jpWang / LiLT

Official PyTorch implementation of LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding (ACL 2022)
MIT License
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Fine-tuning on custom data #3

Open siamakzd opened 2 years ago

siamakzd commented 2 years ago

Thank you for sharing your great work!

If I want to fine-tune on a custom dataset, what should be the steps? i.e.

-Which scripts we need to modify?

Thanks in advance!

jpWang commented 2 years ago

Hi, I think the main steps should be:

If you want to do something beyond training/evaluating, You can add your code to the lines after the model makes predictions, such as https://github.com/jpWang/LiLT/blob/main/examples/run_funsd.py#L345 in run_funsd.py.

NielsRogge commented 1 year ago

Hi,

See also my demo notebooks here: https://github.com/NielsRogge/Transformers-Tutorials/tree/master/LiLT

hamzabchiri commented 1 year ago

Hello,

Could you let me know when you have a Custom dataset and how to organize your dataset into the format of FUNSD/XFUND?

and do you recommend any tutorial for this step?

Thank you in advance.