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README.md
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- accuracy
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- f1
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---
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- accuracy
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- f1
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---
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Detects cat breed (from the list of 48 common breeds) based on image.
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See https://www.kaggle.com/code/dima806/cat-breed-image-detection-vit for more details.
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```
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Classification report:
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precision recall f1-score support
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Abyssinian 0.6599 0.8106 0.7276 565
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American Bobtail 0.0000 0.0000 0.0000 564
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American Curl 0.6816 0.2695 0.3863 564
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American Shorthair 0.2222 0.0035 0.0070 564
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Applehead Siamese 0.3788 0.5894 0.4612 565
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Balinese 0.4385 0.2784 0.3406 564
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Bengal 0.5389 0.6879 0.6044 564
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Birman 0.3479 0.6903 0.4626 565
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Bombay 0.2989 0.7681 0.4303 565
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British Shorthair 0.5662 0.2726 0.3680 565
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Burmese 0.7568 0.0993 0.1755 564
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Calico 0.3903 0.4858 0.4329 564
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Cornish Rex 0.5780 0.8655 0.6931 565
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Devon Rex 0.6615 0.1525 0.2478 564
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Dilute Calico 0.4311 0.3493 0.3859 564
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Dilute Tortoiseshell 0.4646 0.5699 0.5119 565
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Domestic Long Hair 0.2783 0.0566 0.0941 565
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Domestic Medium Hair 0.2083 0.0089 0.0170 564
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Domestic Short Hair 0.4615 0.0319 0.0596 565
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Egyptian Mau 0.4387 0.6720 0.5308 564
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Exotic Shorthair 0.7238 0.2319 0.3512 565
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Extra-Toes Cat - Hemingway Polydactyl 0.3333 0.0018 0.0035 565
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Havana 0.5521 0.7876 0.6492 565
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Himalayan 0.4467 0.3858 0.4141 565
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Japanese Bobtail 0.4333 0.0230 0.0437 565
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Maine Coon 0.2336 0.4602 0.3099 565
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Manx 0.2143 0.0053 0.0104 564
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Munchkin 0.0000 0.0000 0.0000 564
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Nebelung 0.5726 0.8584 0.6870 565
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Norwegian Forest 0.3390 0.3883 0.3620 564
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Oriental Short Hair 0.0000 0.0000 0.0000 564
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Persian 0.5197 0.7713 0.6210 564
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Ragamuffin 0.4580 0.1064 0.1727 564
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Ragdoll 0.3282 0.1897 0.2404 564
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Russian Blue 0.5151 0.8779 0.6492 565
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Scottish Fold 0.4830 0.5798 0.5270 564
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Siamese 0.3663 0.1310 0.1930 565
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Siberian 0.3880 0.1717 0.2380 565
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Snowshoe 0.4918 0.6354 0.5544 565
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Sphynx 0.8734 0.9663 0.9175 564
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Tabby 0.1694 0.1841 0.1764 565
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Tiger 0.1860 0.5532 0.2784 564
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Tonkinese 0.4064 0.6507 0.5003 564
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Torbie 0.3701 0.4397 0.4019 564
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Tortoiseshell 0.4806 0.7890 0.5973 564
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Turkish Angora 0.4681 0.5841 0.5197 565
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Turkish Van 0.2744 0.7558 0.4026 565
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Tuxedo 0.3315 0.8655 0.4794 565
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accuracy 0.4179 27096
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macro avg 0.4117 0.4178 0.3591 27096
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weighted avg 0.4117 0.4179 0.3591 27096
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```
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