Add missing loss_type in ValueError message (#1067)

trl/trainer/dpo_trainer.py

@@ -466,7 +466,7 @@ def dpo_loss(
             # eqn (17) of the paper where beta is the regularization parameter for the IPO loss, denoted by tau in the paper.
             losses = (logits - 1 / (2 * self.beta)) ** 2
         else:
-            raise ValueError(f"Unknown loss type: {self.loss_type}. Should be one of ['sigmoid', 'hinge']")
+            raise ValueError(f"Unknown loss type: {self.loss_type}. Should be one of ['sigmoid', 'hinge', 'ipo']")
 
         chosen_rewards = self.beta * (policy_chosen_logps - reference_chosen_logps).detach()
         rejected_rewards = self.beta * (policy_rejected_logps - reference_rejected_logps).detach()