diff --git a/models/config.py b/models/config.py
index 978411e5..56fd9cb4 100644
--- a/models/config.py
+++ b/models/config.py
@@ -4,7 +4,7 @@
 @dataclass
 class VLMConfig:
     vit_hidden_dim: int = 768
-    vit_inter_dim: int = 4 * vit_hidden_dim
+    vit_inter_dim: int = field(init=False)
     vit_patch_size: int = 16
     vit_img_size: int = 256
     vit_n_heads: int = 12
@@ -21,7 +21,7 @@ class VLMConfig:
     lm_max_position_embeddings: int = 8192
     lm_base_vocab_size: int = 49152
     extra_token_amount: int = 1  # Number of extra tokens for the VLM (image start, image end, image token)
-    lm_vocab_size: int = lm_base_vocab_size + extra_token_amount # Not a great way to do this, but it works for now (vlm_extra_tokens cannot be a dict, since this is mutable, and a Field has no len() function)
+    lm_vocab_size: int = field(init=False)
     lm_n_heads: int = 9
     lm_n_kv_heads: int = 3
     lm_dropout: float = 0.0
@@ -41,6 +41,10 @@ class VLMConfig:
     vlm_load_backbone_weights: bool = True
     vlm_checkpoint_path: str = 'checkpoints'
     hf_repo_name: str = 'nanoVLM'
+    def __post_init__(self):
+        self.vit_inter_dim = 4 * self.vit_hidden_dim
+        self.lm_vocab_size = self.lm_base_vocab_size + self.extra_token_amount
+
 
 
 @dataclass
@@ -54,8 +58,8 @@ class TrainConfig:
     mmstar_batch_size: int = 32
     max_grad_norm: float = 1.0
     eval_in_epochs: bool = True
-    eval_interval: int = gradient_accumulation_steps * 100
-    stats_log_interval: int = gradient_accumulation_steps * 25
+    eval_interval: int = field(init=False)
+    stats_log_interval: int = field(init=False)
     max_training_steps: int = 5000
     max_images_per_example: int = 4
     max_images_per_knapsack: int = 18
@@ -70,4 +74,7 @@ class TrainConfig:
     use_lmms_eval: bool = True # Use lmms-eval for evaluation
     lmms_eval_tasks: str = 'mmstar,mmmu,ocrbench,textvqa' # Pass additional task as one string, seperated by commas without spaces (e.g. 'mmstar,mmmu,ocrbench')
     lmms_eval_limit: int = None
-    lmms_eval_batch_size: int = 128
\ No newline at end of file
+    lmms_eval_batch_size: int = 128
+    def __post_init__(self):
+        self.eval_interval = self.gradient_accumulation_steps * 100
+        self.stats_log_interval = self.gradient_accumulation_steps * 25