Update README.md

README.md

@@ -12,6 +12,8 @@ library_name: transformers
 
 Finetuned BERT model for 14-class classification. It was introduced in the paper: [Automatic Slide Generation Using Discourse Relations](https://link.springer.com/chapter/10.1007/978-3-031-36336-8_61) and first released in this repository. This model is uncased: it does not make a difference between english and English.
 
+In our proposed method in this [paper](https://link.springer.com/chapter/10.1007/978-3-031-36336-8_61), we only used this model for the classification of discourse relation between the FIRST and SECOND sentence in summarized sentences. The model that is used between the other sentences is [this model](https://huggingface.co/bert-woco). If you are curious about our proposed method, it's better to see that model.
+
 # Descliption
 
 This model can classify the relation between the sentence pair of input.
@@ -19,7 +21,7 @@ This model can classify the relation between the sentence pair of input.
 Now we are working on preparing the Model card. Please wait for a few days.
 
 
-The model trained from [bert-large-uncased](https://huggingface.co/bert-large-uncased]) on the dataset published in the paper: [Automatic Prediction of Discourse Connectives](https://arxiv.org/abs/1702.00992).
+The model trained from [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the dataset published in the paper: [Automatic Prediction of Discourse Connectives](https://arxiv.org/abs/1702.00992).
 
 The dataset to make this model is based on English Wikipedia data and has 20 labels. However, this model will classify into 14 labels. This is because the 20-class data set was restructured to 14 classes to suit our research objective of "automatic slide generation. This distribution is shown below.