Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Languages:
Vietnamese
Size:
10K - 100K
License:
File size: 3,498 Bytes
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---
dataset_info:
features:
- name: text
dtype: string
- name: lang
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 4512776
num_examples: 25942
- name: validation
num_bytes: 644682
num_examples: 3706
- name: test
num_bytes: 1289538
num_examples: 7413
download_size: 4254592
dataset_size: 6446996
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
license: mit
task_categories:
- text-classification
language:
- vi
---
# Multilingual Text Classification Dataset
This dataset is designed for **multilingual text classification** tasks.
It includes labeled text samples across **8 languages**, making it ideal for training and evaluating models on **cross-lingual transfer**, **language identification**, and **multilingual understanding**.
## Dataset Overview
| Split | # Examples | Size (bytes) |
| ---------- | ---------- | ------------- |
| Train | 18,657 | 2,651,248 |
| Validation | 2,665 | 378,709 |
| Test | 5,331 | 757,560 |
| **Total** | **26,653** | **3,787,517** |
**Total Download Size:** 2.6 MB
**Total Dataset Size:** 3.8 MB
**Task Type:** Text Classification
## Data Fields
| Field | Type | Description |
| ------- | -------- | -------------------------------------------------- |
| `text` | `string` | The input text sample. |
| `lang` | `string` | The ISO 639-3 language code of the text. |
| `label` | `int64` | The integer label representing the language class. |
## Language Labels
| Language | Code | Label ID |
| --------------- | ----- | -------- |
| German | `deu` | 0 |
| Chinese | `zho` | 1 |
| Amharic | `amh` | 2 |
| Hindi | `hin` | 3 |
| Arabic | `arb` | 4 |
| Hausa | `hau` | 5 |
| Turkish | `tur` | 6 |
| Urdu | `urd` | 7 |
| Spanish | `spa` | 8 |
| Persian (Farsi) | `fas` | 9 |
| English | `eng` | 10 |
| Nepali | `nep` | 11 |
## Intended Uses
* Multilingual language classification
* Cross-lingual and zero-shot evaluation
* Benchmarking multilingual embeddings (e.g., mBERT, XLM-R, LaBSE)
* Studying language similarity and confusion patterns
## Usage Example
You can easily load the dataset using the Hugging Face `datasets` library:
```python
from datasets import load_dataset
dataset = load_dataset("8Opt/multilingual-classification-0001")
example = dataset["train"][0]
print(example)
```
Output:
```python
{
"text": "Das ist ein Beispielsatz.",
"lang": "deu",
"label": 0
}
```
Label mapping:
```python
label2idx = {
'deu': 0,
'zho': 1,
'amh': 2,
'hin': 3,
'arb': 4,
'hau': 5,
'tur': 6,
'urd': 7,
'spa': 8,
'fas': 9,
'eng': 10,
'nep': 11
}
```
## Configurations
**Configuration name:** `default`
Each split is stored under `data/`:
```
data/
├── train-*
├── validation-*
└── test-*
```
---
## Citation
If you use this dataset in your work, please cite it as:
```
@dataset{8Opt,
title={Multilingual Text Classification Dataset},
author={8Opt},
year={2025},
url={https://huggingface.co/datasets/8Opt/multilingual-classification-0001}
}
``` |