Update README.md

README.md

@@ -26,21 +26,23 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-The aim of this model is to provide gender-neutral terms for job titles in Polish in single sentences. The optimal outcome looks like this:
-  Jestem pracownikiem tej firmy.
-  turns into
-  Jestem osobą pracowniczą tej firmy.
-Sentences not containing such terms are not expected to change at all, for example:
-Mam uroczego kotka.
-  turns into
-Mam uroczego kotka.
+The aim of this model is to provide gender-neutral terms for job titles in Polish in single sentences. The optimal outcome looks like this:<br>
+  *Jestem pracownikiem tej firmy.*<br>
+  turns into<br>
+  *Jestem osobą pracowniczą tej firmy.*<br>
+Sentences not containing such terms are not expected to change at all, for example:<br>
+  *Mam uroczego kotka.*<br>
+  turns into<br>
+  *Mam uroczego kotka.*<br>
+
+In terms of actual outcomes and errors in outputs, see our [readme](https://github.com/ArielUW/IMLLA-FinalProject/blob/main/README.md).
 
 ## Intended uses & limitations
 The model has only been fine-tuned for single-sentence inputs, so other types of inputs can be unstable. So far, it underperforms for low-frequency items, morphosyntactically complex cases and feminine nouns. 
 
 ## Training and evaluation data
 
-The model's performance has been evaluated in terms of neutralization attempt precision and recall, as well as Levenshtein distance from gold-standard items. More information on the evaluation outcomes can be found [here](https://github.com/ArielUW/IMLLA-FinalProject/blob/main/README.md).
+The model's performance has been evaluated in terms of neutralization attempt precision and recall, as well as Levenshtein distance from gold-standard items. More information on the evaluation outcomes can be found in [our readme](https://github.com/ArielUW/IMLLA-FinalProject/blob/main/README.md).
 
 ## Training procedure