Update README.md
Browse files
README.md
CHANGED
@@ -39,7 +39,28 @@ datasets:
|
|
39 |
|
40 |
This model is a SentenceTransformer fine-tuned from [`Shuu12121/CodeModernBERT-Owl🦉`](https://huggingface.co/Shuu12121/CodeModernBERT-Owl) on the [BigCloneBench](https://huggingface.co/datasets/google/code_x_glue_cc_clone_detection_big_clone_bench) dataset for **code clone detection**. It maps code snippets into a 768-dimensional dense vector space for semantic similarity tasks.
|
41 |
|
42 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
43 |
|
44 |
## 📌 Model Overview
|
45 |
|
|
|
39 |
|
40 |
This model is a SentenceTransformer fine-tuned from [`Shuu12121/CodeModernBERT-Owl🦉`](https://huggingface.co/Shuu12121/CodeModernBERT-Owl) on the [BigCloneBench](https://huggingface.co/datasets/google/code_x_glue_cc_clone_detection_big_clone_bench) dataset for **code clone detection**. It maps code snippets into a 768-dimensional dense vector space for semantic similarity tasks.
|
41 |
|
42 |
+
|
43 |
+
|
44 |
+
## 🎯 Distinctive Performance and Stability
|
45 |
+
|
46 |
+
This model achieves **very high accuracy and F1 scores** in code clone detection.
|
47 |
+
One particularly noteworthy characteristic is that **changing the similarity threshold has minimal impact on classification performance**.
|
48 |
+
This indicates that the model has learned to **clearly separate clones from non-clones**, resulting in a **stable and reliable similarity score distribution**.
|
49 |
+
|
50 |
+
| Threshold | Accuracy | F1 Score |
|
51 |
+
|-------------------|-------------------|--------------------|
|
52 |
+
| 0.5 | 0.9900 | 0.9633 |
|
53 |
+
| 0.85 | 0.9903 | 0.9641 |
|
54 |
+
| 0.90 | 0.9902 | 0.9637 |
|
55 |
+
| 0.95 | 0.9887 | 0.9579 |
|
56 |
+
| 0.98 | 0.9879 | 0.9540 |
|
57 |
+
|
58 |
+
- **High Stability**: Between thresholds of 0.85 and 0.98, accuracy and F1 scores remain nearly constant.
|
59 |
+
_(This suggests that code pairs considered clones generally score between 0.9 and 1.0 in cosine similarity.)_
|
60 |
+
|
61 |
+
- **Reliable in Real-World Applications**: Even if the similarity threshold is slightly adjusted for different tasks or environments, the model maintains consistent performance without significant degradation.
|
62 |
+
|
63 |
+
|
64 |
|
65 |
## 📌 Model Overview
|
66 |
|