diff --git a/fastNLP/core/drivers/torch_driver/torch_driver.py b/fastNLP/core/drivers/torch_driver/torch_driver.py
index 9113de51..156681be 100644
--- a/fastNLP/core/drivers/torch_driver/torch_driver.py
+++ b/fastNLP/core/drivers/torch_driver/torch_driver.py
@@ -55,7 +55,7 @@ class TorchDriver(Driver):
         # 因为 ddp 和 single_device 的混合精度训练的设置是一样的，因此可以统一抽象到这里；
         self.fp16 = fp16
         if parse_version(torch.__version__) < parse_version('1.6'):
-            raise RuntimeError("Pytorch supports float16 after version 1.6, please upgrade your pytorch version.")
+            raise RuntimeError(f"Pytorch({torch.__version__}) need to be older than 1.6.")
         self.auto_cast, _grad_scaler = _build_fp16_env(dummy=not fp16)
         self.grad_scaler = _grad_scaler()
 
diff --git a/fastNLP/core/drivers/torch_driver/utils.py b/fastNLP/core/drivers/torch_driver/utils.py
index 57e57061..14f5b9f3 100644
--- a/fastNLP/core/drivers/torch_driver/utils.py
+++ b/fastNLP/core/drivers/torch_driver/utils.py
@@ -160,7 +160,7 @@ def _build_fp16_env(dummy=False):
         GradScaler = DummyGradScaler
     else:
         if not torch.cuda.is_available():
-            raise RuntimeError("No cuda")
+            raise RuntimeError("Pytorch is not installed in gpu version, please use device='cpu'.")
         if torch.cuda.get_device_capability(0)[0] < 7:
             logger.rank_zero_warning(
                 "NOTE: your device does NOT support faster training with fp16, "