Update README.md

README.md

@@ -37,9 +37,9 @@ A QLoRA (Quantized Low-Rank Adaptation) approach was used for efficient fine-tun
 ### Training Data
 The training process involved two main stages:
 
-1.  **Domain Pre-training:** The base model was adapted to the *Wings of Fire* universe using a custom dataset of **3 million tokens** compiled directly from the book series. This step saturated the model with the specific lore, characters, and writing style of the source material.
+1.  **Domain training:** The base model was adapted to the *Wings of Fire* universe using a custom dataset of **3 million tokens** compiled directly from the book series. This step saturated the model with the specific lore, characters, and writing style of the source material.
 
-2.  **Instruction & Chat Fine-tuning:** The model was then fine-tuned on a mixed dataset of **2,200 examples**:
+2.  **Instruction & Chat Fine-tuning:** The model was fine-tuned on a mixed dataset of **2,200 examples**:
     * **1,400 Roleplay Conversations:** Multi-turn conversational examples designed to teach the model how to adopt and maintain character personas from the series.
     * **800 Assistant Examples:** Instruction-response pairs focused on answering lore questions and following commands within the context of the *Wings of Fire* world.