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
Detailed results can be found here
| 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 |