Update README.md

README.md

@@ -166,8 +166,6 @@ Making use of an unsupervised training approach, Swissbert for Sentence Embeddin
 | Text Classification FR | 94.55    | 88.52   | 95.30          |**89.91**|
 | Text Classification IT | 93.48    | 88.29   | 94.85          |**90.36**|
 
-#### Baselines
+#### Baseline
 
-The first baseline uses mean pooling embeddings from the last hidden state of the original swissbert model.
-
-The second baseline is [distiluse-base-multilingual-cased](https://www.sbert.net/examples/training/multilingual/README.html), a high-performing Sentence Transformer model that is able to process German, French and Italian (and more).
+The baseline uses mean pooling embeddings from the last hidden state of the original swissbert model.