Create model.py

model.py

@@ -0,0 +1,28 @@
+import torch
+import torch.nn as nn
+
+class IndoBERTMultitask(nn.Module):
+    def __init__(self, base_model, hidden_size=768, num_event_labels=43):
+        super(IndoBERTMultitask, self).__init__()
+        self.bert = base_model
+        self.dropout = nn.Dropout(0.3)
+
+        # Task heads
+        self.sentiment_head = nn.Linear(hidden_size, 3)                # 3 kelas
+        self.event_head = nn.Linear(hidden_size, num_event_labels)    # Event (43 kelas)
+
+        # IDX sektor (multi-label 11 sektor)
+        self.idx_heads = nn.ModuleList([
+            nn.Linear(hidden_size, 1) for _ in range(11)
+        ])
+
+    def forward(self, input_ids, attention_mask):
+        outputs = self.bert(input_ids=input_ids, attention_mask=attention_mask)
+        pooled = outputs.last_hidden_state[:, 0]  # Ambil token CLS
+        pooled = self.dropout(pooled)
+
+        sentiment_logits = self.sentiment_head(pooled)
+        event_logits = self.event_head(pooled)
+        idx_logits = torch.cat([head(pooled) for head in self.idx_heads], dim=1)
+
+        return sentiment_logits, event_logits, idx_logits