diff --git a/train.py b/train.py
index c8f3594..77e713b 100644
--- a/train.py
+++ b/train.py
@@ -211,15 +211,15 @@ def estimate_loss():
     return out
 
 # learning rate decay scheduler (cosine with warmup)
-def get_lr(iter):
+def get_lr(it):
     # 1) linear warmup for warmup_iters steps
-    if iter < warmup_iters:
-        return learning_rate * iter / warmup_iters
-    # 2) if iter > lr_decay_iters, return min learning rate
-    if iter > lr_decay_iters:
+    if it < warmup_iters:
+        return learning_rate * it / warmup_iters
+    # 2) if it > lr_decay_iters, return min learning rate
+    if it > lr_decay_iters:
         return min_lr
     # 3) in between, use cosine decay down to min learning rate
-    decay_ratio = (iter - warmup_iters) / (lr_decay_iters - warmup_iters)
+    decay_ratio = (it - warmup_iters) / (lr_decay_iters - warmup_iters)
     assert 0 <= decay_ratio <= 1
     coeff = 0.5 * (1.0 + math.cos(math.pi * decay_ratio)) # coeff ranges 0..1
     return min_lr + coeff * (learning_rate - min_lr)