Update README.md

README.md

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 Welcome to **RoBERTArg**!
 
-🤖 **Model description**: 
+🤖 **Model description**
+
 This model was trained on ~40k heterogeneous manually annotated sentences (📚 Stab et al. 2018) of controversial topics (abortion etc.) to classify text into one of two labels: 🏷 **NON-ARGUMENT** (0) and **ARGUMENT** (1).
 
 **Dataset**
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 ```
 
 **Evaluation**
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 The model was evaluated using 20% of the sentences (80-20 train-test split).
 
 | Model | Acc | F1 | R arg | R non | P arg | P non |
@@ -38,6 +40,7 @@ Showing the **confusion matrix** using the 20% of the sentences as an evaluation
 | NON-ARGUMENT | 325 | 1790 |
 
 **Intended Uses & Potential Limitations**
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 The model can be a practical starting point to the complex topic **Argument Mining**. It is a quite challenging task due to the different conceptions of an argument. 
 
 This model is a part of an open-source project providing several models to detect arguments in text.