diff --git a/deeplabcut/pose_estimation_pytorch/config/logger.py b/deeplabcut/pose_estimation_pytorch/config/logger.py
index a37a7d33c..de025590c 100644
--- a/deeplabcut/pose_estimation_pytorch/config/logger.py
+++ b/deeplabcut/pose_estimation_pytorch/config/logger.py
@@ -41,16 +41,27 @@ class WandbLoggerConfig(LoggerConfig):  #
         type: Logger type (should be 'WandbLogger')
         project_name: The name of the wandb project
         run_name: The name of the wandb run
+        entity: The wandb user or team under which the run is logged
+        notes: A longer description of the run, displayed in the wandb UI
+        tags: Tags for the run, used to organize and filter runs in the wandb UI
+        group: The name of the group to which this run belongs
+        job_type: The type of job being logged (e.g. 'train' or 'eval')
         image_log_interval: How often train/test images are logged in epochs
             (if None, train/test inputs are never logged)
         model: The model architecture to log
         train_folder: The path of the folder containing training files.
-        wandb_kwargs: Additional keyword arguments to pass to wandb.init
+        wandb_kwargs: Additional keyword arguments to pass to wandb.init. Use this for
+            wandb.init parameters which are not declared above.
     """
 
     type: Literal[LoggerType.WandbLogger]
     project_name: str = "deeplabcut"
     run_name: str = "tmp"
+    entity: str | None = None
+    notes: str | None = None
+    tags: list[str] | None = None
+    group: str | None = None
+    job_type: str | None = None
     image_log_interval: int | None = None
     model: dict | None = None
     train_folder: str | None = None
diff --git a/deeplabcut/pose_estimation_pytorch/runners/logger.py b/deeplabcut/pose_estimation_pytorch/runners/logger.py
index 22c747bf1..ed179aa39 100644
--- a/deeplabcut/pose_estimation_pytorch/runners/logger.py
+++ b/deeplabcut/pose_estimation_pytorch/runners/logger.py
@@ -275,7 +275,9 @@ def __init__(
                 None, train/test inputs are never logged).
             model: The model to log. Defaults to None.
             train_folder: path to the train folder (used to store the W&B run identifiers)
-            wandb_kwargs: extra arguments to pass to ``wb.init``
+            wandb_kwargs: extra arguments to pass to ``wb.init``. These can be given as
+                keyword arguments, or collected in a single ``wandb_kwargs`` mapping (as
+                declared by ``WandbLoggerConfig``).
 
         Example:
             logger = WandbLogger(project_name="mice", run_name="exp1", model=my_model)
@@ -291,6 +293,9 @@ def __init__(
         if wandb.run is not None:
             wandb.finish()
 
+        # A nested ``wandb_kwargs``mapping must be flattened
+        wandb_kwargs.update(wandb_kwargs.pop("wandb_kwargs", None) or {})
+
         self.run = wandb.init(
             project=project_name,
             name=run_name,