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Data synthesis for SOTA LLMs (Practical AI #255)

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CHAPTER

Fine-Tuning Models and Hyperparameters

The speakers discuss the process of fine-tuning models and offer advice on hyperparameter selection. They recommend training for more tokens and epochs if overfitting is not an issue and mention Axolotl as a useful library. Various techniques such as instruction tuning, model merging, and reward model stuff are also discussed.

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