基于 ConvNeXt 网络对 4种苹果叶片病害识别【包含数据集、完整代码、训练的结果、混淆矩阵结果等等】

[train hyper-parameters: Namespace(batch_size=8, compute_gray=True, epochs=20, lr=0.002, lrf=0.001, model='base', optim='SGD')] [train mean: [0.435 0.466 0.441],train std:[0.199 0.172 0.218]] [epoch: 1] train loss:0.3563 train accuracy:0.7182 train loss:0.3563 test accuracy:0.7192 [epoch: 2] train loss:0.1085 train accuracy:0.7351 train loss:0.1085 test accuracy:0.7287 [epoch: 3] train loss:0.0731 train accuracy:0.7868 train loss:0.0731 test accuracy:0.7934 [epoch: 4] train loss:0.0556 train accuracy:0.8143 train loss:0.0556 test accuracy:0.8565 [epoch: 5] train loss:0.0525 train accuracy:0.8490 train loss:0.0525 test accuracy:0.8565 [epoch: 6] train loss:0.0444 train accuracy:0.8825 train loss:0.0444 test accuracy:0.9038 [epoch: 7] train loss:0.0400 train accuracy:0.8573 train loss:0.0400 test accuracy:0.8533 [epoch: 8] train loss:0.0353 train accuracy:0.8522 train loss:0.0353 test accuracy:0.8565 [epoch: 9] train loss:0.0335 train accuracy:0.9184 train loss:0.0335 test accuracy:0.9164 [epoch: 10] train loss:0.0328 train accuracy:0.9172 train loss:0.0328 test accuracy:0.9164 [epoch: 11] train loss:0.0282 train accuracy:0.9326 train loss:0.0282 test accuracy:0.9338 [epoch: 12] train loss:0.0268 train accuracy:0.9164 train loss:0.0268 test accuracy:0.9101 [epoch: 13] train loss:0.0266 train accuracy:0.9062 train loss:0.0266 test accuracy:0.9148 [epoch: 14] train loss:0.0236 train accuracy:0.9235 train loss:0.0236 test accuracy:0.9227 [epoch: 15] train loss:0.0226 train accuracy:0.9436 train loss:0.0226 test accuracy:0.9511 [epoch: 16] train loss:0.0208 train accuracy:0.9401 train loss:0.0208 test accuracy:0.9322 [epoch: 17] train loss:0.0206 train accuracy:0.9417 train loss:0.0206 test accuracy:0.9338 [epoch: 18] train loss:0.0192 train accuracy:0.9452 train loss:0.0192 test accuracy:0.9448 [epoch: 19] train loss:0.0190 train accuracy:0.9448 train loss:0.0190 test accuracy:0.9527 [epoch: 20] train loss:0.0187 train accuracy:0.9480 train loss:0.0187 test accuracy:0.9511