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language:
- en
- ru
tags:
- efficientrag
- multi-hop-qa
- token-classification
- deberta-v3
license: mit
base_model: microsoft/mdeberta-v3-base
---
# EfficientRAG Filter (mdeberta-v3-base)
**Filter** component of [EfficientRAG](https://arxiv.org/abs/2408.04259) — constructs next-hop queries via token selection.
## What it does
Given the original question + extracted useful tokens, the Filter selects which tokens to keep in the next retrieval query. This is extractive (no generation) — it picks words from the input.
## Architecture
- Base: `microsoft/mdeberta-v3-base` (86M params, multilingual)
- Standard `DebertaV2ForTokenClassification` with 2 labels (keep/discard)
## Training
| | |
|--|--|
| Data | 5,691 samples (HotpotQA EN + Dragon-derec RU) |
| Epochs | 2 |
| Batch size | 4 |
| LR | 1e-5 |
| Max length | 128 |
| Hardware | Apple M3 Pro, ~17 minutes |
## Usage
## Related
- Training data: [Necent/efficientrag-filter-training-data](https://huggingface.co/datasets/Necent/efficientrag-filter-training-data)
- Labeler model: [Necent/efficientrag-labeler-mdeberta-v3-base](https://huggingface.co/Necent/efficientrag-labeler-mdeberta-v3-base)
- Paper: [EfficientRAG (arXiv:2408.04259)](https://arxiv.org/abs/2408.04259)
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