Initial commit

README.md

@@ -92,12 +92,12 @@ model-index:
       value: 80.742
 ---
 
-v0.1 - full evaluation not complete
-# {MODEL_NAME}
+full evaluation not complete
+
+# Fin-MPNET-Base (v0.1)
 
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
-<!--- Describe your model here -->
 
 ## Usage (Sentence-Transformers)
 
@@ -113,7 +113,7 @@ 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('mukaj/fin-mpnet-base')
 embeddings = model.encode(sentences)
 print(embeddings)
 ```
@@ -130,4 +130,4 @@ The model will have likely suffered some performance on other benchmarks, i.e. B
 
 ## Training
 
-"sentence-transformers/all-mpnet-base-v2" was fine-tuned on 150k financial document QA examples using MNR Loss.
+"sentence-transformers/all-mpnet-base-v2" was fine-tuned on 150k+ financial document QA examples using MNR Loss.