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### Model Description
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This model was
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The goal of the competition was to apply novel approaches to achieve the highest possible accuracy on a bird classification task with 200 classes.
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We were given a labeled dataset of 3,926 images and an unlabeled dataset of 4,000 test images.
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Out of 32 groups and 1,083 submissions, we achieved the #1 accuracy on the test set with a score of 0.87950.
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### Model Description
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This model was finetuned for the "Feather in Focus!" Kaggle competition of the Information Studies Master's Applied Machine Learning course at the University of Amsterdam.
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The goal of the competition was to apply novel approaches to achieve the highest possible accuracy on a bird classification task with 200 classes.
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We were given a labeled dataset of 3,926 images and an unlabeled dataset of 4,000 test images.
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Out of 32 groups and 1,083 submissions, we achieved the #1 accuracy on the test set with a score of 0.87950.
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