--- license: apache-2.0 metrics: - accuracy base_model: - google/vit-base-patch16-224-in21k --- Predicts dogs breed based on an image. Achieved about 92% accuracy on unseen (test) data. See [my Kaggle notebook](https://www.kaggle.com/code/dima806/70-dog-breed-image-detection-vit) and [my Medium article](https://medium.com/gitconnected/paws-and-pixels-creating-a-dog-breeds-classifier-with-googles-vision-transformer-431137422830) for more details. ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6449300e3adf50d864095b90/KdUJH1qZauUr5kargckRa.png) ``` Classification report: precision recall f1-score support Afghan 0.9753 0.9080 0.9405 87 African Wild Dog 1.0000 1.0000 1.0000 88 Airedale 1.0000 0.9885 0.9942 87 American Hairless 0.9841 0.7126 0.8267 87 American Spaniel 0.9054 0.7701 0.8323 87 Basenji 0.9659 0.9770 0.9714 87 Basset 0.9551 0.9770 0.9659 87 Beagle 0.9659 0.9659 0.9659 88 Bearded Collie 0.8614 1.0000 0.9255 87 Bermaise 0.9457 1.0000 0.9721 87 Bichon Frise 0.9551 0.9770 0.9659 87 Blenheim 0.9062 1.0000 0.9508 87 Bloodhound 0.9659 0.9770 0.9714 87 Bluetick 1.0000 0.9540 0.9765 87 Border Collie 0.8830 0.9540 0.9171 87 Borzoi 1.0000 0.9432 0.9708 88 Boston Terrier 0.5513 0.9773 0.7049 88 Boxer 1.0000 0.9655 0.9825 87 Bull Mastiff 0.9655 0.9655 0.9655 87 Bull Terrier 1.0000 0.9885 0.9942 87 Bulldog 0.9583 0.2614 0.4107 88 Cairn 0.8737 0.9540 0.9121 87 Chihuahua 0.9610 0.8409 0.8970 88 Chinese Crested 0.9750 0.8966 0.9341 87 Chow 1.0000 1.0000 1.0000 88 Clumber 0.9884 0.9770 0.9827 87 Cockapoo 0.7238 0.8736 0.7917 87 Cocker 0.9868 0.8621 0.9202 87 Collie 0.9630 0.8966 0.9286 87 Corgi 0.9881 0.9540 0.9708 87 Coyote 0.9560 1.0000 0.9775 87 Dalmation 0.9560 1.0000 0.9775 87 Dhole 0.9765 0.9540 0.9651 87 Dingo 0.8966 0.8966 0.8966 87 Doberman 0.9333 0.9655 0.9492 87 Elk Hound 0.9775 1.0000 0.9886 87 French Bulldog 0.8810 0.8506 0.8655 87 German Sheperd 0.6803 0.9432 0.7905 88 Golden Retriever 0.9767 0.9655 0.9711 87 Great Dane 0.8929 0.8621 0.8772 87 Great Perenees 0.9667 1.0000 0.9831 87 Greyhound 0.9750 0.8966 0.9341 87 Groenendael 0.9062 1.0000 0.9508 87 Irish Spaniel 0.8173 0.9770 0.8901 87 Irish Wolfhound 0.9239 0.9770 0.9497 87 Japanese Spaniel 0.9101 0.9310 0.9205 87 Komondor 0.9885 0.9885 0.9885 87 Labradoodle 0.8750 0.6437 0.7417 87 Labrador 1.0000 0.9091 0.9524 88 Lhasa 0.9231 0.5517 0.6906 87 Malinois 0.9756 0.4598 0.6250 87 Maltese 0.8958 0.9773 0.9348 88 Mex Hairless 0.7870 0.9770 0.8718 87 Newfoundland 0.9438 0.9655 0.9545 87 Pekinese 0.9333 0.9545 0.9438 88 Pit Bull 0.8969 1.0000 0.9457 87 Pomeranian 0.9121 0.9540 0.9326 87 Poodle 0.9759 0.9205 0.9474 88 Pug 0.9529 0.9310 0.9419 87 Rhodesian 0.9130 0.9655 0.9385 87 Rottweiler 0.9556 0.9885 0.9718 87 Saint Bernard 0.9773 0.9885 0.9829 87 Schnauzer 0.8684 0.7586 0.8098 87 Scotch Terrier 0.9506 0.8851 0.9167 87 Shar_Pei 0.9886 1.0000 0.9943 87 Shiba Inu 0.9286 0.8966 0.9123 87 Shih-Tzu 0.6957 0.9195 0.7921 87 Siberian Husky 0.9667 1.0000 0.9831 87 Vizsla 0.9355 0.9886 0.9613 88 Yorkie 0.9457 0.9886 0.9667 88 accuracy 0.9192 6104 macro avg 0.9288 0.9193 0.9161 6104 weighted avg 0.9288 0.9192 0.9161 6104 ```