Update README.md

README.md

@@ -3,7 +3,7 @@ library_name: transformers
 tags:
 - detoxification
 - text_style_transfer
-license: mit
+license: openrail++
 datasets:
 - s-nlp/synthdetoxm
 language:
@@ -79,11 +79,11 @@ Specifically, we use the following metrics:
 
 - **Style Transfer Accuracy** (**STA**) is calculated with a [`textdetox/xlmr-large-toxicity-classifier`](https://huggingface.co/textdetox/xlmr-large-toxicity-classifier).
 - **Text Similarity** (**SIM**) is calculated as a similarity of text embeddings given by a [`sentence-transformers/LaBSE`](https://huggingface.co/sentence-transformers/LaBSE) encoder.
-- **Fluency** (**FL**) is calculated as a character n-gram F score - [$\text{ChrF}_1$](https://github.com/m-popovic/chrF).
+- **Fluency** (**FL**) is calculated as a character n-gram F score - [ChrF1](https://github.com/m-popovic/chrF).
 
 These metrics are aggregated in a final **Joint** metric (**J**):
  
-$$\textbf{J} = \frac{1}{n}\sum\limits_{i=1}^{n}\textbf{STA}(y_i) \cdot \textbf{SIM}(x_i,y_i) \cdot \textbf{FL}(x_i, y_i)$$,
+$$\textbf{J} = \frac{1}{n}\sum\limits_{i=1}^{n}\textbf{STA}(y_i) \cdot \textbf{SIM}(x_i,y_i) \cdot \textbf{FL}(x_i, y_i)$$
 
 ### Evaluation Results