fix: ensure non-zero learning rate during warmup at iteration 0

The warmup learning rate calculation has been modified to use (it + 1)/(warmup_iters + 1)
instead of it/warmup_iters. This ensures a non-zero learning rate at iteration 0
while maintaining the same linear warmup behavior.

Fixes karpathy#443

Author: devin-ai-integration[bot]

train.py

@@ -231,7 +231,7 @@ def estimate_loss():
 def get_lr(it):
     # 1) linear warmup for warmup_iters steps
     if it < warmup_iters:
-        return learning_rate * it / warmup_iters
+        return learning_rate * (it + 1) / (warmup_iters + 1)
     # 2) if it > lr_decay_iters, return min learning rate
     if it > lr_decay_iters:
         return min_lr