2nd LL

README.md

@@ -20,16 +20,19 @@ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co
 - Accuracy: 0.936
 
 ## Model description
+This model is a simple Pytorch Custom Model that uses BERT to classify the emotions of a given text 
 
-More information needed
 
 ## Intended uses & limitations
 
-More information needed
+- It only supports English for now (am willing to add French next)
+- The input text has a limit in size, it can suit a mid-size paragraph easily but can't handle large documents (you can bypass this by dividing the document to paragraphs and make a weights summation)
+- The emotions it can recognize are limited (the 6 major emotions) so it can't detail to mixed psychological outcomes
+- Fine Tuning time : well we all know how BERT can be slow sometimes so i suggest for anyone who wants to develop over the idea to use DistelBERT for faster results  
 
 ## Training and evaluation data
 
-More information needed
+This dataset contains two key columns: 'text' and 'label'. The 'label' column represents six different emotion classes: sadness (0), joy (1), love (2), anger (3), fear (4), and surprise (5). Get ready to dive deep into the world of human emotions
 
 ## Training procedure