diff --git a/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/README.md b/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/README.md
index 984ff4a1028e3a40a78539669a5b4832ec338256..36a99fc64ceb2011cad1a19b8703efd58103ee3f 100644
--- a/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/README.md
+++ b/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/README.md
@@ -157,7 +157,7 @@ python3 xnlp_fmk.py \
 **ALBERT_zh**
 ***
 * ALBERT_zh使用albert_zh做为模型的名称, 每个下游任务各自做为模型名称。
-* ALBERT_zh支持afqmc,cmnli,csl,iflytek,tnews和wsc任务
+* ALBERT_zh支持afqmc,cmnli,csl,iflytek,tnews,lcqmc和wsc任务
 * 改变模型入参，以支持不同的任务
 * 仅ALBERT_zh Tiny测试过
 ***
@@ -166,7 +166,7 @@ python3 xnlp_fmk.py \
 * --output_dir的传参与--data_dir相同, 预处理脚本会将文本转换为该路径下的bin文件
 * --vocab_file, --bert_config_file, --do_lower_case, --max_seq_length, --doc_stride等参数进行微调
 * --model_name：当进行ALBERT_en任务时，参数为albert_en
-* --task_name为下游所需的任务名, 仅支持afqmc, cmnli, csl, iflytek, tnews 和 wsc 任务
+* --task_name为下游所需的任务名, 仅支持afqmc, cmnli, csl, iflytek, tnews, lcqmc 和 wsc 任务
 ```Bash
 python3 xnlp_fmk.py \
     --data_dir=./data/TNEWS \
diff --git a/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/README_EN.md b/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/README_EN.md
index f6a501beb2e6cb9c08046b3b435f67ab778bfe0d..69192912fa0e649e261ebe510f4872e963daf495 100644
--- a/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/README_EN.md
+++ b/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/README_EN.md
@@ -157,7 +157,7 @@ python3 xnlp_fmk.py \
 **ALBERT_zh**
 ***
 * ALBERT_zh use albert_zh for model_name parameter, each downstream task name for task_name
-* ALBERT_zh support afqmc, cmnli, csl, iflytek, tnews and wsc tasks
+* ALBERT_zh support afqmc, cmnli, csl, iflytek, tnews , lcqmc and wsc tasks
 * Change the parameters for different tasks
 * Only ALBERT_zh Tiny has been tested
 ***
@@ -166,7 +166,7 @@ python3 xnlp_fmk.py \
 * Change --output_dir to the same with --data_dir, and preprocess script will convert text to bin files under this path
 * Keep the --vocab_file, --bert_config_file, --do_lower_case, --max_seq_length, --doc_stride, etc. the same with fine-tuning parameters
 * Keep the --model_name=albert_zh when do the ALBERT_zh tasks
-* Change --task_name to the downstream task you want to do, only support afqmc, cmnli, csl, iflytek, tnews and wsc tasks
+* Change --task_name to the downstream task you want to do, only support afqmc, cmnli, csl, iflytek, tnews, lcqmc and wsc tasks
 ```Bash
 python3 xnlp_fmk.py \
     --data_dir=./data/TNEWS \
diff --git a/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/libs/convert_txt2json.py b/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/libs/convert_txt2json.py
new file mode 100644
index 0000000000000000000000000000000000000000..32d4e0170115c4a9e8c227187a861b6718a8c614
--- /dev/null
+++ b/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/libs/convert_txt2json.py
@@ -0,0 +1,19 @@
+#针对lcqmc数据集，做txt到json文件转换
+import json
+
+def convert_txt2Json(txt_path, json_path):
+    '''
+        txt_path为lcqmc数据集dev.txt路径
+        json_path为输出json文件的路径
+    '''
+    dev_txt = open(txt_path)
+    lines = dev_txt.read().split('\n')
+    lines.pop()
+    with open(json_path, 'w') as f:
+        for line in lines:
+            json_line = line.split('\t')
+            dict_line = {"sentence1": json_line[0], "sentence2": json_line[1], "label": json_line[2]}
+            arr = json.dumps(dict_line)
+            f.write(arr + '\n')
+    dev_txt.close()
+
diff --git a/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/network/run_albert_lcqmc.py b/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/network/run_albert_lcqmc.py
new file mode 100644
index 0000000000000000000000000000000000000000..82ba2ea108d33c481b3a7e6e0f5af0cc9c664230
--- /dev/null
+++ b/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/network/run_albert_lcqmc.py
@@ -0,0 +1,88 @@
+# -*- coding: utf-8 -*-
+# @Author: fengtingyan
+# @Date:   2023-3-29 21:11:00
+# @Last Modified by:   fengtingyan
+# @Last Modified time: 2023-3-29 21:11:00
+
+# Copyright 2018 The Google AI Language Team Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Copyright 2020 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.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""BERT finetuning runner."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import csv
+import json
+import os
+
+import tensorflow.compat.v1 as tf
+from absl import flags
+
+from network import tokenization
+from network.classifier_utils import DataProcessor, InputExample
+
+FLAGS = flags.FLAGS
+
+__all__ = 'LcqmcProcessor'
+
+
+class LcqmcProcessor(DataProcessor):
+    """Processor for the AFQMC data set."""
+
+    def get_examples(self):
+        """See base class."""
+        return self.create_examples(self.read_json(os.path.join(FLAGS.data_dir, "dev.json")), "dev")
+
+    def get_labels(self):
+        """See base class."""
+        return ["0", "1"]
+
+    @staticmethod
+    def create_examples(lines, set_type):
+        """Creates examples for the training and dev sets."""
+        #todo
+        examples = []
+        for (i, line) in enumerate(lines):
+            guid = "%s-%s" % (set_type, i)
+            text_a = tokenization.convert_to_unicode(line['sentence1'])
+            text_b = tokenization.convert_to_unicode(line['sentence2'])
+            label = tokenization.convert_to_unicode(line['label']) if set_type != 'test' else '0'
+            examples.append(InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
+        return examples
+
+    @staticmethod
+    def read_label(input_file):
+        with tf.io.gfile.GFile(input_file, "r") as f:
+            reader = csv.reader(f, delimiter="\t", quotechar=None)
+            labels = []
+            for (i, line) in enumerate(reader):
+                data_json = json.loads(line[0])
+                labels.append(int(data_json['label']))
+            return labels
diff --git a/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/xnlp_fmk.py b/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/xnlp_fmk.py
index b5c26ce44e290dc059c09b2826b5eb786af366dc..723312d01aee5f4f684cff3e6b3f6d40a5e02f9f 100644
--- a/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/xnlp_fmk.py
+++ b/ACL_TensorFlow/contrib/nlp/ALBERT_for_ACL/xnlp_fmk.py
@@ -30,6 +30,7 @@ from libs.predict_pb import pb_predict
 from libs.preprocess import preprocess
 from network.run_albert_afqmc import AfqmcProcessor as AlbertAfqmc
 from network.run_albert_cmnli import CmnliProcessor as AlbertCmnli
+from network.run_albert_lcqmc import LcqmcProcessor as AlbertLcqmc
 from network.run_albert_csl import CslProcessor as AlbertCsl
 from network.run_albert_iflytek import IflytekProcessor as AlbertIflytek
 from network.run_albert_race import RaceProcessor as AlbertRace
@@ -66,6 +67,7 @@ MODEL = {
         "iflytek": AlbertIflytek,
         "tnews": BertTnews,
         "wsc": AlbertWsc,
+        "lcqmc": AlbertLcqmc,
     },
     "bert": {
         # BERT by google