I want to Trouble you again .
Sorry for this ,Plz help me
I am facing same issue with another model.I am building simple digit classifier using ANN
code=
class NET(nn.Module):
    def __init__(self):
        super().__init__()
        self.model=nn.Sequential(
            nn.Linear(784, 128),
            nn.ReLU(),
            nn.Linear(128, 256),
            nn.ReLU(),
            nn.Linear(256, 512),
            nn.ReLU(),
            nn.Linear(512, 10),
        
        )
    def forward(self,x):
            return self.model(x)


loss_fn=nn.CrossEntropyLoss()
opt=optim.Adam(net.parameters() , lr=0.01)

loss_epoch=[]
epochs=5
for i in range(epochs):
        
        opt.zero_grad()
        output=net(x_train)
        loss=loss_fn(output, y_train)
        loss.backward()
        opt.step()
        loss_epoch.append(loss.item())
        
        print("Epochs: {}/{} , Loss:{}".format(i,epochs,loss))

OUTPUT=
 Epochs: 0/5, Loss:2.301159143447876

 Epochs: 1/5, Loss:2.301161289215088

 Epochs: 2/5, Loss:2.3011562824249268

 Epochs: 3/5, Loss:2.3011701107025146

 Epochs: 4/5, Loss:2.3011698722839355

data- Mnist Digit data