task_categories:text-classification task_categories:question-answering task_categories:summarization task_categories:conversational task_categories:text-generation size_categories:10K<n<100K language:en region:us
---
task_categories:
- text-classification
- question-answering
- summarization
- conversational
- text-generation
language:
- en
size_categories:
- 10K<n<100K
---

<p align="center"><img src="https://cdn-uploads.huggingface.co/production/uploads/63e087b6a98d931aa90c1b9c/jm4fCY9DMGDxDRyhIeDZh.jpeg"></p>

# The Wyvern 🐉 Dataset

Let's introduce the **Wyvern 🐉** dataset, the new combination of datasets([Open-Orca](https://huggingface.co/datasets/Open-Orca/OpenOrca), 
[Open-Platypus](https://huggingface.co/datasets/garage-bAInd/Open-Platypus), [airoboros](https://huggingface.co/datasets/jondurbin/airoboros-2.1), 
[Dolly](https://huggingface.co/datasets/databricks/databricks-dolly-15k))!
We have integrated high-quality datasets following the claim that quality is more matter than quantity.
In addition, we have deduplicated the duplication of datasets to improve the dataset's quality because each dataset has some data contaminations.
Please see below for more details about the dataset!


# Dataset Details

**Wyvern 🐉** dataset is mixture of several datasets(Open-Orca, Open-Platypus, airoboros, Dolly) as mentioned above.
The specific configuration of the dataset is as follows. 
(Open-Orca GPT-4 answered dataset was sampled using stratified sampling)

- **Open-Platypus(100%) + airoboros(100%) + Open-Orca(GPT-4)(5%)(stratified sampled) + Dolly-15k(100%)**

|Dataset Name|Sampled Size(ratio)|Deduped Size|License Type|
|---|---|---|---|
|[Open-Platypus](https://huggingface.co/datasets/garage-bAInd/Open-Platypus)|24.9k(100%)|16.8k|None|
|[airoboros](https://huggingface.co/datasets/jondurbin/airoboros-2.1)|36.3k(100%)|11k|apache-2.0|
|[Open-Orca](https://huggingface.co/datasets/Open-Orca/OpenOrca)|999.9k → 49.7k(5%)|35.6k|MIT|
|[Dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k)|15k(100%)|11k|cc-by-sa-3.0|

After the deduplication process, the size of the combination dataset is changed from 125k to 74k! (125k → 74k)

# Data Deduplication

We referred to Open-Platypus's [data similarity check code](https://github.com/arielnlee/Platypus/blob/main/data_pipeline/data_similarity.ipynb) to deduplicate the duplicated data.
The specific code for deduplication will be uploaded soon!

# Citations

```
@article{platypus2023,
    title={Platypus: Quick, Cheap, and Powerful Refinement of LLMs}, 
    author={Ariel N. Lee and Cole J. Hunter and Nataniel Ruiz},
    booktitle={arXiv preprint arxiv:2308.07317},
    year={2023}
}
```

```
@misc{OpenOrca,
  title = {OpenOrca: An Open Dataset of GPT Augmented FLAN Reasoning Traces},
  author = {Wing Lian and Bleys Goodson and Eugene Pentland and Austin Cook and Chanvichet Vong and "Teknium"},
  year = {2023},
  publisher = {HuggingFace},
  journal = {HuggingFace repository},
  howpublished = {\url{https://https://huggingface.co/Open-Orca/OpenOrca},
}
```

```
@online{DatabricksBlog2023DollyV2,
    author    = {Mike Conover and Matt Hayes and Ankit Mathur and Jianwei Xie and Jun Wan and Sam Shah and Ali Ghodsi and Patrick Wendell and Matei Zaharia and Reynold Xin},
    title     = {Free Dolly: Introducing the World's First Truly Open Instruction-Tuned LLM},
    year      = {2023},
    url       = {https://www.databricks.com/blog/2023/04/12/dolly-first-open-commercially-viable-instruction-tuned-llm},
    urldate   = {2023-06-30}
}
```