Restructured in preparation for packaging

src/mltraining/trainers.py

@@ -57,7 +57,7 @@ class TokenClassificationTrainer:
         )
 
         labels = []
-        for i, label in enumerate(examples[f"ner_tags"]):
+        for i, label in enumerate(examples["ner_tags"]):
             word_ids = tokenized_inputs.word_ids(
                 batch_index=i
             )  # Map tokens to their respective word.
@@ -100,7 +100,7 @@ class TokenClassificationTrainer:
         results: dict[str, float] = self._evaluator.compute(
             predictions=true_predictions, references=true_labels
         )  # type: ignore
-        
+
         return {
             "precision": results["overall_precision"],
             "recall": results["overall_recall"],