create DKK-nli

.gitignore

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+.venv/

get_all.py

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+from datasets import load_dataset, load_metric, ClassLabel, Sequence, Dataset, DatasetDict, concatenate_datasets
+import pandas as pd
+
+def load_klue():
+    dataset = load_dataset('klue', 'nli')
+    dataset = dataset.filter(lambda row: row['label'] in [0, 1, 2])
+    def label_map(row):
+        labels = [
+            'entailment',
+            'neutral',
+            'contradiction',
+        ]
+        row['labell'] = list(map(lambda x: labels[x], row['label']))
+        return row
+    dataset = dataset.map(label_map, batched=True, remove_columns=['label'])
+    dataset = dataset.rename_column('labell', 'label')
+    return dataset.select_columns(['premise', 'hypothesis', 'label'])
+
+def load_dacon():
+    dataset = load_dataset('csv', data_files={'train': ['data/dacon_train_data.csv'], 'validation': 'data/dacon_test_data.csv'})
+    return dataset.select_columns(['premise', 'hypothesis', 'label'])
+
+def load_kakao():
+    kakao_snli = pd.read_csv('data/snli_1.0_train.ko.tsv', sep='\t', encoding='utf-8')
+    kakao_dev = pd.read_csv('data/xnli.dev.ko.tsv', sep='\t', encoding='utf-8')
+    kakao_train = pd.concat([kakao_dev, kakao_snli])
+    kakao_train.rename(columns = {'sentence1':'premise','sentence2':'hypothesis','gold_label':'label'}, inplace=True)
+    kakao_train = kakao_train[['premise', 'hypothesis', 'label']]
+    kakao_train.reset_index(drop=True, inplace=True)
+    kakao_test = pd.read_csv('data/xnli.test.ko.tsv', sep='\t', encoding='utf-8')
+    kakao_test.rename(columns = {'sentence1':'premise','sentence2':'hypothesis','gold_label':'label'}, inplace=True)
+    kakao_test = kakao_test[['premise', 'hypothesis', 'label']]
+    kakao_test.reset_index(drop=True, inplace=True)
+    train_ds = Dataset.from_pandas(kakao_train)
+    test_ds = Dataset.from_pandas(kakao_test)
+    return DatasetDict({
+        'train': train_ds,
+        'validation': test_ds,
+    })
+
+
+datasets = {}
+datasets['klue'] = load_klue()
+datasets['dacon'] = load_dacon()
+datasets['kakao'] = load_kakao()
+
+trains, tests = zip(*[
+    [ds_dict['train'], ds_dict['validation']]
+    for source, ds_dict in datasets.items()
+])
+
+datasets = DatasetDict({
+    'train': concatenate_datasets(trains),
+    'validation': concatenate_datasets(tests),
+})
+
+# datasets.push_to_hub("seongs1024/DKK-nli", private=True)
+
+# datasets = load_dataset('seongs1024/DKK-nli')

requirements.txt

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+datasets==2.10.0
+torch==1.9.0
+transformers==4.26.0