README.md

---
license: apache-2.0
library_name: transformers
tags:
- mergekit
- merge
base_model:
- mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: my-first-blend
  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: 69.37
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pandego/my-first-blend
      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: 83.03
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pandego/my-first-blend
      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: 53.91
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pandego/my-first-blend
      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: 70.7
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pandego/my-first-blend
      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: 79.32
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pandego/my-first-blend
      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: 25.63
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=pandego/my-first-blend
      name: Open LLM Leaderboard
---
# my-first-blend

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 [task arithmetic](https://arxiv.org/abs/2212.04089) merge method using mistralai/Mistral-7B-Instruct-v0.2 as a base.

### Models Merged

The following models were included in the merge:
* SanjiWatsuki/Kunoichi-DPO-v2-7B
* paulml/NeuralOmniWestBeaglake-7B

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: SanjiWatsuki/Kunoichi-DPO-v2-7B
    parameters:
      weight: 0.4
  - model: paulml/NeuralOmniWestBeaglake-7B
    parameters:
      weight: 0.6
base_model: mistralai/Mistral-7B-Instruct-v0.2
merge_method: task_arithmetic
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_pandego__my-first-blend)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |63.66|
|AI2 Reasoning Challenge (25-Shot)|69.37|
|HellaSwag (10-Shot)              |83.03|
|MMLU (5-Shot)                    |53.91|
|TruthfulQA (0-shot)              |70.70|
|Winogrande (5-shot)              |79.32|
|GSM8k (5-shot)                   |25.63|