Update README.md

README.md

@@ -30,17 +30,15 @@ tags:
 ---
 
 
-# **CodeModernBERT-Owl🦉**
+# **CodeModernBERT-Owl**
 
 ## **概要 / Overview**
 
-### **CodeModernBERT-Owl🦉: 高精度なコード検索 & コード理解モデル**  
+### **🦉 CodeModernBERT-Owl: 高精度なコード検索 & コード理解モデル**  
 **CodeModernBERT-Owl** is a **pretrained model** designed from scratch for **code search and code understanding tasks**.  
 
 Compared to previous versions such as **CodeHawks-ModernBERT** and **CodeMorph-ModernBERT**, this model **now supports Rust** and **improves search accuracy** in Python, PHP, Java, JavaScript, Go, and Ruby.  
 
----
-
 ### **🛠 主な特徴 / Key Features**
 ✅ **Supports long sequences up to 2048 tokens** (compared to Microsoft's 512-token models)  
 ✅ **Optimized for code search, code understanding, and code clone detection**  
@@ -71,20 +69,20 @@ Compared to previous versions such as **CodeHawks-ModernBERT** and **CodeMorph-M
 ## **💻 モデルの使用方法 / How to Use**
 This model can be easily loaded using the **Hugging Face Transformers** library.  
 
-⚠️ **Requires `transformers >= 4.48.0`**  
+⚠️ **Requires transformers >= 4.48.0**  
 
 🔗 **[Colab Demo (Replace with "CodeModernBERT-Owl")](https://github.com/Shun0212/CodeBERTPretrained/blob/main/UseMyCodeMorph_ModernBERT.ipynb)**
 
 ### **モデルのロード / Load the Model**
-```python
+python
 from transformers import AutoModelForMaskedLM, AutoTokenizer
 
 tokenizer = AutoTokenizer.from_pretrained("Shuu12121/CodeModernBERT-Owl")
 model = AutoModelForMaskedLM.from_pretrained("Shuu12121/CodeModernBERT-Owl")
-```
+
 
 ### **コード埋め込みの取得 / Get Code Embeddings**
-```python
+python
 import torch
 
 def get_embedding(text, model, tokenizer, device="cuda"):
@@ -98,15 +96,15 @@ def get_embedding(text, model, tokenizer, device="cuda"):
 
 embedding = get_embedding("def my_function(): pass", model, tokenizer)
 print(embedding.shape)
-```
+
 
 ---
 
 # **🔍 評価結果 / Evaluation Results**
 
 ### **データセット / Dataset**
-📌 **Tested on `code_x_glue_ct_code_to_text` with a candidate pool size of 100.**  
-📌 **Rust-specific evaluations were conducted using `Shuu12121/rust-codesearch-dataset-open`.**  
+📌 **Tested on code_x_glue_ct_code_to_text with a candidate pool size of 100.**  
+📌 **Rust-specific evaluations were conducted using Shuu12121/rust-codesearch-dataset-open.**  
 
 ---
 
@@ -120,6 +118,28 @@ print(embedding.shape)
 | **Ruby**       | **0.8038**  | 0.7469  | **0.7568**  | 0.3318  | 0.5876  |
 | **Go**         | **0.9386**  | 0.9043  | 0.8117  | 0.3262  | 0.4243  |
 
+✅ **Achieves the highest accuracy in all target languages.**  
+✅ **Significantly improved Java accuracy using additional fine-tuned GitHub data.**  
+✅ **Outperforms previous models, especially in PHP and Go.**  
+
+---
+
+## **📊 Rust (独自データセット) / Rust Performance**
+| 指標 / Metric | **CodeModernBERT-Owl** |
+|--------------|----------------|
+| **MRR**      | 0.7940 | 
+| **MAP**      | 0.7940 |
+| **R-Precision** | 0.7173 |
+
+### **📌 K別評価指標 / Evaluation Metrics by K**
+| K  | **Recall@K** | **Precision@K** | **NDCG@K** | **F1@K** | **Success Rate@K** | **Query Coverage@K** |
+|----|-------------|---------------|------------|--------|-----------------|-----------------|
+| **1**   | 0.7173  | 0.7173  | 0.7173  | 0.7173  | 0.7173  | 0.7173  |
+| **5**   | 0.8913  | 0.7852  | 0.8118  | 0.8132  | 0.8913  | 0.8913  |
+| **10**  | 0.9333  | 0.7908  | 0.8254  | 0.8230  | 0.9333  | 0.9333  |
+| **50**  | 0.9887  | 0.7938  | 0.8383  | 0.8288  | 0.9887  | 0.9887  |
+| **100** | 1.0000  | 0.7940  | 0.8401  | 0.8291  | 1.0000  | 1.0000  |
+
 ---
 
 ## **🔁 別のおすすめモデル / Recommended Alternative Models**
@@ -138,15 +158,13 @@ If you need a pretrained model that supports **longer sequences or a smaller mod
 For those looking for a model that combines **long sequence length and code search specialization**, this model is the best choice.  
 **コードサーチに特化しつつ長いシーケンスを処理できるモデル**が欲しい場合にはこちらがおすすめです。  
 - **Maximum Sequence Length:** 8192 tokens  
-- **High Code Search Performance**  
+- **High Code Search Performance**
 
----
 
 ## **📝 結論 / Conclusion**
 ✅ **Top performance in all languages**  
 ✅ **Rust support successfully added through dataset augmentation**  
 ✅ **Further performance improvements possible with better datasets**  
-✅ **Recommended for various code search and understanding tasks**  
 
 ---
 
@@ -155,6 +173,4 @@ For those looking for a model that combines **long sequence length and code sear
 
 ## **📧 連絡先 / Contact**
 📩 **For any questions, please contact:**  
-📧 **shun0212114@outlook.jp**  
-
----
+📧 **shun0212114@outlook.jp**