metadata

base_model: []
library_name: transformers
tags:
  - mergekit
  - merge
model-index:
  - name: Llama3.1-8B-drill
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: wis-k/instruction-following-eval
          split: train
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 76.52
            name: averaged accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-8B-drill
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: SaylorTwift/bbh
          split: test
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 28.79
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-8B-drill
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: lighteval/MATH-Hard
          split: test
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 16.54
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-8B-drill
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          split: train
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 2.35
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-8B-drill
          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: 4.7
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-8B-drill
          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: 30.84
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-8B-drill
          name: Open LLM Leaderboard

Llama3.1-8B-drill

This is a merge of some highest scoring Llama 3.1 8B models on the IFEval task on the Open LLM Leaderboard.
The purpose is to create a model that can follow instructions well.
It's not meant to be a particularly smart, stylish, or uncensored model.

Update: This turned out to be a mediocre model compared to its parents at even the IFEval task. Consider those models instead. 😕

Merge Details

Merge Method

This model was merged using the Model Stock merge method using Meta-Llama-3.1-8B-Instruct as a base using mergekit.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: Configurable-Llama-3.1-8B-Instruct
  - model: Llama-3.1-Tulu-3-8B
  - model: Llama-3.1-8B-Ultra-Instruct
  - model: Llama-3.1-Storm-8B
merge_method: model_stock
base_model: Meta-Llama-3.1-8B-Instruct
parameters:
  normalize: true
  weight: 1.0
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here! Summarized results can be found here!

Metric	Value (%)
Average	26.62
IFEval (0-Shot)	76.52
BBH (3-Shot)	28.79
MATH Lvl 5 (4-Shot)	16.54
GPQA (0-shot)	2.35
MuSR (0-shot)	4.70
MMLU-PRO (5-shot)	30.84