Datasets:
Card: Success@5/Recall@1000 columns, mean query length, truncation counts, self-match note only where it applies
Browse files
README.md
CHANGED
|
@@ -36,8 +36,8 @@ respectively), see [Encoding](#encoding).
|
|
| 36 |
| `qrels.test.tsv` | text | 66,336 rows | TREC qrels, `qid \t 0 \t docid \t relevance`, no header |
|
| 37 |
| `gt_top100.tsv` | text | 5,000 rows | exact MaxSim top-100, see below |
|
| 38 |
|
| 39 |
-
All positional indices (`
|
| 40 |
-
of `doc_ids.npy` and `queries_ids.npy`. Reordering either file invalidates
|
| 41 |
|
| 42 |
## Statistics
|
| 43 |
|
|
@@ -47,7 +47,7 @@ of `doc_ids.npy` and `queries_ids.npy`. Reordering either file invalidates `gt_t
|
|
| 47 |
| document vectors | 29,313,062 |
|
| 48 |
| vectors per document (min / median / mean / max) | 3 / 210 / 171.1 / 299 |
|
| 49 |
| queries | 50 |
|
| 50 |
-
| vectors per query (min / median / max) | 10 / 17 / 32 |
|
| 51 |
| queries with at least one qrel | 50 |
|
| 52 |
| qrels rows | 66,336 |
|
| 53 |
| embedding dimension | 128 |
|
|
@@ -64,7 +64,7 @@ of `doc_ids.npy` and `queries_ids.npy`. Reordering either file invalidates `gt_t
|
|
| 64 |
| query compute dtype | float32 (model weights loaded at this dtype for the query pass) |
|
| 65 |
| query storage dtype | fp32 |
|
| 66 |
| normalization | L2, by the model's own `Normalize` module, before the storage cast |
|
| 67 |
-
| document truncation | 300 tokens (the checkpoint's `document_length`), before the skiplist; longest
|
| 68 |
| query truncation | 32 tokens (the checkpoint's `query_length`) |
|
| 69 |
| document skiplist | 32 words removed: ['!', '"', '#', '$', '%', '&', "'", '(', ')', '*', '+', ',', '-', '.', '/', ':', ';', '<', '=', '>', '?', '@', '[', '\\', ']', '^', '_', '`', '{', '|', '}', '~'] |
|
| 70 |
| document input | `title + "\n\n" + text` when the corpus has a title, else `text`; stripped |
|
|
@@ -77,6 +77,7 @@ of `doc_ids.npy` and `queries_ids.npy`. Reordering either file invalidates `gt_t
|
|
| 77 |
## Ground truth: `gt_top100.tsv`
|
| 78 |
|
| 79 |
Exact brute-force MaxSim top-100 per query over the full corpus, from the vectors in this repo.
|
|
|
|
| 80 |
No header; tab-separated `qidx docidx rank score`:
|
| 81 |
|
| 82 |
- `qidx`: 0-based row into `queries_ids.npy` / `queries.npy`
|
|
@@ -86,16 +87,14 @@ No header; tab-separated `qidx docidx rank score`:
|
|
| 86 |
dot product`, computed in fp32 with the fp16 document vectors upcast to fp32. Expansion vectors
|
| 87 |
are included in the sum. Printed to 6 decimals.
|
| 88 |
|
| 89 |
-
No query id appears as a document id, so there are no self-matches.
|
| 90 |
-
|
| 91 |
## Retrieval quality
|
| 92 |
|
| 93 |
-
Sanity check of the vectors, not a leaderboard number: exact MaxSim over the full
|
| 94 |
-
against `qrels.test.tsv` with ir_measures.
|
| 95 |
|
| 96 |
-
| nDCG@10 | Recall@100 |
|
| 97 |
-
|---|---|---|---|
|
| 98 |
-
| 0.8390 | 0.
|
| 99 |
|
| 100 |
## Loading
|
| 101 |
|
|
@@ -152,3 +151,4 @@ Checks run by the exporter on the files exactly as written here:
|
|
| 152 |
|---|---|
|
| 153 |
| exported | 2026-09-25 |
|
| 154 |
| hardware | Tesla V100S-PCIE-32GB |
|
|
|
|
|
|
| 36 |
| `qrels.test.tsv` | text | 66,336 rows | TREC qrels, `qid \t 0 \t docid \t relevance`, no header |
|
| 37 |
| `gt_top100.tsv` | text | 5,000 rows | exact MaxSim top-100, see below |
|
| 38 |
|
| 39 |
+
All positional indices (the `gt_top*.tsv` files, and the row order of every `.npy` file) refer to the
|
| 40 |
+
order of `doc_ids.npy` and `queries_ids.npy`. Reordering either file invalidates the ground truth.
|
| 41 |
|
| 42 |
## Statistics
|
| 43 |
|
|
|
|
| 47 |
| document vectors | 29,313,062 |
|
| 48 |
| vectors per document (min / median / mean / max) | 3 / 210 / 171.1 / 299 |
|
| 49 |
| queries | 50 |
|
| 50 |
+
| vectors per query (min / median / mean / max) | 10 / 17 / 17.4 / 32 |
|
| 51 |
| queries with at least one qrel | 50 |
|
| 52 |
| qrels rows | 66,336 |
|
| 53 |
| embedding dimension | 128 |
|
|
|
|
| 64 |
| query compute dtype | float32 (model weights loaded at this dtype for the query pass) |
|
| 65 |
| query storage dtype | fp32 |
|
| 66 |
| normalization | L2, by the model's own `Normalize` module, before the storage cast |
|
| 67 |
+
| document truncation | 300 tokens (the checkpoint's `document_length`), applied before the skiplist. 60,950 of 171,332 documents (36%) were longer and were cut to it; longest here 299 vectors |
|
| 68 |
| query truncation | 32 tokens (the checkpoint's `query_length`) |
|
| 69 |
| document skiplist | 32 words removed: ['!', '"', '#', '$', '%', '&', "'", '(', ')', '*', '+', ',', '-', '.', '/', ':', ';', '<', '=', '>', '?', '@', '[', '\\', ']', '^', '_', '`', '{', '|', '}', '~'] |
|
| 70 |
| document input | `title + "\n\n" + text` when the corpus has a title, else `text`; stripped |
|
|
|
|
| 77 |
## Ground truth: `gt_top100.tsv`
|
| 78 |
|
| 79 |
Exact brute-force MaxSim top-100 per query over the full corpus, from the vectors in this repo.
|
| 80 |
+
|
| 81 |
No header; tab-separated `qidx docidx rank score`:
|
| 82 |
|
| 83 |
- `qidx`: 0-based row into `queries_ids.npy` / `queries.npy`
|
|
|
|
| 87 |
dot product`, computed in fp32 with the fp16 document vectors upcast to fp32. Expansion vectors
|
| 88 |
are included in the sum. Printed to 6 decimals.
|
| 89 |
|
|
|
|
|
|
|
| 90 |
## Retrieval quality
|
| 91 |
|
| 92 |
+
Sanity check of the vectors, not a leaderboard number: `gt_top100.tsv` (exact MaxSim over the full
|
| 93 |
+
corpus) scored against `qrels.test.tsv` with ir_measures.
|
| 94 |
|
| 95 |
+
| nDCG@10 | MRR@10 | Success@5 | Recall@100 | Recall@1000 | MAP@100 |
|
| 96 |
+
|---|---|---|---|---|---|
|
| 97 |
+
| 0.8390 | 0.9750 | 1.0000 | 0.1604 | n/a (gt is top-100) | 0.1311 |
|
| 98 |
|
| 99 |
## Loading
|
| 100 |
|
|
|
|
| 151 |
|---|---|
|
| 152 |
| exported | 2026-09-25 |
|
| 153 |
| hardware | Tesla V100S-PCIE-32GB |
|
| 154 |
+
| revised | 2026-09-28: card regenerated; every other file unchanged |
|