diff --git a/keras/applications/convnext.py b/keras/applications/convnext.py
index 8304d776e5d7..7e5e209bf200 100644
--- a/keras/applications/convnext.py
+++ b/keras/applications/convnext.py
@@ -124,7 +124,7 @@
 
   Args:
     include_top: Whether to include the fully-connected
-      layer at the top of the network. Defaults to True.
+      layer at the top of the network. Defaults to `True`.
     weights: One of `None` (random initialization),
       `"imagenet"` (pre-training on ImageNet-1k), or the path to the weights
       file to be loaded. Defaults to `"imagenet"`.
@@ -135,7 +135,7 @@
       if `include_top` is False.
       It should have exactly 3 inputs channels.
     pooling: Optional pooling mode for feature extraction
-      when `include_top` is `False`. Defaults to None.
+      when `include_top` is `False`.
       - `None` means that the output of the model will be
         the 4D tensor output of the last convolutional layer.
       - `avg` means that global average pooling
@@ -144,16 +144,16 @@
         the output of the model will be a 2D tensor.
       - `max` means that global max pooling will
         be applied.
+      Defaults to `None`.
     classes: Optional number of classes to classify images
       into, only to be specified if `include_top` is True, and
-      if no `weights` argument is specified. Defaults to 1000 (number of
-      ImageNet classes).
+      if no `weights` argument is specified. 1000 is how many
+      ImageNet classes there are. Defaults to `1000`.
     classifier_activation: A `str` or callable. The activation function to use
       on the "top" layer. Ignored unless `include_top=True`. Set
       `classifier_activation=None` to return the logits of the "top" layer.
-      Defaults to `"softmax"`.
       When loading pretrained weights, `classifier_activation` can only
-      be `None` or `"softmax"`.
+      be `None` or `"softmax"`. Defaults to `"softmax"`.
 
   Returns:
     A `keras.Model` instance.
@@ -754,10 +754,10 @@ def preprocess_input(x, data_format=None):
 
     Args:
       x: A floating point `numpy.array` or a `tf.Tensor`.
-      data_format: Optional data format of the image tensor/array. Defaults to
-        None, in which case the global setting
-        `tf.keras.backend.image_data_format()` is used (unless you changed it,
-        it defaults to "channels_last").{mode}
+      data_format: Optional data format of the image tensor/array. `None` means
+        the global setting `tf.keras.backend.image_data_format()` is used
+        (unless you changed it, it uses "channels_last").{mode}.
+        Defaults to `None`.
 
     Returns:
       Unchanged `numpy.array` or `tf.Tensor`.