README.md

---
license: apache-2.0
multilinguality: monolingual
size_categories:
- 10K<n<100K
language: ro
task_categories:
- sentence-similarity
pretty_name: ROSTSC
---

# RO-STS-Cupidon

## Overview
RoSTSC is a Romanian Semantic Textual Similarity (STS) dataset designed for evaluating and training sentence embedding models. It contains pairs of Romanian sentences along with similarity scores that indicate the degree of semantic equivalence between them.

## Dataset Structure
- **sentence1**: The first sentence in the pair.
- **sentence2**: The second sentence in the pair.
- **score**: A numerical value representing the semantic similarity between the two sentences, normalized between 0 and 1.

## Dataset Composition
| Source Dataset | Split | Number of Pairs |
|---------------|-------|----------------|
| mteb/sts17-crosslingual-sts | en-en | 250 |
| mteb/sts12-sts | train | 2225 |
| mteb/sts12-sts | test | 3029 |
| mteb/biosses-sts | test | 100 |
| mteb/sts16-sts | test | 1184 |
| mteb/sts15-sts | test | 2992 |
| mteb/sts14-sts | test | 3749 |
| mteb/sts13-sts | test | 1498 |
| mteb/sickr-sts | test | 9927 |
| dumitrescustefan/ro_sts | full | 8628 |
| andyP/ro-paraphrase-bible | train | 30000 |
| manual/generated | hand | 7012 |
| **Total** |  | **70594** |

## Data Collection and Processing
The data has been collected from existing datasets, primarily in English, and translated into Romanian. Some datasets were originally in Romanian and were used either in full or in part.

## Usage
This dataset can be used for:
- Fine-tuning and evaluating sentence embedding models for Romanian.
- Research on semantic textual similarity and natural language understanding (NLU) in Romanian.

### How to Load the Dataset

You can load the dataset using the `datasets` library from Hugging Face:

```python
from datasets import load_dataset

dataset = load_dataset("BlackKakapo/RoSTSC")

# Access the train split
train_data = dataset["train"]

# View an example
print(train_data[0])
```

Alternatively, if you have the dataset as a CSV file, you can load it using `pandas`:

```python
import pandas as pd

df = pd.read_csv("RoSTSC.csv")
print(df.head())
```

This allows you to easily integrate the dataset into your training or evaluation pipeline.

## License
This dataset is licensed under **Apache 2.0**.

## Citation
If you use RO-STS-Corpus in your research, please cite this dataset as follows:
```
@misc{ro_sts_corpus,
  title={RoSTSC: A Romanian STS Cupidon},
  author={BlackKakapo},
  year={2025},
}
```

## Acknowledgments
We acknowledge contributions from various resources used in compiling and annotating this dataset.

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Further details and additional metadata will be added in future versions.