Escaping the Big Data Paradigm with Compact Transformers

Benchmark Model Rank Results
fine-grained-image-classification-on-oxfordCCT-14/7x2#23FLOPS: 15GPARAMS: 22.5M
image-classification-on-cifar-10CCT-7/3x1*#60Percentage correct: 98
image-classification-on-cifar-10CCT-6/3x1#133Percentage correct: 95.29
image-classification-on-cifar-100CCT-7/3x1*#94Percentage correct: 82.72
image-classification-on-cifar-100CCT-6/3x1#135Percentage correct: 77.31PARAMS: 3.17M
image-classification-on-flowers-102CCT-14/7x2#1Accuracy: 99.76
image-classification-on-imagenetCCT-14/7x2#984Number of params: 22.36MGFLOPs: 11.06