| | --- |
| | language: |
| | - mr |
| | license: cc-by-4.0 |
| | size_categories: |
| | - 10K<n<100K |
| | task_categories: |
| | - sentence-similarity |
| | - text-retrieval |
| | - text-ranking |
| | pretty_name: MahaSTS |
| | tags: |
| | - Marathi NLP |
| | - Sentence Similarity |
| | - Marathi STS |
| | - low-resource |
| | --- |
| | |
| | # MahaSTS Dataset |
| |
|
| | The MahaSTS dataset is a human-annotated Sentence Textual Similarity (STS) dataset for Marathi, consisting of 16,860 sentence pairs labeled with continuous similarity scores in the range of 0-5. It is designed to enable effective training for sentence similarity tasks in Marathi, particularly in low-resource settings. |
| |
|
| | **Paper**: [L3Cube-MahaSTS: A Marathi Sentence Similarity Dataset and Models](https://huggingface.co/papers/2508.21569) |
| | **Code**: [https://github.com/l3cube-pune/MarathiNLP](https://github.com/l3cube-pune/MarathiNLP) |
| | **Project page**: [https://github.com/l3cube-pune/MarathiNLP](https://github.com/l3cube-pune/MarathiNLP) |
| |
|
| | ## Overview: |
| | The **MahaSTS Dataset** is a human-annotated dataset for Sentence Textual Similarity (STS) in **Marathi**, designed to train and evaluate models on sentence similarity tasks. The dataset contains 16,860 Marathi sentence pairs, each labeled with a continuous similarity score in the range of 0–5. The dataset is split into training, validation, and test sets with a ratio of 85:10:5, ensuring balanced supervision. |
| |
|
| | Alongside the dataset, the **MahaSBERT-STS-v2** model is fine-tuned for regression-based similarity scoring, providing a baseline for Marathi sentence similarity tasks. |
| |
|
| | ## Language: |
| | - **Primary Language**: Marathi (Low-resource Indic Language) |
| |
|
| | ## Dataset Size: |
| | - **Total Sentence Pairs**: 16,860 |
| | - **Train**: 14,328 sentence pairs |
| | - **Validation**: 840 sentence pairs |
| | - **Test**: 1,692 sentence pairs |
| | - **Bucket Distribution**: |
| | - 6 similarity buckets (0-5) |
| | - 2,810 sentence pairs per bucket |
| |
|
| | ## Annotation: |
| | Each sentence pair is labeled with a continuous similarity score in the range of 0 to 5. The labels represent the degree of similarity between the two sentences, with 0 indicating no similarity and 5 indicating high similarity. |
| |
|
| | ## Intended Use: |
| | The dataset is intended for: |
| | - **Sentence Similarity** |
| | - **Regression Tasks** |
| | - **Sentence Embeddings** |
| | - **Marathi Embedding Model Benchmarking** |
| |
|
| | ## Model Benchmarks: |
| | The **MahaSBERT-STS-v2** model, fine-tuned on this dataset, provides a performance baseline. Other models like **MahaBERT**, **MuRIL**, **IndicBERT**, and **IndicSBERT** can be benchmarked for comparison. |
| |
|
| | ## Sample Usage |
| |
|
| | The `L3Cube-MahaNLP` library, which includes resources related to this dataset, can be installed via pip: |
| |
|
| | ```bash |
| | pip install mahaNLP |
| | ``` |
| |
|
| | Usage examples are provided in this demo [Colab notebook](https://colab.research.google.com/drive/1POx3Bi1cML6-s3Z3u8g8VpqzpoYCyv2q). |
| |
|
| | ## Citation: |
| | If you use this dataset, please cite the following paper: |
| |
|
| | ```bibtex |
| | @article{joshi2025l3cubemahasts, |
| | title={L3Cube-MahaSTS: A Marathi Sentence Similarity Dataset and Models}, |
| | author={Joshi, Raviraj and others}, |
| | journal={arXiv preprint arXiv:2508.21569}, |
| | year={2025}, |
| | url={https://huggingface.co/papers/2508.21569} |
| | } |
| | |
| | @article{joshi2022l3cube, |
| | title={L3cube-mahanlp: Marathi natural language processing datasets, models, and library}, |
| | author={Joshi, Raviraj}, |
| | journal={arXiv preprint arXiv:2205.14728}, |
| | year={2022} |
| | } |
| | ``` |
| |
|
| | ## License |
| |
|
| | This dataset is licensed under the [Creative Commons Attribution 4.0 International License (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/). |
