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---
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|
|