README.md

metadata

library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - arcee-ai/SuperNova-Medius
  - huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
  - allura-org/TQ2.5-14B-Aletheia-v1
  - EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
  - v000000/Qwen2.5-Lumen-14B
model-index:
  - name: Q2.5-Veltha-14B-0.5
    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: 77.96
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B-0.5
          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: 50.32
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B-0.5
          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: 33.84
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B-0.5
          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: 15.77
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B-0.5
          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: 14.17
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B-0.5
          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: 47.72
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/Q2.5-Veltha-14B-0.5
          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_linear merge method using arcee-ai/SuperNova-Medius as a base.

Models Merged

The following models were included in the merge:

• huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
• allura-org/TQ2.5-14B-Aletheia-v1
• EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
• v000000/Qwen2.5-Lumen-14B

Configuration

The following YAML configuration was used to produce this model:

merge_method: della_linear
dtype: float32
out_dtype: bfloat16
parameters:
  epsilon: 0.04
  lambda: 1.05
  normalize: true
base_model: arcee-ai/SuperNova-Medius
tokenizer_source: arcee-ai/SuperNova-Medius
models:
  - model: arcee-ai/SuperNova-Medius
    parameters:
      weight: 10
      density: 1
  - model: EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
    parameters:
      weight: 7
      density: 0.5
  - model: v000000/Qwen2.5-Lumen-14B
    parameters:
      weight: 7
      density: 0.4
  - model: allura-org/TQ2.5-14B-Aletheia-v1
    parameters:
      weight: 8
      density: 0.4
  - model: huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
    parameters:
      weight: 8
      density: 0.45

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	39.96
IFEval (0-Shot)	77.96
BBH (3-Shot)	50.32
MATH Lvl 5 (4-Shot)	33.84
GPQA (0-shot)	15.77
MuSR (0-shot)	14.17
MMLU-PRO (5-shot)	47.72