diff --git a/astrai/model/transformer.py b/astrai/model/transformer.py
index 2198a4b..553f682 100644
--- a/astrai/model/transformer.py
+++ b/astrai/model/transformer.py
@@ -76,7 +76,7 @@ class Transformer(AutoModel):
     def __init__(self, config: ModelConfig):
         super().__init__(config)
         self.config = config
-        self.rotary_embeding = RotaryEmbedding(
+        self.rotary_embedding = RotaryEmbedding(
             config.dim // config.n_heads, config.max_len
         )
         self.embed_tokens = Embedding(config.vocab_size, config.dim)
@@ -152,7 +152,7 @@ class Transformer(AutoModel):
         assert input_ids.ndim == 2
 
         x = self.embed_tokens(input_ids)
-        rotary_emb = self.rotary_embeding(x, start_pos)
+        rotary_emb = self.rotary_embedding(x, start_pos)
 
         attn_mask = process_attention_mask(input_mask, x, start_pos, is_causal=True)
 
diff --git a/astrai/trainer/strategy.py b/astrai/trainer/strategy.py
index fd3d1d5..eb5a6e5 100644
--- a/astrai/trainer/strategy.py
+++ b/astrai/trainer/strategy.py
@@ -237,14 +237,14 @@ class DPOStrategy(BaseStrategy):
         chosen_ids, rejected_ids = batch["chosen"], batch["rejected"]
         chosen_mask, rejected_mask = batch["chosen_mask"], batch["rejected_mask"]
 
-        contact_ids = torch.cat([chosen_ids, rejected_ids], dim=0)
-        contact_mask = torch.cat([chosen_mask, rejected_mask], dim=0)
+        concat_ids = torch.cat([chosen_ids, rejected_ids], dim=0)
+        concat_mask = torch.cat([chosen_mask, rejected_mask], dim=0)
 
-        log_pi = get_logprobs(self.model, contact_ids, contact_mask, self.reduction)
+        log_pi = get_logprobs(self.model, concat_ids, concat_mask, self.reduction)
 
         with torch.no_grad():
             log_ref = get_logprobs(
-                self.ref_model, contact_ids, contact_mask, self.reduction
+                self.ref_model, concat_ids, concat_mask, self.reduction
             )
 
         log_pi_chosen = log_pi[: chosen_ids.shape[0]]