<FrameworkSwitchCourse {fw} />

# Fine-tuning, Check![[fine-tuning-check]]

<CourseFloatingBanner
    chapter={3}
    classNames="absolute z-10 right-0 top-0"
/>

That was fun! In the first two chapters you learned about models and tokenizers, and now you know how to fine-tune them for your own data. To recap, in this chapter you:

{#if fw === 'pt'}
* Learned about datasets in the [Hub](https://huggingface.co/datasets)
* Learned how to load and preprocess datasets, including using dynamic padding and collators
* Implemented your own fine-tuning and evaluation of a model
* Implemented a lower-level training loop
* Used 🤗 Accelerate to easily adapt your training loop so it works for multiple GPUs or TPUs

{:else}
* Learned about datasets in the [Hub](https://huggingface.co/datasets)
* Learned how to load and preprocess datasets
* Learned how to fine-tune and evaluate a model with Keras
* Implemented a custom metric

{/if}
