README.md

---
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- sft
base_model: athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1
model-index:
- name: Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
  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: 45.21
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
      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: 28.02
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
      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: 8.84
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
      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: 5.59
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
      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: 8.3
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
      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: 28.5
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
      name: Open LLM Leaderboard
---

**athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1** further pretrained on 1 epoch of the dirty stories from nothingiisreal/Reddit-Dirty-And-WritingPrompts, with all scores below 2 dropped.

-----

Why do this? I have a niche use case where I cannot increase compute over 8b, and L3/3.1 are the only models in this size category that meet my needs for logic. However, both versions of L3/3.1 have the damn repetition/token overconfidence problem, and this is meant to disrupt that certainty without disrupting the model's ability to function.

By the way, I *think* it's the lm_head that is causing the looping, but it might be the embeddings being too separated. I'm not going to pay two more times to test them separately, however :p
# [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/details_athirdpath__Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |20.74|
|IFEval (0-Shot)    |45.21|
|BBH (3-Shot)       |28.02|
|MATH Lvl 5 (4-Shot)| 8.84|
|GPQA (0-shot)      | 5.59|
|MuSR (0-shot)      | 8.30|
|MMLU-PRO (5-shot)  |28.50|