Case one CEL

Code/train.py

@@ -143,9 +143,9 @@ def train(model, name, seed,gradient_accumulation_steps,mixup, threshold, lambda
 #Fkt vom Meeting
 def cross_entropy(logits, target):
 	logprobs = torch.nn.functional.log_softmax(logits, dim = 1)
-	value = tensor.item()
+	value = target.item()
 	if value == 1 or value == 0:
-		value = tensor.item()
+		value = target.item()
 		one_hot = torch.tensor([1-value,value], device='cuda:0')
 		loss_clear_labels = one_hot * logprobs
 		return loss_clear_labels