Update model.py

model.py

@@ -3,8 +3,8 @@ import torch.nn as nn
 from transformers import BertModel
 
 class HybridModel(nn.Module):
-    def _init_(self, dropout=0.3):
-        super(HybridModel, self)._init_()
+    def __init__(self, dropout=0.3):
+        super(HybridModel, self).__init__()
         self.bert = BertModel.from_pretrained("indobenchmark/indobert-base-p1")
         self.lstm = nn.LSTM(768, 128, bidirectional=True, batch_first=True)
         self.dropout = nn.Dropout(dropout)
@@ -15,4 +15,4 @@ class HybridModel(nn.Module):
             outputs = self.bert(input_ids=input_ids, attention_mask=attention_mask)
         lstm_out, _ = self.lstm(outputs.last_hidden_state)
         x = self.dropout(lstm_out[:, -1, :])
-        return torch.sigmoid(self.classifier(x))
+        return torch.sigmoid(self.classifier(x))