Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
Swedish
Size:
100K - 1M
License:
Commit
•
367454c
1
Parent(s):
105ba6b
Convert dataset to Parquet (#4)
Browse files- Convert dataset to Parquet (1e129d3bcd1ca9553e24f7f386b3498744b8acd5)
- Delete loading script (e11dd7ed28f7eea9c3dad925cbc00d286ff3e1f0)
Co-authored-by: Albert Villanova <albertvillanova@users.noreply.huggingface.co>
README.md
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@@ -19,6 +19,7 @@ task_ids:
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- sentiment-classification
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pretty_name: Swedish Reviews
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dataset_info:
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features:
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- name: text
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dtype: string
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@@ -28,19 +29,28 @@ dataset_info:
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names:
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'0': negative
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'1': positive
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config_name: plain_text
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splits:
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- name: test
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-
num_bytes:
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num_examples: 20697
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- name: validation
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-
num_bytes:
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num_examples: 20696
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- name: train
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-
num_bytes:
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num_examples: 62089
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download_size:
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dataset_size:
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---
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# Dataset Card for Swedish Reviews
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- sentiment-classification
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pretty_name: Swedish Reviews
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dataset_info:
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+
config_name: plain_text
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features:
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- name: text
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dtype: string
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names:
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'0': negative
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'1': positive
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splits:
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- name: test
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num_bytes: 6296529
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num_examples: 20697
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- name: validation
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num_bytes: 6359215
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num_examples: 20696
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- name: train
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num_bytes: 18842863
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num_examples: 62089
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download_size: 19622770
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dataset_size: 31498607
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configs:
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- config_name: plain_text
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data_files:
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- split: test
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path: plain_text/test-*
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- split: validation
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path: plain_text/validation-*
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- split: train
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path: plain_text/train-*
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default: true
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---
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# Dataset Card for Swedish Reviews
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plain_text/test-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:a33dda3140526ea954d2f19de9bf3dc3630683252a23136cbf5caba0f978e229
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size 3905563
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plain_text/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:6d837bdac3cefabaf2ac65b70084bf7cfb60488cf850907f7a67ad1be8fa926a
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+
size 11760702
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plain_text/validation-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:d7c7d60749b6d78449386a9a0984f735b397ea0b1d0e859fd622af0c908410f8
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+
size 3956505
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swedish_reviews.py
DELETED
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# coding=utf-8
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# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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-
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# Lint as: python3
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-
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-
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import csv
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import os
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-
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import datasets
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from datasets.tasks import TextClassification
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_DOWNLOAD_URL = "https://raw.githubusercontent.com/timpal0l/swedish-sentiment/main/swedish_sentiment.zip"
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_TRAIN_FILE = "train.csv"
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_VAL_FILE = "dev.csv"
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_TEST_FILE = "test.csv"
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_CITATION = ""
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_DESCRIPTION = "Swedish reviews scarped from various public available websites"
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class SwedishReviews(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name="plain_text",
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version=datasets.Version("1.0.0", ""),
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description="Plain text import of the Swedish Reviews dataset",
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)
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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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{"text": datasets.Value("string"), "label": datasets.ClassLabel(names=["negative", "positive"])}
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),
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supervised_keys=None,
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homepage="https://github.com/timpal0l/swedish-sentiment",
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citation=_CITATION,
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task_templates=[TextClassification(text_column="text", label_column="label")],
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)
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-
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def _split_generators(self, dl_manager):
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dl_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={"filepath": os.path.join(dl_dir, _TEST_FILE)},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={"filepath": os.path.join(dl_dir, _VAL_FILE)},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={"filepath": os.path.join(dl_dir, _TRAIN_FILE)},
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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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"""This function returns the examples in the raw (text) form."""
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with open(filepath, encoding="utf-8") as f:
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reader = csv.DictReader(f)
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for idx, row in enumerate(reader):
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yield idx, {
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"text": row["text"],
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"label": row["sentiment"],
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}
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