README.md

metadata

library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - Etherll/Qwen2.5-7B-della-test
  - jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0
  - fblgit/cybertron-v4-qw7B-MGS
  - Qwen/Qwen2.5-7B
model-index:
  - name: QandoraExp-7B
    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: 75.09
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QandoraExp-7B
          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: 35.92
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QandoraExp-7B
          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: 0.91
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QandoraExp-7B
          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: 8.05
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QandoraExp-7B
          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: 13.2
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QandoraExp-7B
          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: 37.89
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/QandoraExp-7B
          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 della merge method using Qwen/Qwen2.5-7B as a base.

Models Merged

The following models were included in the merge:

• Etherll/Qwen2.5-7B-della-test
• jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0
• fblgit/cybertron-v4-qw7B-MGS

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: Etherll/Qwen2.5-7B-della-test
    parameters:
      weight: 1 
      density: 1
      lambda: 0.9
  - model: jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0
    parameters:
      weight: 1 
      density: 1
      lambda: 0.9
  - model: fblgit/cybertron-v4-qw7B-MGS
    parameters:
      weight: 1 
      density: 1
      lambda: 0.9
merge_method: della
base_model: Qwen/Qwen2.5-7B
parameters:
  weight: 1 
  density: 1
  lambda: 0.9
  int8_mask: true
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	28.51
IFEval (0-Shot)	75.09
BBH (3-Shot)	35.92
MATH Lvl 5 (4-Shot)	0.91
GPQA (0-shot)	8.05
MuSR (0-shot)	13.20
MMLU-PRO (5-shot)	37.89