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# vit_tickers_binaryclf
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the cord dataset.
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- Loss: 0.0116
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- F1: 0.9991
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# vit_tickers_binaryclf
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the cord, rvl-cdip, visual-genome and an external receipt tickers dataset, to carry out Binary Classification (`ticket` vs `no_ticket`).
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It achieves the following results on the evaluation set, which contain pictures from the above datasets in scanned, photography or mobile picture formats (color and grayscale):
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- Loss: 0.0116
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- F1: 0.9991
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