README.md

metadata

library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - meta-llama/Meta-Llama-3-8B-Instruct
  - meta-llama/Meta-Llama-3.1-8B-Instruct
model-index:
  - name: LlamaExecutor-8B-3.0.5
    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: 74.03
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
          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: 28.41
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
          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: 8.53
            name: exact match
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
          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: 0.78
            name: acc_norm
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
          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: 4.65
            name: acc_norm
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
          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: 29.17
            name: accuracy
        source:
          url: >-
            https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
          name: Open LLM Leaderboard

mergellama

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the task arithmetic merge method using meta-llama/Meta-Llama-3.1-8B-Instruct as a base.

Models Merged

The following models were included in the merge:

• meta-llama/Meta-Llama-3-8B-Instruct

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: meta-llama/Meta-Llama-3-8B-Instruct
    parameters:
      weight: 0.2
  - model: meta-llama/Meta-Llama-3.1-8B-Instruct
    parameters:
      weight: 0.8

base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
merge_method: task_arithmetic
parameters:
  normalize: true
  int8_mask: true

dtype: bfloat16
  
  

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	24.26
IFEval (0-Shot)	74.03
BBH (3-Shot)	28.41
MATH Lvl 5 (4-Shot)	8.53
GPQA (0-shot)	0.78
MuSR (0-shot)	4.65
MMLU-PRO (5-shot)	29.17