README.md

---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- bardsai/jaskier-7b-dpo-v5.6
- eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO
model-index:
- name: Ogno-Monarch-Neurotic-7B-Dare-Ties
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 73.21
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AtAndDev/Ogno-Monarch-Neurotic-7B-Dare-Ties
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 88.99
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AtAndDev/Ogno-Monarch-Neurotic-7B-Dare-Ties
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 64.58
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AtAndDev/Ogno-Monarch-Neurotic-7B-Dare-Ties
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 77.53
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AtAndDev/Ogno-Monarch-Neurotic-7B-Dare-Ties
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 84.53
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AtAndDev/Ogno-Monarch-Neurotic-7B-Dare-Ties
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 69.07
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AtAndDev/Ogno-Monarch-Neurotic-7B-Dare-Ties
      name: Open LLM Leaderboard
---

# Ogno-Monarch-Neurotic-7B-Dare-Ties

Ogno-Monarch-Neurotic-7B-Dare-Ties is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [bardsai/jaskier-7b-dpo-v5.6](https://huggingface.co/bardsai/jaskier-7b-dpo-v5.6)
* [eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO](https://huggingface.co/eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO)

## 🧩 Configuration

```yaml
models:
  - model: bardsai/jaskier-7b-dpo-v5.6
    parameters:
      density: .53
      weight: .6
  - model: eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO
    parameters:
      density: .53
      weight: .5
merge_method: dare_ties
base_model: bardsai/jaskier-7b-dpo-v5.6
parameters:
  int8_mask: true
dtype: bfloat16
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_AtAndDev__Ogno-Monarch-Neurotic-7B-Dare-Ties)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |76.32|
|AI2 Reasoning Challenge (25-Shot)|73.21|
|HellaSwag (10-Shot)              |88.99|
|MMLU (5-Shot)                    |64.58|
|TruthfulQA (0-shot)              |77.53|
|Winogrande (5-shot)              |84.53|
|GSM8k (5-shot)                   |69.07|