diff --git a/dualpipe/dualpipe.py b/dualpipe/dualpipe.py
index 099f84f..686fb53 100644
--- a/dualpipe/dualpipe.py
+++ b/dualpipe/dualpipe.py
@@ -20,7 +20,7 @@ class DualPipe(nn.Module):
 
         assert next(modules[0].parameters()).device == torch.device(torch.cuda.current_device())
         self.module = nn.ModuleList(modules)
-        self.overlaped_forward_backward = type(modules[0]) == type(modules[1]) and hasattr(type(modules[0]), "overlaped_forward_backward")
+        self.overlapped_forward_backward = type(modules[0]) == type(modules[1]) and hasattr(type(modules[0]), "overlapped_forward_backward")
         self.batch_dim = batch_dim
         self.group = process_group or dist.distributed_c10d._get_default_group()
         self.num_ranks = self.group.size()
@@ -123,7 +123,7 @@ class DualPipe(nn.Module):
             self._forward_compute_chunk(phase0)
             return
 
-        if not self.overlaped_forward_backward:
+        if not self.overlapped_forward_backward:
             self._forward_compute_chunk(phase0)
             self._backward_compute_chunk(phase1)
             return
@@ -165,7 +165,7 @@ class DualPipe(nn.Module):
             outputs1, output_grads1 = list(zip(*non_empty))
 
         # forward & backward
-        outputs0, loss0 = type(module0).overlaped_forward_backward(
+        outputs0, loss0 = type(module0).overlapped_forward_backward(
             module0, inputs0, criterion0, labels0,
             module1, loss1, outputs1, output_grads1,
         )
@@ -300,7 +300,7 @@ class DualPipe(nn.Module):
         return_outputs: bool = False,
     ) -> Tuple[Optional[torch.Tensor], Optional[Union[torch.Tensor, Tuple[torch.Tensor]]]]:
         """
-        Execute a traning or inference step.
+        Execute a training or inference step.
 
         Arguments:
             *inputs: Module inputs. Required only on the first/last ranks.
@@ -352,7 +352,7 @@ class DualPipe(nn.Module):
             self.labels = (labels, [])
         self.criterion = criterion
 
-        # For the fisrt half of the ranks: phase 0 means forward direction, phase 1 means reverse direction.
+        # For the first half of the ranks: phase 0 means forward direction, phase 1 means reverse direction.
         # For the second half of the ranks: phase 0 means reverse direction, phase 1 means forward direction.
 
         # Step 1: nF0