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modeling_empathy.py

@@ -99,10 +99,11 @@ class BiEncoderAttentionWithRationaleClassification(nn.Module):
         
         self.apply(self._init_weights)
         
-        # Load pretrained RoBERTa encoders
+        # Initialize RoBERTa encoders (will be loaded from saved weights)
+        # Don't use from_pretrained here to avoid overwriting trained weights
         roberta_config = RobertaConfig.from_pretrained("roberta-base")
-        self.seeker_encoder = RobertaModel.from_pretrained("roberta-base", config=roberta_config)
-        self.responder_encoder = RobertaModel.from_pretrained("roberta-base", config=roberta_config)
+        self.seeker_encoder = RobertaModel(config=roberta_config)
+        self.responder_encoder = RobertaModel(config=roberta_config)
     
     def _init_weights(self, module):
         """Initialize the weights"""
@@ -212,6 +213,7 @@ class EmpathyModelConfig(PretrainedConfig):
 class EmpathyModel(PreTrainedModel):
     """HuggingFace wrapper for Empathy Model"""
     config_class = EmpathyModelConfig
+    base_model_prefix = "model"  # Important: matches the saved state_dict structure
     
     def __init__(self, config):
         super().__init__(config)