Update README.md

README.md

@@ -8,6 +8,17 @@ library_name: sentence-transformers
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 <h2 align="left">Yuan-embedding-2.0-en</h2>
 
+Yuan-embedding-2.0-en is an embedding model specifically designed for English text retrieval tasks. Built on the foundation of [Qwen/Qwen3-Embedding-0.6B](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B), we have further optimized it for both Retrieval and Reranking tasks. The key work is as follows:
+
+- Data Augmentation
+  - Hard negative sampling: Dual evaluation is conducted using a Rerank model and LLM to filter out high-quality positive and negative samples
+  - LLM-synthesized data: The [Yuan2-M32](https://huggingface.co/IEITYuan/Yuan2-M32) is employed to perform LLM-based rewriting on the query data within the training dataset
+- Loss function design
+  - Multi-Task loss
+  - Matryoshka Representation Learning
+  - The Retrieval tasks adopt InfoNCE with in-batch-negative
+  - The Reranking tasks adopt InfoNCE with in-batch-negative
+
 Yuan-embedding-2.0-en 是专门为英文文本检索任务设计的嵌入模型。我们在[Qwen/Qwen3-Embedding-0.6B](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B)的基础上，针对Retrieval任务与Reranking任务进行了进一步优化。主要工作如下：
 
 - 数据增强
@@ -18,7 +29,7 @@ Yuan-embedding-2.0-en 是专门为英文文本检索任务设计的嵌入模型
   - Matryoshka Representation Learning
   - Retrieval任务使用InfoNCE with in-batch-negative
   - 针对Reranking任务使用InfoNCE with in-batch-negative
-  
+
 
 <h2 align="left">Usage</h2>