---
license: cc-by-nc-4.0
---

Replaced Zephyr by Airoboros 2.2 and OpenOrca by SynthIA in the mix, the reason why is to see if using merged Mistral models using all the same prompt format would be a better step or not.

## Description

This repo contains fp16 files of Mistral-11B-SynthIAirOmniMix.

## Model used
- [SynthIA-7B-v1.5](https://huggingface.co/migtissera/SynthIA-7B-v1.5)
- [Mistral-7B-v0.1-Open-Platypus](https://huggingface.co/akjindal53244/Mistral-7B-v0.1-Open-Platypus)
- [CollectiveCognition-v1.1-Mistral-7B](https://huggingface.co/teknium/CollectiveCognition-v1.1-Mistral-7B)
- [airoboros-mistral2.2-7b](https://huggingface.co/teknium/airoboros-mistral2.2-7b)

## Prompt template

3 out of 4 models use the same prompting format in this merge.

The best one should be this one, since Zephyr and OpenOrca is out of the merge:

```
(SYSTEM: {context}) - Not mandatory
USER: {prompt}
ASSISTANT:
```

But this one (maybe) work too:

```
Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:

```

## The secret sauce

Mistral-11B-SynthIAOpenPlatypus :
```
slices:
  - sources:
    - model: "/content/drive/MyDrive/SynthIA-7B-v1.5-bf16"
      layer_range: [0, 24]
  - sources:
    - model: akjindal53244/Mistral-7B-v0.1-Open-Platypus
      layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16
```

Mistral-11B-CC-Airo :
```
slices:
  - sources:
    - model: "/content/drive/MyDrive/CC-v1.1-7B-bf16"
      layer_range: [0, 24]
  - sources:
    - model: "/content/drive/MyDrive/Mistral-7B-Airoboros-2.2-bf16"
      layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16
```

Mistral-11B-SynthIAirOmniMix :
```
slices:
  - sources:
      - model: Mistral-11B-SynthIAOpenPlatypus
        layer_range: [0, 48]
      - model: Mistral-11B-CC-Airo
        layer_range: [0, 48]
merge_method: slerp
base_model: Mistral-11B-OpenOrcaPlatypus
parameters:
  t:
    - filter: lm_head 
      value: [0.75]
    - filter: embed_tokens
      value: [0.75]
    - filter: self_attn
      value: [0.75, 0.25]
    - filter: mlp
      value:  [0.25, 0.75]
    - filter: layernorm
      value: [0.5, 0.5]
    - filter: modelnorm
      value: [0.75]
    - value: 0.5 # fallback for rest of tensors
dtype: bfloat16
```
I use [mergekit](https://github.com/cg123/mergekit) for all the manipulation told here.

## Some scoring I done myself


![image/png](https://cdn-uploads.huggingface.co/production/uploads/63ab1241ad514ca8d1430003/rnraBZz-I9CUD1GVNVF00.png)

|    Task     |Version| Metric |Value |   |Stderr|
|-------------|------:|--------|-----:|---|-----:|
|arc_challenge|      0|acc     |0.5410|±  |0.0146|
|             |       |acc_norm|0.5640|±  |0.0145|
|arc_easy     |      0|acc     |0.8228|±  |0.0078|
|             |       |acc_norm|0.8068|±  |0.0081|
|hellaswag    |      0|acc     |0.6274|±  |0.0048|
|             |       |acc_norm|0.8167|±  |0.0039|
|piqa         |      0|acc     |0.8052|±  |0.0092|
|             |       |acc_norm|0.8232|±  |0.0089|
|truthfulqa_mc|      1|mc1     |0.3905|±  |0.0171|
|             |       |mc2     |0.5592|±  |0.0155|
|winogrande   |      0|acc     |0.7364|±  |0.0124|

## Others

Special thanks to Sushi, [Henky](https://github.com/KoboldAI/KoboldAI-Client) for the machine he give me for big task, and [Charles Goddard](https://github.com/cg123) for his amazing tool.

If you want to support me, you can [here](https://ko-fi.com/undiai).
# [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_NeverSleep__Mistral-11B-SynthIAirOmniMix)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 54.56   |
| ARC (25-shot)         | 62.46          |
| HellaSwag (10-shot)   | 83.13    |
| MMLU (5-shot)         | 63.47         |
| TruthfulQA (0-shot)   | 55.69   |
| Winogrande (5-shot)   | 76.4   |
| GSM8K (5-shot)        | 11.9        |
| DROP (3-shot)         | 28.88         |