Update README.md

README.md

@@ -22,17 +22,20 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This model is fine-tuned from the pre-trained sentence-transformers/all-MiniLM-L6-v2 on the Semantic Textual Similarity Benchmark (STS-B) dataset. It is designed to compute similarity scores between pairs of sentences, returning a continuous score between 0 and 1, where 1 represents maximum semantic similarity.
 
-## Intended uses & limitations
+The model generates embeddings for input sentences and can be used for tasks such as text similarity, sentence clustering, or semantic search.
 
-More information needed
 
 ## Training and evaluation data
 
-More information needed
+The model was trained on the STS-B dataset using the following splits:
+
+Train set: 5,749 examples
+Validation set: 1,500 examples
+Test set: 1,379 examples
+Each example consists of two sentences and a similarity score (from 0 to 1) indicating their semantic closeness.
 
-## Training procedure
 
 ### Training hyperparameters