常见猫咪图像分类数据集（8分类）图像分类实战项目：基于VGG16网络的迁移学习

[train hyper-parameters: Namespace(batch_size=16, lr=0.001, lrf=0.01)] [epoch: 1] train loss:0.0778 test accuracy:0.7938 [epoch: 2] train loss:0.0358 test accuracy:0.8139 [epoch: 3] train loss:0.0242 test accuracy:0.8540 [epoch: 4] train loss:0.0186 test accuracy:0.8303 [epoch: 5] train loss:0.0134 test accuracy:0.8449 [epoch: 6] train loss:0.0106 test accuracy:0.8613 [epoch: 7] train loss:0.0080 test accuracy:0.8321 [epoch: 8] train loss:0.0088 test accuracy:0.8467 [epoch: 9] train loss:0.0049 test accuracy:0.8595 [epoch: 10] train loss:0.0036 test accuracy:0.8358 [epoch: 11] train loss:0.0043 test accuracy:0.8631 [epoch: 12] train loss:0.0047 test accuracy:0.8431 [epoch: 13] train loss:0.0039 test accuracy:0.8668 [epoch: 14] train loss:0.0025 test accuracy:0.8741 [epoch: 15] train loss:0.0026 test accuracy:0.8358 [epoch: 16] train loss:0.0025 test accuracy:0.8522 [epoch: 17] train loss:0.0025 test accuracy:0.8668 [epoch: 18] train loss:0.0017 test accuracy:0.8723 [epoch: 19] train loss:0.0025 test accuracy:0.8577 [epoch: 20] train loss:0.0011 test accuracy:0.8613 [epoch: 21] train loss:0.0013 test accuracy:0.8631 [epoch: 22] train loss:0.0016 test accuracy:0.8558 [epoch: 23] train loss:0.0009 test accuracy:0.8631 [epoch: 24] train loss:0.0008 test accuracy:0.8613 [epoch: 25] train loss:0.0007 test accuracy:0.8668 [epoch: 26] train loss:0.0005 test accuracy:0.8723 [epoch: 27] train loss:0.0003 test accuracy:0.8650 [epoch: 28] train loss:0.0007 test accuracy:0.8668 [epoch: 29] train loss:0.0002 test accuracy:0.8686 [epoch: 30] train loss:0.0001 test accuracy:0.8741 [epoch: 31] train loss:0.0004 test accuracy:0.8595 [epoch: 32] train loss:0.0005 test accuracy:0.8650 [epoch: 33] train loss:0.0003 test accuracy:0.8759 [epoch: 34] train loss:0.0005 test accuracy:0.8650 [epoch: 35] train loss:0.0002 test accuracy:0.8650 [epoch: 36] train loss:0.0001 test accuracy:0.8796 [epoch: 37] train loss:0.0002 test accuracy:0.8723 [epoch: 38] train loss:0.0002 test accuracy:0.8759 [epoch: 39] train loss:0.0001 test accuracy:0.8686 [epoch: 40] train loss:0.0002 test accuracy:0.8759 [epoch: 41] train loss:0.0001 test accuracy:0.8759 [epoch: 42] train loss:0.0000 test accuracy:0.8723 [epoch: 43] train loss:0.0002 test accuracy:0.8759 [epoch: 44] train loss:0.0001 test accuracy:0.8777 [epoch: 45] train loss:0.0001 test accuracy:0.8723 [epoch: 46] train loss:0.0002 test accuracy:0.8668 [epoch: 47] train loss:0.0001 test accuracy:0.8650 [epoch: 48] train loss:0.0002 test accuracy:0.8759 [epoch: 49] train loss:0.0001 test accuracy:0.8741 [epoch: 50] train loss:0.0002 test accuracy:0.8631 [epoch: 51] train loss:0.0001 test accuracy:0.8723 [epoch: 52] train loss:0.0001 test accuracy:0.8631 [epoch: 53] train loss:0.0002 test accuracy:0.8613 [epoch: 54] train loss:0.0001 test accuracy:0.8723 [epoch: 55] train loss:0.0001 test accuracy:0.8704 [epoch: 56] train loss:0.0001 test accuracy:0.8668 [epoch: 57] train loss:0.0001 test accuracy:0.8668 [epoch: 58] train loss:0.0001 test accuracy:0.8759 [epoch: 59] train loss:0.0001 test accuracy:0.8704 [epoch: 60] train loss:0.0001 test accuracy:0.8704 [epoch: 61] train loss:0.0001 test accuracy:0.8686 [epoch: 62] train loss:0.0001 test accuracy:0.8777 [epoch: 63] train loss:0.0001 test accuracy:0.8777 [epoch: 64] train loss:0.0001 test accuracy:0.8759 [epoch: 65] train loss:0.0001 test accuracy:0.8668 [epoch: 66] train loss:0.0001 test accuracy:0.8668 [epoch: 67] train loss:0.0001 test accuracy:0.8686 [epoch: 68] train loss:0.0000 test accuracy:0.8704 [epoch: 69] train loss:0.0001 test accuracy:0.8686 [epoch: 70] train loss:0.0000 test accuracy:0.8686 [epoch: 71] train loss:0.0001 test accuracy:0.8668 [epoch: 72] train loss:0.0001 test accuracy:0.8686 [epoch: 73] train loss:0.0001 test accuracy:0.8723 [epoch: 74] train loss:0.0000 test accuracy:0.8704 [epoch: 75] train loss:0.0001 test accuracy:0.8704 [epoch: 76] train loss:0.0001 test accuracy:0.8741 [epoch: 77] train loss:0.0000 test accuracy:0.8741 [epoch: 78] train loss:0.0001 test accuracy:0.8723 [epoch: 79] train loss:0.0000 test accuracy:0.8704 [epoch: 80] train loss:0.0001 test accuracy:0.8704 [epoch: 81] train loss:0.0000 test accuracy:0.8704 [epoch: 82] train loss:0.0001 test accuracy:0.8704 [epoch: 83] train loss:0.0001 test accuracy:0.8704 [epoch: 84] train loss:0.0000 test accuracy:0.8704 [epoch: 85] train loss:0.0001 test accuracy:0.8704 [epoch: 86] train loss:0.0000 test accuracy:0.8704 [epoch: 87] train loss:0.0001 test accuracy:0.8704 [epoch: 88] train loss:0.0000 test accuracy:0.8686 [epoch: 89] train loss:0.0000 test accuracy:0.8704 [epoch: 90] train loss:0.0001 test accuracy:0.8686 [epoch: 91] train loss:0.0001 test accuracy:0.8686 [epoch: 92] train loss:0.0001 test accuracy:0.8686 [epoch: 93] train loss:0.0000 test accuracy:0.8686 [epoch: 94] train loss:0.0001 test accuracy:0.8686 [epoch: 95] train loss:0.0001 test accuracy:0.8686 [epoch: 96] train loss:0.0001 test accuracy:0.8704 [epoch: 97] train loss:0.0000 test accuracy:0.8704 [epoch: 98] train loss:0.0000 test accuracy:0.8686 [epoch: 99] train loss:0.0001 test accuracy:0.8686 [epoch: 100] train loss:0.0001 test accuracy:0.8686