Minor bug fixes on run_ner.py

examples/run_ner.py

@@ -127,7 +127,7 @@ def train(args, train_dataset, model, tokenizer, labels, pad_token_label_id):
                       "attention_mask": batch[1],
                       "labels": batch[3]}
             if args.model_type != "distilbert":
-                inputs["token_type_ids"]: batch[2] if args.model_type in ["bert", "xlnet"] else None  # XLM and RoBERTa don"t use segment_ids
+                inputs["token_type_ids"] = batch[2] if args.model_type in ["bert", "xlnet"] else None  # XLM and RoBERTa don"t use segment_ids
 
             outputs = model(**inputs)
             loss = outputs[0]  # model outputs are always tuple in pytorch-transformers (see doc)
@@ -217,7 +217,7 @@ def evaluate(args, model, tokenizer, labels, pad_token_label_id, mode, prefix=""
                       "attention_mask": batch[1],
                       "labels": batch[3]}
             if args.model_type != "distilbert":
-                inputs["token_type_ids"]: batch[2] if args.model_type in ["bert", "xlnet"] else None  # XLM and RoBERTa don"t use segment_ids
+                inputs["token_type_ids"] = batch[2] if args.model_type in ["bert", "xlnet"] else None  # XLM and RoBERTa don"t use segment_ids
             outputs = model(**inputs)
             tmp_eval_loss, logits = outputs[:2]