diff --git a/mlair/plotting/data_insight_plotting.py b/mlair/plotting/data_insight_plotting.py
index 0a3b28cea19d2bbfd97fef470c352248c169fced..29693b3f1c5832a460925819da9cc7aeef66a54e 100644
--- a/mlair/plotting/data_insight_plotting.py
+++ b/mlair/plotting/data_insight_plotting.py
@@ -23,7 +23,7 @@ from mlair.plotting.abstract_plot_class import AbstractPlotClass
 @TimeTrackingWrapper
 class PlotOversampling(AbstractPlotClass):
 
-    def __init__(self, data, bin_edges, oversampling_rates, plot_folder: str = ".",
+    def __init__(self, data, bin_edges, bin_edges_retransformed, oversampling_rates, plot_folder: str = ".",
                  plot_names=["oversampling_histogram", "oversampling_density_histogram", "oversampling_rates",
                             "oversampling_rates_deviation"]):
 
@@ -31,10 +31,10 @@ class PlotOversampling(AbstractPlotClass):
 
         Y_hist, Y_extreme_hist, Y_hist_dens, Y_extreme_hist_dens = self._calculate_hist(data, bin_edges)
         real_oversampling = Y_extreme_hist / Y_hist
-        self._plot_oversampling_histogram(Y_hist, Y_extreme_hist, bin_edges)
+        self._plot_oversampling_histogram(Y_hist, Y_extreme_hist, bin_edges_retransformed)
         self._save()
         self.plot_name = plot_names[1]
-        self._plot_oversampling_histogram(Y_hist_dens, Y_extreme_hist_dens, bin_edges)
+        self._plot_oversampling_histogram(Y_hist_dens, Y_extreme_hist_dens, bin_edges_retransformed)
         self._save()
         self.plot_name = plot_names[2]
         self._plot_oversampling_rates(oversampling_rates, real_oversampling)
diff --git a/mlair/run_modules/post_processing.py b/mlair/run_modules/post_processing.py
index aef5c8e079c849ae1e0ec8ec14e0a6df46f772ad..a19ddbe1dd09fa6da833d4c448f113c1bd02b44c 100644
--- a/mlair/run_modules/post_processing.py
+++ b/mlair/run_modules/post_processing.py
@@ -356,8 +356,9 @@ class PostProcessing(RunEnvironment):
             if (self.data_store.get('oversampling_method')=='bin_oversampling') and (
                     "PlotOversampling" in plot_list):
                 bin_edges = self.data_store.get('oversampling_bin_edges')
+                bin_edges_retransformed = self.data_store.get('oversampling_bin_edges_retransformed')
                 oversampling_rates = self.data_store.get('oversampling_rates_capped', 'train')
-                PlotOversampling(self.train_data, bin_edges, oversampling_rates, plot_folder=self.plot_path)
+                PlotOversampling(self.train_data, bin_edges, bin_edges_retransformed, oversampling_rates, plot_folder=self.plot_path)
         except Exception as e:
             logging.error(f"Could not create plot OversamplingPlots due to the following error: {e}")
 
diff --git a/mlair/run_modules/pre_processing.py b/mlair/run_modules/pre_processing.py
index 3354e78c0c9ee85dad71f15a7a0171248913c0b7..ef6f32552c5bc20107755d1f0fa5eff0f4171441 100644
--- a/mlair/run_modules/pre_processing.py
+++ b/mlair/run_modules/pre_processing.py
@@ -99,10 +99,15 @@ class PreProcessing(RunEnvironment):
         # Get Oversampling rates (with and without cap)
         oversampling_rates = 1 / histogram
         oversampling_rates_capped = np.minimum(oversampling_rates, rates_cap)
+        # Get transformer variables
+        o3_mean = self.data_store.get("transformation")[0]["o3"]["mean"].values
+        o3_std = self.data_store.get("transformation")[0]["o3"]["std"].values
+        bin_edges_retransformed = np.floor(bin_edges*o3_std+o3_mean)
         # Add to datastore
         self.data_store.set('oversampling_rates', oversampling_rates, 'train')
         self.data_store.set('oversampling_rates_capped', oversampling_rates_capped, 'train')
         self.data_store.set('oversampling_bin_edges', bin_edges)
+        self.data_store.set('oversampling_bin_edges_retransformed', bin_edges_retransformed)
         #Y = None
         #Y_extreme = None
         for station in data: