Update README.md

README.md

@@ -1,3 +1,29 @@
+---
+license: apache-2.0 # Or your model's specific license, e.g., mit, gpl-3.0, custom
+tags:
+  - text-embedding
+  - qwen
+  - lora
+  - fine-tuning
+  - representation-learning
+language: en # Example, adjust if your model is for other languages
+model-index:
+  - name: qwen3-embedding-0.6b-lora-fine-tuned
+    results:
+      - task:
+          type: text-embedding
+          name: Text Embedding
+        dataset:
+          name: "Semantic Similar Dataset"
+          type: "Semantic"
+        metrics:
+          - type: average_precision # Use a standard metric identifier if possible
+            value: 0.85 # Your model's score for this metric
+            name: Average Precision @ K
+          - type: recall
+            value: 0.92
+            name: Recall @ K
+---
 # Model Card: Qwen3-Embedding-0.6B Fine-tuned with LoRA
 
 ## Model Details
@@ -10,11 +36,15 @@
 * **Contact:** [Your Email/Contact Information Here]
 * **Date:** July 13, 2025
 
+---
+
 ## Model Description
 
-This model is a fine-tuned version of the Qwen3-Embedding-0.6B model, adapted using the LoRA method. The goal of this fine-tuning was to enhance its performance on specific downstream tasks (e.g., semantic search, clustering, recommendation systems) by aligning its embeddings more closely with the characteristics of a particular dataset.
+This model is a fine-tuned version of the **Qwen3-Embedding-0.6B** model, adapted using the **LoRA** method. The goal of this fine-tuning was to enhance its performance on specific downstream tasks (e.g., semantic search, clustering, recommendation systems) by aligning its embeddings more closely with the characteristics of a particular dataset.
+
+**Qwen3-Embedding-0.6B** is an efficient and performant embedding model from the Qwen series, designed to convert text into high-dimensional numerical vectors (embeddings) that capture semantic meaning. **LoRA** fine-tuning allows for efficient adaptation of large pre-trained models with minimal computational cost and storage requirements, making it ideal for targeted performance improvements without full model retraining.
 
-Qwen3-Embedding-0.6B is an efficient and performant embedding model from the Qwen series, designed to convert text into high-dimensional numerical vectors (embeddings) that capture semantic meaning. LoRA fine-tuning allows for efficient adaptation of large pre-trained models with minimal computational cost and storage requirements, making it ideal for targeted performance improvements without full model retraining.
+---
 
 ## Intended Use
 
@@ -26,6 +56,8 @@ This model is intended for:
 * Information retrieval and recommendation systems.
 * As a component in larger NLP pipelines where robust text representations are required.
 
+---
+
 ## Limitations and Biases
 
 * **Domain Specificity:** While fine-tuned, the model's performance may degrade on data significantly different from its training distribution.
@@ -33,6 +65,8 @@ This model is intended for:
 * **Computational Resources:** While LoRA reduces resource demands for fine-tuning, inference still requires appropriate computational resources.
 * **Language:** Primarily designed for [Specify Language(s) if known, e.g., English] text. Performance on other languages may vary.
 
+---
+
 ## Training Details
 
 * **Fine-tuning Method:** LoRA (Low-Rank Adaptation)
@@ -47,6 +81,8 @@ This model is intended for:
 * **Optimization Strategy:** [e.g., AdamW, learning rate schedule]
 * **Software Frameworks:** [e.g., PyTorch, Hugging Face Transformers, PEFT library]
 
+---
+
 ## Performance Metrics
 
 *(Note: Provide actual metrics from your evaluation. Examples below are placeholders.)*
@@ -57,6 +93,8 @@ This model is intended for:
 * **Metric 3 (e.g., Cosine Similarity Distribution):** [Description or relevant statistics]
 * **Comparison to Base Model (if available):** [e.g., "This fine-tuned model showed a 15% improvement in Average Precision @ 10 compared to the base Qwen3-Embedding-0.6B model on our internal benchmark."]
 
+---
+
 ## Usage
 
 You can load and use this model with the Hugging Face `transformers` and `peft` libraries.
@@ -109,17 +147,3 @@ If you use this fine-tuned model in your research or application, please conside
   year={2025},
   note={Available at [Link to your model if uploaded]}
 }
-
----
-
-## License
-
-This fine-tuned model inherits the license of the original **Qwen/Qwen3-Embedding-0.6B** model. Please refer to the [original model's license]([Link to original model's license, e.g., Hugging Face model page]) for details.
-
----
-
-## Acknowledgements
-
-* The developers of **Qwen/Qwen3-Embedding-0.6B** for providing the base model.
-* The developers of the **PEFT** library for enabling efficient LoRA fine-tuning.
-* [Any other relevant acknowledgements, e.g., dataset creators, funding bodies]