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| Label | Class |
|---|---|
| 0 | airplane |
| 1 | automobile |
| 2 | bird |
| 3 | cat |
| 4 | deer |
| 5 | dog |
| 6 | frog |
| 7 | horse |
| 8 | ship |
| 9 | truck |
| Metric | Value |
|---|---|
| Test Accuracy | 84.62% |
mobilenetv2_cifar10.pth1model = MobileNetV2()
2
3model.load_state_dict(
4 torch.load("mobilenetv2_cifar10.pth")
5)
6
7model.eval()1with torch.no_grad():
2 outputs = model(images)
3 _, predicted = torch.max(outputs, 1)