diff --git a/sleap_nn/config/model_config.py b/sleap_nn/config/model_config.py
index 1bd48cd1..8aae8628 100644
--- a/sleap_nn/config/model_config.py
+++ b/sleap_nn/config/model_config.py
@@ -259,10 +259,12 @@ class ModelConfig:
     init_weight: str = "default"
     pre_trained_weights: str = None
     backbone_config: BackboneConfig = attrs.field(factory=BackboneConfig)
+    backbone_type: str = None
     head_configs: HeadConfig = attrs.field(factory=HeadConfig)
 
     # post-initialization
     def __attrs_post_init__(self):
+        self.validate_backbone_type()
         self.validate_pre_trained_weights()
 
     # validate the pre-trained weights
@@ -274,3 +276,24 @@ def validate_pre_trained_weights(self):
             "ConvNeXt_Large_Weights",
         ]
         swint_weights = ["Swin_T_Weights", "Swin_S_Weights", "Swin_B_Weights"]
+        if self.backbone_type == "convnext":
+            if self.pre_trained_weights not in convnext_weights:
+                raise ValueError(
+                    f"Invalid pre-trained weights for ConvNext. Must be one of {convnext_weights}"
+                )
+        elif self.backbone_type == "swint":
+            if self.pre_trained_weights not in swint_weights:
+                raise ValueError(
+                    f"Invalid pre-trained weights for SwinT. Must be one of {swint_weights}"
+                )
+        elif (
+            self.backbone_type == "unet"
+            and self.pre_trained_weights is not None
+        ):
+            raise ValueError("UNet does not support pre-trained weights.")
+    
+    def validate_backbone_type(self):
+        if self.backbone_type not in ["unet", "convnext", "swint"]:
+            raise ValueError(
+                'backbone_type must be one of "unet", "convnext", "swint"'
+            )
diff --git a/tests/config/test_model_config.py b/tests/config/test_model_config.py
index 377d6f82..8ecf00c8 100644
--- a/tests/config/test_model_config.py
+++ b/tests/config/test_model_config.py
@@ -23,6 +23,7 @@ def default_config():
     return ModelConfig(
                         init_weight="default", 
                         pre_trained_weights=None,
+                        backbone_type="unet",
                         backbone_config=BackboneConfig(),
                         head_configs=HeadConfig()
                         )
@@ -33,23 +34,15 @@ def test_default_initialization(default_config):
     assert default_config.init_weight == "default"
     assert default_config.pre_trained_weights == None
 
-# def test_invalid_pre_trained_weights():
-#     """Test validation failure with an invalid pre_trained_weights."""
-#     with pytest.raises(ValueError):
-#         ModelConfig(pre_trained_weights="weights")
+def test_invalid_pre_trained_weights():
+    """Test validation failure with an invalid pre_trained_weights."""
+    with pytest.raises(ValueError):
+        ModelConfig(pre_trained_weights="here", backbone_type="unet")
 
-# def test_invalid_input_size():
-#     """Test validation failure with an invalid input_size."""
-#     with pytest.raises(ValueError, match="input_size must be a tuple of two positive integers"):
-#         ModelConfig(model_type="default", input_size=(224, -1), num_classes=10)
-
-#     with pytest.raises(ValueError, match="input_size must be a tuple of two positive integers"):
-#         ModelConfig(model_type="default", input_size="224,224", num_classes=10)
-
-# def test_invalid_num_classes():
-#     """Test validation failure with an invalid num_classes."""
-#     with pytest.raises(ValueError, match="num_classes must be a positive integer"):
-#         ModelConfig(model_type="default", input_size=(224, 224), num_classes=-5)
+def test_invalid_backbonetype():
+    """Test validation failure with an invalid pre_trained_weights."""
+    with pytest.raises(ValueError, match='backbone_type must be one of "unet", "convnext", "swint"'):
+        ModelConfig(backbone_type="net")
 
 # def test_update_config(default_config):
 #     """Test updating configuration attributes."""