diff --git a/src/torchmetrics/classification/dice.py b/src/torchmetrics/classification/dice.py
index bd9c42219cb..770830e19ba 100644
--- a/src/torchmetrics/classification/dice.py
+++ b/src/torchmetrics/classification/dice.py
@@ -56,7 +56,7 @@ class Dice(Metric):
 
     Args:
         num_classes:
-            Number of classes. Necessary for ``'macro'``, ``'weighted'`` and ``None`` average methods.
+            Number of classes. Necessary for ``'macro'``, and ``None`` average methods.
         threshold:
             Threshold for transforming probability or logit predictions to binary (0,1) predictions, in the case
             of binary or multi-label inputs. Default value of 0.5 corresponds to input being probabilities.
@@ -116,7 +116,7 @@ class Dice(Metric):
 
     Raises:
         ValueError:
-            If ``average`` is none of ``"micro"``, ``"macro"``, ``"weighted"``, ``"samples"``, ``"none"``, ``None``.
+            If ``average`` is none of ``"micro"``, ``"macro"``, ``"samples"``, ``"none"``, ``None``.
         ValueError:
             If ``mdmc_average`` is not one of ``None``, ``"samplewise"``, ``"global"``.
         ValueError:
@@ -146,7 +146,7 @@ def __init__(
         zero_division: int = 0,
         num_classes: Optional[int] = None,
         threshold: float = 0.5,
-        average: Optional[Literal["micro", "macro", "weighted", "none"]] = "micro",
+        average: Optional[Literal["micro", "macro", "none"]] = "micro",
         mdmc_average: Optional[str] = "global",
         ignore_index: Optional[int] = None,
         top_k: Optional[int] = None,
@@ -154,7 +154,7 @@ def __init__(
         **kwargs: Any,
     ) -> None:
         super().__init__(**kwargs)
-        allowed_average = ("micro", "macro", "weighted", "samples", "none", None)
+        allowed_average = ("micro", "macro", "samples", "none", None)
         if average not in allowed_average:
             raise ValueError(f"The `average` has to be one of {allowed_average}, got {average}.")