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README.md

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----
-task_categories:
-- text-classification
-language:
-- zh
-- en
----

default/emotion_chinese_english-test.parquet

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+size 11249

default/emotion_chinese_english-train.parquet

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default/emotion_chinese_english-validation.parquet

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emotion_chinese_english.py

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-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# 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.
-"""emotion_chinese_english dataset: A multilingual emotion dataset of wilde's children's literature"""
-
-
-import datasets
-
-
-_DESCRIPTION = """\
-The emotion_chinese_english dataset is a multilingual emotion dataset annotated by language experts under a project. \
-The dataset can be used for tasks such as multilingual (Chinese and English) emotion classification and identification.
-"""
-
-
-_HOMEPAGE = "https://github.com/nana-lyj/emotion_chinese_english"
-
-_URLS = {
-    "train": f"https://raw.githubusercontent.com/nana-lyj/emotion_chinese_english/main/data/train.tsv",
-    "dev": f"https://raw.githubusercontent.com/nana-lyj/emotion_chinese_english/main/data/dev.tsv",
-    "test": f"https://raw.githubusercontent.com/nana-lyj/emotion_chinese_english/main/data/test.tsv",
-}
-
-_LABEL_MAPPING = {0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8}
-
-
-class emotionchineseenglish(datasets.GeneratorBasedBuilder):
-    """emotion_chinese_english dataset: A multilingual emotion dataset of wilde's children's literature"""
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("int32"),
-                    "sentence": datasets.Value("string"),
-                    "label": datasets.ClassLabel(names=["joy", "sadness", "anger", "fear", "trust", "disgust", "surprise", "anticipation", "other"]),
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download(_URLS)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding="utf-8") as f:
-            lines = f.readlines()
-            for line in lines:
-                fields = line.strip().split("\t")
-                idx, sentence, label = fields
-                label = _LABEL_MAPPING[int(label)]
-                yield int(idx), {"id": int(idx), "sentence": sentence, "label": label}