Add HAKARI-Bench results for e5-v2 dense models and mxbai reranker
#6
by hotchpotch - opened
Add HAKARI-Bench results for e5-v2 dense models and mxbai reranker
This PR adds .json.xz benchmark result files for four models under hakari-results/. It intentionally excludes local model-card YAML, DuckDB files, caches, HTML reports, and scratch artifacts.
Submitted models
| Model | Method | Result files | Notes |
|---|---|---|---|
intfloat/e5-large-v2 |
dense | 551 | query prompt query: and document prompt passage: ; batch size 128; dtype bf16; attention sdpa; max sequence length 512. |
intfloat/e5-base-v2 |
dense | 551 | query prompt query: and document prompt passage: ; batch size 192; dtype bf16; attention sdpa; max sequence length 512. |
intfloat/e5-small-v2 |
dense | 551 | query prompt query: and document prompt passage: ; batch size 256; dtype bf16; attention sdpa; max sequence length 512. |
mixedbread-ai/mxbai-rerank-base-v2 |
reranker | 551 | reranker evaluation; candidate ranking reranking_hybrid; batch size varied across resumed runs (1, 4, 8); dtype bf16; attention sdpa; max sequence length 32768; evaluated with sentence-transformers 5.7.0.dev0 from git for the long-token scoring fix. |
Reconstructed commands
uv run hakari-bench evaluate dense --model intfloat/e5-large-v2 --all --dtype bf16 --device cuda:0 --batch-size 128 --attn-implementation sdpa --query-prompt "query: " --document-prompt "passage: "
uv run hakari-bench evaluate dense --model intfloat/e5-base-v2 --all --dtype bf16 --device cuda:0 --batch-size 192 --attn-implementation sdpa --query-prompt "query: " --document-prompt "passage: "
uv run hakari-bench evaluate dense --model intfloat/e5-small-v2 --all --dtype bf16 --device cuda:0 --batch-size 256 --attn-implementation sdpa --query-prompt "query: " --document-prompt "passage: "
uv run hakari-bench evaluate reranker --model mixedbread-ai/mxbai-rerank-base-v2 --all --dtype bf16 --device cuda:0 --batch-size 4 --attn-implementation sdpa --model-max-seq-length 32768 --candidate-ranking reranking_hybrid
The mxbai reranker result set includes resumed runs with batch sizes 1, 4, and 8 as recorded in the JSON metadata. Dense result JSON records candidate_ranking=reranking_hybrid and five embedding evaluation entries per task, including the default embedding variants.
Validation
- 2204 staged files total: 551
.json.xzfiles per model. - Non-
.json.xzfiles under the submitted result directories: 0. - DuckDB /
.duckdb.walartifacts under the submitted result directories: 0. - Dense prompts checked in JSON:
query_prompt="query: ",document_prompt="passage: ". - mxbai checked in JSON as
method="reranker",max_seq_length=32768, andsentence-transformers=5.7.0.dev0.
Per-model details
Add HAKARI-Bench results for intfloat/e5-large-v2
Summary
| Field | Value |
|---|---|
| Model | intfloat/e5-large-v2 |
| Result directory | intfloat__e5-large-v2 |
| Target path | hakari-results/intfloat__e5-large-v2 |
| Result files | 551 total, 551 .json.xz |
| Evaluation method | dense |
| Overall nDCG@10 | 0.3627 |
| Overall score units | 369 grouped units from 538 raw task results |
Overall nDCG@10
| Overall component | nDCG@10 | Score units | Raw task results |
|---|---|---|---|
| NanoMMTEB-v2 | 0.4060 | 18 | 18 |
| NanoRTEB | 0.5336 | 14 | 14 |
| MNanoBEIR | 0.3540 | 13 | 182 |
| NanoBIRCO | 0.2659 | 5 | 5 |
| NanoMLDR | 0.2457 | 13 | 13 |
| NanoLongEmbed | 0.5348 | 6 | 6 |
| NanoDAPFAM | 0.2810 | 12 | 12 |
| NanoCoIR | 0.7130 | 10 | 10 |
| NanoIFIR | 0.2449 | 4 | 4 |
| NanoLaw | 0.3476 | 4 | 4 |
| NanoMedical | 0.2994 | 7 | 7 |
| NanoRARb | 0.2921 | 14 | 14 |
| NanoBRIGHT | 0.2456 | 20 | 20 |
| NanoCodeRAG | 0.8246 | 4 | 4 |
| NanoChemTEB | 0.8100 | 3 | 3 |
| NanoR2MED | 0.1741 | 8 | 8 |
| NanoBuiltBench | 0.5158 | 2 | 2 |
| NanoCMTEB | 0.1595 | 8 | 8 |
| NanoIndicQA | 0.1111 | 11 | 11 |
| NanoMuPLeR | 0.5268 | 14 | 14 |
| NanoMTEB-v2 | 0.5707 | 10 | 10 |
| NanoMTEB-Dutch | 0.4421 | 27 | 27 |
| NanoMTEB-French | 0.4257 | 8 | 8 |
| NanoMTEB-German | 0.5055 | 5 | 5 |
| NanoJMTEB-v2 | 0.3114 | 11 | 11 |
| NanoMTEB-Korean | 0.1552 | 5 | 5 |
| NanoFaMTEB-v2 | 0.1644 | 17 | 17 |
| NanoMTEB-Polish | 0.3011 | 14 | 14 |
| NanoRuMTEB | 0.4373 | 3 | 3 |
| NanoMTEB-Scandinavian | 0.6065 | 7 | 7 |
| NanoMTEB-Spanish | 0.3973 | 7 | 7 |
| NanoMTEB-Thai | 0.0934 | 9 | 9 |
| NanoVNMTEB | 0.3272 | 26 | 26 |
| NanoMTEB-Misc | 0.5027 | 12 | 12 |
| NanoMIRACL | 0.3465 | 18 | 18 |
Reproducibility
| Field | Value |
|---|---|
| Model source | intfloat/e5-large-v2 |
| Model revision | f169b11e22de13617baa190a028a32f3493550b6 |
| Dataset revision(s) | 017849a95097eea984680cbab35972f8d3812376, 0a6b8e4feaac801f0748d2f77291e93ceb2cfdc1, 0c8fdb149eee31b8dd5dc17fc82e6795dd1e8681, 158ceac28e2468e55a56b3d056ccbe33e13aa8d8, 193d979abe245c7e7e6dec6e9ad6360cf98edbf9, ... (48 total) |
| Evaluated at UTC | 2026-06-16T23:26:25.195908+00:00 to 2026-06-17T02:04:08.199915+00:00 |
| Generated at UTC | 2026-06-16T23:26:25.393192+00:00 to 2026-06-17T02:04:08.199929+00:00 |
| dtype | bf16 |
| device | cuda:0 |
| batch size | 128 |
| attention implementation | sdpa |
| trust remote code | False |
| max sequence length | 512 |
| candidate ranking | reranking_hybrid |
| rerank top-k | not recorded |
| query prompt name | not recorded |
| document prompt name | not recorded |
| Python | 3.12.12 (main, Dec 9 2025, 19:02:36) [Clang 21.1.4 ] |
| Platform | Linux-6.8.0-107-generic-x86_64-with-glibc2.39 |
| torch | 2.9.0 |
| transformers | 5.3.0 |
| sentence-transformers | 5.4.1 |
| datasets | 4.8.4 |
| CUDA | available=True, version=12.8 |
| CUDA devices | 0: NVIDIA GeForce RTX 5090 |
Checklist
- Result files are committed under
hakari-results/intfloat__e5-large-v2/. - Result files are compressed
.json.xz; no caches, DuckDB files, HTML reports, or local scratch artifacts are included. - The result JSON records model revision, dataset revision, runtime configuration, and package versions.
- Overall nDCG@10 above was generated from the submitted result files.
- Any non-default prompt, sequence length, attention implementation, candidate ranking, or reranker setting is documented above.
Add HAKARI-Bench results for intfloat/e5-base-v2
Summary
| Field | Value |
|---|---|
| Model | intfloat/e5-base-v2 |
| Result directory | intfloat__e5-base-v2 |
| Target path | hakari-results/intfloat__e5-base-v2 |
| Result files | 551 total, 551 .json.xz |
| Evaluation method | dense |
| Overall nDCG@10 | 0.3411 |
| Overall score units | 369 grouped units from 538 raw task results |
Overall nDCG@10
| Overall component | nDCG@10 | Score units | Raw task results |
|---|---|---|---|
| NanoMMTEB-v2 | 0.3993 | 18 | 18 |
| NanoRTEB | 0.5147 | 14 | 14 |
| MNanoBEIR | 0.3336 | 13 | 182 |
| NanoBIRCO | 0.2458 | 5 | 5 |
| NanoMLDR | 0.2253 | 13 | 13 |
| NanoLongEmbed | 0.5124 | 6 | 6 |
| NanoDAPFAM | 0.2785 | 12 | 12 |
| NanoCoIR | 0.6885 | 10 | 10 |
| NanoIFIR | 0.2254 | 4 | 4 |
| NanoLaw | 0.3111 | 4 | 4 |
| NanoMedical | 0.2851 | 7 | 7 |
| NanoRARb | 0.2698 | 14 | 14 |
| NanoBRIGHT | 0.2486 | 20 | 20 |
| NanoCodeRAG | 0.8139 | 4 | 4 |
| NanoChemTEB | 0.7830 | 3 | 3 |
| NanoR2MED | 0.1492 | 8 | 8 |
| NanoBuiltBench | 0.4916 | 2 | 2 |
| NanoCMTEB | 0.1516 | 8 | 8 |
| NanoIndicQA | 0.0853 | 11 | 11 |
| NanoMuPLeR | 0.4450 | 14 | 14 |
| NanoMTEB-v2 | 0.5741 | 10 | 10 |
| NanoMTEB-Dutch | 0.4304 | 27 | 27 |
| NanoMTEB-French | 0.4037 | 8 | 8 |
| NanoMTEB-German | 0.4820 | 5 | 5 |
| NanoJMTEB-v2 | 0.2792 | 11 | 11 |
| NanoMTEB-Korean | 0.0929 | 5 | 5 |
| NanoFaMTEB-v2 | 0.1655 | 17 | 17 |
| NanoMTEB-Polish | 0.2783 | 14 | 14 |
| NanoRuMTEB | 0.3806 | 3 | 3 |
| NanoMTEB-Scandinavian | 0.5694 | 7 | 7 |
| NanoMTEB-Spanish | 0.3625 | 7 | 7 |
| NanoMTEB-Thai | 0.0907 | 9 | 9 |
| NanoVNMTEB | 0.2913 | 26 | 26 |
| NanoMTEB-Misc | 0.4551 | 12 | 12 |
| NanoMIRACL | 0.3253 | 18 | 18 |
Reproducibility
| Field | Value |
|---|---|
| Model source | intfloat/e5-base-v2 |
| Model revision | f52bf8ec8c7124536f0efb74aca902b2995e5bcd |
| Dataset revision(s) | 017849a95097eea984680cbab35972f8d3812376, 0a6b8e4feaac801f0748d2f77291e93ceb2cfdc1, 0c8fdb149eee31b8dd5dc17fc82e6795dd1e8681, 158ceac28e2468e55a56b3d056ccbe33e13aa8d8, 193d979abe245c7e7e6dec6e9ad6360cf98edbf9, ... (48 total) |
| Evaluated at UTC | 2026-06-16T23:26:56.005431+00:00 to 2026-06-17T01:55:42.609508+00:00 |
| Generated at UTC | 2026-06-16T23:26:56.201238+00:00 to 2026-06-17T01:55:42.609522+00:00 |
| dtype | bf16 |
| device | cuda:0 |
| batch size | 192 |
| attention implementation | sdpa |
| trust remote code | False |
| max sequence length | 512 |
| candidate ranking | reranking_hybrid |
| rerank top-k | not recorded |
| query prompt name | not recorded |
| document prompt name | not recorded |
| Python | 3.12.12 (main, Dec 9 2025, 19:02:36) [Clang 21.1.4 ] |
| Platform | Linux-6.8.0-107-generic-x86_64-with-glibc2.39 |
| torch | 2.9.0 |
| transformers | 5.3.0 |
| sentence-transformers | 5.4.1 |
| datasets | 4.8.4 |
| CUDA | available=True, version=12.8 |
| CUDA devices | 0: NVIDIA GeForce RTX 5090 |
Checklist
- Result files are committed under
hakari-results/intfloat__e5-base-v2/. - Result files are compressed
.json.xz; no caches, DuckDB files, HTML reports, or local scratch artifacts are included. - The result JSON records model revision, dataset revision, runtime configuration, and package versions.
- Overall nDCG@10 above was generated from the submitted result files.
- Any non-default prompt, sequence length, attention implementation, candidate ranking, or reranker setting is documented above.
Add HAKARI-Bench results for intfloat/e5-small-v2
Summary
| Field | Value |
|---|---|
| Model | intfloat/e5-small-v2 |
| Result directory | intfloat__e5-small-v2 |
| Target path | hakari-results/intfloat__e5-small-v2 |
| Result files | 551 total, 551 .json.xz |
| Evaluation method | dense |
| Overall nDCG@10 | 0.3094 |
| Overall score units | 369 grouped units from 538 raw task results |
Overall nDCG@10
| Overall component | nDCG@10 | Score units | Raw task results |
|---|---|---|---|
| NanoMMTEB-v2 | 0.3874 | 18 | 18 |
| NanoRTEB | 0.4854 | 14 | 14 |
| MNanoBEIR | 0.3060 | 13 | 182 |
| NanoBIRCO | 0.2109 | 5 | 5 |
| NanoMLDR | 0.1955 | 13 | 13 |
| NanoLongEmbed | 0.5095 | 6 | 6 |
| NanoDAPFAM | 0.2689 | 12 | 12 |
| NanoCoIR | 0.6604 | 10 | 10 |
| NanoIFIR | 0.2117 | 4 | 4 |
| NanoLaw | 0.3048 | 4 | 4 |
| NanoMedical | 0.2779 | 7 | 7 |
| NanoRARb | 0.2256 | 14 | 14 |
| NanoBRIGHT | 0.1918 | 20 | 20 |
| NanoCodeRAG | 0.7724 | 4 | 4 |
| NanoChemTEB | 0.7711 | 3 | 3 |
| NanoR2MED | 0.1228 | 8 | 8 |
| NanoBuiltBench | 0.4704 | 2 | 2 |
| NanoCMTEB | 0.1465 | 8 | 8 |
| NanoIndicQA | 0.0666 | 11 | 11 |
| NanoMuPLeR | 0.3961 | 14 | 14 |
| NanoMTEB-v2 | 0.5600 | 10 | 10 |
| NanoMTEB-Dutch | 0.3975 | 27 | 27 |
| NanoMTEB-French | 0.3646 | 8 | 8 |
| NanoMTEB-German | 0.4466 | 5 | 5 |
| NanoJMTEB-v2 | 0.2527 | 11 | 11 |
| NanoMTEB-Korean | 0.0401 | 5 | 5 |
| NanoFaMTEB-v2 | 0.0679 | 17 | 17 |
| NanoMTEB-Polish | 0.2664 | 14 | 14 |
| NanoRuMTEB | 0.1248 | 3 | 3 |
| NanoMTEB-Scandinavian | 0.5148 | 7 | 7 |
| NanoMTEB-Spanish | 0.3452 | 7 | 7 |
| NanoMTEB-Thai | 0.0835 | 9 | 9 |
| NanoVNMTEB | 0.2867 | 26 | 26 |
| NanoMTEB-Misc | 0.4096 | 12 | 12 |
| NanoMIRACL | 0.2949 | 18 | 18 |
Reproducibility
| Field | Value |
|---|---|
| Model source | intfloat/e5-small-v2 |
| Model revision | ffb93f3bd4047442299a41ebb6fa998a38507c52 |
| Dataset revision(s) | 017849a95097eea984680cbab35972f8d3812376, 0a6b8e4feaac801f0748d2f77291e93ceb2cfdc1, 0c8fdb149eee31b8dd5dc17fc82e6795dd1e8681, 158ceac28e2468e55a56b3d056ccbe33e13aa8d8, 193d979abe245c7e7e6dec6e9ad6360cf98edbf9, ... (48 total) |
| Evaluated at UTC | 2026-06-16T23:26:48.162430+00:00 to 2026-06-17T01:17:48.957333+00:00 |
| Generated at UTC | 2026-06-16T23:26:48.342123+00:00 to 2026-06-17T01:17:48.957351+00:00 |
| dtype | bf16 |
| device | cuda:0 |
| batch size | 256 |
| attention implementation | sdpa |
| trust remote code | False |
| max sequence length | 512 |
| candidate ranking | reranking_hybrid |
| rerank top-k | not recorded |
| query prompt name | not recorded |
| document prompt name | not recorded |
| Python | 3.12.12 (main, Dec 9 2025, 19:02:36) [Clang 21.1.4 ] |
| Platform | Linux-6.8.0-107-generic-x86_64-with-glibc2.39 |
| torch | 2.9.0 |
| transformers | 5.3.0 |
| sentence-transformers | 5.4.1 |
| datasets | 4.8.4 |
| CUDA | available=True, version=12.8 |
| CUDA devices | 0: NVIDIA GeForce RTX 5090 |
Checklist
- Result files are committed under
hakari-results/intfloat__e5-small-v2/. - Result files are compressed
.json.xz; no caches, DuckDB files, HTML reports, or local scratch artifacts are included. - The result JSON records model revision, dataset revision, runtime configuration, and package versions.
- Overall nDCG@10 above was generated from the submitted result files.
- Any non-default prompt, sequence length, attention implementation, candidate ranking, or reranker setting is documented above.
Add HAKARI-Bench results for mixedbread-ai/mxbai-rerank-base-v2
Summary
| Field | Value |
|---|---|
| Model | mixedbread-ai/mxbai-rerank-base-v2 |
| Result directory | mixedbread-ai__mxbai-rerank-base-v2 |
| Target path | hakari-results/mixedbread-ai__mxbai-rerank-base-v2 |
| Result files | 551 total, 551 .json.xz |
| Evaluation method | reranker |
| Overall nDCG@10 | 0.5963 |
| Overall score units | 369 grouped units from 538 raw task results |
Overall nDCG@10
| Overall component | nDCG@10 | Score units | Raw task results |
|---|---|---|---|
| NanoMMTEB-v2 | 0.5455 | 18 | 18 |
| NanoRTEB | 0.6076 | 14 | 14 |
| MNanoBEIR | 0.5567 | 13 | 182 |
| NanoBIRCO | 0.3729 | 5 | 5 |
| NanoMLDR | 0.6115 | 13 | 13 |
| NanoLongEmbed | 0.6754 | 6 | 6 |
| NanoDAPFAM | 0.2855 | 12 | 12 |
| NanoCoIR | 0.7916 | 10 | 10 |
| NanoIFIR | 0.3934 | 4 | 4 |
| NanoLaw | 0.5082 | 4 | 4 |
| NanoMedical | 0.5595 | 7 | 7 |
| NanoRARb | 0.3360 | 14 | 14 |
| NanoBRIGHT | 0.3552 | 20 | 20 |
| NanoCodeRAG | 0.8117 | 4 | 4 |
| NanoChemTEB | 0.8297 | 3 | 3 |
| NanoR2MED | 0.3351 | 8 | 8 |
| NanoBuiltBench | 0.5178 | 2 | 2 |
| NanoCMTEB | 0.7859 | 8 | 8 |
| NanoIndicQA | 0.6120 | 11 | 11 |
| NanoMuPLeR | 0.8906 | 14 | 14 |
| NanoMTEB-v2 | 0.6270 | 10 | 10 |
| NanoMTEB-Dutch | 0.5434 | 27 | 27 |
| NanoMTEB-French | 0.6116 | 8 | 8 |
| NanoMTEB-German | 0.5963 | 5 | 5 |
| NanoJMTEB-v2 | 0.7760 | 11 | 11 |
| NanoMTEB-Korean | 0.8325 | 5 | 5 |
| NanoFaMTEB-v2 | 0.6362 | 17 | 17 |
| NanoMTEB-Polish | 0.4546 | 14 | 14 |
| NanoRuMTEB | 0.8741 | 3 | 3 |
| NanoMTEB-Scandinavian | 0.6537 | 7 | 7 |
| NanoMTEB-Spanish | 0.5879 | 7 | 7 |
| NanoMTEB-Thai | 0.7410 | 9 | 9 |
| NanoVNMTEB | 0.5856 | 26 | 26 |
| NanoMTEB-Misc | 0.7328 | 12 | 12 |
| NanoMIRACL | 0.7946 | 18 | 18 |
Reproducibility
| Field | Value |
|---|---|
| Model source | mixedbread-ai/mxbai-rerank-base-v2 |
| Model revision | 3ea9d4dffa7d12a4f366be8e275c349de9fc9865 |
| Dataset revision(s) | 017849a95097eea984680cbab35972f8d3812376, 0a6b8e4feaac801f0748d2f77291e93ceb2cfdc1, 0c8fdb149eee31b8dd5dc17fc82e6795dd1e8681, 158ceac28e2468e55a56b3d056ccbe33e13aa8d8, 193d979abe245c7e7e6dec6e9ad6360cf98edbf9, ... (48 total) |
| Evaluated at UTC | 2026-06-17T00:14:29.735639+00:00 to 2026-06-19T13:11:54.832614+00:00 |
| Generated at UTC | 2026-06-17T00:14:29.946677+00:00 to 2026-06-19T13:11:54.832635+00:00 |
| dtype | bf16 |
| device | cuda:0 |
| batch size | 1, 4, 8 |
| attention implementation | sdpa |
| trust remote code | False |
| max sequence length | 32768 |
| candidate ranking | reranking_hybrid |
| rerank top-k | not recorded |
| query prompt name | not recorded |
| document prompt name | not recorded |
| Python | 3.12.12 (main, Dec 9 2025, 19:02:36) [Clang 21.1.4 ] |
| Platform | Linux-6.8.0-107-generic-x86_64-with-glibc2.39 |
| torch | 2.9.1 |
| transformers | 5.10.2 |
| sentence-transformers | 5.7.0.dev0 |
| datasets | 5.0.0 |
| CUDA | available=True, version=12.8 |
| CUDA devices | 0: NVIDIA GeForce RTX 5090 |
Checklist
- Result files are committed under
hakari-results/mixedbread-ai__mxbai-rerank-base-v2/. - Result files are compressed
.json.xz; no caches, DuckDB files, HTML reports, or local scratch artifacts are included. - The result JSON records model revision, dataset revision, runtime configuration, and package versions.
- Overall nDCG@10 above was generated from the submitted result files.
- Any non-default prompt, sequence length, attention implementation, candidate ranking, or reranker setting is documented above.
hotchpotch changed pull request status to open
hotchpotch changed pull request status to merged