diff --git a/official/nlp/transformer/README.md b/official/nlp/transformer/README.md
index 072f8a3844f27abc1ef1b17d5d3a14147a9ab01a..75f211980c3ae77942949b0af6799943e1314e73 100644
--- a/official/nlp/transformer/README.md
+++ b/official/nlp/transformer/README.md
@@ -98,12 +98,12 @@ bash scripts/run_eval.sh GPU [DEVICE_ID] [MINDRECORD_DATA] [CKPT_PATH] [CONFIG_P
     ```bash
     # Train 8p with Ascend
     # (1) Perform a or b.
-    #       a. Set "enable_modelarts=True" on default_config.yaml file.
-    #          Set "distribute=True" on default_config.yaml file.
-    #          Set "dataset_path='/cache/data'" on default_config.yaml file.
-    #          Set "epoch_size: 52" on default_config.yaml file.
-    #          (optional)Set "checkpoint_url='s3://dir_to_your_pretrained/'" on default_config.yaml file.
-    #          Set other parameters on default_config.yaml file you need.
+    #       a. Set "enable_modelarts=True" on default_config_large.yaml file.
+    #          Set "distribute=True" on default_config_large.yaml file.
+    #          Set "dataset_path='/cache/data'" on default_config_large.yaml file.
+    #          Set "epoch_size: 52" on default_config_large.yaml file.
+    #          (optional)Set "checkpoint_url='s3://dir_to_your_pretrained/'" on default_config_large.yaml file.
+    #          Set other parameters on default_config_large.yaml file you need.
     #       b. Add "enable_modelarts=True" on the website UI interface.
     #          Add "distribute=True" on the website UI interface.
     #          Add "dataset_path=/cache/data" on the website UI interface.
@@ -124,11 +124,11 @@ bash scripts/run_eval.sh GPU [DEVICE_ID] [MINDRECORD_DATA] [CKPT_PATH] [CONFIG_P
     #
     # Train 1p with Ascend
     # (1) Perform a or b.
-    #       a. Set "enable_modelarts=True" on default_config.yaml file.
-    #          Set "dataset_path='/cache/data'" on default_config.yaml file.
-    #          Set "epoch_size: 52" on default_config.yaml file.
-    #          (optional)Set "checkpoint_url='s3://dir_to_your_pretrained/'" on default_config.yaml file.
-    #          Set other parameters on default_config.yaml file you need.
+    #       a. Set "enable_modelarts=True" on default_config_large.yaml file.
+    #          Set "dataset_path='/cache/data'" on default_config_large.yaml file.
+    #          Set "epoch_size: 52" on default_config_large.yaml file.
+    #          (optional)Set "checkpoint_url='s3://dir_to_your_pretrained/'" on default_config_large.yaml file.
+    #          Set other parameters on default_config_large.yaml file you need.
     #       b. Add "enable_modelarts=True" on the website UI interface.
     #          Add "dataset_path='/cache/data'" on the website UI interface.
     #          Add "epoch_size: 52" on the website UI interface.
@@ -148,11 +148,11 @@ bash scripts/run_eval.sh GPU [DEVICE_ID] [MINDRECORD_DATA] [CKPT_PATH] [CONFIG_P
     #
     # Eval 1p with Ascend
     # (1) Perform a or b.
-    #       a. Set "enable_modelarts=True" on default_config.yaml file.
+    #       a. Set "enable_modelarts=True" on default_config_large.yaml file.
     #          Set "checkpoint_url='s3://dir_to_your_trained_model/'" on base_config.yaml file.
-    #          Set "checkpoint='./transformer/transformer_trained.ckpt'" on default_config.yaml file.
-    #          Set "dataset_path='/cache/data'" on default_config.yaml file.
-    #          Set other parameters on default_config.yaml file you need.
+    #          Set "checkpoint='./transformer/transformer_trained.ckpt'" on default_config_large.yaml file.
+    #          Set "dataset_path='/cache/data'" on default_config_large.yaml file.
+    #          Set other parameters on default_config_large.yaml file you need.
     #       b. Add "enable_modelarts=True" on the website UI interface.
     #          Add "checkpoint_url='s3://dir_to_your_trained_model/'" on the website UI interface.
     #          Add "checkpoint='./transformer/transformer_trained.ckpt'" on the website UI interface.
@@ -284,7 +284,7 @@ options:
 #### Running Options
 
 ```text
-default_config.yaml:
+default_config_large.yaml:
     transformer_network             version of Transformer model: base | large, default is large
     init_loss_scale_value           initial value of loss scale: N, default is 2^10
     scale_factor                    factor used to update loss scale: N, default is 2
@@ -354,7 +354,7 @@ Parameters for learning rate:
 
 ## [Training Process](#contents)
 
-- Set options in `default_config.yaml`, including loss_scale, learning rate and network hyperparameters. Click [here](https://www.mindspore.cn/tutorials/en/master/advanced/dataset.html) for more information about dataset.
+- Set options in `default_config_large.yaml`, including loss_scale, learning rate and network hyperparameters. Click [here](https://www.mindspore.cn/tutorials/en/master/advanced/dataset.html) for more information about dataset.
 
 - Run `run_standalone_train.sh` for non-distributed training of Transformer model.
 
@@ -402,7 +402,7 @@ Parameters for learning rate:
 - Export your model to ONNX:
 
   ```bash
-  python export.py --device_target GPU --config default_config.yaml --model_file /path/to/transformer.ckpt --file_name /path/to/transformer.onnx --file_format ONNX
+  python export.py --device_target GPU --config default_config_large.yaml --model_file /path/to/transformer.ckpt --file_name /path/to/transformer.onnx --file_format ONNX
   ```
 
 - Run ONNX evaluation:
@@ -458,33 +458,35 @@ Inference result is saved in current path, 'output_file' will generate in path s
 
 #### Training Performance
 
-| Parameters                 | Ascend                                     | GPU                             |
-| -------------------------- | -------------------------------------------| --------------------------------|
-| Resource                   | Ascend 910; OS Euler2.8                    | GPU(Tesla V100 SXM2)            |
-| uploaded Date              | 07/05/2021 (month/day/year)                | 12/21/2021 (month/day/year)     |
-| MindSpore Version          | 1.3.0                                      | 1.5.0                           |
-| Dataset                    | WMT Englis-German                          | WMT Englis-German               |
-| Training Parameters        | epoch=52, batch_size=96                    | epoch=52, batch_size=32         |
-| Optimizer                  | Adam                                       | Adam                            |
-| Loss Function              | Softmax Cross Entropy                      | Softmax Cross Entropy           |
-| BLEU Score                 | 28.7                                       | 24.4                            |
-| Speed                      | 400ms/step (8pcs)                          | 337 ms/step (8pcs)              |
-| Loss                       | 2.8                                        | 2.9                             |
-| Params (M)                 | 213.7                                      | 213.7                           |
-| Checkpoint for inference   | 2.4G (.ckpt file)                          | 2.4G (.ckpt file)               |
+| Parameters                 | Ascend                                                                                         | GPU                             |
+| -------------------------- |------------------------------------------------------------------------------------------------| --------------------------------|
+| Resource                   | Ascend 910; OS Euler2.8                                                                        | GPU(Tesla V100 SXM2)            |
+| uploaded Date              | 07/05/2021 (month/day/year)                                                                    | 12/21/2021 (month/day/year)     |
+| MindSpore Version          | 1.3.0                                                                                          | 1.5.0                           |
+| Dataset                    | WMT Englis-German                                                                              | WMT Englis-German               |
+| Training Parameters        | epoch=52, batch_size=96                                                                        | epoch=52, batch_size=32         |
+| Optimizer                  | Adam                                                                                           | Adam                            |
+| Loss Function              | Softmax Cross Entropy                                                                          | Softmax Cross Entropy           |
+| BLEU Score                 | 28.7                                                                                           | 24.4                            |
+| Speed                      | 400ms/step (8pcs)                                                                              | 337 ms/step (8pcs)              |
+| Loss                       | 2.8                                                                                            | 2.9                             |
+| Params (M)                 | 213.7                                                                                          | 213.7                           |
+| Checkpoint for inference   | 2.4G (.ckpt file)                                                                              | 2.4G (.ckpt file)               |
 | Scripts                    | [Transformer scripts](https://gitee.com/mindspore/models/tree/master/official/nlp/transformer) |
+| Model Version       | large                                                                                          |large|
 
 #### Evaluation Performance
 
-| Parameters          | Ascend                      | GPU                         |
-| ------------------- | --------------------------- | ----------------------------|
-| Resource            | Ascend 910; OS Euler2.8     | GPU(Tesla V100 SXM2)        |
-| Uploaded Date       | 07/05/2021 (month/day/year) | 12/21/2021 (month/day/year) |
-| MindSpore Version   | 1.3.0                       | 1.5.0                       |
-| Dataset             | WMT newstest2014            | WMT newstest2014            |
-| batch_size          | 1                           | 1                           |
-| outputs             | BLEU score                  | BLEU score                  |
-| Accuracy            | BLEU=28.7                   | BLEU=24.4                   |
+| Parameters        | Ascend                      | GPU                         |
+| ----------------- | --------------------------- | --------------------------- |
+| Resource          | Ascend 910; OS Euler2.8     | GPU(Tesla V100 SXM2)        |
+| Uploaded Date     | 07/05/2021 (month/day/year) | 12/21/2021 (month/day/year) |
+| MindSpore Version | 1.3.0                       | 1.5.0                       |
+| Dataset           | WMT newstest2014            | WMT newstest2014            |
+| batch_size        | 1                           | 1                           |
+| outputs           | BLEU score                  | BLEU score                  |
+| Accuracy          | BLEU=28.7                   | BLEU=24.4                   |
+| Model Version     | large                       | large                       |
 
 ## [Description of Random Situation](#contents)
 
@@ -494,7 +496,7 @@ There are three random situations:
 - Initialization of some model weights.
 - Dropout operations.
 
-Some seeds have already been set in train.py to avoid the randomness of dataset shuffle and weight initialization. If you want to disable dropout, please set the corresponding dropout_prob parameter to 0 in default_config.yaml.
+Some seeds have already been set in train.py to avoid the randomness of dataset shuffle and weight initialization. If you want to disable dropout, please set the corresponding dropout_prob parameter to 0 in default_config_large.yaml.
 
 ## [ModelZoo Homepage](#contents)
 
diff --git a/official/nlp/transformer/README_CN.md b/official/nlp/transformer/README_CN.md
index 6cdf5b3f6d02814fd7216b44f8937e26926c8b57..97ccce0192c7969182708cdac3da2f23299e45b8 100644
--- a/official/nlp/transformer/README_CN.md
+++ b/official/nlp/transformer/README_CN.md
@@ -99,12 +99,12 @@ bash scripts/run_eval.sh GPU [DEVICE_ID] [MINDRECORD_DATA] [CKPT_PATH] [CONFIG_P
     ```python
     # 鍦� ModelArts 涓婁娇鐢�8鍗¤缁�
     # (1) 鎵цa鎴栬€卋
-    #       a. 鍦� default_config.yaml 鏂囦欢涓缃� "enable_modelarts=True"
-    #          鍦� default_config.yaml 鏂囦欢涓缃� "distribute=True"
-    #          鍦� default_config.yaml 鏂囦欢涓缃� "dataset_path='/cache/data'"
-    #          鍦� default_config.yaml 鏂囦欢涓缃� "epoch_size: 52"
-    #          (鍙€�)鍦� default_config.yaml 鏂囦欢涓缃� "checkpoint_url='s3://dir_to_your_pretrained/'"
-    #          鍦� default_config.yaml 鏂囦欢涓缃� 鍏朵粬鍙傛暟
+    #       a. 鍦� default_config_large.yaml 鏂囦欢涓缃� "enable_modelarts=True"
+    #          鍦� default_config_large.yaml 鏂囦欢涓缃� "distribute=True"
+    #          鍦� default_config_large.yaml 鏂囦欢涓缃� "dataset_path='/cache/data'"
+    #          鍦� default_config_large.yaml 鏂囦欢涓缃� "epoch_size: 52"
+    #          (鍙€�)鍦� default_config_large.yaml 鏂囦欢涓缃� "checkpoint_url='s3://dir_to_your_pretrained/'"
+    #          鍦� default_config_large.yaml 鏂囦欢涓缃� 鍏朵粬鍙傛暟
     #       b. 鍦ㄧ綉椤典笂璁剧疆 "enable_modelarts=True"
     #          鍦ㄧ綉椤典笂璁剧疆 "distribute=True"
     #          鍦ㄧ綉椤典笂璁剧疆 "dataset_path=/cache/data"
@@ -125,11 +125,11 @@ bash scripts/run_eval.sh GPU [DEVICE_ID] [MINDRECORD_DATA] [CKPT_PATH] [CONFIG_P
     #
     # 鍦� ModelArts 涓婁娇鐢ㄥ崟鍗¤缁�
     # (1) 鎵цa鎴栬€卋
-    #       a. 鍦� default_config.yaml 鏂囦欢涓缃� "enable_modelarts=True"
-    #          鍦� default_config.yaml 鏂囦欢涓缃� "dataset_path='/cache/data'"
-    #          鍦� default_config.yaml 鏂囦欢涓缃� "epoch_size: 52"
-    #          (鍙€�)鍦� default_config.yaml 鏂囦欢涓缃� "checkpoint_url='s3://dir_to_your_pretrained/'"
-    #          鍦� default_config.yaml 鏂囦欢涓缃� 鍏朵粬鍙傛暟
+    #       a. 鍦� default_config_large.yaml 鏂囦欢涓缃� "enable_modelarts=True"
+    #          鍦� default_config_large.yaml 鏂囦欢涓缃� "dataset_path='/cache/data'"
+    #          鍦� default_config_large.yaml 鏂囦欢涓缃� "epoch_size: 52"
+    #          (鍙€�)鍦� default_config_large.yaml 鏂囦欢涓缃� "checkpoint_url='s3://dir_to_your_pretrained/'"
+    #          鍦� default_config_large.yaml 鏂囦欢涓缃� 鍏朵粬鍙傛暟
     #       b. 鍦ㄧ綉椤典笂璁剧疆 "enable_modelarts=True"
     #          鍦ㄧ綉椤典笂璁剧疆 "dataset_path='/cache/data'"
     #          鍦ㄧ綉椤典笂璁剧疆 "epoch_size: 52"
@@ -149,11 +149,11 @@ bash scripts/run_eval.sh GPU [DEVICE_ID] [MINDRECORD_DATA] [CKPT_PATH] [CONFIG_P
     #
     # 鍦� ModelArts 涓婁娇鐢ㄥ崟鍗￠獙璇�
     # (1) 鎵цa鎴栬€卋
-    #       a. 鍦� default_config.yaml 鏂囦欢涓缃� "enable_modelarts=True"
-    #          鍦� default_config.yaml 鏂囦欢涓缃� "checkpoint_url='s3://dir_to_your_trained_model/'"
-    #          鍦� default_config.yaml 鏂囦欢涓缃� "checkpoint='./transformer/transformer_trained.ckpt'"
-    #          鍦� default_config.yaml 鏂囦欢涓缃� "dataset_path='/cache/data'"
-    #          鍦� default_config.yaml 鏂囦欢涓缃� 鍏朵粬鍙傛暟
+    #       a. 鍦� default_config_large.yaml 鏂囦欢涓缃� "enable_modelarts=True"
+    #          鍦� default_config_large.yaml 鏂囦欢涓缃� "checkpoint_url='s3://dir_to_your_trained_model/'"
+    #          鍦� default_config_large.yaml 鏂囦欢涓缃� "checkpoint='./transformer/transformer_trained.ckpt'"
+    #          鍦� default_config_large.yaml 鏂囦欢涓缃� "dataset_path='/cache/data'"
+    #          鍦� default_config_large.yaml 鏂囦欢涓缃� 鍏朵粬鍙傛暟
     #       b. 鍦ㄧ綉椤典笂璁剧疆 "enable_modelarts=True"
     #          鍦ㄧ綉椤典笂璁剧疆 "checkpoint_url='s3://dir_to_your_trained_model/'"
     #          鍦ㄧ綉椤典笂璁剧疆 "checkpoint='./transformer/transformer_trained.ckpt'"
@@ -285,7 +285,7 @@ options:
 #### 杩愯閫夐」
 
 ```text
-default_config.yaml:
+default_config_large.yaml:
     transformer_network             version of Transformer model: base | large, default is large
     init_loss_scale_value           initial value of loss scale: N, default is 2^10
     scale_factor                    factor used to update loss scale: N, default is 2
@@ -356,7 +356,7 @@ Parameters for learning rate:
 
 ### 璁粌杩囩▼
 
-- 鍦╜default_config.yaml`涓缃€夐」锛屽寘鎷琹oss_scale銆佸涔犵巼鍜岀綉缁滆秴鍙傛暟銆傜偣鍑籟杩欓噷](https://www.mindspore.cn/tutorials/zh-CN/master/advanced/dataset.html)鏌ョ湅鏇村鏁版嵁闆嗕俊鎭€�
+- 鍦╜default_config_large.yaml`涓缃€夐」锛屽寘鎷琹oss_scale銆佸涔犵巼鍜岀綉缁滆秴鍙傛暟銆傜偣鍑籟杩欓噷](https://www.mindspore.cn/tutorials/zh-CN/master/advanced/dataset.html)鏌ョ湅鏇村鏁版嵁闆嗕俊鎭€�
 
 - 杩愯`run_standalone_train.sh`锛岃繘琛孴ransformer妯″瀷鐨勫崟鍗¤缁冦€�
 
@@ -432,21 +432,22 @@ bash run_infer_310.sh [MINDIR_PATH] [NEED_PREPROCESS] [DEVICE_ID] [CONFIG_PATH]
 
 #### 璁粌鎬ц兘
 
-| 鍙傛暟                        | Ascend                           | GPU                             |
-| -------------------------- | -------------------------------- | --------------------------------|
-| 璧勬簮                        | Ascend 910锛涚郴缁� Euler2.8         | GPU(Tesla V100 SXM2)            |
-| 涓婁紶鏃ユ湡                    | 2021-07-05                        | 2021-12-21                      |
-| MindSpore鐗堟湰               | 1.3.0                            | 1.5.0                           |
-| 鏁版嵁闆�                      | WMT鑻�-寰风炕璇戞暟鎹泦                  | WMT鑻�-寰风炕璇戞暟鎹泦                |
-| 璁粌鍙傛暟                     | epoch=52, batch_size=96          | epoch=52, batch_size=32         |
-| 浼樺寲鍣�                      | Adam                              | Adam                            |
-| 鎹熷け鍑芥暟                     | Softmax Cross Entropy            | Softmax Cross Entropy           |
-| BLEU鍒嗘暟                    | 28.7                              | 24.4                           |
-| 閫熷害                        | 400姣/姝�(8鍗�)                    | 337 ms/step(8鍗�)                |
-| 鎹熷け                        | 2.8                               | 2.9                            |
-| 鍙傛暟 (M)                    | 213.7                             | 213.7                          |
-| 鎺ㄧ悊妫€鏌ョ偣                   | 2.4G 锛�.ckpt鏂囦欢锛�                 | 2.4G                            |
-| 鑴氭湰                        | <https://gitee.com/mindspore/models/tree/master/official/nlp/transformer> |
+| 鍙傛暟                        | Ascend                                                                                    | GPU                             |
+| -------------------------- |-------------------------------------------------------------------------------------------| --------------------------------|
+| 璧勬簮                        | Ascend 910锛涚郴缁� Euler2.8                                                                    | GPU(Tesla V100 SXM2)            |
+| 涓婁紶鏃ユ湡                    | 2021-07-05                                                                                | 2021-12-21                      |
+| MindSpore鐗堟湰               | 1.3.0                                                                                     | 1.5.0                           |
+| 鏁版嵁闆�                      | WMT鑻�-寰风炕璇戞暟鎹泦                                                                               | WMT鑻�-寰风炕璇戞暟鎹泦                |
+| 璁粌鍙傛暟                     | epoch=52, batch_size=96                                                                   | epoch=52, batch_size=32         |
+| 浼樺寲鍣�                      | Adam                                                                                      | Adam                            |
+| 鎹熷け鍑芥暟                     | Softmax Cross Entropy                                                                     | Softmax Cross Entropy           |
+| BLEU鍒嗘暟                    | 28.7                                                                                      | 24.4                           |
+| 閫熷害                        | 400姣/姝�(8鍗�)                                                                               | 337 ms/step(8鍗�)                |
+| 鎹熷け                        | 2.8                                                                                       | 2.9                            |
+| 鍙傛暟 (M)                    | 213.7                                                                                     | 213.7                          |
+| 鎺ㄧ悊妫€鏌ョ偣                   | 2.4G 锛�.ckpt鏂囦欢锛�                                                                            | 2.4G                            |
+| 鑴氭湰                        | [Transformer 鑴氭湰](https://gitee.com/mindspore/models/tree/master/official/nlp/transformer) |
+| 妯″瀷鐗堟湰            | large                                                                                     |large|
 
 #### 璇勪及鎬ц兘
 
@@ -459,6 +460,7 @@ bash run_infer_310.sh [MINDIR_PATH] [NEED_PREPROCESS] [DEVICE_ID] [CONFIG_PATH]
 | batch_size          | 1                           | 1                           |
 | 杈撳嚭             | BLEU score                  | BLEU score                  |
 | 鍑嗙‘鐜�            | BLEU=28.7                   | BLEU=24.4                   |
+| 妯″瀷鐗堟湰 | large | large |
 
 ## 闅忔満鎯呭喌璇存槑
 
@@ -468,7 +470,7 @@ bash run_infer_310.sh [MINDIR_PATH] [NEED_PREPROCESS] [DEVICE_ID] [CONFIG_PATH]
 - 鍒濆鍖栭儴鍒嗘ā鍨嬫潈閲�
 - 闅忔満澶辨椿杩愯
 
-train.py宸茬粡璁剧疆浜嗕竴浜涚瀛愶紝閬垮厤鏁版嵁闆嗚疆鎹㈠拰鏉冮噸鍒濆鍖栫殑闅忔満鎬с€傝嫢闇€鍏抽棴闅忔満澶辨椿锛屽皢default_config.yaml涓浉搴旂殑dropout_prob鍙傛暟璁剧疆涓�0銆�
+train.py宸茬粡璁剧疆浜嗕竴浜涚瀛愶紝閬垮厤鏁版嵁闆嗚疆鎹㈠拰鏉冮噸鍒濆鍖栫殑闅忔満鎬с€傝嫢闇€鍏抽棴闅忔満澶辨椿锛屽皢default_config_large.yaml涓浉搴旂殑dropout_prob鍙傛暟璁剧疆涓�0銆�
 
 ## ModelZoo涓婚〉
 
diff --git a/official/nlp/transformer/infer/README.md b/official/nlp/transformer/infer/README.md
index 0bdcd449a85b0c8bd68954848b79059b3ec2e6b2..71c1f1078a4de5ae10b56d6750e9038574932212 100644
--- a/official/nlp/transformer/infer/README.md
+++ b/official/nlp/transformer/infer/README.md
@@ -115,7 +115,7 @@ bash wmt16_en_de.sh
 paste newstest2014.tok.bpe.32000.en newstest2014.tok.bpe.32000.de > test.all
 ```
 
-灏哾efault_config.yaml涓璪ucket鏀逛负bucket: [128]
+灏哾efault_config_large.yaml涓璪ucket鏀逛负bucket: [128]
 
 ```text
 # create_data.py
@@ -134,7 +134,7 @@ bucket: [128]
 python3 create_data.py --input_file ./infer/data/data/test.all --vocab_file ./infer/data/data/vocab.bpe.32000 --output_file ./infer/data/data/newstest2014-l128-mindrecord --num_splits 1 --max_seq_length 128 --clip_to_max_len True
 ```
 
-鏇存敼default_config.yaml涓弬鏁帮細
+鏇存敼default_config_large.yaml涓弬鏁帮細
 
 ```text
 #eval_config/cfg edict
diff --git a/official/nlp/transformer/scripts/run_eval.sh b/official/nlp/transformer/scripts/run_eval.sh
index 9628e782092804f5cb6d1be03dfb0c1c234a1533..0ce68c6ae1ac306aa4a93a9d704760d49db2d6ae 100644
--- a/official/nlp/transformer/scripts/run_eval.sh
+++ b/official/nlp/transformer/scripts/run_eval.sh
@@ -1,5 +1,5 @@
 #!/bin/bash
-# Copyright 2020 Huawei Technologies Co., Ltd
+# Copyright 2020-2022 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -16,9 +16,9 @@
 if [ $# != 5 ] ; then
 echo "=============================================================================================================="
 echo "Please run the script as: "
-echo "sh scripts/run_eval.sh DEVICE_TARGET DEVICE_ID MINDRECORD_DATA CKPT_PATH CONFIG_PATH"
-echo "for example: sh run_eval.sh Ascend 0 /your/path/evaluation.mindrecord /your/path/checkpoint_file ./default_config_large_gpu.yaml"
-echo "Note: set the checkpoint and dataset path in default_config.yaml"
+echo "bash scripts/run_eval.sh DEVICE_TARGET DEVICE_ID MINDRECORD_DATA CKPT_PATH CONFIG_PATH"
+echo "for example: bash run_eval.sh Ascend 0 /your/path/evaluation.mindrecord /your/path/checkpoint_file ./default_config_large_gpu.yaml"
+echo "Note: set the checkpoint and dataset path in default_config_large.yaml"
 echo "=============================================================================================================="
 exit 1;
 fi
diff --git a/official/nlp/transformer/scripts/run_eval_onnx.sh b/official/nlp/transformer/scripts/run_eval_onnx.sh
index a7804f157c6f0def67c1120ab981225770113d25..8d83bd67d682f9ae87c792ea6eab4fef179d262d 100644
--- a/official/nlp/transformer/scripts/run_eval_onnx.sh
+++ b/official/nlp/transformer/scripts/run_eval_onnx.sh
@@ -1,5 +1,5 @@
 #!/bin/bash
-# Copyright 2021 Huawei Technologies Co., Ltd
+# Copyright 2021-2022 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -31,7 +31,7 @@ get_real_path(){
 
 ONNX_MODEL=$(get_real_path $1)
 MINDRECORD_DATA=$(get_real_path $2)
-CONFIG_PATH=${3:-"./default_config.yaml"}
+CONFIG_PATH=${3:-"./default_config_large.yaml"}
 CONFIG_PATH=$(get_real_path $CONFIG_PATH)
 DEVICE_TARGET=${4:-"GPU"}
 DEVICE_ID=${5:-0}
diff --git a/official/nlp/transformer/src/model_utils/config.py b/official/nlp/transformer/src/model_utils/config.py
index 5dff477aed4c7ea9af926186b82d84505024c2fe..851dcc97c9cb768d6aa85458d7e7f990ecbf91e2 100644
--- a/official/nlp/transformer/src/model_utils/config.py
+++ b/official/nlp/transformer/src/model_utils/config.py
@@ -1,4 +1,4 @@
-# Copyright 2021 Huawei Technologies Co., Ltd
+# Copyright 2021-2022 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -39,7 +39,7 @@ class Config:
         return self.__str__()
 
 
-def parse_cli_to_yaml(parser, cfg, helper=None, choices=None, cfg_path="default_config.yaml"):
+def parse_cli_to_yaml(parser, cfg, helper=None, choices=None, cfg_path="default_config_large.yaml"):
     """
     Parse command line arguments to the configuration according to the default yaml.
 
@@ -115,7 +115,7 @@ def get_config():
     """
     parser = argparse.ArgumentParser(description="default name", add_help=False)
     current_dir = os.path.dirname(os.path.abspath(__file__))
-    parser.add_argument("--config_path", type=str, default=os.path.join(current_dir, "../../default_config.yaml"),
+    parser.add_argument("--config_path", type=str, default=os.path.join(current_dir, "../../default_config_large.yaml"),
                         help="Config file path")
     path_args, _ = parser.parse_known_args()
     default, helper, choices = parse_yaml(path_args.config_path)