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