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# vit-artworkclassifier
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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 imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1392
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- Accuracy: 0.5948
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# vit-artworkclassifier
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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 imagefolder dataset. This is a subset of the artbench-10 dataset, with a train set of 1000 artworks per class and a test set of 100 artworks per class.
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It achieves the following results on the evaluation set:
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- Loss: 1.1392
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- Accuracy: 0.5948
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