diff --git a/template/steps/data_preprocessor.py b/template/steps/data_preprocessor.py
index cd87063..c4039a9 100644
--- a/template/steps/data_preprocessor.py
+++ b/template/steps/data_preprocessor.py
@@ -7,7 +7,7 @@
 from sklearn.preprocessing import MinMaxScaler
 from typing_extensions import Annotated
 from utils.preprocess import ColumnsDropper, DataFrameCaster, NADropper
-from zenml import log_artifact_metadata, step
+from zenml import log_metadata, step
 
 
 @step
@@ -67,7 +67,7 @@ def data_preprocessor(
     dataset_tst = preprocess_pipeline.transform(dataset_tst)
 
     # Log metadata so we can load it in the inference pipeline
-    log_artifact_metadata(
+    log_metadata(
         artifact_name="preprocess_pipeline",
         metadata={"random_state": random_state, "target": target},
     )
diff --git a/template/steps/model_evaluator.py b/template/steps/model_evaluator.py
index 835d9ea..95cc6be 100644
--- a/template/steps/model_evaluator.py
+++ b/template/steps/model_evaluator.py
@@ -4,7 +4,7 @@
 
 import pandas as pd
 from sklearn.base import ClassifierMixin
-from zenml import log_artifact_metadata, step
+from zenml import log_metadata, step
 from zenml.logger import get_logger
 
 logger = get_logger(__name__)
@@ -79,7 +79,7 @@ def model_evaluator(
         for message in messages:
             logger.warning(message)
 
-    log_artifact_metadata(
+    log_metadata(
         metadata={"train_accuracy": float(trn_acc), "test_accuracy": float(tst_acc)},
         artifact_name="sklearn_classifier",
     )