README.md

metadata

license: apache-2.0
library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
  - VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct
  - DeepMount00/Llama-3-8b-Ita
  - nbeerbower/llama-3-gutenberg-8B
  - jpacifico/French-Alpaca-Llama3-8B-Instruct-v1.0
  - meta-llama/Meta-Llama-3-8B-Instruct
model-index:
  - name: Llama-3-8B-Instruct_ties-density-0.9
    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: 38.58
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_ties-density-0.9
          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: 25.46
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_ties-density-0.9
          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: 5.59
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_ties-density-0.9
          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: 6.6
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_ties-density-0.9
          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: 7.74
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_ties-density-0.9
          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: 24.24
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_ties-density-0.9
          name: Open LLM Leaderboard

Model Merge Parameters

Base model: meta-llama/Meta-Llama-3-8B-Instruct Models: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct DeepMount00/Llama-3-8b-Ita nbeerbower/llama-3-gutenberg-8B jpacifico/French-Alpaca-Llama3-8B-Instruct-v1.0 meta-llama/Meta-Llama-3-8B-Instruct Merge method: ties Random seed: 42 density: 0.9 normalize: true weight: 1.0

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	18.04
IFEval (0-Shot)	38.58
BBH (3-Shot)	25.46
MATH Lvl 5 (4-Shot)	5.59
GPQA (0-shot)	6.60
MuSR (0-shot)	7.74
MMLU-PRO (5-shot)	24.24