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--- |
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license: apache-2.0 |
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metrics: |
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- accuracy |
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- f1 |
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base_model: |
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- google/vit-base-patch16-224-in21k |
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--- |
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Returns car brand with about 69% accuracy given an image. |
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See https://www.kaggle.com/code/dima806/car-brands-image-detection-vit for details. |
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 |
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``` |
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Classification report: |
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precision recall f1-score support |
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Acura 0.3799 0.5658 0.4546 2066 |
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Alfa Romeo 0.7487 0.9424 0.8344 2067 |
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Aston Martin 0.9377 0.8162 0.8727 2067 |
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Audi 0.3810 0.6623 0.4837 2067 |
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BMW 0.4379 0.1824 0.2575 2067 |
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Bentley 0.7206 0.8360 0.7740 2067 |
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Bugatti 0.9862 1.0000 0.9930 2067 |
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Buick 0.5081 0.4981 0.5031 2066 |
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Cadillac 0.7252 0.4315 0.5411 2067 |
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Chevrolet 0.3715 0.1553 0.2190 2067 |
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Chrysler 0.6298 0.7551 0.6868 2066 |
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Citroen 0.9597 0.9903 0.9748 2067 |
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Daewoo 0.9745 1.0000 0.9871 2067 |
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Dodge 0.5020 0.6618 0.5710 2067 |
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Ferrari 0.9238 0.9908 0.9561 2067 |
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Fiat 0.8116 0.8670 0.8384 2067 |
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Ford 0.4484 0.0798 0.1355 2067 |
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GMC 0.5630 0.7842 0.6555 2067 |
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Genesis 0.6549 0.8916 0.7552 2067 |
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Honda 0.3684 0.3880 0.3779 2067 |
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Hudson 0.9584 0.8132 0.8798 2066 |
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Hyundai 0.3593 0.3527 0.3560 2067 |
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Infiniti 0.4569 0.6546 0.5382 2067 |
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Jaguar 0.4496 0.2975 0.3581 2067 |
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Jeep 0.8256 0.8563 0.8407 2067 |
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Kia 0.3308 0.1035 0.1577 2067 |
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Lamborghini 0.9252 0.9811 0.9523 2067 |
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Land Rover 0.5205 0.8365 0.6417 2067 |
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Lexus 0.4655 0.2221 0.3007 2067 |
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Lincoln 0.5455 0.5244 0.5348 2067 |
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MG 0.7773 0.9879 0.8700 2067 |
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Maserati 0.7179 0.8162 0.7639 2067 |
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Mazda 0.4517 0.4664 0.4589 2067 |
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McLaren 0.9782 1.0000 0.9890 2066 |
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Mercedes-Benz 0.3383 0.0329 0.0600 2067 |
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Mini 0.8048 0.9337 0.8645 2067 |
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Mitsubishi 0.4671 0.7928 0.5878 2066 |
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Nissan 0.5305 0.0672 0.1194 2067 |
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Oldsmobile 0.8832 0.9918 0.9344 2067 |
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Peugeot 0.9070 1.0000 0.9512 2067 |
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Pontiac 0.9641 0.9884 0.9761 2067 |
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Porsche 0.5380 0.6376 0.5836 2067 |
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Ram 0.8475 0.9652 0.9025 2067 |
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Ram Trucks 0.9626 0.9831 0.9727 2067 |
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Renault 0.9686 1.0000 0.9840 2066 |
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Rolls-Royce 0.8737 0.9671 0.9180 2067 |
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Saab 0.9311 1.0000 0.9643 2067 |
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Smart 0.9247 0.9627 0.9433 2066 |
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Studebaker 0.9645 1.0000 0.9819 2067 |
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Subaru 0.4404 0.3112 0.3647 2066 |
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Suzuki 0.9425 1.0000 0.9704 2067 |
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Tesla 0.7482 0.9390 0.8328 2066 |
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Toyota 0.2884 0.0755 0.1196 2067 |
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Volkswagen 0.4282 0.4964 0.4598 2067 |
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Volvo 0.4807 0.5300 0.5041 2066 |
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|
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accuracy 0.6925 113674 |
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macro avg 0.6733 0.6925 0.6638 113674 |
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weighted avg 0.6733 0.6925 0.6638 113674 |
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``` |
