Update to use new and improved bert model

app.py

@@ -50,7 +50,7 @@ def predict(input_query):
 
 
 textbox = gr.Textbox(label="Query",
-                     placeholder="Where can I get a quick bite to eat?")
+                     placeholder="Quick bite to eat near me")
 label = gr.Label(label="Result", num_top_classes=5)
 
 gradio_app = gr.Interface(
@@ -59,7 +59,7 @@ gradio_app = gr.Interface(
     outputs=[label],
     title="Query Classification",
     allow_flagging="manual",
-    flagging_options=["potentially harmful", "wrong classification"],
+    flagging_options=["correct classification", "incorrect classification"],
     flagging_callback=flag_callback,
 )
 

hydra.py

@@ -35,7 +35,7 @@ class Hydra(BertModel):
         super().__init__(config)
         self.config = config
         self.pre_classifier = nn.Linear(config.hidden_size, config.hidden_size)
-        self.classifiers = nn.Linear(config.hidden_size, sum(
+        self.classifier = nn.Linear(config.hidden_size, sum(
             [len(group) for group in config.label_groups]))
         self.dropout = nn.Dropout(config.hidden_dropout_prob)
 
@@ -70,7 +70,7 @@ class Hydra(BertModel):
         pooled_output = self.pre_classifier(pooled_output)  # (bs, dim)
         pooled_output = nn.ReLU()(pooled_output)  # (bs, dim)
         pooled_output = self.dropout(pooled_output)  # (bs, dim)
-        logits = self.classifiers(pooled_output)  # (bs, num_labels)
+        logits = self.classifier(pooled_output)  # (bs, num_labels)
 
         loss = None
         if labels is not None:
@@ -107,6 +107,6 @@ class Hydra(BertModel):
     def to(self, device):
         super().to(device)
         self.pre_classifier.to(device)
-        self.classifiers.to(device)
+        self.classifier.to(device)
         self.dropout.to(device)
         return self