[update]add covid_19

README.md

@@ -20,6 +20,7 @@ size_categories:
 | AFQMC | 汉语 | [AFQMC](https://tianchi.aliyun.com/dataset/106411) | TRAIN: 34334, VALID: 4316, TEST: 3861 | 蚂蚁金融语义相似度数据集，用于问题相似度计算。即：给定客服里用户描述的两句话，用算法来判断是否表示了相同的语义。 |  |
 | 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/) |
 
 
 <details>

data/covid_19.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:350a8e6c5c38760d13c9b6181b33335786585bfa9b416e71fcb242fa30ffdefd
+size 2181571

examples/preprocess/process_covid_19.py

@@ -0,0 +1,95 @@
+#!/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
+import pandas as pd
+from tqdm import tqdm
+
+from project_settings import project_path
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("--data_dir", default="./data/covid_19", type=str)
+    parser.add_argument(
+        "--output_file",
+        default=(project_path / "data/covid_19.jsonl"),
+        type=str
+    )
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    args = get_args()
+
+    data_dir = Path(args.data_dir)
+
+    train_filename = data_dir / "COVID-19/data/Dataset/train_20200228.csv"
+    valid_filename = data_dir / "COVID-19/data/Dataset/dev_20200228.csv"
+
+    df_train = pd.read_csv(train_filename)
+    df_valid = pd.read_csv(valid_filename)
+
+    with open(args.output_file, "w", encoding="utf-8") as f:
+        for i, row in df_train.iterrows():
+            category = row["category"]
+            query1 = row["query1"]
+            query2 = row["query2"]
+            label = row["label"]
+
+            label = str(int(label)) if label is not None else None
+
+            if label not in ("0", "1", None):
+                raise AssertionError
+
+            row = {
+                "sentence1": query1,
+                "sentence2": query2,
+                "label": label,
+                "category": category,
+                "data_source": "COVID-19",
+                "split": "train"
+            }
+
+            row = json.dumps(row, ensure_ascii=False)
+            f.write("{}\n".format(row))
+
+        for i, row in df_valid.iterrows():
+            category = row["category"]
+            query1 = row["query1"]
+            query2 = row["query2"]
+            label = row["label"]
+
+            label = str(int(label)) if label is not None else None
+
+            if label not in ("0", "1", None):
+                raise AssertionError
+
+            row = {
+                "sentence1": query1,
+                "sentence2": query2,
+                "label": label,
+                "category": category,
+                "data_source": "COVID-19",
+                "split": "validation"
+            }
+
+            row = json.dumps(row, ensure_ascii=False)
+            f.write("{}\n".format(row))
+
+    return
+
+
+if __name__ == '__main__':
+    main()

sentence_pair.py

@@ -9,8 +9,12 @@ import datasets
 
 
 _URLS = {
+    "afqmc": "data/afqmc.jsonl",
+    "bustm": "data/bustm.jsonl",
     "ccks2018_task3": "data/ccks2018_task3.jsonl",
     "chinese_sts": "data/chinese_sts.jsonl",
+    "chip2019": "data/chip2019.jsonl",
+    "covid_19": "data/covid_19.jsonl",
     "diac2019": "data/diac2019.jsonl",
     "lcqmc": "data/lcqmc.jsonl",