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---
language:
- en
license: llama3
model-index:
- name: L3-8B-Lunaris-v1
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: 68.95
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Sao10K/L3-8B-Lunaris-v1
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: 32.11
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Sao10K/L3-8B-Lunaris-v1
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: 8.46
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Sao10K/L3-8B-Lunaris-v1
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: 6.82
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Sao10K/L3-8B-Lunaris-v1
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: 5.55
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Sao10K/L3-8B-Lunaris-v1
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: 30.97
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Sao10K/L3-8B-Lunaris-v1
name: Open LLM Leaderboard
---
A generalist / roleplaying model merge based on Llama 3. Models are selected from my personal experience while using them.
I personally think this is an improvement over Stheno v3.2, considering the other models helped balance out its creativity and at the same time improving its logic.
Settings:
```
Instruct // Context Template: Llama-3-Instruct
Temperature: 1.4
min_p: 0.1
```
---
Merging seems to be a black box magic though? In my personal experience merging multiple models from different datasets / data works better than combining them all in one.
*Values chosen are from long-running personal experimentation since Llama-2 Merging Era. I have tweaked them to fit this recipe.*
Mergekit Config
```
models:
- model: meta-llama/Meta-Llama-3-8B-Instruct
- model: crestf411/L3-8B-sunfall-v0.1 # Another RP Model trained on... stuff
parameters:
density: 0.4
weight: 0.25
- model: Hastagaras/Jamet-8B-L3-MK1 - # Another RP / Storytelling Model
parameters:
density: 0.5
weight: 0.3
- model: maldv/badger-iota-llama-3-8b #Megamerge - Helps with General Knowledge
parameters:
density: 0.6
weight: 0.35
- model: Sao10K/Stheno-3.2-Beta # This is Stheno v3.2's Initial Name
parameters:
density: 0.7
weight: 0.4
merge_method: ties
base_model: meta-llama/Meta-Llama-3-8B-Instruct
parameters:
int8_mask: true
rescale: true
normalize: false
dtype: bfloat16
```
# [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_Sao10K__L3-8B-Lunaris-v1)
| Metric |Value|
|-------------------|----:|
|Avg. |25.48|
|IFEval (0-Shot) |68.95|
|BBH (3-Shot) |32.11|
|MATH Lvl 5 (4-Shot)| 8.46|
|GPQA (0-shot) | 6.82|
|MuSR (0-shot) | 5.55|
|MMLU-PRO (5-shot) |30.97|
|