license: apache-2.0
model-index:
- name: ArliAI-RPMax-12B-v1.1
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: 53.49
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/ArliAI-RPMax-12B-v1.1
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: 24.81
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/ArliAI-RPMax-12B-v1.1
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: 9.21
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/ArliAI-RPMax-12B-v1.1
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: 4.25
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/ArliAI-RPMax-12B-v1.1
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: 5.56
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/ArliAI-RPMax-12B-v1.1
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: 26.49
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/ArliAI-RPMax-12B-v1.1
name: Open LLM Leaderboard
ArliAI-RPMax-12B-v1.1
=====================================
RPMax Series Overview
| 2B | 3.8B | 8B | 9B | 12B | 20B | 22B | 70B |
RPMax is a series of models that are trained on a diverse set of curated creative writing and RP datasets with a focus on variety and deduplication. This model is designed to be highly creative and non-repetitive by making sure no two entries in the dataset have repeated characters or situations, which makes sure the model does not latch on to a certain personality and be capable of understanding and acting appropriately to any characters or situations.
Early tests by users mentioned that these models does not feel like any other RP models, having a different style and generally doesn't feel in-bred.
You can access the model at https://arliai.com and ask questions at https://www.reddit.com/r/ArliAI/
We also have a models ranking page at https://www.arliai.com/models-ranking
Ask questions in our new Discord Server! https://discord.com/invite/t75KbPgwhk
Model Description
ArliAI-RPMax-12B-v1.1 is a variant based on Mistral Nemo 12B Instruct 2407.
This is arguably the most successful RPMax model due to how Mistral is already very uncensored in the first place.
Training Details
- Sequence Length: 8192
- Training Duration: Approximately 2 days on 2x3090Ti
- Epochs: 1 epoch training for minimized repetition sickness
- QLORA: 64-rank 128-alpha, resulting in ~2% trainable weights
- Learning Rate: 0.00001
- Gradient accumulation: Very low 32 for better learning.
Quantization
The model is available in quantized formats:
- FP16: https://huggingface.co/ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1
- GPTQ_Q4: https://huggingface.co/ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1-GPTQ_Q4
- GPTQ_Q8: https://huggingface.co/ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1-GPTQ_Q8
- GGUF: https://huggingface.co/ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1-GGUF
Suggested Prompt Format
Mistral Instruct Prompt Format
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 20.64 |
IFEval (0-Shot) | 53.49 |
BBH (3-Shot) | 24.81 |
MATH Lvl 5 (4-Shot) | 9.21 |
GPQA (0-shot) | 4.25 |
MuSR (0-shot) | 5.56 |
MMLU-PRO (5-shot) | 26.49 |