Update files from the datasets library (from 1.5.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.5.0

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README.md

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+---
+annotations_creators:
+- found
+language_creators:
+- found
+languages:
+- ro
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- sentiment-classification
+---
+
+# Dataset Card for RoSent
+
+## Table of Contents
+- [Dataset Card for RoSent](#dataset-card-for-ro_sent)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+    - [Annotations](#annotations)
+      - [Annotation process](#annotation-process)
+      - [Who are the annotators?](#who-are-the-annotators)
+    - [Personal and Sensitive Information](#personal-and-sensitive-information)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+  - [Additional Information](#additional-information)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+    - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [GitHub](https://github.com/dumitrescustefan/Romanian-Transformers/tree/examples/examples/sentiment_analysis)
+- **Repository:** [GitHub](https://github.com/dumitrescustefan/Romanian-Transformers/tree/examples/examples/sentiment_analysis)
+- **Paper:** [arXiv preprint](https://arxiv.org/pdf/2009.08712.pdf)
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+This dataset is a Romanian Sentiment Analysis dataset. It is present in a processed form, as used by the authors of [`Romanian Transformers`](https://github.com/dumitrescustefan/Romanian-Transformers) in their examples and based on the original data present in at [this GitHub repository](https://github.com/katakonst/sentiment-analysis-tensorflow). The original data contains product and movie reviews in Romanian.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+This dataset is present in Romanian language.
+
+## Dataset Structure
+
+### Data Instances
+
+An instance from the `train` split:
+```
+{'id': '0', 'label': 1, 'original_id': '0', 'sentence': 'acest document mi-a deschis cu adevarat ochii la ceea ce oamenii din afara statelor unite s-au gandit la atacurile din 11 septembrie. acest film a fost construit in mod expert si prezinta acest dezastru ca fiind mai mult decat un atac asupra pamantului american. urmarile acestui dezastru sunt previzionate din multe tari si perspective diferite. cred ca acest film ar trebui sa fie mai bine distribuit pentru acest punct. de asemenea, el ajuta in procesul de vindecare sa vada in cele din urma altceva decat stirile despre atacurile teroriste. si unele dintre piese sunt de fapt amuzante, dar nu abuziv asa. acest film a fost extrem de recomandat pentru mine, si am trecut pe acelasi sentiment.'}
+```
+
+### Data Fields
+
+- `original_id`: a `string` feature containing the original id from the file.
+- `id`: a `string` feature .
+- `sentence`: a `string` feature.
+- `label`: a classification label, with possible values including `negative` (0), `positive` (1).
+
+### Data Splits
+
+This dataset has two splits: `train` with 17941 examples, and `test` with 11005 examples.
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+The source dataset is present at the [this GitHub repository](https://github.com/katakonst/sentiment-analysis-tensorflow) and is based on product and movie reviews. The original source is unknown.
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+Stefan Daniel Dumitrescu, Andrei-Marious Avram, Sampo Pyysalo, [@katakonst](https://github.com/katakonst)
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+```
+@article{dumitrescu2020birth,
+  title={The birth of Romanian BERT},
+  author={Dumitrescu, Stefan Daniel and Avram, Andrei-Marius and Pyysalo, Sampo},
+  journal={arXiv preprint arXiv:2009.08712},
+  year={2020}
+}
+```
+
+### Contributions
+
+Thanks to [@gchhablani](https://github.com/gchhablani) and [@iliemihai](https://github.com/iliemihai) for adding this dataset.

dataset_infos.json

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+{"default": {"description": "This dataset is a Romanian Sentiment Analysis dataset.\nIt is present in a processed form, as used by the authors of `Romanian Transformers`\nin their examples and based on the original data present in\n`https://github.com/katakonst/sentiment-analysis-tensorflow`.\n", "citation": "\n@article{dumitrescu2020birth,\n  title={The birth of Romanian BERT},\n  author={Dumitrescu, Stefan Daniel and Avram, Andrei-Marius and Pyysalo, Sampo},\n  journal={arXiv preprint arXiv:2009.08712},\n  year={2020}\n}\n", "homepage": "https://github.com/dumitrescustefan/Romanian-Transformers/tree/examples/examples/sentiment_analysis", "license": "", "features": {"original_id": {"dtype": "string", "id": null, "_type": "Value"}, "id": {"dtype": "string", "id": null, "_type": "Value"}, "sentence": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["negative", "positive"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": {"input": "sentence", "output": "label"}, "builder_name": "ro_sent", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 8367687, "num_examples": 17941, "dataset_name": "ro_sent"}, "test": {"name": "test", "num_bytes": 6837430, "num_examples": 11005, "dataset_name": "ro_sent"}}, "download_checksums": {"https://raw.githubusercontent.com/dumitrescustefan/Romanian-Transformers/examples/examples/sentiment_analysis/ro/train.csv": {"num_bytes": 8048544, "checksum": "5b5f36aba3895e75832d1f084459f23ebeec0418d55ab1fbaa015d154879ed0f"}, "https://raw.githubusercontent.com/dumitrescustefan/Romanian-Transformers/examples/examples/sentiment_analysis/ro/test.csv": {"num_bytes": 6651513, "checksum": "2491ca36849e7055f1497575fa691f91671d64b7365f43a3be84ce552b6b65bd"}}, "download_size": 14700057, "post_processing_size": null, "dataset_size": 15205117, "size_in_bytes": 29905174}}

dummy/default/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:516253ed4c61649e4d72f55ee218d805d2df1fa65fc340f114720ca5e8f621bc
+size 4654

ro_sent.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.
+"""Introduction in a Romanian sentiment dataset."""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+
+import datasets
+from datasets.builder import BuilderConfig
+
+
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """
+@article{dumitrescu2020birth,
+  title={The birth of Romanian BERT},
+  author={Dumitrescu, Stefan Daniel and Avram, Andrei-Marius and Pyysalo, Sampo},
+  journal={arXiv preprint arXiv:2009.08712},
+  year={2020}
+}
+"""
+
+_DESCRIPTION = """\
+This dataset is a Romanian Sentiment Analysis dataset.
+It is present in a processed form, as used by the authors of `Romanian Transformers`
+in their examples and based on the original data present in
+`https://github.com/katakonst/sentiment-analysis-tensorflow`. The original dataset is collected
+from product and movie reviews in Romanian.
+"""
+
+_HOMEPAGE = "https://github.com/dumitrescustefan/Romanian-Transformers/tree/examples/examples/sentiment_analysis"
+
+_LICENSE = ""
+
+_URL = (
+    "https://raw.githubusercontent.com/dumitrescustefan/Romanian-Transformers/examples/examples/sentiment_analysis/ro/"
+)
+_URLs = {"train": _URL + "train.csv", "test": _URL + "test.csv"}
+
+
+class RoSent(datasets.GeneratorBasedBuilder):
+    """Romanian Sentiment Analysis dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        BuilderConfig(
+            name="default",
+            version=VERSION,
+            description="This configuration handles all of Romanian Sentiment Analysis dataset.",
+        ),
+    ]
+
+    def _info(self):
+
+        features = datasets.Features(
+            {
+                "original_id": datasets.Value("string"),
+                "id": datasets.Value("string"),
+                "sentence": datasets.Value("string"),
+                "label": datasets.ClassLabel(names=["negative", "positive"]),  # 0 is negative
+            }
+        )
+
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=("sentence", "label"),
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+
+        paths = dl_manager.download(_URLs)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": paths["train"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": paths["test"]},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """ Yields examples. """
+
+        with open(filepath, encoding="utf-8") as f:
+            data = csv.DictReader(f, delimiter=",", quotechar='"')
+
+            for row_id, row in enumerate(data):
+                yield row_id, {
+                    "original_id": row["index"] if "index" in row.keys() else row[""],  # test has no 'index' key
+                    "id": str(row_id),  # this is needed because indices are repeated in the files.
+                    "sentence": row["text"],
+                    "label": int(row["label"]),
+                }