Align logits and labels in OPT (#17237)

src/transformers/models/opt/modeling_opt.py

@@ -951,9 +951,12 @@ class OPTForCausalLM(OPTPreTrainedModel):
 
         loss = None
         if labels is not None:
+            # Shift so that tokens < n predict n
+            shift_logits = logits[..., :-1, :].contiguous()
+            shift_labels = labels[..., 1:].contiguous()
+            # Flatten the tokens
             loss_fct = CrossEntropyLoss()
-
-            loss = loss_fct(logits.view(-1, self.config.vocab_size), labels.view(-1))
+            loss = loss_fct(shift_logits.view(-1, self.config.vocab_size), shift_labels.view(-1))
 
         if not return_dict:
             output = (logits,) + outputs[1:]