Update README.md

README.md

@@ -35,7 +35,7 @@ You can use this classifier to determine which of the 4P's of marketing, also kn
 ### Model Description
 
 This classifier is a fine-tuned checkpoint of [cardiffnlp/twitter-roberta-large-2022-154m] (https://huggingface.co/cardiffnlp/twitter-roberta-large-2022-154m). 
-It was trained on 15K Tweets that mentioned at least one of 699 brands. The Tweets were cleaned and labeled using OpenAI's GPT4. 
+It was trained on 15K Tweets that mentioned at least one of 699 brands. The Tweets were first cleaned and then labeled using OpenAI's GPT4. 
 
 Because this is a multi-label classification problem, we use binary cross-entropy (BCE) with logits loss for the fine-tuning. We basically combine a sigmoid layer with BCELoss in a single class.
 To obtain the probabilities for each label (i.e., marketing mix variable), you need to "push" the predictions through a sigmoid function. This is already done in the accompanying python notebook.