diff --git a/docs/tutorials/fit_simple_neural_radiance_field.ipynb b/docs/tutorials/fit_simple_neural_radiance_field.ipynb
index 6490c5270..94e52ab50 100644
--- a/docs/tutorials/fit_simple_neural_radiance_field.ipynb
+++ b/docs/tutorials/fit_simple_neural_radiance_field.ipynb
@@ -815,7 +815,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 5. Visualizing the optimized neural radiance field\n",
+    "## 6. Visualizing the optimized neural radiance field\n",
     "\n",
     "Finally, we visualize the neural radiance field by rendering from multiple viewpoints that rotate around the volume's y-axis."
    ]
@@ -865,7 +865,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 6. Conclusion\n",
+    "## 7. Conclusion\n",
     "\n",
     "In this tutorial, we have shown how to optimize an implicit representation of a scene such that the renders of the scene from known viewpoints match the observed images for each viewpoint. The rendering was carried out using the PyTorch3D's implicit function renderer composed of either a `MonteCarloRaysampler` or `NDCMultinomialRaysampler`, and an `EmissionAbsorptionRaymarcher`."
    ]