diff --git a/src/transformers/training_args.py b/src/transformers/training_args.py
index 6d68405ab35a24..bc83b131a2e677 100644
--- a/src/transformers/training_args.py
+++ b/src/transformers/training_args.py
@@ -1820,7 +1820,7 @@ def __post_init__(self):
             raise ValueError("warmup_steps must be either 0 or > 1")
 
         if isinstance(self.fsdp, bool):
-            self.fsdp = "full_shard" if self.fsdp else ""
+            self.fsdp = [FSDPOption.FULL_SHARD] if self.fsdp else ""
         if isinstance(self.fsdp, str):
             self.fsdp = [FSDPOption(s) for s in self.fsdp.split()]
         if self.fsdp == [FSDPOption.OFFLOAD]:
@@ -1831,6 +1831,15 @@ def __post_init__(self):
         elif FSDPOption.FULL_SHARD in self.fsdp and FSDPOption.SHARD_GRAD_OP in self.fsdp:
             raise ValueError("`--fsdp full_shard` is not compatible with `--fsdp shard_grad_op`.")
 
+        if self.gradient_checkpointing and (
+            FSDPOption.FULL_SHARD in self.fsdp or FSDPOption.HYBRID_SHARD in self.fsdp
+        ):
+            logger.warning(
+                "When using FSDP full shard, instead of using `gradient_checkpointing` in TrainingArguments, please"
+                " use `activation_checkpointing` in `fsdp_config`. The former introduces a redundant AllGather"
+                " operation in backward pass. Reference: https://github.com/huggingface/transformers/issues/30404"
+            )
+
         if self.fsdp_config is None:
             self.fsdp_config = {}