README.md

---
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_breadcrumbs_ties-density-0.1-gamma-0.1
  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: 42.02
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_breadcrumbs_ties-density-0.1-gamma-0.1
      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: 28.5
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_breadcrumbs_ties-density-0.1-gamma-0.1
      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: 8.84
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_breadcrumbs_ties-density-0.1-gamma-0.1
      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: 6.71
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_breadcrumbs_ties-density-0.1-gamma-0.1
      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: 10.78
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_breadcrumbs_ties-density-0.1-gamma-0.1
      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: 29.99
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=johnsutor/Llama-3-8B-Instruct_breadcrumbs_ties-density-0.1-gamma-0.1
      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: breadcrumbs_ties
Random seed: 42
density: 0.1
gamma: 0.1
normalize: true
weight: 1.0


# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_johnsutor__Llama-3-8B-Instruct_breadcrumbs_ties-density-0.1-gamma-0.1)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |21.14|
|IFEval (0-Shot)    |42.02|
|BBH (3-Shot)       |28.50|
|MATH Lvl 5 (4-Shot)| 8.84|
|GPQA (0-shot)      | 6.71|
|MuSR (0-shot)      |10.78|
|MMLU-PRO (5-shot)  |29.99|