README.md

---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- meta-llama/Meta-Llama-3-8B-Instruct
- meta-llama/Meta-Llama-3.1-8B-Instruct
model-index:
- name: LlamaExecutor-8B-3.0.5
  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: 74.03
      name: strict accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
      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: 28.41
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
      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: 8.53
      name: exact match
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
      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: 0.78
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
      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: 4.65
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
      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: 29.17
      name: accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=UKzExecution/LlamaExecutor-8B-3.0.5
      name: Open LLM Leaderboard
---
# mergellama

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the [task arithmetic](https://arxiv.org/abs/2212.04089) merge method using [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3.1-8B-Instruct) as a base.

### Models Merged

The following models were included in the merge:
* [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3-8B-Instruct)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: meta-llama/Meta-Llama-3-8B-Instruct
    parameters:
      weight: 0.2
  - model: meta-llama/Meta-Llama-3.1-8B-Instruct
    parameters:
      weight: 0.8

base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
merge_method: task_arithmetic
parameters:
  normalize: true
  int8_mask: true

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_UKzExecution__LlamaExecutor-8B-3.0.5)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |24.26|
|IFEval (0-Shot)    |74.03|
|BBH (3-Shot)       |28.41|
|MATH Lvl 5 (4-Shot)| 8.53|
|GPQA (0-shot)      | 0.78|
|MuSR (0-shot)      | 4.65|
|MMLU-PRO (5-shot)  |29.17|