f1073992df
Model: athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit Source: Original Platform
130 lines
4.2 KiB
Markdown
130 lines
4.2 KiB
Markdown
---
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language:
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- en
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license: apache-2.0
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- llama
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- trl
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- sft
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base_model: athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1
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model-index:
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- name: Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 45.21
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name: strict accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 28.02
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 8.84
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name: exact match
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 5.59
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 8.3
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 28.5
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit
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name: Open LLM Leaderboard
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---
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**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.
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-----
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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.
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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
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_athirdpath__Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |20.74|
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|IFEval (0-Shot) |45.21|
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|BBH (3-Shot) |28.02|
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|MATH Lvl 5 (4-Shot)| 8.84|
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|GPQA (0-shot) | 5.59|
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|MuSR (0-shot) | 8.30|
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|MMLU-PRO (5-shot) |28.50|
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