SCORE
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: HuggingFaceH4/ifeval
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 43.71
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=LeroyDyer/LCARS_TOP_SCORE
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: BBH
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 31.7
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=LeroyDyer/LCARS_TOP_SCORE
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: hendrycks/competition_math
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 6.72
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=LeroyDyer/LCARS_TOP_SCORE
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 4.81
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=LeroyDyer/LCARS_TOP_SCORE
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MuSR (0-shot)
          type: TAUR-Lab/MuSR
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 12.43
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=LeroyDyer/LCARS_TOP_SCORE
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU-PRO (5-shot)
          type: TIGER-Lab/MMLU-Pro
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 22.57
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=LeroyDyer/LCARS_TOP_SCORE
          name: Open LLM Leaderboard

Used as the Boss of Other Agents!

SOmeHow the best at testing !!! ohters may contain more paradigms and even data ... but somehow this one is top at leaderboard testing !

VERY GOOD MODEL !!!!! (HIGH SCORES) - 78.9 Average

@misc{open-llm-leaderboard-v2, author = {Clémentine Fourrier and Nathan Habib and Alina Lozovskaya and Konrad Szafer and Thomas Wolf}, title = {Open LLM Leaderboard v2}, year = {2024}, publisher = {Hugging Face}, howpublished = "\url{https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard}", }

@software{eval-harness, author = {Gao, Leo and Tow, Jonathan and Biderman, Stella and Black, Sid and DiPofi, Anthony and Foster, Charles and Golding, Laurence and Hsu, Jeffrey and McDonell, Kyle and Muennighoff, Niklas and Phang, Jason and Reynolds, Laria and Tang, Eric and Thite, Anish and Wang, Ben and Wang, Kevin and Zou, Andy}, title = {A framework for few-shot language model evaluation}, month = sep, year = 2021, publisher = {Zenodo}, version = {v0.0.1}, doi = {10.5281/zenodo.5371628}, url = {https://doi.org/10.5281/zenodo.5371628}, }

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 20.32
IFEval (0-Shot) 43.71
BBH (3-Shot) 31.70
MATH Lvl 5 (4-Shot) 6.72
GPQA (0-shot) 4.81
MuSR (0-shot) 12.43
MMLU-PRO (5-shot) 22.57