经典轻量级CNN网络之EfficientNet图像分类网络实战项目：8种水果图像分类项目

[train hyper-parameters: Namespace(batch_size=16, epochs=50)] [epoch: 1] train loss:0.1111 test accuracy:0.4545 [epoch: 2] train loss:0.0910 test accuracy:0.5545 [epoch: 3] train loss:0.0834 test accuracy:0.5673 [epoch: 4] train loss:0.0761 test accuracy:0.6491 [epoch: 5] train loss:0.0700 test accuracy:0.6291 [epoch: 6] train loss:0.0666 test accuracy:0.6855 [epoch: 7] train loss:0.0662 test accuracy:0.6382 [epoch: 8] train loss:0.0618 test accuracy:0.7000 [epoch: 9] train loss:0.0586 test accuracy:0.7109 [epoch: 10] train loss:0.0569 test accuracy:0.6691 [epoch: 11] train loss:0.0524 test accuracy:0.7036 [epoch: 12] train loss:0.0522 test accuracy:0.7400 [epoch: 13] train loss:0.0488 test accuracy:0.7309 [epoch: 14] train loss:0.0468 test accuracy:0.7182 [epoch: 15] train loss:0.0460 test accuracy:0.7327 [epoch: 16] train loss:0.0434 test accuracy:0.7273 [epoch: 17] train loss:0.0410 test accuracy:0.7309 [epoch: 18] train loss:0.0392 test accuracy:0.7164 [epoch: 19] train loss:0.0401 test accuracy:0.7327 [epoch: 20] train loss:0.0390 test accuracy:0.7527 [epoch: 21] train loss:0.0337 test accuracy:0.7418 [epoch: 22] train loss:0.0336 test accuracy:0.7582 [epoch: 23] train loss:0.0309 test accuracy:0.7545 [epoch: 24] train loss:0.0313 test accuracy:0.7491 [epoch: 25] train loss:0.0295 test accuracy:0.7273 [epoch: 26] train loss:0.0269 test accuracy:0.7455 [epoch: 27] train loss:0.0279 test accuracy:0.7364 [epoch: 28] train loss:0.0240 test accuracy:0.7418 [epoch: 29] train loss:0.0247 test accuracy:0.7200 [epoch: 30] train loss:0.0236 test accuracy:0.7400 [epoch: 31] train loss:0.0201 test accuracy:0.7509 [epoch: 32] train loss:0.0195 test accuracy:0.7364 [epoch: 33] train loss:0.0197 test accuracy:0.7455 [epoch: 34] train loss:0.0186 test accuracy:0.7727 [epoch: 35] train loss:0.0184 test accuracy:0.7745 [epoch: 36] train loss:0.0194 test accuracy:0.7545 [epoch: 37] train loss:0.0182 test accuracy:0.7473 [epoch: 38] train loss:0.0147 test accuracy:0.7509 [epoch: 39] train loss:0.0138 test accuracy:0.7545 [epoch: 40] train loss:0.0154 test accuracy:0.7545 [epoch: 41] train loss:0.0140 test accuracy:0.7836 [epoch: 42] train loss:0.0145 test accuracy:0.7418 [epoch: 43] train loss:0.0156 test accuracy:0.7200 [epoch: 44] train loss:0.0134 test accuracy:0.7764 [epoch: 45] train loss:0.0111 test accuracy:0.7600 [epoch: 46] train loss:0.0111 test accuracy:0.7418 [epoch: 47] train loss:0.0128 test accuracy:0.7727 [epoch: 48] train loss:0.0109 test accuracy:0.7509 [epoch: 49] train loss:0.0108 test accuracy:0.7600 [epoch: 50] train loss:0.0101 test accuracy:0.7473