diff --git a/lerobot/common/policies/act/policy.py b/lerobot/common/policies/act/policy.py
index e14a1e88..b8276214 100644
--- a/lerobot/common/policies/act/policy.py
+++ b/lerobot/common/policies/act/policy.py
@@ -641,7 +641,7 @@ class _SinusoidalPositionEmbedding2D(nn.Module):
         """
         not_mask = torch.ones_like(x[0, :1])  # (1, H, W)
         # Note: These are like range(1, H+1) and range(1, W+1) respectively, but in most implementations
-        # they would be range(0, H) and range(0, W). Keeping it at as to match the original code.
+        # they would be range(0, H) and range(0, W). Keeping it at as is to match the original code.
         y_range = not_mask.cumsum(1, dtype=torch.float32)
         x_range = not_mask.cumsum(2, dtype=torch.float32)
 
@@ -659,7 +659,7 @@ class _SinusoidalPositionEmbedding2D(nn.Module):
         y_range = y_range.unsqueeze(-1) / inverse_frequency  # (1, H, W, 1)
 
         # Note: this stack then flatten operation results in interleaved sine and cosine terms.
-        # pos_embed_x and pos_embed are (1, H, W, C // 2).
+        # pos_embed_x and pos_embed_y are (1, H, W, C // 2).
         pos_embed_x = torch.stack((x_range[..., 0::2].sin(), x_range[..., 1::2].cos()), dim=-1).flatten(3)
         pos_embed_y = torch.stack((y_range[..., 0::2].sin(), y_range[..., 1::2].cos()), dim=-1).flatten(3)
         pos_embed = torch.cat((pos_embed_y, pos_embed_x), dim=3).permute(0, 3, 1, 2)  # (1, C, H, W)