cel

Code/train.py

@@ -139,7 +139,7 @@ def train(model, name, seed,gradient_accumulation_steps,mixup, threshold, lambda
 
 	return evaluation_test, evaluation_train
 
-#-L(y, y') = -1/N * ∑( ∑(y'i * log(softmax(logits_i))) )
+
 def cross_entropy(logits, target):
     log_q = torch.log_softmax(logits, dim=1)
     return -torch.sum(log_q[range(log_q.shape[0]), target])