README.md

metadata

library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - TheDrummer/Gemmasutra-9B-v1
  - Nekuromento/Hematoma-Gemma-Model-Stock-9B
model-index:
  - name: G2-GSHT
    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: 56.3
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/G2-GSHT
          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: 30.99
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/G2-GSHT
          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: 3.17
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/G2-GSHT
          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: 10.07
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/G2-GSHT
          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: 8.17
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/G2-GSHT
          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: 23
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/G2-GSHT
          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 SLERP merge method.

Models Merged

The following models were included in the merge:

• TheDrummer/Gemmasutra-9B-v1
• Nekuromento/Hematoma-Gemma-Model-Stock-9B

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: Nekuromento/Hematoma-Gemma-Model-Stock-9B
  - model: TheDrummer/Gemmasutra-9B-v1
merge_method: slerp
base_model: TheDrummer/Gemmasutra-9B-v1
parameters:
  t:
    - filter: self_attn
      value: [0.3, 0.4, 0.3, 0.5, 0.6]
    - filter: mlp
      value: [0.6, 0.5, 0.6, 0.5, 0.5, 0.4, 0.5]
    - value: [0.6, 0.6, 0.4, 0.6, 0.7, 0.4, 0.4]
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	21.95
IFEval (0-Shot)	56.30
BBH (3-Shot)	30.99
MATH Lvl 5 (4-Shot)	3.17
GPQA (0-shot)	10.07
MuSR (0-shot)	8.17
MMLU-PRO (5-shot)	23.00