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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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Recommendations for inference and further fine-tuning #16

Closed leitouran closed 1 year ago

leitouran commented 2 years ago

Hi,

Just got my XFUND-ES finetuning job to work! While I wait, I am trying to work my way through the code to create an inference script. Would running the run_xfun_ser.py script with --do_predict (and passing the checkpoint I obtained by finetuning) suffice? Also, if I wanted to create my own dataset to finetune further, would you recommend a transfer learning approach starting from this XFUND fine-tuned checkpoint or should I go straight to create the custom dataset?

Thank you very much in advance. This is great work!

jpWang commented 2 years ago

Hi, (1) Yes. You can write what you want to do under https://github.com/jpWang/LiLT/blob/main/examples/run_xfun_ser.py#L268. (2) I think you can go straight to create your own custom dataset.