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donut-booking-extract – AI Model by uartimcs | AlphaNeural AI
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uartimcs
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donut-booking-extract
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transformers
pytorch
tensorboard
donut
logistics
document-parsing
image-text-to-text
en
naver-clova-ix/donut-base-finetuned-cord-v2
finetune
endpoints_compatible
us
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🏗️ This is a FYP project topic on document parsing of 🚚 logistics 🚚 shipping documents for system integration.
https://huggingface.co/uartimcs/donut-booking-extract/blob/main/FYP.pdf
Latest update on the version of modules used to continue run the program because there is no recent update for the donut pretrained model.
My use case:
Extract common key datafields from shipping documents generated from ten different shipping lines.
Repo & Datasets
donut.zip (Original Donut Repo + Labelled Booking Dummy Datasets with JSONL files + Config Files)
sample-image-to-play.zip (Excess dummy datasets used to play and test the model)
https://huggingface.co/spaces/uartimcs/donut-booking-gradio
Colab Notebooks
donut-booking-train.ipynb (Train the model in Colab using T4 TPU / A100 GPU environment)
donut-booking-run.ipynb (Run the model in Colab using gradio using T4 TPU / A100 GPU environment)
Size of dataset
Follow the CORD-v2 dataset ratio:
train: 800 (80 pics x 10 classes)
validation: 100 (10 pics x 10 classes)
test: 100 (10 pics x 10 classes)
