Bookworm-10.7B-v0.4-DPO

Bookworm-10.7B-v0.4-DPO

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Our Dedicated Team (Alphabetical Order)

About the Model

This model is a fine-tuned version of yanolja/KoSOLAR-10.7B-v0.2, which is a Korean vocabulary-extended version of upstage/SOLAR-10.7B-v1.0. Specifically, we employed Direct Preference Optimization (DPO) based on LLaMA-Factory.

Training Data

• Korean-translated version of Open-Orca/SlimOrca-Dedup
• Korean-translated version of argilla/ultrafeedback-binarized-preferences-cleaned
• No other dataset was used

Citation

@misc{cui2023ultrafeedback,
      title={UltraFeedback: Boosting Language Models with High-quality Feedback}, 
      author={Ganqu Cui and Lifan Yuan and Ning Ding and Guanming Yao and Wei Zhu and Yuan Ni and Guotong Xie and Zhiyuan Liu and Maosong Sun},
      year={2023},
      eprint={2310.01377},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@misc{SlimOrcaDedup,
  title = {SlimOrca Dedup: A Deduplicated Subset of SlimOrca},
  author = {Wing Lian and Guan Wang and Bleys Goodson and Eugene Pentland and Austin Cook and Chanvichet Vong and "Teknium" and Nathan Hoos},
  year = {2023},
  publisher = {HuggingFace},
  url = {https://huggingface.co/datasets/Open-Orca/SlimOrca-Dedup/}
}

@misc{mukherjee2023orca,
      title={Orca: Progressive Learning from Complex Explanation Traces of GPT-4}, 
      author={Subhabrata Mukherjee and Arindam Mitra and Ganesh Jawahar and Sahaj Agarwal and Hamid Palangi and Ahmed Awadallah},
      year={2023},
      eprint={2306.02707},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}