Update README.md

README.md

@@ -158,9 +158,6 @@ model-index:
   - task:
       type: semantic-similarity
       name: Semantic Similarity
-    dataset:
-      name: Unknown
-      type: unknown
     metrics:
     - type: pearson_cosine
       value: 0.9021917485421888
@@ -177,7 +174,7 @@ datasets:
 
 # SentenceTransformer based on sentence-transformers/paraphrase-multilingual-mpnet-base-v2
 
-This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity and stylistic textual similarity (main task). Using an SBERT model for stylistic textual similarity is an experimental usecase but it works really well and I recommend it.
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for paraphrase similarity (main task) and semantic textual similarity. Using an SBERT model for stylistic textual similarity is an experimental use case but it works really well and I recommend it.
 
 ## Model Details