基于pytorch实现的MobileViT 迁移学习对30种球类体育运动图像分类完整项目【毕业设计&课程设计&项目开发】

[train hyper-parameters: Namespace(batch_size=8, epochs=50, freeze_layers=True, lr=0.0002, model='s')] [epoch: 1] train loss:0.3796 train accuracy:0.5761 val loss:0.3903 val accuracy:0.7697 [epoch: 2] train loss:0.2947 train accuracy:0.8117 val loss:0.3599 val accuracy:0.7632 [epoch: 3] train loss:0.2342 train accuracy:0.8234 val loss:0.3392 val accuracy:0.7829 [epoch: 4] train loss:0.1918 train accuracy:0.8420 val loss:0.3189 val accuracy:0.8180 [epoch: 5] train loss:0.1625 train accuracy:0.8583 val loss:0.3104 val accuracy:0.8377 [epoch: 6] train loss:0.1414 train accuracy:0.8715 val loss:0.2999 val accuracy:0.8443 [epoch: 7] train loss:0.1258 train accuracy:0.8776 val loss:0.2966 val accuracy:0.8706 [epoch: 8] train loss:0.1154 train accuracy:0.8858 val loss:0.2905 val accuracy:0.8575 [epoch: 9] train loss:0.1039 train accuracy:0.8942 val loss:0.2848 val accuracy:0.8706 [epoch: 10] train loss:0.0986 train accuracy:0.8984 val loss:0.2859 val accuracy:0.8838 [epoch: 11] train loss:0.0903 train accuracy:0.9042 val loss:0.2827 val accuracy:0.8838 [epoch: 12] train loss:0.0852 train accuracy:0.9106 val loss:0.2800 val accuracy:0.8969 [epoch: 13] train loss:0.0812 train accuracy:0.9144 val loss:0.2749 val accuracy:0.9035 [epoch: 14] train loss:0.0782 train accuracy:0.9128 val loss:0.2717 val accuracy:0.9189 [epoch: 15] train loss:0.0729 train accuracy:0.9242 val loss:0.2774 val accuracy:0.9057 [epoch: 16] train loss:0.0696 train accuracy:0.9258 val loss:0.2776 val accuracy:0.9057 [epoch: 17] train loss:0.0684 train accuracy:0.9244 val loss:0.2765 val accuracy:0.9189 [epoch: 18] train loss:0.0661 train accuracy:0.9272 val loss:0.2742 val accuracy:0.9057 [epoch: 19] train loss:0.0632 train accuracy:0.9300 val loss:0.2693 val accuracy:0.9211 [epoch: 20] train loss:0.0603 train accuracy:0.9369 val loss:0.2739 val accuracy:0.9189 [epoch: 21] train loss:0.0603 train accuracy:0.9319 val loss:0.2713 val accuracy:0.9123 [epoch: 22] train loss:0.0581 train accuracy:0.9353 val loss:0.2730 val accuracy:0.9320 [epoch: 23] train loss:0.0562 train accuracy:0.9364 val loss:0.2760 val accuracy:0.9276 [epoch: 24] train loss:0.0569 train accuracy:0.9362 val loss:0.2725 val accuracy:0.9123 [epoch: 25] train loss:0.0557 train accuracy:0.9356 val loss:0.2741 val accuracy:0.9342 [epoch: 26] train loss:0.0536 train accuracy:0.9389 val loss:0.2700 val accuracy:0.9276 [epoch: 27] train loss:0.0535 train accuracy:0.9436 val loss:0.2732 val accuracy:0.9342 [epoch: 28] train loss:0.0505 train accuracy:0.9456 val loss:0.2709 val accuracy:0.9408 [epoch: 29] train loss:0.0484 train accuracy:0.9492 val loss:0.2725 val accuracy:0.9408 [epoch: 30] train loss:0.0490 train accuracy:0.9444 val loss:0.2719 val accuracy:0.9342 [epoch: 31] train loss:0.0481 train accuracy:0.9458 val loss:0.2718 val accuracy:0.9342 [epoch: 32] train loss:0.0490 train accuracy:0.9481 val loss:0.2730 val accuracy:0.9276 [epoch: 33] train loss:0.0459 train accuracy:0.9494 val loss:0.2751 val accuracy:0.9276 [epoch: 34] train loss:0.0453 train accuracy:0.9514 val loss:0.2764 val accuracy:0.9342 [epoch: 35] train loss:0.0456 train accuracy:0.9506 val loss:0.2782 val accuracy:0.9342 [epoch: 36] train loss:0.0448 train accuracy:0.9494 val loss:0.2773 val accuracy:0.9408 [epoch: 37] train loss:0.0445 train accuracy:0.9494 val loss:0.2764 val accuracy:0.9342 [epoch: 38] train loss:0.0449 train accuracy:0.9533 val loss:0.2756 val accuracy:0.9408 [epoch: 39] train loss:0.0451 train accuracy:0.9558 val loss:0.2787 val accuracy:0.9342 [epoch: 40] train loss:0.0437 train accuracy:0.9542 val loss:0.2816 val accuracy:0.9342 [epoch: 41] train loss:0.0419 train accuracy:0.9569 val loss:0.2804 val accuracy:0.9342 [epoch: 42] train loss:0.0421 train accuracy:0.9569 val loss:0.2833 val accuracy:0.9408 [epoch: 43] train loss:0.0425 train accuracy:0.9550 val loss:0.2785 val accuracy:0.9408 [epoch: 44] train loss:0.0412 train accuracy:0.9533 val loss:0.2739 val accuracy:0.9474 [epoch: 45] train loss:0.0419 train accuracy:0.9531 val loss:0.2768 val accuracy:0.9342 [epoch: 46] train loss:0.0397 train accuracy:0.9589 val loss:0.2799 val accuracy:0.9408 [epoch: 47] train loss:0.0407 train accuracy:0.9584 val loss:0.2764 val accuracy:0.9342 [epoch: 48] train loss:0.0395 train accuracy:0.9594 val loss:0.2801 val accuracy:0.9474 [epoch: 49] train loss:0.0398 train accuracy:0.9600 val loss:0.2836 val accuracy:0.9408 [epoch: 50] train loss:0.0403 train accuracy:0.9597 val loss:0.2758 val accuracy:0.9408