diff --git a/pvnet/models/base_model.py b/pvnet/models/base_model.py
index 3d26174f..b056a90c 100644
--- a/pvnet/models/base_model.py
+++ b/pvnet/models/base_model.py
@@ -370,7 +370,9 @@ def _calculate_val_losses(self, y, y_hat):
             # Take median value for remaining metric calculations
             y_hat = self._quantiles_to_prediction(y_hat)
 
-        common_metrics_each_step = common_metrics(predictions=y_hat.numpy(), target=y.numpy())
+        common_metrics_each_step = common_metrics(
+            predictions=y_hat.cpu().numpy(), target=y.cpu().numpy()
+        )
         mse_each_step = common_metrics_each_step["rmse"] ** 2
         mae_each_step = common_metrics_each_step["mae"]
 
diff --git a/pvnet/training.py b/pvnet/training.py
index 08b40354..5f28215e 100644
--- a/pvnet/training.py
+++ b/pvnet/training.py
@@ -103,6 +103,8 @@ def train(config: DictConfig) -> Optional[float]:
         for callback in callbacks:
             log.info(f"{callback}")
             if isinstance(callback, ModelCheckpoint):
+                # Need to call the .experiment property to initialise the logger
+                wandb_logger.experiment
                 callback.dirpath = "/".join(
                     callback.dirpath.split("/")[:-1] + [wandb_logger.version]
                 )