diff --git a/ch05/01_main-chapter-code/exercise-solutions.ipynb b/ch05/01_main-chapter-code/exercise-solutions.ipynb
index 99a8626..1b03893 100644
--- a/ch05/01_main-chapter-code/exercise-solutions.ipynb
+++ b/ch05/01_main-chapter-code/exercise-solutions.ipynb
@@ -193,12 +193,31 @@
     "There is a 4.3% probability that the word \"pizza\" is sampled if the temperature is set to 5."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "b510ffb0-adca-4d64-8a12-38c4646fd736",
+   "metadata": {},
+   "source": [
+    "# Exercise 5.2: Different temperature and top-k settings"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "884990db-d1a6-4c4e-8e36-2c1e4c1e67c7",
+   "metadata": {},
+   "source": [
+    "- Both temperature and top-k settings have to be adjusted based on the individual LLM (a kind of trial and error process until it generates desirable outputs)\n",
+    "- The desirable outcomes are also application-specific, though\n",
+    "  - Lower top-k and temperatures result in less random outcomes, which is desired when creating educational content, technical writing or question answering, data analyses, code generation, and so forth\n",
+    "  - Higher top-k and temperatures result in more diverse and random outputs, which is more desirable for brainstorming tasks, creative writing, and so forth"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "3f35425d-529d-4179-a1c4-63cb8b25b156",
    "metadata": {},
    "source": [
-    "# Exercise 5.2: Deterministic behavior in the decoding functions"
+    "# Exercise 5.3: Deterministic behavior in the decoding functions"
    ]
   },
   {
@@ -357,7 +376,7 @@
    "id": "6d0480e5-fb4e-41f8-a161-7ac980d71d47",
    "metadata": {},
    "source": [
-    "# Exercise 5.3: Continued pretraining"
+    "# Exercise 5.4: Continued pretraining"
    ]
   },
   {
@@ -507,7 +526,7 @@
    "id": "3384e788-f5a1-407c-8dd1-87959b75026d",
    "metadata": {},
    "source": [
-    "# Exercise 5.4: Training and validation set losses of the pretrained model"
+    "# Exercise 5.5: Training and validation set losses of the pretrained model"
    ]
   },
   {
@@ -774,7 +793,7 @@
    "id": "3a76a1e0-9635-480a-9391-3bda7aea402d",
    "metadata": {},
    "source": [
-    "# Exercise 5.5: Trying larger models"
+    "# Exercise 5.6: Trying larger models"
    ]
   },
   {