diff --git a/optim_nn.py b/optim_nn.py
index 8f66952..f50dbe7 100755
--- a/optim_nn.py
+++ b/optim_nn.py
@@ -859,11 +859,11 @@ def run(program, args=None):
 
         if config.log10_loss:
             fmt = "epoch {:4.0f}, rate {:10.8f}, log10-loss {:+6.3f}"
-            log("info", fmt.format(learner.epoch + 1, learner.rate, np.log10(avg_loss)),
+            log("info", fmt.format(learner.epoch, learner.rate, np.log10(avg_loss)),
                 update=True)
         else:
             fmt = "epoch {:4.0f}, rate {:10.8f}, loss {:12.6e}"
-            log("info", fmt.format(learner.epoch + 1, learner.rate, avg_loss),
+            log("info", fmt.format(learner.epoch, learner.rate, avg_loss),
                 update=True)
 
     measure_error()
diff --git a/optim_nn_core.py b/optim_nn_core.py
index 9361f20..47316db 100644
--- a/optim_nn_core.py
+++ b/optim_nn_core.py
@@ -845,7 +845,8 @@ class Learner:
     @epoch.setter
     def epoch(self, new_epoch):
         self._epoch = int(new_epoch)
-        self.rate = self.rate_at(self._epoch)
+        if 0 <= self.epoch <= self.epochs:
+            self.rate = self.rate_at(self._epoch)
 
     @property
     def rate(self):
@@ -860,13 +861,11 @@ class Learner:
 
     def next(self):
         # prepares the next epoch. returns whether or not to continue training.
-        if self.epoch + 1 >= self.epochs:
-            return False
-        if self.started:
-            self.epoch += 1
-        else:
+        if not self.started:
             self.started = True
-            self.epoch = self.epoch # poke property setter just in case
+        self.epoch += 1
+        if self.epoch > self.epochs:
+            return False
         return True
 
     def batch(self, progress): # TODO: rename
@@ -874,7 +873,7 @@ class Learner:
         # unlike epochs, we do not store batch number as a state.
         # i.e. calling next() will not respect progress.
         assert 0 <= progress <= 1
-        self.rate = self.rate_at(self._epoch + progress)
+        self.rate = self.rate_at(self._epoch - 1 + progress)
 
     @property
     def final_rate(self):
@@ -921,7 +920,7 @@ class SGDR(Learner):
     def split_num(self, epoch):
         shit = [0] + self.splits # hack
         for i in range(0, len(self.splits)):
-            if epoch < self.splits[i]:
+            if epoch < self.splits[i] + 1:
                 sub_epoch = epoch - shit[i]
                 next_restart = self.splits[i] - shit[i]
                 return i, sub_epoch, next_restart
diff --git a/optim_nn_mnist.py b/optim_nn_mnist.py
old mode 100644
new mode 100755
index ce3e257..fc092ef
--- a/optim_nn_mnist.py
+++ b/optim_nn_mnist.py
@@ -161,14 +161,14 @@ while learner.next():
         batch_size=bs,
         return_losses='both')
     fmt = "rate {:10.8f}, loss {:12.6e}, accuracy {:6.2f}%"
-    log("epoch {}".format(learner.epoch + 1),
+    log("epoch {}".format(learner.epoch),
         fmt.format(learner.rate, avg_loss, avg_mloss * 100))
 
     batch_losses += losses
     batch_mlosses += mlosses
 
     if measure_every_epoch:
-        quiet = learner.epoch + 1 != learner.epochs
+        quiet = learner.epoch != learner.epochs
         measure_error(quiet=quiet)
 
 if not measure_every_epoch: