README.md

metadata

license: apache-2.0
tags:
  - merge
  - mergekit
  - lazymergekit
  - jpacifico/Chocolatine-3B-Instruct-DPO-Revised
  - microsoft/Phi-3.5-mini-instruct
model-index:
  - name: ECE-PRYMMAL-3B-SLERP-V1
    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: 29.33
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lesubra/ECE-PRYMMAL-3B-SLERP-V1
          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: 35.05
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lesubra/ECE-PRYMMAL-3B-SLERP-V1
          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: 9.82
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lesubra/ECE-PRYMMAL-3B-SLERP-V1
          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: 8.95
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lesubra/ECE-PRYMMAL-3B-SLERP-V1
          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: 16.64
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lesubra/ECE-PRYMMAL-3B-SLERP-V1
          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: 32.23
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lesubra/ECE-PRYMMAL-3B-SLERP-V1
          name: Open LLM Leaderboard

ECE-PRYMMAL-3B-SLERP-V1

ECE-PRYMMAL-3B-SLERP-V1 is a merge of the following models using mergekit:

• jpacifico/Chocolatine-3B-Instruct-DPO-Revised
• microsoft/Phi-3.5-mini-instruct

🧩 Configuration

slices:
  - sources:
      - model: jpacifico/Chocolatine-3B-Instruct-DPO-Revised
        layer_range: [0, 32]
      - model: microsoft/Phi-3.5-mini-instruct
        layer_range: [0, 32]
merge_method: slerp
base_model: jpacifico/Chocolatine-3B-Instruct-DPO-Revised
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	22.00
IFEval (0-Shot)	29.33
BBH (3-Shot)	35.05
MATH Lvl 5 (4-Shot)	9.82
GPQA (0-shot)	8.95
MuSR (0-shot)	16.64
MMLU-PRO (5-shot)	32.23