Update README.md

Added disclaimer and removed MTEB comparison. Please refer to the official MTEB page for all results.

README.md

@@ -13,9 +13,10 @@ tags:
 We trained the **PwC-Embedding-expr** model on top of the [multilingual-e5-large-instruct](https://huggingface.co/intfloat/multilingual-e5-large-instruct) embedding model.  
 To enhance performance in Korean, we applied our curated augmentation to STS datasets and fine-tuned the E5 model using a carefully balanced ratio across datasets.
 
+> ⚠️ This is an experimental model and is under continuous development.
 
 ### To-do
-- [ ] MTEB Leaderboard  
+- [x] MTEB Leaderboard  
 - [ ] Technical Report
 
 
@@ -23,15 +24,15 @@ To enhance performance in Korean, we applied our curated augmentation to STS dat
 PwC-Embedding_expr was evaluated on the Korean subset of MTEB.  
 A leaderboard link will be added once it is published.
 
-| Task             | PwC-Embedding_expr | multilingual-e5-large | Max Result |
-|------------------|--------------------|-----------------------|------------|
-| KLUE-STS         | 0.88               | 0.83                  | 0.90       |
-| KLUE-TC          | 0.73               | 0.61                  | 0.73       |
-| Ko-StrategyQA    | 0.80               | 0.80                  | 0.83       |
-| KorSTS           | 0.84               | 0.81                  | 0.98       |
-| MIRACL-Reranking | 0.72               | 0.65                  | 0.72       |
-| MIRACL-Retrieval | 0.65               | 0.59                  | 0.72       |
-| **Average**      | **0.77**           | 0.71                  | 0.81       |
+| Task             | PwC-Embedding_expr |
+|------------------|--------------------|
+| KLUE-STS         | 0.88               | 
+| KLUE-TC          | 0.73               |
+| Ko-StrategyQA    | 0.80               | 
+| KorSTS           | 0.84               | 
+| MIRACL-Reranking | 0.72               | 
+| MIRACL-Retrieval | 0.65               |
+| **Average**      | **0.77**           |
 
 
 ## Model