diff --git a/code/model_Unet.py b/code/model_Unet.py
index b1df0cef0e0a554885414f20382891caa3e483b6..a4185db49ee2c6f520fafd3e3643855f8f7af41e 100644
--- a/code/model_Unet.py
+++ b/code/model_Unet.py
@@ -31,13 +31,13 @@ class TestModule(pl.LightningModule):
 
         # Define the model
         self.model = smp.Unet(
-            encoder_name="resnet18",  # Also consider using smaller or larger encoders
+            encoder_name="resnet34",  # Also consider using smaller or larger encoders
             encoder_weights= "imagenet",  # Do the pretrained weights help? Try with or without
             in_channels=1,  # We use 1 chanel transmittance as input
             classes=1,  # classes == output channels. We use one output channel for cyto data
             activation="sigmoid"
         )
-        self.loss_f = RMILoss(with_logits=True) #torch.nn.L1Loss() #RMILoss(with_logits=True) #torch.nn.MSELoss()
+        self.loss_f = torch.nn.L1Loss() #torch.nn.L1Loss() #RMILoss(with_logits=True) #torch.nn.MSELoss()
 
     def forward(self, x):
         x = self.model(x)