水果数据集的五分类图像识别项目：基于Swin-Transformer网络的迁移学习

[train hyper-parameters: Namespace(batch_size=16, lr=0.001, lrf=0.01, num_classes=5)] [epoch: 1] train loss:0.0320 test accuracy:0.8966 [epoch: 2] train loss:0.0097 test accuracy:0.9328 [epoch: 3] train loss:0.0075 test accuracy:0.8966 [epoch: 4] train loss:0.0036 test accuracy:0.9096 [epoch: 5] train loss:0.0023 test accuracy:0.9251 [epoch: 6] train loss:0.0016 test accuracy:0.9225 [epoch: 7] train loss:0.0010 test accuracy:0.9276 [epoch: 8] train loss:0.0006 test accuracy:0.9199 [epoch: 9] train loss:0.0005 test accuracy:0.9276 [epoch: 10] train loss:0.0004 test accuracy:0.9225 [epoch: 11] train loss:0.0003 test accuracy:0.9173 [epoch: 12] train loss:0.0003 test accuracy:0.9096 [epoch: 13] train loss:0.0003 test accuracy:0.9199 [epoch: 14] train loss:0.0002 test accuracy:0.9199 [epoch: 15] train loss:0.0002 test accuracy:0.9199 [epoch: 16] train loss:0.0002 test accuracy:0.9173 [epoch: 17] train loss:0.0001 test accuracy:0.9199 [epoch: 18] train loss:0.0001 test accuracy:0.9225 [epoch: 19] train loss:0.0001 test accuracy:0.9199 [epoch: 20] train loss:0.0002 test accuracy:0.9276 [epoch: 21] train loss:0.0002 test accuracy:0.9251 [epoch: 22] train loss:0.0001 test accuracy:0.9199 [epoch: 23] train loss:0.0001 test accuracy:0.9225 [epoch: 24] train loss:0.0002 test accuracy:0.9251 [epoch: 25] train loss:0.0001 test accuracy:0.9225 [epoch: 26] train loss:0.0002 test accuracy:0.9251 [epoch: 27] train loss:0.0001 test accuracy:0.9225 [epoch: 28] train loss:0.0001 test accuracy:0.9225 [epoch: 29] train loss:0.0001 test accuracy:0.9199 [epoch: 30] train loss:0.0001 test accuracy:0.9199 [epoch: 31] train loss:0.0002 test accuracy:0.9173 [epoch: 32] train loss:0.0001 test accuracy:0.9225 [epoch: 33] train loss:0.0001 test accuracy:0.9251 [epoch: 34] train loss:0.0001 test accuracy:0.9251 [epoch: 35] train loss:0.0001 test accuracy:0.9251 [epoch: 36] train loss:0.0001 test accuracy:0.9251 [epoch: 37] train loss:0.0001 test accuracy:0.9225 [epoch: 38] train loss:0.0001 test accuracy:0.9225 [epoch: 39] train loss:0.0001 test accuracy:0.9251 [epoch: 40] train loss:0.0001 test accuracy:0.9251 [epoch: 41] train loss:0.0001 test accuracy:0.9251 [epoch: 42] train loss:0.0001 test accuracy:0.9251 [epoch: 43] train loss:0.0001 test accuracy:0.9251 [epoch: 44] train loss:0.0001 test accuracy:0.9251 [epoch: 45] train loss:0.0001 test accuracy:0.9251 [epoch: 46] train loss:0.0001 test accuracy:0.9251 [epoch: 47] train loss:0.0001 test accuracy:0.9251 [epoch: 48] train loss:0.0001 test accuracy:0.9251 [epoch: 49] train loss:0.0001 test accuracy:0.9251 [epoch: 50] train loss:0.0001 test accuracy:0.9251