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Although it's unlikely you'll ever use it, This model was trained for classifying different types of kimchi (Korean cabbage). It achieved 89% accuracy on a test set comprising of 11 different classes of this Korean delicacy.

labels_eng = ['baechu', 'baik', 'boochoo', 'chongkak', 'got', 'kkakdoogi', 'moosaengchae', 'nabak', 'ohyeesobaki', 'pa', 'yeolmoo']
labels_kr = ['๋ฐฐ์ถ”', '๋ฐฑ(๋Œ€ํŒŒ)', '๋ถ€์ถ”', '์ด๊ฐ๊น€์น˜', '๊ณ ์ถ”', '๊น๋‘๊ธฐ', '๋ฌด์ƒ์ฑ„', '๋‚˜๋ฐ•', '์˜ค์ด์†Œ๋ฐ•์ด', 'ํŒŒ', '์—ด๋ฌด']

This model is basically a fintuned version of the vision tranformer .

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Dataset used to train pawlo2013/kimchi-classification

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