<FrameworkSwitchCourse {fw} />
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
- 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
- Learned how to load and preprocess datasets
- Learned how to fine-tune and evaluate a model with Keras
- Implemented a custom metric
{/if}