训练循环中损失显着增加
pytorch 250
原文标题 ：loss increasing significantly in training loop
我的训练损失正在急剧增加。不知道为什么会这样。我在想这可能与我计算损失的方式有关，但不确定。我认为这可能是因为我正在打印运行损失而不是每批损失。下面是我的训练循环：
def train_model(model, optimizer, train_loader, num_epochs, criterion=criterion):
total_epochs = notebook.tqdm(range(num_epochs))
model.train()
running_loss=0
correct=0
total=0
for epoch in total_epochs:
for i, (x_train, y_train) in enumerate(train_loader):
x_train = x_train.to(device)
y_train = y_train.to(device)
y_pred = model(x_train)
loss = criterion(y_pred, y_train)
optimizer.zero_grad()
loss.backward()
optimizer.step()
running_loss += loss.item()
_, predicted = y_pred.max(1)
train_loss=running_loss/len(train_loader)
total += y_train.size(0)
correct += predicted.eq(y_train).sum().item()
train_loss=running_loss/len(train_loader)
train_accu=100.*correct/total
print('Train Loss: %.3f | Train Accuracy: %.3f'%(train_loss,train_accu))
但是，当我调用 train_model() 时：
train_md = train_model(cnn_net, optimizer, data_loaders['train'], 10)
它返回这个：
Train Loss: 1.472 | Train Accuracy: 47.949
Train Loss: 2.655 | Train Accuracy: 53.324
Train Loss: 3.732 | Train Accuracy: 56.521
Train Loss: 4.750 | Train Accuracy: 58.565
Train Loss: 5.728 | Train Accuracy: 60.130
Train Loss: 6.673 | Train Accuracy: 61.364
Train Loss: 7.590 | Train Accuracy: 62.335
Train Loss: 8.484 | Train Accuracy: 63.190
Train Loss: 9.365 | Train Accuracy: 63.934
Train Loss: 10.225 | Train Accuracy: 64.571
