---
datasets:
- unicamp-dl/mmarco
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
license: mit
widget: []
base_model:
- BAAI/bge-m3
---

# BGE-m3 RU mMARCO/v2 Native Queries

This is a [BGE-M3](https://huggingface.co/BAAI/bge-m3) model post-trained on the Russian dataset from MMARCO/v2. 

The model was used for the SIGIR 2025 Short paper: Lost in Transliteration: Bridging the Script Gap in Neural IR.

## Model Details

### Model Description
- **Model Type:** Sentence Transformer
<!-- - **Base model:** [Unknown](https://huggingface.co/unknown) -->
- **Maximum Sequence Length:** 8192 tokens
- **Output Dimensionality:** 1024 tokens
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->

## Training Details

### Framework Versions
- Python: 3.10.13
- Sentence Transformers: 3.1.1
- Transformers: 4.45.1
- PyTorch: 2.4.1
- Accelerate: 0.34.2
- Datasets: 3.0.1
- Tokenizers: 0.20.3