diff --git a/exec.py b/exec.py
index 49e6d4f..a996055 100644
--- a/exec.py
+++ b/exec.py
@@ -100,7 +100,7 @@ def train(logger):
                 model_selector.run_model_selection(net, optimizer, monitor_metrics, epoch)
 
             # update monitoring and prediction plots
-            TrainingPlot.update_and_save(monitor_metrics, epoch)
+            TrainingPlot.update_and_save(monitor_metrics, starting_epoch, epoch)
             epoch_time = time.time() - start_time
             logger.info('trained epoch {}: took {} sec. ({} train / {} val)'.format(
                 epoch, epoch_time, train_time, epoch_time-train_time))
diff --git a/plotting.py b/plotting.py
index 4e15c74..bf7408b 100644
--- a/plotting.py
+++ b/plotting.py
@@ -180,17 +180,17 @@ def __init__(self, cf):
         self.figure_list[0].ax1.set_ylim(0, 1.5)
         self.color_palette = ['b', 'c', 'r', 'purple', 'm', 'y', 'k', 'tab:gray']
 
-    def update_and_save(self, metrics, epoch):
+    def update_and_save(self, metrics, starting_epoch, epoch):
 
         for figure_ix in range(len(self.figure_list)):
             fig = self.figure_list[figure_ix]
-            detection_monitoring_plot(fig.ax1, metrics, self.exp_name, self.color_palette, epoch, figure_ix,
+            detection_monitoring_plot(fig.ax1, metrics, starting_epoch, self.exp_name, self.color_palette, epoch, figure_ix,
                                       self.separate_values_dict,
                                       self.do_validation)
             fig.savefig(self.file_name + '_{}'.format(figure_ix))
 
 
-def detection_monitoring_plot(ax1, metrics, exp_name, color_palette, epoch, figure_ix, separate_values_dict, do_validation):
+def detection_monitoring_plot(ax1, metrics, starting_epoch, exp_name, color_palette, epoch, figure_ix, separate_values_dict, do_validation):
 
     monitor_values_keys = metrics['train']['monitor_values'][1][0].keys()
     separate_values = [v for fig_ix in separate_values_dict.values() for v in fig_ix]
@@ -217,7 +217,7 @@ def detection_monitoring_plot(ax1, metrics, exp_name, color_palette, epoch, figu
         if do_validation:
             ax1.plot(x, y_val, label='val_{}'.format(pk), linestyle='-', color=color_palette[kix])
 
-    if epoch == 1:
+    if epoch == starting_epoch:
         box = ax1.get_position()
         ax1.set_position([box.x0, box.y0, box.width * 0.8, box.height])
         ax1.legend(loc='center left', bbox_to_anchor=(1, 0.5))