README.md

---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- lemon07r/Gemma-2-Ataraxy-v3b-9B
- zelk12/recoilme-gemma-2-Ataraxy-9B-v0.1-t0.25
model-index:
- name: Gemma-2-Ataraxy-v4c-9B
  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: 69.45
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v4c-9B
      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: 44.13
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v4c-9B
      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: 17.98
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v4c-9B
      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: 11.19
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v4c-9B
      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: 15.3
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v4c-9B
      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: 37.72
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v4c-9B
      name: Open LLM Leaderboard
---
# Gemma-2-Ataraxy-v4c-9B

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 SLERP merge method.

### Models Merged

The following models were included in the merge:
* [lemon07r/Gemma-2-Ataraxy-v3b-9B](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-v3b-9B)
* [zelk12/recoilme-gemma-2-Ataraxy-9B-v0.1-t0.25](https://huggingface.co/zelk12/recoilme-gemma-2-Ataraxy-9B-v0.1-t0.25)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: zelk12/recoilme-gemma-2-Ataraxy-9B-v0.1-t0.25
dtype: bfloat16
merge_method: slerp
parameters:
  t: 0.25
slices:
- sources:
  - layer_range: [0, 42]
    model: zelk12/recoilme-gemma-2-Ataraxy-9B-v0.1-t0.25
  - layer_range: [0, 42]
    model: lemon07r/Gemma-2-Ataraxy-v3b-9B
```

# [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_lemon07r__Gemma-2-Ataraxy-v4c-9B)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |32.63|
|IFEval (0-Shot)    |69.45|
|BBH (3-Shot)       |44.13|
|MATH Lvl 5 (4-Shot)|17.98|
|GPQA (0-shot)      |11.19|
|MuSR (0-shot)      |15.30|
|MMLU-PRO (5-shot)  |37.72|