diff --git a/nbs/common.base_model.ipynb b/nbs/common.base_model.ipynb
index 0f1daeeb5..8334c759c 100644
--- a/nbs/common.base_model.ipynb
+++ b/nbs/common.base_model.ipynb
@@ -358,13 +358,15 @@
     "            datamodule_constructor = TimeSeriesDataModule\n",
     "        else:\n",
     "            datamodule_constructor = _DistributedTimeSeriesDataModule\n",
+    "        \n",
+    "        dataloader_kwargs = self.dataloader_kwargs if self.dataloader_kwargs is not None else {}\n",
     "        datamodule = datamodule_constructor(\n",
     "            dataset=dataset, \n",
     "            batch_size=batch_size,\n",
     "            valid_batch_size=valid_batch_size,\n",
     "            drop_last=self.drop_last_loader,\n",
     "            shuffle_train=shuffle_train,\n",
-    "            **self.dataloader_kwargs\n",
+    "            **dataloader_kwargs\n",
     "        )\n",
     "\n",
     "        if self.val_check_steps > self.max_steps:\n",
diff --git a/neuralforecast/common/_base_model.py b/neuralforecast/common/_base_model.py
index b17a90efa..fdad6184f 100644
--- a/neuralforecast/common/_base_model.py
+++ b/neuralforecast/common/_base_model.py
@@ -332,13 +332,17 @@ def _fit(
             datamodule_constructor = TimeSeriesDataModule
         else:
             datamodule_constructor = _DistributedTimeSeriesDataModule
+
+        dataloader_kwargs = (
+            self.dataloader_kwargs if self.dataloader_kwargs is not None else {}
+        )
         datamodule = datamodule_constructor(
             dataset=dataset,
             batch_size=batch_size,
             valid_batch_size=valid_batch_size,
             drop_last=self.drop_last_loader,
             shuffle_train=shuffle_train,
-            **self.dataloader_kwargs,
+            **dataloader_kwargs,
         )
 
         if self.val_check_steps > self.max_steps: