resnet_cifar10_loss_accuracy_epoch_line
- enviroment, hyperparameters:
- GPU: NVIDIA A40 CPU: 12 × Intel(R) Xeon(R) Gold 5318Y CPU @ 2.10GHz 内存: 86GB 硬盘: 350GB
- test_batch_size = 256, train_batch_size = 1280,epoches = 25
- transforms.Resize(256)
- transforms.CenterCrop(224)
- transforms.ToTensor()
- transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])
- output:
- Files already downloaded and verified
- Files already downloaded and verified
- cifar10_train size: 50000 cifar10_test_size: 10000
- train shape: torch.Size([1280, 3, 224, 224]) train label shape: torch.Size([1280]) test shape: torch.Size([256, 3, 224, 224]) test - label shape: torch.Size([256])
- epoch: 1, current epoch min loss: 1.4769628047943115
- epoch: 1, accuracy: 0.3507
- epoch: 2, current epoch min loss: 1.1555131673812866
- epoch: 2, accuracy: 0.4587
- epoch: 3, current epoch min loss: 0.9124709367752075
- epoch: 3, accuracy: 0.5473
- epoch: 4, current epoch min loss: 0.7965725660324097
- epoch: 4, accuracy: 0.5424
- epoch: 5, current epoch min loss: 0.6539226770401001
- epoch: 5, accuracy: 0.6482
- epoch: 6, current epoch min loss: 0.5314575433731079
- epoch: 6, accuracy: 0.7026
- epoch: 7, current epoch min loss: 0.47418370842933655
- epoch: 7, accuracy: 0.7147
- epoch: 8, current epoch min loss: 0.3847983479499817
- epoch: 8, accuracy: 0.6632
- epoch: 9, current epoch min loss: 0.3222113847732544
- epoch: 9, accuracy: 0.726
- epoch: 10, current epoch min loss: 0.2987883985042572
- epoch: 10, accuracy: 0.791
- epoch: 11, current epoch min loss: 0.2234237939119339
- epoch: 11, accuracy: 0.7081
- epoch: 12, current epoch min loss: 0.21544614434242249
- epoch: 12, accuracy: 0.7946
- epoch: 13, current epoch min loss: 0.17288713157176971
- epoch: 13, accuracy: 0.7042
- epoch: 14, current epoch min loss: 0.109545037150383
- epoch: 14, accuracy: 0.7725
- epoch: 15, current epoch min loss: 0.09756408631801605
- epoch: 15, accuracy: 0.795
- epoch: 16, current epoch min loss: 0.11165265738964081
- epoch: 16, accuracy: 0.7371
- epoch: 17, current epoch min loss: 0.07507659494876862
- epoch: 17, accuracy: 0.7656
- epoch: 18, current epoch min loss: 0.05396381765604019
- epoch: 18, accuracy: 0.8091
- epoch: 19, current epoch min loss: 0.047468364238739014
- epoch: 19, accuracy: 0.8139
- epoch: 20, current epoch min loss: 0.012718533165752888
- epoch: 20, accuracy: 0.8287
- epoch: 21, current epoch min loss: 0.010760265402495861
- epoch: 21, accuracy: 0.8367
- epoch: 22, current epoch min loss: 0.00593204889446497
- epoch: 22, accuracy: 0.8497
- epoch: 23, current epoch min loss: 0.006378650665283203
- epoch: 23, accuracy: 0.8437
- epoch: 24, current epoch min loss: 0.0032134423963725567
- epoch: 24, accuracy: 0.8516
- epoch: 25, current epoch min loss: 0.0017822051886469126
- epoch: 25, accuracy: 0.8588