---
license: mpl-2.0
task_categories:
- text-classification
language:
- tl
size_categories:
- 1K<n<10K
dataset_info:
  features:
  - name: label
    dtype:
      class_label:
        names:
          '0': 1 star
          '1': 2 star
          '2': 3 stars
          '3': 4 stars
          '4': 5 stars
  - name: text
    dtype: string
tags:
- reviews
- shopee
---

# Dataset Card for Dataset Name

## Dataset Description

- **Homepage:** 
- **Repository:** 
- **Paper:** [Enhancement to Low Resource Text Classification via Sequential Transfer Learning](#)
- **Leaderboard:** 
- **Point of Contact:** [Neil Riego](mailto:neilchristianriego3@gmail.com)

### Dataset Summary

This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

Tagalog (TL)

## Dataset Structure

### Data Instances

A typical data point, comprises of a text and the corresponding label.

An example from the YelpReviewFull test set looks as follows:
```
{
    'label': 2,
    'text': 'Madaling masira yung sa may sinisintasan nya. Wala rin syang box. Sana mas ginawa pa na matibay para sana sulit yung pagkakabili'
}
```

### Data Fields

- 'text': The review texts are escaped using double quotes ("), and any internal double quote is escaped by 2 double quotes ("").
- 'label': Corresponds to the score associated with the review (between 1 and 5).

### Data Splits

The Shopee reviews tl 15 dataset is constructed by randomly taking 2100 training samples and 450 samples for testing and validation for each review star from 1 to 5.
In total there are 10500 trainig samples and 2250 each in validation and testing samples.

## 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]

### Contributions

[More Information Needed]