---
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.