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