25ep

train.py

@@ -29,8 +29,8 @@ ds_path = "datasets/576"
 project = "unet"
 batch_size = 25
 base_learning_rate = 9.5e-6
-min_learning_rate = 9e-6
-num_epochs = 2
+min_learning_rate = 7e-6
+num_epochs = 24
 # samples/save per epoch
 sample_interval_share = 10
 use_wandb = True
@@ -904,7 +904,7 @@ for epoch in range(start_epoch, start_epoch + num_epochs):
             if (global_step % 100 == 0) or (global_step % sample_interval == 0):
                 accelerator.wait_for_everyone()
                 
-            grad = torch.tensor(0.0, device=device)  # стало
+            grad = torch.tensor(0.0, device=device)
             if not fbp:
                 if accelerator.sync_gradients:
                     with torch.amp.autocast('cuda', enabled=False):