diff --git a/trl/trainer/grpo_config.py b/trl/trainer/grpo_config.py
index f9edc2a3e05..2d97d67bd8e 100644
--- a/trl/trainer/grpo_config.py
+++ b/trl/trainer/grpo_config.py
@@ -258,9 +258,20 @@ class GRPOConfig(TrainingArguments):
             `trackio`.
         num_completions_to_print (`int`, *optional*):
             Number of completions to print with `rich`. If `None`, all completions are logged.
-        wandb_log_unique_prompts (`bool`, *optional*, defaults to `False`):
-            Whether to log unique prompts in wandb. If `True`, only unique prompts are logged. If `False`, all prompts
-            are logged.
+        log_unique_prompts (`bool`, *optional*, defaults to `False`):
+            Whether to log unique prompts. If `True`, only unique prompts are logged. If `False`, all prompts are
+            logged.
+
+        > Deprecated arguments
+
+        wandb_log_unique_prompts (`bool`, *optional*):
+
+            <Deprecated version="0.26.0">
+
+            Parameter `wandb_log_unique_prompts` is deprecated and will be removed in version 0.27.0. Use
+            `log_unique_prompts` instead.
+
+            </Deprecated>
     """
 
     _VALID_DICT_FIELDS = TrainingArguments._VALID_DICT_FIELDS + ["model_init_kwargs"]
@@ -681,14 +692,19 @@ class GRPOConfig(TrainingArguments):
         default=None,
         metadata={"help": "Number of completions to print with `rich`. If `None`, all completions are logged."},
     )
-    wandb_log_unique_prompts: bool | None = field(
+    log_unique_prompts: bool = field(
         default=False,
         metadata={
-            "help": "Whether to log unique prompts in wandb. If `True`, only unique prompts are logged. If `False`, "
-            "all prompts are logged."
+            "help": "Whether to log unique prompts. If `True`, only unique prompts are logged. If `False`, all prompts are logged."
         },
     )
 
+    # Deprecated arguments
+    wandb_log_unique_prompts: bool | None = field(
+        default=None,
+        metadata={"help": "Deprecated, use `log_unique_prompts` instead."},
+    )
+
     def __post_init__(self):
         self.bf16 = not (self.fp16) if self.bf16 is None else self.bf16
 
@@ -751,3 +767,12 @@ def __post_init__(self):
 
         if self.delta is not None and self.use_liger_kernel:
             raise ValueError("Liger kernel does not support two-sided GRPO loss yet.")
+
+        if self.wandb_log_unique_prompts is not None:
+            warnings.warn(
+                "The `wandb_log_unique_prompts` argument is deprecated and will be removed in version 0.27.0. Please "
+                "use `log_unique_prompts` instead.",
+                FutureWarning,
+                stacklevel=2,
+            )
+            self.log_unique_prompts = self.wandb_log_unique_prompts
diff --git a/trl/trainer/grpo_trainer.py b/trl/trainer/grpo_trainer.py
index 856a7aad224..6b245b3511c 100644
--- a/trl/trainer/grpo_trainer.py
+++ b/trl/trainer/grpo_trainer.py
@@ -532,7 +532,7 @@ def cast_outputs_to_original_dtype(module, args, output):
         self._metrics = {"train": defaultdict(list), "eval": defaultdict(list)}
         self._total_train_tokens = 0
         self.log_completions = args.log_completions
-        self.wandb_log_unique_prompts = args.wandb_log_unique_prompts
+        self.log_unique_prompts = args.log_unique_prompts
         self.num_completions_to_print = args.num_completions_to_print
         # Keep logs sized to the generation batch to record only outputs from the latest model update.
         self._logs = {
@@ -1973,7 +1973,7 @@ def log(self, logs: dict[str, float], start_time: float | None = None) -> None:
                 else:
                     df = df_base
 
-                if self.wandb_log_unique_prompts:
+                if self.log_unique_prompts:
                     df = df.drop_duplicates(subset=["prompt"])
 
                 logging_backend.log({"completions": logging_backend.Table(dataframe=df)})
diff --git a/trl/trainer/rloo_config.py b/trl/trainer/rloo_config.py
index 6a101ae0583..eb893c604c8 100644
--- a/trl/trainer/rloo_config.py
+++ b/trl/trainer/rloo_config.py
@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import warnings
 from dataclasses import dataclass, field
 
 from transformers import TrainingArguments
@@ -191,9 +192,20 @@ class RLOOConfig(TrainingArguments):
             `trackio`.
         num_completions_to_print (`int`, *optional*):
             Number of completions to print with `rich`. If `None`, all completions are logged.
-        wandb_log_unique_prompts (`bool`, *optional*, defaults to `False`):
-            Whether to log unique prompts in wandb. If `True`, only unique prompts are logged. If `False`, all prompts
-            are logged.
+        log_unique_prompts (`bool`, *optional*, defaults to `False`):
+            Whether to log unique prompts. If `True`, only unique prompts are logged. If `False`, all prompts are
+            logged.
+
+        > Deprecated arguments
+
+        wandb_log_unique_prompts (`bool`, *optional*):
+
+            <Deprecated version="0.26.0">
+
+            Parameter `wandb_log_unique_prompts` is deprecated and will be removed in version 0.27.0. Use
+            `log_unique_prompts` instead.
+
+            </Deprecated>
     """
 
     _VALID_DICT_FIELDS = TrainingArguments._VALID_DICT_FIELDS + ["model_init_kwargs"]
@@ -530,14 +542,20 @@ class RLOOConfig(TrainingArguments):
         default=None,
         metadata={"help": "Number of completions to print with `rich`. If `None`, all completions are logged."},
     )
-    wandb_log_unique_prompts: bool | None = field(
+    log_unique_prompts: bool = field(
         default=False,
         metadata={
-            "help": "Whether to log unique prompts in wandb. If `True`, only unique prompts are logged. If `False`, "
-            "all prompts are logged."
+            "help": "Whether to log unique prompts. If `True`, only unique prompts are logged. If `False`, all "
+            "prompts are logged."
         },
     )
 
+    # Deprecated arguments
+    wandb_log_unique_prompts: bool | None = field(
+        default=None,
+        metadata={"help": "Deprecated, use `log_unique_prompts` instead."},
+    )
+
     def __post_init__(self):
         self.bf16 = not (self.fp16) if self.bf16 is None else self.bf16
 
@@ -586,3 +604,12 @@ def __post_init__(self):
                 "RLOO requires at least 2 generations per prompt to calculate the advantages. You provided "
                 f"{self.num_generations}, which is less than the minimum required."
             )
+
+        if self.wandb_log_unique_prompts is not None:
+            warnings.warn(
+                "The `wandb_log_unique_prompts` argument is deprecated and will be removed in version 0.27.0. Please "
+                "use `log_unique_prompts` instead.",
+                FutureWarning,
+                stacklevel=2,
+            )
+            self.log_unique_prompts = self.wandb_log_unique_prompts
diff --git a/trl/trainer/rloo_trainer.py b/trl/trainer/rloo_trainer.py
index e2c38a03555..7203862fa1d 100644
--- a/trl/trainer/rloo_trainer.py
+++ b/trl/trainer/rloo_trainer.py
@@ -449,7 +449,7 @@ def __init__(
         self._metrics = {"train": defaultdict(list), "eval": defaultdict(list)}
         self._total_train_tokens = 0
         self.log_completions = args.log_completions
-        self.wandb_log_unique_prompts = args.wandb_log_unique_prompts
+        self.log_unique_prompts = args.log_unique_prompts
         self.num_completions_to_print = args.num_completions_to_print
         # Keep logs sized to the generation batch to record only outputs from the latest model update.
         self._logs = {
@@ -1564,7 +1564,7 @@ def log(self, logs: dict[str, float], start_time: float | None = None) -> None:
                 else:
                     df = df_base
 
-                if self.wandb_log_unique_prompts:
+                if self.log_unique_prompts:
                     df = df.drop_duplicates(subset=["prompt"])
 
                 logging_backend.log({"completions": logging_backend.Table(dataframe=df)})