README.md

---
license: llama3.1
datasets:
- agentlans/crash-course
base_model:
- DreadPoor/LemonP-8B-Model_Stock
- Youlln/1PARAMMYL-8B-ModelStock
- jaspionjader/f-2-8b
- Etherll/SuperHermes
- meta-llama/Llama-3.1-8B
tags:
- merge
- mergekit
model-index:
- name: Llama3.1-Daredevilish
  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: 62.92
      name: averaged accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish
      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: 29.2
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish
      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: 12.76
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish
      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: 6.82
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish
      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: 11.6
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish
      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: 29.96
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FLlama3.1-Daredevilish
      name: Open LLM Leaderboard
---
# Llama 3.1 Daredevilish

- This model is an experimental Llama 3.1-based merge, inspired by [mlabonne/Daredevil-8B](https://huggingface.co/mlabonne/Daredevil-8B). 
- It combines the top-performing Llama 3.1 8B models on the MMLU-Pro task as of January 21, 2025.

## Model Details

- **Architecture:** Llama 3.1 (8.03B parameters)
- **Training:** Merged from top MMLU-Pro models, with additional supervised fine-tuning (SFT)
- **Release Date:** January 21, 2025

> [!IMPORTANT]
> The model fails to end replies properly when used with some system prompts.
> If this is a problem, consider using [agentlans/Llama3.1-Daredevilish-Instruct](https://huggingface.co/agentlans/Llama3.1-Daredevilish-Instruct) in instruct mode.

## Key Features

1. **Merged Architecture:** Combines high-performing MMLU-Pro models to enhance overall capabilities.
2. **Llama 3 Compatibility:** Additional Supervised Fine-Tuning (SFT) ensures adherence to Llama 3 prompt format.
3. **SFT Dataset:** [agentlans/crash-course](https://huggingface.co/datasets/agentlans/crash-course) dataset (1200 row configuration) for supervised fine-tuning in [LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory).
4. **Fine-Tuning Approach:** 
   - 1 epoch training
   - Rank 4 LoRA
   - Alpha = 4
   - rslora

## 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
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-details)!
Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=agentlans%2FLlama3.1-Daredevilish&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!

|      Metric       |Value (%)|
|-------------------|--------:|
|**Average**        |    25.54|
|IFEval (0-Shot)    |    62.92|
|BBH (3-Shot)       |    29.20|
|MATH Lvl 5 (4-Shot)|    12.76|
|GPQA (0-shot)      |     6.82|
|MuSR (0-shot)      |    11.60|
|MMLU-PRO (5-shot)  |    29.96|