README.md

---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- cognitivecomputations/Dolphin3.0-Llama3.2-3B
- bunnycore/Llama-3.2-3B-Smart-v1-lora
model-index:
- name: Dolphin3-Llama3.2-Smart
  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: 41.37
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Dolphin3-Llama3.2-Smart
      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: 15.35
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Dolphin3-Llama3.2-Smart
      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: 2.11
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Dolphin3-Llama3.2-Smart
      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: 2.57
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Dolphin3-Llama3.2-Smart
      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: 8.15
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Dolphin3-Llama3.2-Smart
      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: 13.28
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Dolphin3-Llama3.2-Smart
      name: Open LLM Leaderboard
---
# merge

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 passthrough merge method using [cognitivecomputations/Dolphin3.0-Llama3.2-3B](https://huggingface.co/cognitivecomputations/Dolphin3.0-Llama3.2-3B) + [bunnycore/Llama-3.2-3B-Smart-v1-lora](https://huggingface.co/bunnycore/Llama-3.2-3B-Smart-v1-lora) as a base.

### Models Merged

The following models were included in the merge:


### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: cognitivecomputations/Dolphin3.0-Llama3.2-3B+bunnycore/Llama-3.2-3B-Smart-v1-lora
dtype: bfloat16
merge_method: passthrough
models:
  - model: cognitivecomputations/Dolphin3.0-Llama3.2-3B+bunnycore/Llama-3.2-3B-Smart-v1-lora


```

# [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/Triangle104__Dolphin3-Llama3.2-Smart-details)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |13.81|
|IFEval (0-Shot)    |41.37|
|BBH (3-Shot)       |15.35|
|MATH Lvl 5 (4-Shot)| 2.11|
|GPQA (0-shot)      | 2.57|
|MuSR (0-shot)      | 8.15|
|MMLU-PRO (5-shot)  |13.28|