metadata

library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - huihui-ai/Dria-Agent-a-3B-abliterated
  - huihui-ai/Qwen2.5-Coder-3B-Instruct-abliterated
  - huihui-ai/Qwen2.5-3B-Instruct-abliterated
model-index:
  - name: Qwen_2.5_3b_Smarteaz_0.01a
    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: 40.12
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nexesenex/Qwen_2.5_3b_Smarteaz_0.01a
          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: 24.37
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nexesenex/Qwen_2.5_3b_Smarteaz_0.01a
          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: 18.05
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nexesenex/Qwen_2.5_3b_Smarteaz_0.01a
          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: 3.69
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nexesenex/Qwen_2.5_3b_Smarteaz_0.01a
          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: 12.87
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nexesenex/Qwen_2.5_3b_Smarteaz_0.01a
          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: 20.67
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nexesenex/Qwen_2.5_3b_Smarteaz_0.01a
          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 huihui-ai/Qwen2.5-3B-Instruct-abliterated as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

merge_method: model_stock
models:
  - model: huihui-ai/Qwen2.5-Coder-3B-Instruct-abliterated
    parameters:
      weight: 1.0
  - model: huihui-ai/Dria-Agent-a-3B-abliterated
    parameters:
      weight: 1.0
base_model: huihui-ai/Qwen2.5-3B-Instruct-abliterated
dtype: bfloat16
normalize: true
chat_template: auto
tokenizer:
  source: union

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	19.96
IFEval (0-Shot)	40.12
BBH (3-Shot)	24.37
MATH Lvl 5 (4-Shot)	18.05
GPQA (0-shot)	3.69
MuSR (0-shot)	12.87
MMLU-PRO (5-shot)	20.67