Marsouuu's picture
Adding Evaluation Results (#1)
0505bdc verified
metadata
license: apache-2.0
library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - Qwen/Qwen2.5-1.5B-Instruct
  - Qwen/Qwen2.5-1.5B
model-index:
  - name: lareneg1_78B-ECE-PRYMMAL-Martial
    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: 27.95
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
          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: 19.02
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
          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: 8.91
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
          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: 4.25
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
          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: 6.51
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
          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: 21.36
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Marsouuu/lareneg1_78B-ECE-PRYMMAL-Martial
          name: Open LLM Leaderboard

my-output

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:

Configuration

The following YAML configuration was used to produce this model:


slices:
  - sources:
      - model: Qwen/Qwen2.5-1.5B
        layer_range: [0, 28]
      - model: Qwen/Qwen2.5-1.5B-Instruct
        layer_range: [0, 28]
merge_method: slerp
base_model: Qwen/Qwen2.5-1.5B-Instruct
parameters:
  t:
    - filter: self_attn
      value: [0, 0.25, 0.5, 0.75, 1]
    - filter: mlp
      value: [1, 0.75, 0.5, 0.25, 0]
    - value: 0.5
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 14.67
IFEval (0-Shot) 27.95
BBH (3-Shot) 19.02
MATH Lvl 5 (4-Shot) 8.91
GPQA (0-shot) 4.25
MuSR (0-shot) 6.51
MMLU-PRO (5-shot) 21.36