diff --git a/src/psycop_model_training/config_schemas/eval.py b/src/psycop_model_training/config_schemas/eval.py
index 15ca2172..dbc7157a 100644
--- a/src/psycop_model_training/config_schemas/eval.py
+++ b/src/psycop_model_training/config_schemas/eval.py
@@ -8,7 +8,7 @@ class EvalConfSchema(BaseModel):
     force: bool = False
     # Whether to force evaluation even if wandb is not "run". Used for testing.
 
-    table_1: bool = True
+    descriptive_stats_table: bool = True
     # Whether to generate table 1.
 
     top_n_feature_importances: int
diff --git a/src/psycop_model_training/model_eval/base_artifacts/base_artifact_generator.py b/src/psycop_model_training/model_eval/base_artifacts/base_artifact_generator.py
index 7c370b34..6e35ebd4 100644
--- a/src/psycop_model_training/model_eval/base_artifacts/base_artifact_generator.py
+++ b/src/psycop_model_training/model_eval/base_artifacts/base_artifact_generator.py
@@ -183,9 +183,9 @@ def get_descriptive_stats_table_artifact(self):
         """Returns descriptive stats table artifact."""
         return [
             ArtifactContainer(
-                label="table_1",
+                label="descriptive_stats_table",
                 artifact=DescriptiveStatsTable(
-                    self.eval_ds
+                    self.eval_ds,
                 ).generate_descriptive_stats_table(),
             ),
         ]
@@ -225,8 +225,8 @@ def get_all_artifacts(self) -> list[ArtifactContainer]:
         """Generates artifacts from an EvalDataset."""
         artifact_containers = self.create_base_plot_artifacts()
 
-        if self.cfg.eval.table_1:
-            artifact_containers += self.get_table_1_artifact()
+        if self.cfg.eval.descriptive_stats_table:
+            artifact_containers += self.get_descriptive_stats_table_artifact()
 
         if self.pipe_metadata and self.pipe_metadata.feature_importances:
             artifact_containers += self.get_feature_importance_artifacts()