Hi everyone, I’m trying to use pretrained resnet18 for my project and it fits very good to my train data but not to validation data. I have tried changing batch size, convolutionlayers, lr_scheduler but there’s still no success.Screenshot from 2020-10-07 09-47-351366×768 137 KB  This is my first project in DNN and I am a beginner. Can someone please give me a suggestion what can I do? Green is Train Loss and gray Validation Loss.
My Code looks like:
class Resnet_Speaker_Recognition(nn.Module):
def init(self):
super(Resnet_Speaker_Recognition, self).init()
    self.resnet_model = models.resnet18(pretrained=True)
    self.resnet_model.conv1 = torch.nn.Conv2d(1, 64, kernel_size=(7,7), stride=(2,2), bias=True)
    self.resnet_model.conv2 = torch.nn.Conv2d(64, 32, kernel_size=(7,7), stride=(2,2), bias=True)
    self.resnet_model.conv3 = torch.nn.Conv2d(32, 64, kernel_size=(7,7), stride=(2,2), bias=True) 

def forward(self,x):
    x=self.resnet_model(x)
    return x