fix missleading warning

automodel.py

@@ -139,7 +139,7 @@ class ClinicalMosaicForSequenceClassification(BertPreTrainedModel):
 
         # Calculate classifier parameters
         num_classifier_params = config.hidden_size * config.num_labels + config.num_labels
-        classifier_keys = {"classifier.weight", "classifier.bias"}
+        classifier_keys = {"classifier.weight", "classifier.bias", "bert.pooler.dense.weight", "bert.pooler.dense.bias"}
         
         # Check if only the classification layer is missing
         if set(missing_keys) == classifier_keys: