README.md

---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- nbeerbower/gemma2-gutenberg-9B
- princeton-nlp/gemma-2-9b-it-SimPO
- jsgreenawalt/gemma-2-9B-it-advanced-v2.1
- UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
- recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
- unsloth/gemma-2-9b-it
- lemon07r/Gemma-2-Ataraxy-v2-9B
- ifable/gemma-2-Ifable-9B
- grimjim/Gemma2-Nephilim-v3-9B
- lemon07r/Gemma-2-Ataraxy-v2a-9B
- wzhouad/gemma-2-9b-it-WPO-HB
- lemon07r/Gemma-2-Ataraxy-9B
model-index:
- name: Gemma-2-Ataraxy-Remix-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: 70.83
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Remix-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: 41.59
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Remix-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: 1.28
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Remix-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: 11.86
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Remix-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: 13.72
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Remix-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: 35.99
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Remix-9B
      name: Open LLM Leaderboard
---
# Gemma-2-Ataraxy-Remix-9B

Another test model. Ignore this for now. Probably wont be good but I am testing a lot of stuff. 

## GGUF to Try
https://huggingface.co/lemon07r/Gemma-2-Ataraxy-Remix-9B-Q8_0-GGUF

## Merge Details
### Merge Method

This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [unsloth/gemma-2-9b-it](https://huggingface.co/unsloth/gemma-2-9b-it) as a base.

### Models Merged

The following models were included in the merge:
* [nbeerbower/gemma2-gutenberg-9B](https://huggingface.co/nbeerbower/gemma2-gutenberg-9B)
* [princeton-nlp/gemma-2-9b-it-SimPO](https://huggingface.co/princeton-nlp/gemma-2-9b-it-SimPO)
* [jsgreenawalt/gemma-2-9B-it-advanced-v2.1](https://huggingface.co/jsgreenawalt/gemma-2-9B-it-advanced-v2.1)
* [UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3)
* [recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp](https://huggingface.co/recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp)
* [lemon07r/Gemma-2-Ataraxy-v2-9B](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-v2-9B)
* [ifable/gemma-2-Ifable-9B](https://huggingface.co/ifable/gemma-2-Ifable-9B)
* [grimjim/Gemma2-Nephilim-v3-9B](https://huggingface.co/grimjim/Gemma2-Nephilim-v3-9B)
* [lemon07r/Gemma-2-Ataraxy-v2a-9B](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-v2a-9B)
* [wzhouad/gemma-2-9b-it-WPO-HB](https://huggingface.co/wzhouad/gemma-2-9b-it-WPO-HB)
* [lemon07r/Gemma-2-Ataraxy-9B](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-9B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: unsloth/gemma-2-9b-it
dtype: bfloat16
merge_method: model_stock
slices:
- sources:
  - layer_range: [0, 42]
    model: lemon07r/Gemma-2-Ataraxy-9B
  - layer_range: [0, 42]
    model: lemon07r/Gemma-2-Ataraxy-v2-9B
  - layer_range: [0, 42]
    model: lemon07r/Gemma-2-Ataraxy-v2a-9B
  - layer_range: [0, 42]
    model: jsgreenawalt/gemma-2-9B-it-advanced-v2.1
  - layer_range: [0, 42]
    model: ifable/gemma-2-Ifable-9B
  - layer_range: [0, 42]
    model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
  - layer_range: [0, 42]
    model: princeton-nlp/gemma-2-9b-it-SimPO
  - layer_range: [0, 42]
    model: wzhouad/gemma-2-9b-it-WPO-HB
  - layer_range: [0, 42]
    model: nbeerbower/gemma2-gutenberg-9B
  - layer_range: [0, 42]
    model: grimjim/Gemma2-Nephilim-v3-9B
  - layer_range: [0, 42]
    model: recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp
  - layer_range: [0, 42]
    model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3
  - layer_range: [0, 42]
    model: unsloth/gemma-2-9b-it
```

# [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-Remix-9B)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |29.21|
|IFEval (0-Shot)    |70.83|
|BBH (3-Shot)       |41.59|
|MATH Lvl 5 (4-Shot)| 1.28|
|GPQA (0-shot)      |11.86|
|MuSR (0-shot)      |13.72|
|MMLU-PRO (5-shot)  |35.99|