diff --git a/scripts/evaluation/evaluate.py b/scripts/evaluation/evaluate.py
index 594f0c2..e928420 100644
--- a/scripts/evaluation/evaluate.py
+++ b/scripts/evaluation/evaluate.py
@@ -9,7 +9,7 @@ import torch
 import typer
 import yaml
 from gluonts.dataset.split import split
-from gluonts.ev.metrics import MASE, MeanWeightedSumQuantileLoss
+from gluonts.ev.metrics import MASE, MeanWeightedSumQuantileLoss, ND
 from gluonts.itertools import batcher
 from gluonts.model.evaluation import evaluate_forecasts
 from gluonts.model.forecast import QuantileForecast, SampleForecast
@@ -19,6 +19,10 @@ from chronos import BaseChronosPipeline, Chronos2Pipeline, ChronosBoltPipeline,
 
 app = typer.Typer(pretty_exceptions_enable=False)
 
+logging.basicConfig(format="%(asctime)s - %(name)s - %(levelname)s - %(message)s")
+logger = logging.getLogger("Chronos Evaluation")
+logger.setLevel(logging.INFO)
+
 QUANTILES = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
 
 
@@ -150,6 +154,7 @@ def eval_pipeline_and_save_results(
                 metrics=[
                     MASE(),
                     MeanWeightedSumQuantileLoss(QUANTILES),
+                    ND(),
                 ],
                 batch_size=5000,
             )
@@ -162,7 +167,7 @@ def eval_pipeline_and_save_results(
     results_df = (
         pd.DataFrame(result_rows)
         .rename(
-            {"MASE[0.5]": "MASE", "mean_weighted_sum_quantile_loss": "WQL"},
+            {"MASE[0.5]": "MASE", "mean_weighted_sum_quantile_loss": "WQL", "ND": "WAPE"},
             axis="columns",
         )
         .sort_values(by="dataset")
@@ -340,7 +345,4 @@ def chronos_2(
 
 
 if __name__ == "__main__":
-    logging.basicConfig(format="%(asctime)s - %(name)s - %(levelname)s - %(message)s")
-    logger = logging.getLogger("Chronos Evaluation")
-    logger.setLevel(logging.INFO)
     app()