Update README.md

README.md

@@ -81,14 +81,14 @@ from sklearn.metrics.pairwise import cosine_similarity
 sentence_1 = ["Der Zug kommt um 9 Uhr in Zürich an."]
 sentence_2 = ["Le train arrive à Lausanne à 9h."]
 
-#Compute embedding for both
+# Compute embedding for both
 embedding_1 = generate_sentence_embedding(sentence_1, language="de")
 embedding_2 = generate_sentence_embedding(sentence_2, language="fr")
 
-#Compute cosine-similarity
+# Compute cosine-similarity
 cosine_score = cosine_similarity(embedding_1, embedding_2)
 
-#Output the score
+# Output the score
 print("The cosine score for", sentence_1, "and", sentence_2, "is", cosine_score)
 ```
 Output:
@@ -119,9 +119,9 @@ The fine-tuning script can be accessed [here](Link).
 
 #### Training Hyperparameters
 
-Number of epochs: 1
-Learning rate: 1e-5
-Batch size: 512
+- Number of epochs: 1
+- Learning rate: 1e-5
+- Batch size: 512
 
 ## Evaluation