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---
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 |
|