--- license: apache-2.0 metrics: - accuracy - f1 --- Predicts plant type given an image. See https://www.kaggle.com/code/dima806/30-plant-types-image-detection-vit for more details. ``` Classification report: precision recall f1-score support guava 0.9846 0.9600 0.9722 200 galangal 0.9418 0.8900 0.9152 200 bilimbi 0.9949 0.9750 0.9848 200 paddy 0.9731 0.9050 0.9378 200 eggplant 0.9848 0.9700 0.9773 200 cucumber 0.9561 0.9800 0.9679 200 cassava 0.9899 0.9800 0.9849 200 papaya 0.9851 0.9950 0.9900 200 banana 0.9950 0.9900 0.9925 200 orange 0.9534 0.9200 0.9364 200 cantaloupe 0.5271 0.3400 0.4134 200 coconut 0.9950 1.0000 0.9975 200 soybeans 0.9754 0.9900 0.9826 200 pomelo 0.9563 0.9850 0.9704 200 pineapple 0.9703 0.9800 0.9751 200 melon 0.5000 0.6150 0.5516 200 shallot 0.9949 0.9750 0.9848 200 peperchili 0.9755 0.9950 0.9851 200 spinach 0.9231 0.9600 0.9412 200 tobacco 0.9151 0.9700 0.9417 200 aloevera 0.9949 0.9800 0.9874 200 curcuma 0.9005 0.8600 0.8798 200 corn 0.9610 0.9850 0.9728 200 ginger 0.8551 0.8850 0.8698 200 sweetpotatoes 1.0000 0.9950 0.9975 200 kale 0.9268 0.9500 0.9383 200 longbeans 0.9850 0.9850 0.9850 200 watermelon 0.9252 0.9900 0.9565 200 mango 0.9239 0.9100 0.9169 200 waterapple 0.8807 0.9600 0.9187 200 accuracy 0.9292 6000 macro avg 0.9282 0.9292 0.9275 6000 weighted avg 0.9282 0.9292 0.9275 6000 ```