Fix typos in Fine-Tuning RAG Qdrant (#806)

examples/fine-tuned_qa/ft_retrieval_augmented_generation_qdrant.ipynb

@@ -678,7 +678,7 @@
     "\n",
     "When we know that a correct answer exists in the context, we can measure the model's performance, there are 3 possible outcomes:\n",
     "\n",
-    "1. ✅ **Answered Correctly**: The model responsded the correct answer. It may have also included other answers that were not in the context.\n",
+    "1. ✅ **Answered Correctly**: The model responded the correct answer. It may have also included other answers that were not in the context.\n",
     "2. ❎ **Skipped**: The model responded with \"I don't know\" (IDK) while the answer was present in the context. It's better than giving the wrong answer. It's better for the model say \"I don't know\" than giving the wrong answer. In our design, we know that a true answer exists and hence we're able to measure it -- this is not always the case. *This is a model error*. We exclude this from the overall error rate. \n",
     "3. ❌ **Wrong**: The model responded with an incorrect answer. **This is a model ERROR.**\n",
     "\n",
@@ -839,7 +839,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Notice that the fine-tuned model skips questions more often -- and makes fewer misakes. This is because the fine-tuned model is more conservative and skips questions when it's not sure."
+    "Notice that the fine-tuned model skips questions more often -- and makes fewer mistakes. This is because the fine-tuned model is more conservative and skips questions when it's not sure."
    ]
   },
   {
@@ -896,7 +896,7 @@
     "    6.1 Embed the Fine-Tuning Data\n",
     "    6.2 Embedding the Questions\n",
     "7. Using Qdrant to Improve RAG Prompt\n",
-    "8. \n",
+    "8. Evaluation\n",
     "\n",
     "\n",
     "## 6. Fine-Tuning OpenAI Model with Qdrant\n",