Update app.py

app.py

@@ -95,7 +95,7 @@ if (should_train_model=='1'): #train model
     
     #tokenizer = BertTokenizer.from_pretrained(repo_name, subfolder="bert_embeddings_finetune
     
-    tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
+    tokenizer = RobertaTokenizer.from_pretrained("roberta-base")
                                               
     # I made sure to add all the ones in the training and eval data to this list
     # since we are training using data that only contains the left tag - we don't need right tags added to this list
@@ -106,7 +106,7 @@ if (should_train_model=='1'): #train model
     # Model
     #model = BertForSequenceClassification.from_pretrained(repo_name, subfolder="bert_embeddings_finetune", output_attentions=True, num_labels=len(label_mapping), output_hidden_states=True).to('cpu')
 
-    model = BertForSequenceClassification.from_pretrained("bert-base-uncased", output_attentions=True, num_labels=len(label_mapping), output_hidden_states=True).to('cpu')
+    model = BertForSequenceClassification.from_pretrained("roberta-base", output_attentions=True, num_labels=len(label_mapping), output_hidden_states=True).to('cpu')
 
     # Reset tokenizer size to include the new size after adding the tags to the tokenizer's tokens
     model.resize_token_embeddings(len(tokenizer))