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license: mit |
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datasets: |
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- bsmock/pubtables-1m |
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tags: |
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- table structure recognition |
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- table extraction |
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--- |
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# Model Card for TATR-v1.1-Pub |
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This repo contains the model weights for TATR (Table Transformer) v1.1 trained on the PubTables-1M dataset, using the training details in the paper: ["Aligning benchmark datasets for table structure recognition"](https://arxiv.org/abs/2303.00716). |
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These model weights are intended to be used with [the Microsoft implementation of Table Transformer (TATR)](https://github.com/microsoft/table-transformer). |
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This model (v1.1) was trained with additional image cropping compared to [v1.0](https://huggingface.co/bsmock/tatr-pubtables1m-v1.0) and works best on tightly cropped table images (5 pixels or less). |
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It was also trained for more epochs, and as a result it outperforms the original model on PubTables-1M. |
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Evaluation metrics in the paper were computed with the PubTables-1M v1.1 dataset, which tightly crops the table images in the test and validation splits. |
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Table images in PubTables-1M v1.0, on the other hand, have ~30 pixels of padding in all three splits (train, test, and val). |
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Model weights that can be loaded into the Hugging Face implementation of TATR are coming soon. |
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## Model Details |
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### Model Description |
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- **Developed by:** Brandon Smock and Rohith Pesala, while at Microsoft |
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- **License:** MIT |
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- **Finetuned from model:** DETR ResNet-18 |
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### Model Sources |
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Please see the following for more details: |
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- **Repository:** ["https://github.com/microsoft/table-transformer"](https://github.com/microsoft/table-transformer) |
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- **Paper:** ["Aligning benchmark datasets for table structure recognition"](https://arxiv.org/abs/2303.00716) |
