diff --git a/src/llmtuner/tuner/core/parser.py b/src/llmtuner/tuner/core/parser.py
index 7dda0a5c..e039513d 100644
--- a/src/llmtuner/tuner/core/parser.py
+++ b/src/llmtuner/tuner/core/parser.py
@@ -151,21 +151,19 @@ def get_train_args(
 
     training_args.optim = "adamw_torch" if training_args.optim == "adamw_hf" else training_args.optim # suppress warning
 
-    if training_args.fp16:
-        model_args.compute_dtype = torch.float16
-    elif training_args.bf16:
+    if training_args.bf16:
         if not torch.cuda.is_bf16_supported():
             raise ValueError("Current device does not support bf16 training.")
         model_args.compute_dtype = torch.bfloat16
     else:
-        model_args.compute_dtype = torch.float32
+        model_args.compute_dtype = torch.float16
 
     model_args.model_max_length = data_args.max_source_length + data_args.max_target_length
 
     # Log on each process the small summary:
-    logger.info("Process rank: {}, device: {}, n_gpu: {}\n  distributed training: {}, 16-bits training: {}".format(
+    logger.info("Process rank: {}, device: {}, n_gpu: {}\n  distributed training: {}, compute dtype: {}".format(
         training_args.local_rank, training_args.device, training_args.n_gpu,
-        bool(training_args.local_rank != -1), training_args.fp16
+        bool(training_args.local_rank != -1), str(model_args.compute_dtype)
     ))
     logger.info(f"Training/evaluation parameters {training_args}")