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---
license: llama3.1
base_model:
- DreadPoor/LemonP-8B-Model_Stock
- Youlln/1PARAMMYL-8B-ModelStock
- jaspionjader/f-2-8b
- Etherll/SuperHermes
- meta-llama/Llama-3.1-8B-Instruct
tags:
- merge
- mergekit
model-index:
- name: Llama3.1-Daredevilish-Instruct
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: wis-k/instruction-following-eval
split: train
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 79.41
name: averaged accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish-Instruct
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: SaylorTwift/bbh
split: test
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 32.22
name: normalized accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish-Instruct
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: lighteval/MATH-Hard
split: test
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 16.77
name: exact match
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish-Instruct
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
split: train
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 7.61
name: acc_norm
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish-Instruct
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: 7.92
name: acc_norm
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish-Instruct
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: 31.97
name: accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish-Instruct
name: Open LLM Leaderboard
---
# Llama 3.1 Daredevilish Instruct
- This model is an experimental Llama 3.1-based merge, inspired by the approach used in [mlabonne/Daredevil-8B](https://huggingface.co./mlabonne/Daredevil-8B).
- It combines top-performing Llama 3.1 8B models on the MMLU-Pro benchmark from the [Open LLM Leaderboard](https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/) as of January 21, 2025.
- Its straightforward language makes it accessible and potentially valuable for everyday use.
## Model Details
- **Architecture:** Llama 3.1 (8.03B parameters)
- **Training:** Merged from top MMLU-Pro models without additional finetuning
- **Release Date:** January 21, 2025
## Merge Configuration
The model was created using [mergekit](https://github.com/arcee-ai/mergekit) with the following merge configuration:
```yaml
models:
- model: DreadPoor/LemonP-8B-Model_Stock
parameters:
density: 0.6
weight: 0.16
- model: Youlln/1PARAMMYL-8B-ModelStock
parameters:
density: 0.6
weight: 0.13
- model: jaspionjader/f-2-8b
parameters:
density: 0.6
weight: 0.10
- model: Etherll/SuperHermes
parameters:
density: 0.6
weight: 0.08
merge_method: dare_ties
base_model: meta-llama/Llama-3.1-8B-Instruct
dtype: bfloat16
```
## Usage and Limitations
This experimental model is designed for research and development purposes. Users should be aware of potential biases and limitations inherent in language models. Always validate outputs and use the model responsibly.
## Future Work
Further evaluation and fine-tuning may be necessary to optimize performance across various tasks. Researchers are encouraged to build upon this experimental merge to advance the capabilities of Llama-based models.
# [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/agentlans__Llama3.1-Daredevilish-Instruct-details)!
Summarized results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/contents/viewer/default/train?q=agentlans%2FLlama3.1-Daredevilish-Instruct&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
| Metric |Value (%)|
|-------------------|--------:|
|**Average** | 29.32|
|IFEval (0-Shot) | 79.41|
|BBH (3-Shot) | 32.22|
|MATH Lvl 5 (4-Shot)| 16.77|
|GPQA (0-shot) | 7.61|
|MuSR (0-shot) | 7.92|
|MMLU-PRO (5-shot) | 31.97|
|