README.md

metadata

library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - Qwen/Qwen2.5-7B
  - rombodawg/Rombos-LLM-V2.5-Qwen-7b
  - fblgit/cybertron-v4-qw7B-MGS
  - sethuiyer/Qwen2.5-7B-Anvita
model-index:
  - name: Qwen2.5-7B-Instruct-Fusion
    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: 69.62
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Fusion
          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: 36.18
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Fusion
          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: 19.94
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Fusion
          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: 7.27
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Fusion
          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: 12.95
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Fusion
          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: 38.53
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Fusion
          name: Open LLM Leaderboard

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the Model Stock merge method using Qwen/Qwen2.5-7B as a base.

Models Merged

The following models were included in the merge:

• rombodawg/Rombos-LLM-V2.5-Qwen-7b
• fblgit/cybertron-v4-qw7B-MGS
• sethuiyer/Qwen2.5-7B-Anvita

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: rombodawg/Rombos-LLM-V2.5-Qwen-7b
  - model: fblgit/cybertron-v4-qw7B-MGS
  - model: sethuiyer/Qwen2.5-7B-Anvita
merge_method: model_stock
base_model: Qwen/Qwen2.5-7B
parameters:
  normalize: false
  int8_mask: true
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	30.75
IFEval (0-Shot)	69.62
BBH (3-Shot)	36.18
MATH Lvl 5 (4-Shot)	19.94
GPQA (0-shot)	7.27
MuSR (0-shot)	12.95
MMLU-PRO (5-shot)	38.53