Create configuration.py

configuration.py

@@ -0,0 +1,27 @@
+from transformers import PretrainedConfig
+
+class AlbertLSTMConfig(PretrainedConfig):
+    model_type = "albertLSTMForSequenceClassification"
+
+    def __init__(self,
+                 num_classes=2,
+                 embed_dim=768,
+                 num_layers=12,
+                 hidden_dim_lstm=256,  # New parameter for LSTM
+                 dropout_rate=0.1,
+                 **kwargs):
+        super().__init__(**kwargs)
+        self.num_classes = num_classes
+        self.embed_dim = embed_dim
+        self.num_layers = num_layers
+        self.hidden_dim_lstm = hidden_dim_lstm  # Assign LSTM hidden dimension
+        self.dropout_rate = dropout_rate
+        self.id2label = {
+            0: "fake",
+            1: "true",
+        }
+        self.label2id = {
+            "fake": 0,
+            "true": 1,
+        }
+