Datasets:
abhik1505040
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Parent(s):
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Create dailydialogue_bn.py
Browse files- dailydialogue_bn.py +98 -0
dailydialogue_bn.py
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"""DailyDialogue Bengali Dataset"""
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import os
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import json
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import datasets
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_CITATION = """\
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@inproceedings{bhattacharjee-etal-2023-banglanlg,
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title = "{B}angla{NLG} and {B}angla{T}5: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in {B}angla",
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author = "Bhattacharjee, Abhik and
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Hasan, Tahmid and
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Ahmad, Wasi Uddin and
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Shahriyar, Rifat",
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booktitle = "Findings of the Association for Computational Linguistics: EACL 2023",
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month = may,
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year = "2023",
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address = "Dubrovnik, Croatia",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2023.findings-eacl.54",
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pages = "726--735",
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abstract = "This work presents {`}BanglaNLG,{'} a comprehensive benchmark for evaluating natural language generation (NLG) models in Bangla, a widely spoken yet low-resource language. We aggregate six challenging conditional text generation tasks under the BanglaNLG benchmark, introducing a new dataset on dialogue generation in the process. Furthermore, using a clean corpus of 27.5 GB of Bangla data, we pretrain {`}BanglaT5{'}, a sequence-to-sequence Transformer language model for Bangla. BanglaT5 achieves state-of-the-art performance in all of these tasks, outperforming several multilingual models by up to 9{\%} absolute gain and 32{\%} relative gain. We are making the new dialogue dataset and the BanglaT5 model publicly available at https://github.com/csebuetnlp/BanglaNLG in the hope of advancing future research on Bangla NLG.",
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}
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"""
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_DESCRIPTION = """\
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DailyDialogue (bengali) has been derived from the original English dataset.
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"""
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_HOMEPAGE = "https://github.com/csebuetnlp/BanglaNLG"
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_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)"
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_URL = "https://huggingface.co/datasets/csebuetnlp/dailydialogue_bn/resolve/main/data/dailydialogue_bn.tar.bz2"
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_VERSION = datasets.Version("0.0.1")
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class DailydialogueBn(datasets.GeneratorBasedBuilder):
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"""DailyDialogue Bengali Dataset"""
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name="dailydialogue_bn",
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version=_VERSION,
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description=_DESCRIPTION,
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)
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]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"id": datasets.Value("string"),
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"dialogue": datasets.features.Sequence(
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datasets.Value("string")
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),
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}
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),
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supervised_keys=None,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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data_dir = os.path.join(dl_manager.download_and_extract(_URL), "dailydialogue_bn")
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepath": os.path.join(data_dir, "train.jsonl"),
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath": os.path.join(data_dir, "test.jsonl"),
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"filepath": os.path.join(data_dir, "validation.jsonl"),
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},
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),
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]
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def _generate_examples(self, filepath):
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"""Yields examples as (key, example) tuples."""
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with open(filepath, encoding="utf-8") as f:
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for i, line in enumerate(f):
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data = json.loads(line.strip())['source']
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yield i, {
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"id": str(i),
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"dialogue": data
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}
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