Updates README.md

README.md

@@ -9,7 +9,7 @@ tags:
 license: mit
 ---
 
-# {MODEL_NAME}
+# bge-large-en-v1.5-ISO-27001
 
 This is a fine-tuned embedding model of [bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5). It was fine-tuned on a dataset based on an ISO 27001 text corpus consisting of text chunks (1024 characters) and associated questions. A total of 2.000 chunk and question pairs were generated. The fine-tuning process is specialized on an Information Retrieval task in which the generated questions are used to find the relevant chunks. The effectiveness of the model is evaluated on whether the correct chunk was retrieved, and the loss is calculated with the multiple negative ranking loss.
 
@@ -27,7 +27,7 @@ Then you can use the model like this:
 from sentence_transformers import SentenceTransformer
 sentences = ["This is an example sentence", "Each sentence is converted"]
 
-model = SentenceTransformer('{MODEL_NAME}')
+model = SentenceTransformer('bge-large-en-v1.5-ISO-27001')
 embeddings = model.encode(sentences)
 print(embeddings)
 ```