Fine-tuning on custom invoices
Hi @magorshunov , great model, I just want to know how we can fine tune it, because as per LayoutLM paper, it was not meant for DocVQA, but I think it is working great than other versions of the model
It would be great If you can redirect me to train this model
Hey! This is just a copy of Impira's model (https://huggingface.co/impira/layoutlm-invoices). I wish I knew how to fine-tune it. If you find out, please let me know :)
Hi, I have been able to finetune it, here is the training code and updated model:
Training Code: https://www.kaggle.com/code/tusharcode/training-layoutlm-docvqa
Model: https://huggingface.co/TusharGoel/LayoutLM-Finetuned-DocVQA
Hi nice work, what is the difference between docvga and squadv2 part? Did you have an improvement in the performance after training?
I found the dataset, sorry but i get an error
processed_inputs = function(*fn_args, *additional_args, **fn_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "training-layoutlm-docvqa.py", line 388, in encode_dataset
while token_type_ids[token_start_index] != 1:
~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^