fix transformer eval device id

model_zoo/official/nlp/transformer/README.md

@@ -193,10 +193,10 @@ Parameters for learning rate:
 
 - Set options in `config.py`, including loss_scale, learning rate and network hyperparameters. Click [here](https://www.mindspore.cn/tutorial/training/zh-CN/master/use/data_preparation.html) for more information about dataset.
 
-- Run `run_standalone_train_ascend.sh` for non-distributed training of Transformer model.
+- Run `run_standalone_train.sh` for non-distributed training of Transformer model.
 
     ``` bash
-    sh scripts/run_standalone_train_ascend.sh DEVICE_ID EPOCH_SIZE DATA_PATH
+    sh scripts/run_standalone_train.sh DEVICE_TARGET DEVICE_ID EPOCH_SIZE DATA_PATH
     ```
 - Run `run_distribute_train_ascend.sh` for distributed training of Transformer model.
 

model_zoo/official/nlp/transformer/eval.py

@@ -100,7 +100,7 @@ def run_transformer_eval():
     parser = argparse.ArgumentParser(description='tranformer')
     parser.add_argument("--device_target", type=str, default="Ascend",
                         help="device where the code will be implemented, default is Ascend")
-    parser.add_argument('--device_id', type=int, default=None, help='device id of GPU or Ascend. (Default: None)')
+    parser.add_argument('--device_id', type=int, default=0, help='device id of GPU or Ascend, default is 0')
     args = parser.parse_args()
 
     context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target, reserve_class_name_in_scope=False,