quicktensor/blockrank-msmarco-train-10p
BlockRank MS MARCO Training Data (10% Sample) Dataset Description A 10% sample of MS MARCO passage ranking data formatted for training in-context ranking LLMs. This dataset is used in the training of the BlockRank project: Scalable In-context Ranking with Generative Models. Format: JSONL (in-context ranking format) Size: 50k training examples (10% sample) Documents per query: 30-50 candidates (mix of positives and hard negatives) Source Original:… See the full description on the dataset page: https://huggingface.co/datasets/quicktensor/blockrank-msmarco-train-10p.
BlockRank MS MARCO Training Data (10% Sample)
Dataset Description
A 10% sample of MS MARCO passage ranking data formatted for training in-context ranking LLMs. This dataset is used in the training of the BlockRank project: Scalable In-context Ranking with Generative Models.
- Format: JSONL (in-context ranking format)
- Size: 50k training examples (10% sample)
- Documents per query: 30-50 candidates (mix of positives and hard negatives)
Source
- Original: MS MARCO Passage Ranking
- Retrieval annotations: sentence-transformers/msmarco-distilbert-base-v3
- Sampling: 10% random sample of training queries
- Negatives: Top dense retrieval results from msmarco-distilbert-base-v3 sbert model (excluding positives)
License
Apache 2.0 (following MS MARCO license)