Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- crowdsourced
+language_creators:
+- expert-generated
+languages:
+- en
+licenses:
+- cc-by-4-0
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- extended|other-ImageFlickr and SemEval-2012 STS MSR-Video Descriptions
+task_categories:
+- text-classification
+- text-scoring
+task_ids:
+- natural-language-inference
+- semantic-similarity-scoring
+---
+
+# Dataset Card for SemEval 2014 - Task 1
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [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)
+
+## Dataset Description
+
+- **Homepage:** [SemEval-2014 Task 1](https://alt.qcri.org/semeval2014/task1/)
+- **Repository:**
+- **Paper:** [Aclweb](https://www.aclweb.org/anthology/S14-2001/)
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### 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
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]

dataset_infos.json

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+{"default": {"description": "The SemEval-2014 Task 1 focuses on Evaluation of Compositional Distributional Semantic Models\non Full Sentences through Semantic Relatedness and Entailment. The task was designed to\npredict the degree of relatedness between two sentences and to detect the entailment\nrelation holding between them.\n", "citation": "@inproceedings{inproceedings,\nauthor = {Marelli, Marco and Bentivogli, Luisa and Baroni, Marco and Bernardi, Raffaella and Menini, Stefano and Zamparelli, Roberto},\nyear = {2014},\nmonth = {08},\npages = {},\ntitle = {SemEval-2014 Task 1: Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment},\ndoi = {10.3115/v1/S14-2001}\n}\n", "homepage": "https://alt.qcri.org/semeval2014/task1/", "license": "", "features": {"sentence_pair_id": {"dtype": "int64", "id": null, "_type": "Value"}, "premise": {"dtype": "string", "id": null, "_type": "Value"}, "hypothesis": {"dtype": "string", "id": null, "_type": "Value"}, "relatedness_score": {"dtype": "float32", "id": null, "_type": "Value"}, "entailment_judgment": {"num_classes": 3, "names": ["NEUTRAL", "ENTAILMENT", "CONTRADICTION"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "sem_eval2014_task1", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 540296, "num_examples": 4500, "dataset_name": "sem_eval2014_task1"}, "test": {"name": "test", "num_bytes": 592320, "num_examples": 4927, "dataset_name": "sem_eval2014_task1"}, "validation": {"name": "validation", "num_bytes": 60981, "num_examples": 500, "dataset_name": "sem_eval2014_task1"}}, "download_checksums": {"https://alt.qcri.org/semeval2014/task1/data/uploads/sick_train.zip": {"num_bytes": 87341, "checksum": "097295b8ad526d80cefc7a56444424d7f39020729e589618b4d40bb654195e1a"}, "https://alt.qcri.org/semeval2014/task1/data/uploads/sick_test_annotated.zip": {"num_bytes": 93443, "checksum": "8a44227bb1f9d7249c0ac10cac54c5a6cc579195982b7f33fb0e3ebf5226b594"}, "https://alt.qcri.org/semeval2014/task1/data/uploads/sick_trial.zip": {"num_bytes": 16446, "checksum": "8a81f25e2807f64a9419218cf4bca1eca86f2b74de03b1311cad6e3262a15e94"}}, "download_size": 197230, "post_processing_size": null, "dataset_size": 1193597, "size_in_bytes": 1390827}}

dummy/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:06e7a4748e6d1e8343ad6aa640ea85c6081b8b2988b7f45a75e69c3c804ed57d
+size 2650

sem_eval_2014_task_1.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.
+"""The SemEval-2014 Task 1 on Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Entailment"""
+
+from __future__ import absolute_import, division, print_function
+
+import os
+
+import datasets
+
+
+_CITATION = """\
+@inproceedings{inproceedings,
+author = {Marelli, Marco and Bentivogli, Luisa and Baroni, Marco and Bernardi, Raffaella and Menini, Stefano and Zamparelli, Roberto},
+year = {2014},
+month = {08},
+pages = {},
+title = {SemEval-2014 Task 1: Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment},
+doi = {10.3115/v1/S14-2001}
+}
+"""
+
+_DESCRIPTION = """\
+The SemEval-2014 Task 1 focuses on Evaluation of Compositional Distributional Semantic Models
+on Full Sentences through Semantic Relatedness and Entailment. The task was designed to
+predict the degree of relatedness between two sentences and to detect the entailment
+relation holding between them.
+"""
+
+_HOMEPAGE = "https://alt.qcri.org/semeval2014/task1/"
+
+_URLs = {
+    "train": "https://alt.qcri.org/semeval2014/task1/data/uploads/sick_train.zip",
+    "test": "https://alt.qcri.org/semeval2014/task1/data/uploads/sick_test_annotated.zip",
+    "validation": "https://alt.qcri.org/semeval2014/task1/data/uploads/sick_trial.zip",
+}
+
+
+class SemEval2014Task1(datasets.GeneratorBasedBuilder):
+    """The SemEval-2014 Task 1 on Evaluation of Compositional
+    Distributional Semantic Models on Full Sentences through
+    Semantic Relatedness and Entailment
+    """
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        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=datasets.Features(
+                {
+                    "sentence_pair_id": datasets.Value("int64"),
+                    "premise": datasets.Value("string"),
+                    "hypothesis": datasets.Value("string"),
+                    "relatedness_score": datasets.Value("float32"),
+                    "entailment_judgment": datasets.features.ClassLabel(
+                        names=["NEUTRAL", "ENTAILMENT", "CONTRADICTION"]
+                    ),
+                }
+            ),
+            # 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=None,
+            # Homepage of the dataset for documentation
+            homepage="https://alt.qcri.org/semeval2014/task1/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # dl_manager is a datasets.download.DownloadManager that can be used to
+        # download and extract URLs
+        dl_dir = dl_manager.download_and_extract(_URLs)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join(dl_dir["train"], "SICK_train.txt"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(dl_dir["test"], "SICK_test_annotated.txt"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": os.path.join(dl_dir["validation"], "SICK_trial.txt"),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """ Yields examples. """
+        with open(filepath, "r", encoding="us-ascii") as file:
+            lines = file.readlines()
+
+            for idx in range(1, len(lines)):
+                features = lines[idx].split("\t")
+                sentence_pair_id = features[0]
+                premise = features[1]
+                hypothesis = features[2]
+                relatedness_score = float(features[3])
+                entailment_judgment = features[4].strip("\n")
+
+                yield idx, {
+                    "sentence_pair_id": sentence_pair_id,
+                    "premise": premise,
+                    "hypothesis": hypothesis,
+                    "relatedness_score": relatedness_score,
+                    "entailment_judgment": entailment_judgment,
+                }