added reports and params

architectures/Model.py

@@ -46,19 +46,23 @@ class Model(ABC):
         file_path = Path(f"{mode}/{self.__class__.__name__.lower()}/time_metrics.txt")
         Util._initialize_log_file(file_path)
         
-        #save_dir.mkdir(parents=True, exist_ok=True)
 
         print(f"Starting training on {self.device}...")
         start_time = time.time()
+        # training phase
         self.model.train()
 
         for epoch in range(epochs):
             total_loss = 0.0
             for inputs, labels in loader:
                 inputs, labels = inputs.to(self.device), labels.to(self.device)
+                # zero param gradients
                 optimizer.zero_grad()
+                # forward pass
                 outputs = self.model(inputs)
+                # comoutew loss
                 loss = criterion(outputs, labels)
+                # backward pass
                 loss.backward()
                 optimizer.step()
                 total_loss += loss.item()
@@ -66,7 +70,8 @@ class Model(ABC):
         
             print(f"Epoch {epoch+1}/{epochs} | Loss: {total_loss / len(loader):.4f}")
         end_time = time.time()
-        Util.log_metric(log_file=file_path, execution_time=(end_time - start_time))
+        execution_time = end_time - start_time
+        Util.log_metric(log_file=file_path, execution_time=execution_time)
         if self.device.type == 'cuda': torch.cuda.synchronize()
         print(f"Training completed in: {time.time() - start_time:.2f}s")