在PyTorch中進行模型微調的步驟如下：
import torchvision.models as models
model = models.resnet18(pretrained=True)
for param in model.parameters():
param.requires_grad = False
model.fc = nn.Linear(model.fc.in_features, num_classes)
criterion = nn.CrossEntropyLoss()
optimizer = optim.SGD(model.parameters(), lr=0.001, momentum=0.9)
for epoch in range(num_epochs):
for images, labels in train_loader:
optimizer.zero_grad()
outputs = model(images)
loss = criterion(outputs, labels)
loss.backward()
optimizer.step()
通過這些步驟，你可以在PyTorch中進行模型微調。記得在微調后評估模型性能，并根據需要調整超參數。
