--- license: apache-2.0 metrics: - accuracy - f1 --- Detects cat breed (from the list of 48 common breeds) based on image. See https://www.kaggle.com/code/dima806/cat-breed-image-detection-vit for more details. ``` Classification report: precision recall f1-score support Abyssinian 0.6599 0.8106 0.7276 565 American Bobtail 0.0000 0.0000 0.0000 564 American Curl 0.6816 0.2695 0.3863 564 American Shorthair 0.2222 0.0035 0.0070 564 Applehead Siamese 0.3788 0.5894 0.4612 565 Balinese 0.4385 0.2784 0.3406 564 Bengal 0.5389 0.6879 0.6044 564 Birman 0.3479 0.6903 0.4626 565 Bombay 0.2989 0.7681 0.4303 565 British Shorthair 0.5662 0.2726 0.3680 565 Burmese 0.7568 0.0993 0.1755 564 Calico 0.3903 0.4858 0.4329 564 Cornish Rex 0.5780 0.8655 0.6931 565 Devon Rex 0.6615 0.1525 0.2478 564 Dilute Calico 0.4311 0.3493 0.3859 564 Dilute Tortoiseshell 0.4646 0.5699 0.5119 565 Domestic Long Hair 0.2783 0.0566 0.0941 565 Domestic Medium Hair 0.2083 0.0089 0.0170 564 Domestic Short Hair 0.4615 0.0319 0.0596 565 Egyptian Mau 0.4387 0.6720 0.5308 564 Exotic Shorthair 0.7238 0.2319 0.3512 565 Extra-Toes Cat - Hemingway Polydactyl 0.3333 0.0018 0.0035 565 Havana 0.5521 0.7876 0.6492 565 Himalayan 0.4467 0.3858 0.4141 565 Japanese Bobtail 0.4333 0.0230 0.0437 565 Maine Coon 0.2336 0.4602 0.3099 565 Manx 0.2143 0.0053 0.0104 564 Munchkin 0.0000 0.0000 0.0000 564 Nebelung 0.5726 0.8584 0.6870 565 Norwegian Forest 0.3390 0.3883 0.3620 564 Oriental Short Hair 0.0000 0.0000 0.0000 564 Persian 0.5197 0.7713 0.6210 564 Ragamuffin 0.4580 0.1064 0.1727 564 Ragdoll 0.3282 0.1897 0.2404 564 Russian Blue 0.5151 0.8779 0.6492 565 Scottish Fold 0.4830 0.5798 0.5270 564 Siamese 0.3663 0.1310 0.1930 565 Siberian 0.3880 0.1717 0.2380 565 Snowshoe 0.4918 0.6354 0.5544 565 Sphynx 0.8734 0.9663 0.9175 564 Tabby 0.1694 0.1841 0.1764 565 Tiger 0.1860 0.5532 0.2784 564 Tonkinese 0.4064 0.6507 0.5003 564 Torbie 0.3701 0.4397 0.4019 564 Tortoiseshell 0.4806 0.7890 0.5973 564 Turkish Angora 0.4681 0.5841 0.5197 565 Turkish Van 0.2744 0.7558 0.4026 565 Tuxedo 0.3315 0.8655 0.4794 565 accuracy 0.4179 27096 macro avg 0.4117 0.4178 0.3591 27096 weighted avg 0.4117 0.4179 0.3591 27096 ```