Add configuration_dualmedbert.py for custom architecture

configuration_dualmedbert.py

@@ -0,0 +1,17 @@
+from transformers import PretrainedConfig
+
+class DualMedBertConfig(PretrainedConfig):
+    model_type = "dualmedbert"
+    def __init__(
+        self,
+        num_classes=27,
+        lora_rank=8,
+        lora_alpha=32,
+        student_ck="distilbert-base-uncased",
+        **kwargs
+    ):
+        super().__init__(**kwargs)
+        self.num_classes = num_classes
+        self.lora_rank = lora_rank
+        self.lora_alpha = lora_alpha
+        self.student_ck = student_ck