Update README.md

README.md

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 ## Introduction
 
-**STAR-0b6** is a highly capable 0.6B parameter language model specialized in function calling, achieving **State-of-the-Art (SOTA)** performance on the [Berkeley Function Calling Leaderboard (BFCL)](https://huggingface.co/spaces/gorilla-llm/berkeley-function-calling-leaderboard) for models in its size class.
+**STAR-0b6** is a highly capable 0.6B parameter language model specialized in function calling, achieving excellent performances on the [Berkeley Function Calling Leaderboard (BFCL)](https://huggingface.co/spaces/gorilla-llm/berkeley-function-calling-leaderboard) for models in its size class.
 
 This model is the result of fine-tuning the `Qwen/Qwen3-0.6B` base model using the novel **STAR (Similarity-guided Teacher-Assisted Refinement)** framework. STAR is a holistic training curriculum designed to effectively transfer the advanced capabilities of large language models (LLMs) into "super-tiny" models, making them powerful, accessible, and efficient for real-world agentic applications.
 
@@ -100,7 +100,7 @@ For local use, applications such as Ollama, LMStudio, MLX-LM, llama.cpp, and KTr
 
 ## Evaluation & Performance
 
-STAR-0b6 has established a new state-of-the-art for models of its size on renowned function calling benchmarks.
+STAR-0b6 has achieved outstanding performance for models of its size on renowned function calling benchmarks.
 
 - BFCLv3: Achieved 51.70% overall accuracy, outperforming all baseline and recent methods.
 - ACEBench: Achieved 53.00% summary score, demonstrating superior generalization and robustness. This score is significantly higher than its base model (27.20%) and even surpasses much larger models like Llama3.1-8B (46.60%).