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--- |
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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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- name: sentiment |
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dtype: float64 |
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splits: |
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- name: train |
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num_bytes: 163565 |
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num_examples: 1464 |
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download_size: 96001 |
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dataset_size: 163565 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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license: apache-2.0 |
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task_categories: |
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- text-classification |
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language: |
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- en |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Compare Models |
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## Overview |
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This dataset is a reduced version of [Tweets Dataset](https://huggingface.co/datasets/AiresPucrs/tweets). |
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Which in turn is a reduced version of the original dataset:[Crowdflower's Data for Everyone library](https://data.world/crowdflower). |
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This dataset contains texts from customers posted on Twitter regarding their air travel experiences, |
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whether they were upset, neutral, or satisfied with the trip and the airline's service. |
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## Dataset Details |
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This version contains whether the sentiment of the tweets in this set was positive, neutral, or negative. |
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The dataset was used in |
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this notebook [model_extraction_nlp](https://github.com/Nkluge-correa/TeenyTinyCastle/blob/master/ML-Adversarial/model_extraction_nlp.ipynb). |
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- Dataset Name: compare-models |
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- Language: English |
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- Total Size: 1,464 |
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## Contents |
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The dataset consists of a data frame with the following column: |
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- text |
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- sentiment |
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```bash |
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{ |
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"text": "usairways how is it that my flt to ewr was cancelled flightled yet flts to nyc from usairways are still flying", |
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"sentiment:" 0, |
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"text: " "jetblue do they have to depart from washington dc", |
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"sentiment:" 1, |
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"text: " "southwestair youre my early frontrunner for best airline oscars2016", |
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"sentiment:" 2, |
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} |
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``` |
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## How to use |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset('AiresPucrs/compare-models', split='train') |
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``` |
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## License |
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This dataset is licensed under the Apache License, version 2.0. |
