Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
French
Size:
100K - 1M
License:
Update files from the datasets library (from 1.8.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.8.0
- allocine.py +2 -0
- dataset_infos.json +1 -1
allocine.py
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@@ -5,6 +5,7 @@ import json
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import os
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import datasets
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_CITATION = """\
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@@ -65,6 +66,7 @@ class AllocineDataset(datasets.GeneratorBasedBuilder):
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supervised_keys=None,
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homepage="https://github.com/TheophileBlard/french-sentiment-analysis-with-bert",
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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import os
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import datasets
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from datasets.tasks import TextClassification
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_CITATION = """\
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supervised_keys=None,
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homepage="https://github.com/TheophileBlard/french-sentiment-analysis-with-bert",
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citation=_CITATION,
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task_templates=[TextClassification(text_column="review", label_column="label")],
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)
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def _split_generators(self, dl_manager):
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dataset_infos.json
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{"allocine": {"description": " Allocine Dataset: A Large-Scale French Movie Reviews Dataset.\n This is a dataset for binary sentiment classification, made of user reviews scraped from Allocine.fr.\n It contains 100k positive and 100k negative reviews divided into 3 balanced splits: train (160k reviews), val (20k) and test (20k).\n", "citation": "@misc{blard2019allocine,\n author = {Blard, Theophile},\n title = {french-sentiment-analysis-with-bert},\n year = {2020},\n publisher = {GitHub},\n journal = {GitHub repository},\n howpublished={\\url{https://github.com/TheophileBlard/french-sentiment-analysis-with-bert}},\n}\n", "homepage": "https://github.com/TheophileBlard/french-sentiment-analysis-with-bert", "license": "", "features": {"review": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["neg", "pos"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "supervised_keys": null, "builder_name": "allocine_dataset", "config_name": "allocine", "version": {"version_str": "1.0.0", "description": null, "
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{"allocine": {"description": " Allocine Dataset: A Large-Scale French Movie Reviews Dataset.\n This is a dataset for binary sentiment classification, made of user reviews scraped from Allocine.fr.\n It contains 100k positive and 100k negative reviews divided into 3 balanced splits: train (160k reviews), val (20k) and test (20k).\n", "citation": "@misc{blard2019allocine,\n author = {Blard, Theophile},\n title = {french-sentiment-analysis-with-bert},\n year = {2020},\n publisher = {GitHub},\n journal = {GitHub repository},\n howpublished={\\url{https://github.com/TheophileBlard/french-sentiment-analysis-with-bert}},\n}\n", "homepage": "https://github.com/TheophileBlard/french-sentiment-analysis-with-bert", "license": "", "features": {"review": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["neg", "pos"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "text-classification", "text_column": "review", "label_column": "label", "labels": ["neg", "pos"]}], "builder_name": "allocine_dataset", "config_name": "allocine", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 91330696, "num_examples": 160000, "dataset_name": "allocine_dataset"}, "validation": {"name": "validation", "num_bytes": 11546250, "num_examples": 20000, "dataset_name": "allocine_dataset"}, "test": {"name": "test", "num_bytes": 11547697, "num_examples": 20000, "dataset_name": "allocine_dataset"}}, "download_checksums": {"https://github.com/TheophileBlard/french-sentiment-analysis-with-bert/raw/master/allocine_dataset/data.tar.bz2": {"num_bytes": 66625305, "checksum": "8c49a8cac783da201697ed1a91b36d2f6618222b3b7ea1c2996f2a3fbc37dfb4"}}, "download_size": 66625305, "post_processing_size": null, "dataset_size": 114424643, "size_in_bytes": 181049948}}
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