[update]add chinese_mnli

README.md

@@ -21,6 +21,7 @@ size_categories:
 | BUSTM | 汉语 | [BUSTM](https://tianchi.aliyun.com/competition/entrance/531851/information); [BUSTM](https://github.com/xiaobu-coai/BUSTM) | 总样本数为：177173，其中，匹配样本个数为：54805，不匹配样本个数为：122368 | 小布助手对话短文本语义匹配比赛数据集 | [BUSTM](https://github.com/CLUEbenchmark/FewCLUE/tree/main/datasets/bustm) |
 | CHIP2019 | 汉语 | [CHIP2019](https://www.biendata.xyz/competition/chip2019/) | 2万 | 平安医疗科技疾病问答迁移学习比赛数据集 |  |
 | COVID-19 | 汉语 | [COVID-19](https://tianchi.aliyun.com/competition/entrance/231776/information) |  | 天池新冠疫情相似句对判定大赛 | [COVID-19](https://gitee.com/liangzongchang/COVID-19-sentence-pair/) |
+| Chinese-MNLI | 汉语 | [Chinese-MNLI](https://github.com/pluto-junzeng/CNSD) | TRAIN: 390K, VALID: 12K, TEST: 13K | 通过翻译加部分人工修正的方法，从英文原数据集生成（原数据是：蕴含，中性，冲突，的句子推理数据集，已转换为句子对。） |  |
 
 
 <details>

data/chinese_mnli.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:994e50bf6964ca0d6073b31fae10af95c2037ebbba434a864591b79c64757045
+size 117184478

examples/preprocess/process_chinese_mnli.py

@@ -0,0 +1,82 @@
+#!/usr/bin/python3
+# -*- coding: utf-8 -*-
+import argparse
+import json
+import os
+from pathlib import Path
+import sys
+
+pwd = os.path.abspath(os.path.dirname(__file__))
+sys.path.append(os.path.join(pwd, '../../'))
+
+from datasets import load_dataset
+from tqdm import tqdm
+
+from project_settings import project_path
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("--data_dir", default="./data/chinese_mnli", type=str)
+
+    parser.add_argument(
+        "--output_file",
+        default=(project_path / "data/chinese_mnli.jsonl"),
+        type=str
+    )
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    args = get_args()
+
+    data_dir = Path(args.data_dir)
+
+    with open(args.output_file, "w", encoding="utf-8") as fout:
+        for name in ["cnsd_multil_train.jsonl", "cnsd_multil_dev_matched.jsonl", "cnsd_multil_dev_mismatched.jsonl"]:
+            filename = data_dir / name
+            with open(filename, "r", encoding="utf-8") as fin:
+                for row in fin:
+                    row = json.loads(row)
+                    sentence1 = row["sentence1"]
+                    sentence2 = row["sentence2"]
+                    gold_label = row["gold_label"]
+
+                    if name == "cnsd_multil_train.jsonl":
+                        label = "1" if gold_label in ("entailment",) else "0"
+                        flag = "train"
+                        category = "cnsd_multil_train"
+                    elif name == "cnsd_multil_dev_matched.jsonl":
+                        label = "1" if gold_label in ("entailment",) else "0"
+                        flag = "validation"
+                        category = "cnsd_multil_dev_matched"
+                    elif name == "cnsd_multil_dev_mismatched.jsonl":
+                        label = "1" if gold_label in ("entailment",) else "0"
+                        flag = "validation"
+                        category = "cnsd_multil_dev_mismatched"
+                    else:
+                        raise AssertionError
+
+                    if label not in ("0", "1", None):
+                        raise AssertionError
+
+                    row = {
+                        "sentence1": sentence1,
+                        "sentence2": sentence2,
+                        "label": label,
+                        "category": category,
+                        "data_source": "Chinese-MNLI",
+                        "split": flag
+                    }
+
+                    row = json.dumps(row, ensure_ascii=False)
+                    fout.write("{}\n".format(row))
+
+    return
+
+
+if __name__ == '__main__':
+    main()

sentence_pair.py

@@ -12,6 +12,7 @@ _URLS = {
     "afqmc": "data/afqmc.jsonl",
     "bustm": "data/bustm.jsonl",
     "ccks2018_task3": "data/ccks2018_task3.jsonl",
+    "chinese_mnli": "data/chinese_mnli.jsonl",
     "chinese_sts": "data/chinese_sts.jsonl",
     "chip2019": "data/chip2019.jsonl",
     "covid_19": "data/covid_19.jsonl",