metadata
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