---
license: mit
datasets:
- Open-Orca/OpenOrca
- conceptofmind/cot_submix_original
- conceptofmind/t0_submix_original
- conceptofmind/niv2_submix_original
- conceptofmind/flan2021_submix_original
- ehartford/dolphin
language:
- en
tags:
- merge
- slerp
inference: false
metrics:
- accuracy
- bleu
---
<h1 style="text-align: center">Dorflan</h1>
<h2 style="text-align: center">An experimental model</h2>
<hr>


|   Model      |  Average ⬆️  |   ARC   | HellaSwag |   MMLU  | TruthfulQA |
|:------------:|:------------:|:-------:|:---------:|:-------:|:----------:|
| formulae/Dorflan 📑 |    58.19     |   54.44   |   75.78   |   51.36   |    51.17   |



## Model Details
Dorflan is an experimental merged model created from the following three foundation models:

- stabilityai/StableBeluga-7B
- ehartford/dolphin-llama2-7b  
- AIDC-ai-business/Marcoroni-7B

Dorflan was created by merging the weights and architectures of these three models using a custom merging technique. No further fine-tuning was performed after the merge.

Once the model obtains it's evaluation scores, then we'll know if it works or not.

## Intended Use
As an experimental model, Dorflan is intended for testing and research purposes only. It should not be used for production systems or to generate content for public use.

## Training Data
Dorflan inherits training data from its three foundation models:

- StableBeluga-7B: COT, Niv2, t0, & FLAN2021
- dolphin-llama2-7b: Dolphin
- Marcoroni-7B: OpenOrca

## Limitations
As an untested merged model, Dorflan has unknown capabilities and limitations. Potential issues include:

- Instability due to merged architectures
- Compounded bias and issues from all three foundation models
- Decreased performance on some tasks compared to the foundation models

Extensive testing is required to characterize Dorflan's capabilities and limitations.

## Ethical Considerations
- Dorflan may exhibit harmful biases inherited from its training data
- Output may be unreliable or manipulated due to instability
- Experimental nature increases potential for misuse

Use this model ethically and do not deploy it for sensitive applications.

## Contact Information
Please report issues or concerns with this model to the creator for further investigation.
# [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_formulae__Dorflan)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 47.44   |
| ARC (25-shot)         | 54.44          |
| HellaSwag (10-shot)   | 75.78    |
| MMLU (5-shot)         | 51.36         |
| TruthfulQA (0-shot)   | 51.17   |
| Winogrande (5-shot)   | 72.61   |
| GSM8K (5-shot)        | 0.38        |
| DROP (3-shot)         | 26.37         |