Create README.md

README.md

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+# Model: LLaMA (IFD Top 30%)
+
+## 🔍 Purpose
+
+Fine-tune `meta-llama/Llama-3.2-1B` on instruction samples with the **highest Instruction Flow Density (IFD)**.  
+This group includes samples where the instruction contributes **least** to the model’s output (i.e., high IFD).
+
+## 📂 Dataset
+
+- `alpaca2000.csv`
+  - IFD score 상위 30% (2000개 중 600개)
+  - 기준: `PPL(y | x) / PPL(y)` (x: instruction+input, y: output)
+
+## ⚙️ Training Config
+
+- Model: `meta-llama/Llama-3.2-1B`
+- Precision: `bf16` or `float32`
+- Epochs: 3
+- Max length: 2048
+- Output: `output/llama_ifd`
+
+## 🧪 Goal
+
+Establish baseline performance of high-IFD samples, before splitting by instruction entropy.