diff --git a/tests/testthat/_snaps/tune_bayes.md b/tests/testthat/_snaps/tune_bayes.md
index 41ae9e42d..ed936a40b 100644
--- a/tests/testthat/_snaps/tune_bayes.md
+++ b/tests/testthat/_snaps/tune_bayes.md
@@ -443,7 +443,7 @@
       res_fail <- tune_bayes(mod, Sale_Price ~ Neighborhood + Gr_Liv_Area +
       Year_Built + Bldg_Type + Latitude + Longitude, resamples = folds, initial = 5,
       metrics = yardstick::metric_set(rsq), param_info = parameters(dials::cost_complexity(
-        c(0.5, 0))))
+        c(0, 0.5))))
     Message
       > A | warning: A correlation computation is required, but `estimate` is constant and has 0 standard deviation, resulting in a divide by 0 error. `NA` will be returned.
       ! All of the rsq estimates were missing. The Gaussian process model cannot be
diff --git a/tests/testthat/test-tune_bayes.R b/tests/testthat/test-tune_bayes.R
index 893af2de5..c8df715fb 100644
--- a/tests/testthat/test-tune_bayes.R
+++ b/tests/testthat/test-tune_bayes.R
@@ -564,11 +564,11 @@ test_that("missing performance values", {
       tune_bayes(
         Sale_Price ~
           Neighborhood +
-            Gr_Liv_Area +
-            Year_Built +
-            Bldg_Type +
-            Latitude +
-            Longitude,
+          Gr_Liv_Area +
+          Year_Built +
+          Bldg_Type +
+          Latitude +
+          Longitude,
         resamples = folds,
         initial = 3,
         metrics = yardstick::metric_set(rsq),
@@ -583,15 +583,15 @@ test_that("missing performance values", {
       tune_bayes(
         Sale_Price ~
           Neighborhood +
-            Gr_Liv_Area +
-            Year_Built +
-            Bldg_Type +
-            Latitude +
-            Longitude,
+          Gr_Liv_Area +
+          Year_Built +
+          Bldg_Type +
+          Latitude +
+          Longitude,
         resamples = folds,
         initial = 5,
         metrics = yardstick::metric_set(rsq),
-        param_info = parameters(dials::cost_complexity(c(0.5, 0)))
+        param_info = parameters(dials::cost_complexity(c(0, 0.5)))
       )
   })
 })