diff --git a/src/llmtuner/hparams/finetuning_args.py b/src/llmtuner/hparams/finetuning_args.py
index 6e5cdb3f..88e4d65c 100644
--- a/src/llmtuner/hparams/finetuning_args.py
+++ b/src/llmtuner/hparams/finetuning_args.py
@@ -90,7 +90,7 @@ class RLHFArguments:
         default=0.1,
         metadata={"help": "The beta parameter for the DPO loss."},
     )
-    dpo_loss: Optional[Literal["sigmoid", "hinge", "ipo", "kto"]] = field(
+    dpo_loss: Optional[Literal["sigmoid", "hinge", "ipo", "kto_pair"]] = field(
         default="sigmoid",
         metadata={"help": "The type of DPO loss to use."},
     )
diff --git a/src/llmtuner/train/dpo/trainer.py b/src/llmtuner/train/dpo/trainer.py
index 2ea4707c..eb989b19 100644
--- a/src/llmtuner/train/dpo/trainer.py
+++ b/src/llmtuner/train/dpo/trainer.py
@@ -18,7 +18,7 @@ class CustomDPOTrainer(DPOTrainer):
     def __init__(
         self,
         beta: float,
-        loss_type: Literal["sigmoid", "hinge", "ipo", "kto"],
+        loss_type: Literal["sigmoid", "hinge", "ipo", "kto_pair"],
         ftx_gamma: float,
         model: Union["PreTrainedModel", torch.nn.Module],
         ref_model: Optional[Union["PreTrainedModel", torch.nn.Module]] = None,
@@ -30,6 +30,7 @@ class CustomDPOTrainer(DPOTrainer):
             if ref_model is not None:
                 disable_dropout_in_model(ref_model)
 
+        self.reference_free = False
         self.use_dpo_data_collator = True  # hack to avoid warning
         self.generate_during_eval = False  # disable at evaluation
         self.label_pad_token_id = IGNORE_INDEX