Update README.md

README.md

@@ -1,22 +1,22 @@
 ---
 language:
-- vi
+  - vi
 license: apache-2.0
 library_name: transformers
 tags:
-- transformers
-- cross-encoder
-- rerank
+  - transformers
+  - cross-encoder
+  - rerank
 datasets:
-- unicamp-dl/mmarco
+  - unicamp-dl/mmarco
 pipeline_tag: text-classification
 widget:
-- text: tỉnh nào có diện tích lớn nhất việt nam
-  output:
-  - label: nghệ an có diện tích lớn nhất việt nam
-    score: 0.99999
-  - label: bắc ninh có diện tích nhỏ nhất việt nam
-    score: 0.0001
+  - text: tỉnh nào có diện tích lớn nhất việt nam
+    output:
+      - label: nghệ an có diện tích lớn nhất việt nam
+        score: 0.99999
+      - label: bắc ninh có diện tích nhỏ nhất việt nam
+        score: 0.0001
 ---
 
 # Reranker
@@ -27,6 +27,8 @@ widget:
 * [Fine tune](#fine-tune)
     * [Data format](#data-format)
 * [Performance](#performance)
+* [Contact](#contact)
+* [Support The Project](#support-the-project)
 * [Citation](#citation)
 
 Different from embedding model, reranker uses question and document as input and directly output similarity instead of
@@ -116,7 +118,8 @@ Train data should be a json file, where each line is a dict like this:
 `query` is the query, and `pos` is a list of positive texts, `neg` is a list of negative texts. If you have no negative
 texts for a query, you can random sample some from the entire corpus as the negatives.
 
-Besides, for each query in the train data, we used LLMs to generate hard negative for them by asking LLMs to create a document that is the opposite one of the documents in 'pos'.
+Besides, for each query in the train data, we used LLMs to generate hard negative for them by asking LLMs to create a
+document that is the opposite one of the documents in 'pos'.
 
 ## Performance
 
@@ -131,6 +134,28 @@ the [MS MMarco Passage Reranking - Vi - Dev](https://huggingface.co/datasets/uni
 | [BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3)                                                               | 0.6087     | 0.5841     | 0.6513     | 0.6062     | 0.6872     | 0.62091    | 3.51       
 | [BAAI/bge-reranker-v2-gemma](https://huggingface.co/BAAI/bge-reranker-v2-gemma)                                                         | 0.6088     | 0.5908     | 0.6446     | 0.6108     | 0.6785     | 0.6249     | 1.29       
 
+## Contact
+
+Email: [email protected]
+
+LinkedIn: [Dang Phuong Nam](https://www.linkedin.com/in/dang-phuong-nam-157912288/)
+
+Facebook: [Phương Nam](https://www.facebook.com/phuong.namdang.7146557)
+
+## Support The Project
+
+If you find this project helpful and wish to support its ongoing development, here are some ways you can contribute:
+
+1. **Star the Repository**: Show your appreciation by starring the repository. Your support motivates further
+   development
+   and enhancements.
+2. **Contribute**: We welcome your contributions! You can help by reporting bugs, submitting pull requests, or
+   suggesting new features.
+3. **Donate**: If you’d like to support financially, consider making a donation. You can donate through:
+    - Vietcombank: 9912692172 - DANG PHUONG NAM
+
+Thank you for your support!
+
 ## Citation
 
 Please cite as