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aceval.py

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+# 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.
+
+import os
+import datasets
+import pandas as pd
+
+
+_CITATION = """\
+@misc{wei2024aceval,
+      title={AC-EVAL: Evaluating Ancient Chinese Language Understanding in Large Language Models}, 
+      author={Yuting Wei and Yuanxing Xu and Xinru Wei and Simin Yang and Yangfu Zhu and Yuqing Li and Di Liu and Bin Wu},
+      year={2024},
+      eprint={2403.06574},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+AC-EVAL presents a thorough evaluation suite for Large Language Models (LLMs) focusing on ancient Chinese, covering eras from the Pre-Qin period to the Qing dynasty. This suite includes 3245 multi-choice questions across 3 levels of difficulty and 13 diverse tasks.
+"""
+
+_HOMEPAGE = "https://github.com/yuting-wei/AC-EVAL"
+
+_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License"
+
+_URL = r"https://huggingface.co/datasets/yuting-wei/aceval/resolve/main/aceval.zip"
+
+task_list = [
+    'historical_facts', 
+    'geography',
+    'social_customs',
+    'art_and_cultural_heritage',
+    'philosophy_and_religion',
+    'lexical_pragmatics_analysis',
+    'allusions_and_idioms',
+    'word_sense_disambiguation',
+    'translation',
+    'event_extraction',
+    'sentence_pauses',
+    'summarization_and_analysis',
+    'poetry_appreciation'
+]
+
+
+class ACEVALConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super().__init__(version=datasets.Version("1.0.0"), **kwargs)
+
+
+class ACEVAL(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        ACEVALConfig(
+            name=task_name
+        ) 
+        for task_name in task_list
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "Question": datasets.Value("string"),
+                "A": datasets.Value("string"),
+                "B": datasets.Value("string"),
+                "C": datasets.Value("string"),
+                "D": datasets.Value("string"),
+                "Answer": datasets.Value("string"),
+                "Explanation":datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download_and_extract(_URL)
+        task_name = self.config.name
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, f"test/{task_name}.xlsx"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split("dev"),
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, f"dev/{task_name}.xlsx"),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        df = pd.read_excel(filepath, encoding="utf-8")
+        for i, instance in enumerate(df.to_dict(orient="records")):
+            if "answer" not in instance.keys():
+                instance["answer"]=""
+            if "explanation" not in instance.keys():
+                instance["explanation"]=""
+            yield i, instance

aceval.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a379e089a0708421cf8c625644b00b08d3da2b43c2f61a606e52d69822475a03
+size 1968794