小编Sar*_*han的帖子

基本上这是 VGG-16 模型，我已经执行了迁移学习并微调了模型，我在 2 周前训练了这个模型，并发现了测试和训练的准确性，但现在我也需要模型的分类准确性，我是试图找出混淆矩阵并也想绘制该矩阵。培训代码：

# Training the model again from the last CNN Block to The End of the Network
dataset = 'C:\\Users\\Sara Latif Khan\\OneDrive\\Desktop\\FYP_\\Scene15\\15-Scene'
model = model.to(device)
optimizer = Adam(filter(lambda p: p.requires_grad, model.parameters()))

#Training Fixed Feature Extractor for 15 epochs
num_epochs = 5
batch_loss = 0
cum_epoch_loss = 0 #cumulative loss for each batch

for e in range(num_epochs):
    cum_epoch_loss = 0
  
    for batch, (images, labels) in enumerate(trainloader,1):
        images = images.to(device)
        labels = labels.to(device)

        optimizer.zero_grad()
        logps = model(images)
        loss …