diff --git a/ch02/01_main-chapter-code/ch02.ipynb b/ch02/01_main-chapter-code/ch02.ipynb
index 90d25c3..8cb54d7 100644
--- a/ch02/01_main-chapter-code/ch02.ipynb
+++ b/ch02/01_main-chapter-code/ch02.ipynb
@@ -43,14 +43,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Total number of character: 20479\n",
       "I HAD always thought Jack Gisburn rather a cheap genius--though a good fellow enough--so it was no \n"
      ]
     }
    ],
    "source": [
-    "with open('the-verdict.txt', 'r', encoding='utf-8') as f:\n",
+    "with open(\"the-verdict.txt\", \"r\", encoding=\"utf-8\") as f:\n",
     "    raw_text = f.read()\n",
     "    \n",
+    "print(\"Total number of character:\", len(raw_text))\n",
     "print(raw_text[:99])"
    ]
   },
@@ -61,7 +63,7 @@
    "source": [
     "- The goal is to tokenize and embed this text for an LLM\n",
     "- Let's develop a simple tokenizer based on some simple sample text that we can then later apply to the text above\n",
-    "- The following regular expressiin will split on a comma"
+    "- The following regular expression will split on whitespaces"
    ]
   },
   {
@@ -74,15 +76,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['Hello', ',', ' world', ',', ' this', ',', ' is', ',', ' a test.']\n"
+      "['Hello,', ' ', 'world.', ' ', 'This,', ' ', 'is', ' ', 'a', ' ', 'test.']\n"
      ]
     }
    ],
    "source": [
     "import re\n",
     "\n",
-    "text = \"Hello, world, this, is, a test.\"\n",
-    "result = re.split(r'(,)', text)\n",
+    "text = \"Hello, world. This, is a test.\"\n",
+    "result = re.split(r'(\\s)', text)\n",
     "\n",
     "print(result)"
    ]
@@ -92,7 +94,7 @@
    "id": "a8c40c18-a9d5-4703-bf71-8261dbcc5ee3",
    "metadata": {},
    "source": [
-    "- We don't only want to split on commas but also whitespaces, so let's modify the regular expression to do that as well"
+    "- We don't only want to split on whitespaces but also commas and periods, so let's modify the regular expression to do that as well"
    ]
   },
   {
@@ -105,14 +107,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['Hello', ',', '', ' ', 'world.', ' ', 'This', ',', '', ' ', 'is', ' ', 'a', ' ', 'test.']\n"
+      "['Hello', ',', '', ' ', 'world', '.', '', ' ', 'This', ',', '', ' ', 'is', ' ', 'a', ' ', 'test', '.', '']\n"
      ]
     }
    ],
    "source": [
-    "text = \"Hello, world. This, is a test.\"\n",
-    "\n",
-    "result = re.split(r'([,]|\\s)', text)\n",
+    "result = re.split(r'([,.]|\\s)', text)\n",
     "\n",
     "print(result)"
    ]
@@ -135,7 +135,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['Hello', ',', 'world.', 'This', ',', 'is', 'a', 'test.']\n"
+      "['Hello', ',', 'world', '.', 'This', ',', 'is', 'a', 'test', '.']\n"
      ]
     }
    ],
@@ -180,7 +180,7 @@
    "id": "5bbea70b-c030-45d9-b09d-4318164c0bb4",
    "metadata": {},
    "source": [
-    "- This is pretty good, and we are now readdy to apply this tokenization to the raw text"
+    "- This is pretty good, and we are now ready to apply this tokenization to the raw text"
    ]
   },
   {
@@ -229,6 +229,14 @@
     "print(len(preprocessed))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "0b5ce8fe-3a07-4f2a-90f1-a0321ce3a231",
+   "metadata": {},
+   "source": [
+    "## 2.3 Converting tokens into token IDs"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "b5973794-7002-4202-8b12-0900cd779720",
@@ -336,15 +344,14 @@
       "('Had', 47)\n",
       "('Hang', 48)\n",
       "('Has', 49)\n",
-      "('He', 50)\n",
-      "('Her', 51)\n"
+      "('He', 50)\n"
      ]
     }
    ],
    "source": [
     "for i, item in enumerate(vocab.items()):\n",
     "    print(item)\n",
-    "    if i > 50:\n",
+    "    if i >= 50:\n",
     "        break"
    ]
   },
@@ -454,7 +461,7 @@
    "id": "4b821ef8-4d53-43b6-a2b2-aef808c343c7",
    "metadata": {},
    "source": [
-    "## 2.3 Adding special context tokens"
+    "## 2.4 Adding special context tokens"
    ]
   },
   {
@@ -678,7 +685,7 @@
    "id": "5c4ba34b-170f-4e71-939b-77aabb776f14",
    "metadata": {},
    "source": [
-    "## 2.4 BytePair encoding"
+    "## 2.5 BytePair encoding"
    ]
   },
   {
@@ -782,7 +789,7 @@
    "id": "abbd7c0d-70f8-4386-a114-907e96c950b0",
    "metadata": {},
    "source": [
-    "## 2.5 Data sampling with a sliding window"
+    "## 2.6 Data sampling with a sliding window"
    ]
   },
   {
@@ -1119,7 +1126,7 @@
    "id": "2cd2fcda-2fda-4aa8-8bc8-de1e496f9db1",
    "metadata": {},
    "source": [
-    "## 2.6 Creating token embeddings"
+    "## 2.7 Creating token embeddings"
    ]
   },
   {
@@ -1304,7 +1311,7 @@
    "id": "c393d270-b950-4bc8-99ea-97d74f2ea0f6",
    "metadata": {},
    "source": [
-    "## 2.7 Encoding word positions"
+    "## 2.8 Encoding word positions"
    ]
   },
   {
@@ -1458,7 +1465,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,