---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- nbeerbower/Gemma2-Gutenberg-Doppel-9B
- ifable/gemma-2-Ifable-9B
- unsloth/gemma-2-9b-it
- wzhouad/gemma-2-9b-it-WPO-HB
model-index:
- name: Gemma-2-Ataraxy-v3i-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: 42.03
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-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: 38.24
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-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: 0.15
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-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: 10.4
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-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: 1.76
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-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: 35.18
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v3i-9B
      name: Open LLM Leaderboard
---
# Gemma-2-Ataraxy-v3i-9B

Another experimental model. This one is in the vein of advanced 2.1, but we replace the simpo model used in the original recipe, with a different simpo model, that was more finetuned with writing in mind, ifable. We also use another writing model, which was trained on gutenberg. We use this one at a higher density because SPPO, on paper is the superior training method, to simpo, and quite frankly, ifable is finicky to work with, and can end up being a little too strong.. or heavy in merges. It's a very strong writer but it introduced quite a bit slop in v2. 

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

## GGUF

https://huggingface.co/lemon07r/Gemma-2-Ataraxy-v3i-9B-Q8_0-GGUF

## Merge Details
### Merge Method

This model was merged using the della 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-Doppel-9B](https://huggingface.co/nbeerbower/Gemma2-Gutenberg-Doppel-9B)
* [ifable/gemma-2-Ifable-9B](https://huggingface.co/ifable/gemma-2-Ifable-9B)
* [wzhouad/gemma-2-9b-it-WPO-HB](https://huggingface.co/wzhouad/gemma-2-9b-it-WPO-HB)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: unsloth/gemma-2-9b-it
dtype: bfloat16
merge_method: della
parameters:
  epsilon: 0.1
  int8_mask: 1.0
  lambda: 1.0
  normalize: 1.0
slices:
- sources:
  - layer_range: [0, 42]
    model: unsloth/gemma-2-9b-it
  - layer_range: [0, 42]
    model: wzhouad/gemma-2-9b-it-WPO-HB
    parameters:
      density: 0.55
      weight: 0.6
  - layer_range: [0, 42]
    model: nbeerbower/Gemma2-Gutenberg-Doppel-9B
    parameters:
      density: 0.35
      weight: 0.6
  - layer_range: [0, 42]
    model: ifable/gemma-2-Ifable-9B
    parameters:
      density: 0.25
      weight: 0.4
```

# [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-v3i-9B)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |21.29|
|IFEval (0-Shot)    |42.03|
|BBH (3-Shot)       |38.24|
|MATH Lvl 5 (4-Shot)| 0.15|
|GPQA (0-shot)      |10.40|
|MuSR (0-shot)      | 1.76|
|MMLU-PRO (5-shot)  |35.18|