README.md

metadata

library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - Triangle104/Q2.5-Humane-RP
  - EVA-UNIT-01/EVA-Qwen2.5-7B-v0.1
model-index:
  - name: Q2.5-EvaHumane-RP
    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: 36.76
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-EvaHumane-RP
          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: 33.76
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-EvaHumane-RP
          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: 27.19
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-EvaHumane-RP
          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: 9.17
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-EvaHumane-RP
          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: 11.39
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-EvaHumane-RP
          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: 37.92
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-EvaHumane-RP
          name: Open LLM Leaderboard

Merge

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

Quant: https://huggingface.co/Triangle104/Q2.5-EvaHumane-RP-Q4_K_M-GGUF

Merge Details

Addition of EVA-Qwen Model to try to broaden RP abilities.

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

• Triangle104/Q2.5-Humane-RP
• EVA-UNIT-01/EVA-Qwen2.5-7B-v0.1

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: Triangle104/Q2.5-Humane-RP
  - model: EVA-UNIT-01/EVA-Qwen2.5-7B-v0.1
merge_method: slerp
base_model: Triangle104/Q2.5-Humane-RP
dtype: bfloat16
parameters:
  t: [0, 0.5, 0.75, 1, 0.75, 0.5, 0]

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	26.03
IFEval (0-Shot)	36.76
BBH (3-Shot)	33.76
MATH Lvl 5 (4-Shot)	27.19
GPQA (0-shot)	9.17
MuSR (0-shot)	11.39
MMLU-PRO (5-shot)	37.92