| ---
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| license: mit
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| base_model:
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| - BAAI/bge-reranker-v2-m3
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| pipeline_tag: sentence-similarity
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| ---
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|
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| # Model Card — BGE-Reranker-VietFinance
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| ## Overview
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| This is a cross-encoder reranker finetuned from `BAAI/bge-reranker-v2-m3` to score (query, passage) pairs for retrieval reranking in Vietnamese financial/news search systems.
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| ## Intended Use
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| - Primary: improve Hit@K by re-ranking candidate passages produced by an upstream retriever (BM25 + embedding-based).
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| - Not for: standalone generation, non-Vietnamese domains, or high-stakes automated decisions without human review.
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| ## Essential Statistics
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| - Base model: `BAAI/bge-reranker-v2-m3`
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| - Embedding model (used for retrieval/hard-negative mining): `BAAI/bge-m3`
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| - Max sequence length for reranking: 1536 tokens (inputs longer than this are truncated)
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| - Retrieval strategy: temporal-aware hybrid (BM25 + dense embeddings with temporal boosting)
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| - Saved artifacts in this folder: `model.safetensors`, `tokenizer.json`, `tokenizer_config.json`, `config.json`.
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| ## Evaluation (concise)
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| - Procedure: retrieve candidate passages (temporal-aware hybrid) → rerank with cross-encoder → compute Hit@K for K ∈ {1,3,5,10,20}.
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| - Numeric results are saved in run outputs (summary CSVs / JSONL); include them here if you want the actual Hit@K values embedded.
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| ## Limitations & Risks
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| - Domain-specific: optimized for Vietnamese financial/news passages; generalization outside this domain/language is uncertain.
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| - Retrieval dependency: reranker cannot recover gold passages not present among retrieval candidates.
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| - Truncation risk: 1536-token truncation may drop important context for long passages.
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| - Data & license: dataset provenance and license are not specified here — verify before public distribution.
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| ## Bias & Safety
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| - Model reflects biases in the source news corpus (topic/regional biases).
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| - Temporal heuristics can misinterpret ambiguous locale-specific dates and cause incorrect boosts.
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| - Do not rely on reranker outputs alone for automated financial, legal, or medical decisions.
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| ## Quick usage (inference)
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| Load this checkpoint with `AutoTokenizer` / `AutoModelForSequenceClassification`, tokenize (query, passage) pairs, score in eval mode, and sort candidates by descending score (higher = more relevant).
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| ## License & Citation
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| - License: not specified in the checkpoint — confirm before redistribution.
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| - Cite the base models `BAAI/bge-reranker-v2-m3` and `BAAI/bge-m3` when reporting results. |
