---
language:
- en
base_model:
- unsloth/Llama-3.2-3B-Instruct
license: llama3.2
model-index:
- name: LLaMa-3.2-Instruct-JankMix-v0.2-SFT-3B
  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: 62.92
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=PJMixers-Dev/LLaMa-3.2-Instruct-JankMix-v0.2-SFT-3B
      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: 23.34
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=PJMixers-Dev/LLaMa-3.2-Instruct-JankMix-v0.2-SFT-3B
      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: 11.33
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=PJMixers-Dev/LLaMa-3.2-Instruct-JankMix-v0.2-SFT-3B
      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: 3.02
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=PJMixers-Dev/LLaMa-3.2-Instruct-JankMix-v0.2-SFT-3B
      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: 4.87
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=PJMixers-Dev/LLaMa-3.2-Instruct-JankMix-v0.2-SFT-3B
      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: 23.5
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=PJMixers-Dev/LLaMa-3.2-Instruct-JankMix-v0.2-SFT-3B
      name: Open LLM Leaderboard
---
A much further trained version, this time done with full finetuning instead of DoRA. Similar ~50/50 mix of completion and instruct data.

Note: This likely has refusals like [PJMixers-Dev/LLaMa-3.2-Instruct-JankMix-v0.1-SFT-3B](https://huggingface.co/PJMixers-Dev/LLaMa-3.2-Instruct-JankMix-v0.1-SFT-3B) since no focus was put on removing refusals. I'm working on a KTO DoRA to solve this, and possibly improve roleplay performance.

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)

Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/PJMixers-Dev__LLaMa-3.2-Instruct-JankMix-v0.2-SFT-3B-details)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |21.50|
|IFEval (0-Shot)    |62.92|
|BBH (3-Shot)       |23.34|
|MATH Lvl 5 (4-Shot)|11.33|
|GPQA (0-shot)      | 3.02|
|MuSR (0-shot)      | 4.87|
|MMLU-PRO (5-shot)  |23.50|