Update README.md

README.md

@@ -9,7 +9,7 @@ We introduce the model for multilabel ESG risks classification. There is 47 clas
 
 ## Usage 
 ```python
-
+from collections import OrderedDict
 from transformers import MPNetPreTrainedModel, MPNetModel, AutoTokenizer
 import torch
 #Mean Pooling - Take attention mask into account for correct averaging
@@ -45,10 +45,11 @@ class ESGify(MPNetPreTrainedModel):
         outputs = self.mpnet(input_ids=input_ids,
                              attention_mask=attention_mask)
          
-        # mean pooling dataset
+        # mean pooling dataset and eed input to classifier to compute logits
         logits = self.classifier( mean_pooling(outputs['last_hidden_state'],attention_mask))
-         # Feed input to classifier to compute logits
- 
+         
+        # apply sigmoid
+        logits  = 1.0 / (1.0 + torch.exp(-logits))
         return logits
 
 model = ESGify.from_pretrained('ai-lab/ESGify')