---
language:
- en
- hi
- bn
- gu
- ur
- kn
- mr
- pa
- ta
- te
license: mit
size_categories:
- 10K<n<100K
task_categories:
- text-classification
- translation
- sentence-similarity
- fill-mask
- text-generation
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype: int64
  - name: uuid
    dtype: string
  splits:
  - name: train
    num_bytes: 31545825
    num_examples: 100020
  download_size: 15044925
  dataset_size: 31545825
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- multilingual
- indian
- languages
- sentiment-classification
---

# IndicVarna for Callchimp.ai (a Dynopii product)

We introduce IndiVarna which was prepared by using Google Translate on the [dair-ai/emotion](https://huggingface.co/datasets/dair-ai/emotion) dataset to get the samples there translated to the top 10 most commonly used Indian languages.

This dataset contains `10000` samples of each of the 10 languages supported.

The dataset further translated the labels in the dataset to 3 label sentiments - 0: Negative, 1: Neutral and 2: Positive. Each language has `3334` samples of each category of sentiment.

The dataset has three columns - `uuid`, `text`, `label`. `uuid` here is the concatenation of `uuid` with `language code` separated by `-`. 

This enabled us to start using the dataset out of the box with Hugging Face based text classification pipelines.

The languages supported by the dataset are:
  1. English - `en`
  2. Hindi - `hi`
  3. Bengali - `bn`
  4. Gujarati - `gu`
  5. Urdu - `ur`
  6. Kannada - `kn`
  7. Marathi - `mr`
  8. Punjabi - `pa`
  9. Tamil - `ta`
  10. Telugu `te`

The dataset can be used to perform any of the following downstream tasks -
  1. Text classification (sentiment analysis models, similarity models)
  2. Text Generation - Fill mask, generation, etc. (samples can be used without the sentiment labels to prepare small corpus for text-generation fine tuning for any of the languages)
  3. Translation - every sentence can be matched with corresponding sentences of the same language code and then used to train translations models between the languages.


We look forward to seeing how you use this dataset! 

## Author
Anubhav Singh (for [callchimp.ai](https://callchimp.ai))

Contact at: anubhav[at]callchimp.ai for any assistance!