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
Dorflan
An experimental model
| 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
Detailed results can be found here
| 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 |