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--- |
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datasets: |
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- unicamp-dl/mmarco |
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library_name: sentence-transformers |
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pipeline_tag: sentence-similarity |
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tags: |
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- sentence-transformers |
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- feature-extraction |
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- sentence-similarity |
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license: mit |
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widget: [] |
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base_model: |
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- BAAI/bge-m3 |
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--- |
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# BGE-m3 RU mMARCO/v2 Native Queries |
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This is a [BGE-M3](https://huggingface.co/BAAI/bge-m3) model post-trained on the Russian dataset from MMARCO/v2. |
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The model was used for the SIGIR 2025 Short paper: Lost in Transliteration: Bridging the Script Gap in Neural IR. |
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## Model Details |
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### Model Description |
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- **Model Type:** Sentence Transformer |
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<!-- - **Base model:** [Unknown](https://huggingface.co/unknown) --> |
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- **Maximum Sequence Length:** 8192 tokens |
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- **Output Dimensionality:** 1024 tokens |
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- **Similarity Function:** Cosine Similarity |
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<!-- - **Training Dataset:** Unknown --> |
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<!-- - **Language:** Unknown --> |
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<!-- - **License:** Unknown --> |
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## Training Details |
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### Framework Versions |
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- Python: 3.10.13 |
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- Sentence Transformers: 3.1.1 |
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- Transformers: 4.45.1 |
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- PyTorch: 2.4.1 |
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- Accelerate: 0.34.2 |
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- Datasets: 3.0.1 |
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- Tokenizers: 0.20.3 |
