Inquiry on training byt5
Hello, I am working on an app to help native speakers of African local languages, I need help with a model to correct typos and spellings.
I was requesting for help with a notebook or code to fine tune the byt5 for a language.
your help will be much appreciated.
It's great that you're working on an app for African local languages. Fine-tuning ByT5 for typo and spelling correction is a good approach, especially since ByT5 operates at the byte level, which is well-suited for a wide variety of languages, including those with unique alphabets and character encodings.
To help you get started, here are two resources that should be helpful:
Fine-Tuning ByT5 Notebook: If you already have a dataset of correct and incorrect text samples for your target language, this notebook will guide you through fine-tuning ByT5 on your dataset. It will help you customize the model to better handle specific spelling and typo correction tasks for your language.
Towards-Lithuanian-Grammatical-Error-Correction : If you don't have a dataset yet, this notebook can help you generate synthetic grammatical mistakes for training purposes. You can adapt this to your specific language needs to create a dataset for fine-tuning. It also contains fine-tuning examples.
Additional Tips:
- Depending on the language you're working with, you may need to modify some preprocessing steps or introduce custom tokenizers.
- Make sure your dataset is representative of the specific error patterns in your target language.
- If your language uses non-Latin scripts or has other complexities, ByT5's byte-level processing should handle it well, but it may require some additional tuning for optimal performance.
Good luck with your project! If you need further clarification or have more specific questions about fine-tuning, feel free to reach out to me.