diff --git a/codes/train.py b/codes/train.py
index aed20554..5ea0e865 100644
--- a/codes/train.py
+++ b/codes/train.py
@@ -37,6 +37,7 @@ class Trainer:
         self.val_compute_fea = opt_get(opt, ['eval', 'compute_fea'], False)
         self.current_step = 0
         self.total_training_data_encountered = 0
+        self.next_eval_step = 0
 
         #### loading resume state if exists
         if opt['path'].get('resume_state', None):
@@ -253,7 +254,9 @@ class Trainer:
             val_freq = opt['train']['val_freq'] * batch_size
         else:
             val_freq = int(opt['train']['val_freq_megasamples'] * 1000000)
-        if opt_get(opt, ['eval', 'pure'], False) and self.total_training_data_encountered % val_freq == 0:
+
+        if opt_get(opt, ['eval', 'pure'], False) and self.total_training_data_encountered > self.next_eval_step:
+            self.next_eval_step = self.total_training_data_encountered + val_freq
             metrics = []
             for val_data in tqdm(self.val_loader):
                 self.model.feed_data(val_data, self.current_step, perform_micro_batching=False)