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Update files from the datasets library (from 1.2.0)

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

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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.bin filter=lfs diff=lfs merge=lfs -text
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+ *.bin.* filter=lfs diff=lfs merge=lfs -text
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+ *.bz2 filter=lfs diff=lfs merge=lfs -text
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+ *.ftz filter=lfs diff=lfs merge=lfs -text
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+ *.joblib filter=lfs diff=lfs merge=lfs -text
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+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
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+ *.model filter=lfs diff=lfs merge=lfs -text
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+ *.msgpack filter=lfs diff=lfs merge=lfs -text
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+ *.onnx filter=lfs diff=lfs merge=lfs -text
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+ *.parquet filter=lfs diff=lfs merge=lfs -text
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+ *.pb filter=lfs diff=lfs merge=lfs -text
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+ *.rar filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tflite filter=lfs diff=lfs merge=lfs -text
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+ *tfevents* filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ annotations_creators:
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+ - crowdsourced
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+ - found
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+ language_creators:
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+ - crowdsourced
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+ - found
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+ languages:
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+ - en
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+ licenses:
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+ - unknown
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+ multilinguality:
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+ - monolingual
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+ size_categories:
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+ - 1K<n<10K
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+ source_datasets:
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+ - extended|other-nus-sms-corpus
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+ task_categories:
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+ - text-classification
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+ task_ids:
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+ - intent-classification
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+ ---
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+
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+ # Dataset Card for [Dataset Name]
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+
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+ ## Table of Contents
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks](#supported-tasks-and-leaderboards)
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+ - [Languages](#languages)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-instances)
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+ - [Data Splits](#data-instances)
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+ - [Dataset Creation](#dataset-creation)
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+ - [Curation Rationale](#curation-rationale)
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+ - [Source Data](#source-data)
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+ - [Annotations](#annotations)
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+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
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+ - [Considerations for Using the Data](#considerations-for-using-the-data)
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+ - [Social Impact of Dataset](#social-impact-of-dataset)
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+ - [Discussion of Biases](#discussion-of-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Additional Information](#additional-information)
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+ - [Dataset Curators](#dataset-curators)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+
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+ ## Dataset Description
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+
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+ - **Homepage:** http://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection
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+ - **Repository:**
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+ - **Paper:** Almeida, T.A., Gomez Hidalgo, J.M., Yamakami, A. Contributions to the study of SMS Spam Filtering: New Collection and Results. Proceedings of the 2011 ACM Symposium on Document Engineering (ACM DOCENG'11), Mountain View, CA, USA, 2011.
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+ - **Leaderboard:**
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+ - **Point of Contact:**
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+
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+ ### Dataset Summary
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+
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+ The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research.
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+ It has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.
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+
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+ ### Supported Tasks and Leaderboards
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+
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+ [More Information Needed]
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+
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+ ### Languages
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+
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+ English
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ [More Information Needed]
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+
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+ ### Data Fields
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+
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+ - sms: the sms message
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+ - label: indicating if the sms message is ham or spam, ham means it is not spam
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+
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+ ### Data Splits
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+
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+ [More Information Needed]
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+
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+ ## Dataset Creation
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+
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+ ### Curation Rationale
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+
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+ [More Information Needed]
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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+
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+ [More Information Needed]
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+
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+ #### Who are the source language producers?
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+
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+ [More Information Needed]
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+
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+ ### Annotations
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+
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+ #### Annotation process
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+
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+ [More Information Needed]
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+
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+ #### Who are the annotators?
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+
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+ [More Information Needed]
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+
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+ ### Personal and Sensitive Information
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+
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+ [More Information Needed]
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+
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+ ## Considerations for Using the Data
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+
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+ ### Social Impact of Dataset
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+
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+ [More Information Needed]
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+
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+ ### Discussion of Biases
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+
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+ [More Information Needed]
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+
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+ ### Other Known Limitations
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+
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+ [More Information Needed]
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+
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+ ## Additional Information
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+
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+ ### Dataset Curators
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+
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+ [More Information Needed]
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+
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+ ### Licensing Information
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+
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+ [More Information Needed]
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+
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+ ### Citation Information
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+
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+ @inproceedings{Almeida2011SpamFiltering,
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+ title={Contributions to the Study of SMS Spam Filtering: New Collection and Results},
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+ author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami},
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+ year={2011},
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+ booktitle = "Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)",
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+ }
dataset_infos.json ADDED
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+ {"plain_text": {"description": "The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research. \nIt has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.\n", "citation": "@inproceedings{Almeida2011SpamFiltering,\n title={Contributions to the Study of SMS Spam Filtering: New Collection and Results},\n author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami},\n year={2011},\n booktitle = \"Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)\",\n}\n", "homepage": "http://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection", "license": "", "features": {"sms": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["ham", "spam"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "sms_spam", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 521756, "num_examples": 5574, "dataset_name": "sms_spam"}}, "download_checksums": {"http://archive.ics.uci.edu/ml/machine-learning-databases/00228/smsspamcollection.zip": {"num_bytes": 203415, "checksum": "1587ea43e58e82b14ff1f5425c88e17f8496bfcdb67a583dbff9eefaf9963ce3"}}, "download_size": 203415, "post_processing_size": null, "dataset_size": 521756, "size_in_bytes": 725171}}
dummy/plain_text/1.0.0/dummy_data.zip ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:105b0e273e0da2af4b3dd786241ae4eb12bf36d1c41f67f7f82dd41e305ff77a
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+ size 733
sms_spam.py ADDED
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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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+ """SMS Spam Collection Data Set"""
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+
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+ from __future__ import absolute_import, division, print_function
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+
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+ import os
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+
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+ import datasets
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+
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+
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+ _CITATION = """\
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+ @inproceedings{Almeida2011SpamFiltering,
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+ title={Contributions to the Study of SMS Spam Filtering: New Collection and Results},
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+ author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami},
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+ year={2011},
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+ booktitle = "Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)",
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+ }
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+ """
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+
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+ _DESCRIPTION = """\
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+ The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research.
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+ It has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.
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+ """
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+
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+ _DATA_URL = "http://archive.ics.uci.edu/ml/machine-learning-databases/00228/smsspamcollection.zip"
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+
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+
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+ class SmsSpam(datasets.GeneratorBasedBuilder):
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+ """SMS Spam Collection Data Set"""
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+
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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 SMS Spam Collection Data Set",
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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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+ {
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+ "sms": datasets.Value("string"),
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+ "label": datasets.features.ClassLabel(names=["ham", "spam"]),
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+ }
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+ ),
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+ supervised_keys=("sms", "label"),
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+ homepage="http://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection",
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+ citation=_CITATION,
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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(_DATA_URL)
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(dl_dir, "SMSSpamCollection")}
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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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+
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+ with open(filepath, encoding="utf-8") as sms_file:
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+ for idx, line in enumerate(sms_file):
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+ fields = line.split("\t")
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+
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+ if fields[0] == "ham":
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+ label = 0
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+ else:
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+ label = 1
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+
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+ yield idx, {
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+ "sms": fields[1],
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+ "label": label,
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+ }