README.md

metadata

license: mit
library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - meta-llama/Meta-Llama-3.1-8B
model-index:
  - name: Llama-3.1-8B-Base-Instruct-SLERP
    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: 29.07
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vhab10/Llama-3.1-8B-Base-Instruct-SLERP
          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: 29.93
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vhab10/Llama-3.1-8B-Base-Instruct-SLERP
          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: 10.5
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vhab10/Llama-3.1-8B-Base-Instruct-SLERP
          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: 6.15
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vhab10/Llama-3.1-8B-Base-Instruct-SLERP
          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: 9.37
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vhab10/Llama-3.1-8B-Base-Instruct-SLERP
          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: 29.12
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=vhab10/Llama-3.1-8B-Base-Instruct-SLERP
          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:

• meta-llama/Meta-Llama-3.1-8B
• meta-llama/Meta-Llama-3.1-8B-Instruct

Configuration

The following YAML configuration was used to produce this model:

slices:
- sources:
  - model: meta-llama/Meta-Llama-3.1-8B
    layer_range:
    - 0
    - 32
  - model: meta-llama/Meta-Llama-3.1-8B-Instruct
    layer_range:
    - 0
    - 32
merge_method: slerp
base_model: meta-llama/Meta-Llama-3.1-8B
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.	19.02
IFEval (0-Shot)	29.07
BBH (3-Shot)	29.93
MATH Lvl 5 (4-Shot)	10.50
GPQA (0-shot)	6.15
MuSR (0-shot)	9.37
MMLU-PRO (5-shot)	29.12