Datasets:
Tasks:
Text Retrieval
Formats:
parquet
Sub-tasks:
document-retrieval
Languages:
English
Size:
10M - 100M
License:
Card: documents cut to 1,024 reranker tokens when scored
Browse files
README.md
CHANGED
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@@ -88,7 +88,8 @@ query set(s) below; queries without a labelled positive are left out.
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(those are kept for every query of the split, sampled or not).
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- **Teacher**: `jinaai/jina-reranker-v3.5`, listwise: a query's positive and all of its candidates are scored together in one
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context of up to 32,768 tokens. `score` is the raw cosine score, one row per (query, positive) and per
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(query, candidate); a labelled negative that was also mined is scored once.
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| configs | queries | hard negatives | teacher scores |
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|---|---:|---:|---:|
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| 88 |
(those are kept for every query of the split, sampled or not).
|
| 89 |
- **Teacher**: `jinaai/jina-reranker-v3.5`, listwise: a query's positive and all of its candidates are scored together in one
|
| 90 |
context of up to 32,768 tokens. `score` is the raw cosine score, one row per (query, positive) and per
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| 91 |
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(query, candidate); a labelled negative that was also mined is scored once. Every document was cut to its first
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1,024 reranker tokens before scoring (`max_doc_tokens=1024`). No filtering is applied to the tables.
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| configs | queries | hard negatives | teacher scores |
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|---|---:|---:|---:|
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