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--- |
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pipeline_tag: sentence-similarity |
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tags: |
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- sentence-transformers |
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- feature-extraction |
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- sentence-similarity |
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- mteb |
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model-index: |
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- name: SGPT-2.7B-weightedmean-msmarco-specb-bitfit |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
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type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
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revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 |
|
metrics: |
|
- type: accuracy |
|
value: 67.56716417910448 |
|
- type: ap |
|
value: 30.75574629595259 |
|
- type: f1 |
|
value: 61.805121301858655 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_polarity |
|
name: MTEB AmazonPolarityClassification |
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config: default |
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split: test |
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revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1 |
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metrics: |
|
- type: accuracy |
|
value: 71.439575 |
|
- type: ap |
|
value: 65.91341330532453 |
|
- type: f1 |
|
value: 70.90561852619555 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
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name: MTEB AmazonReviewsClassification (en) |
|
config: en |
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split: test |
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revision: c379a6705fec24a2493fa68e011692605f44e119 |
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metrics: |
|
- type: accuracy |
|
value: 35.748000000000005 |
|
- type: f1 |
|
value: 35.48576287186347 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: arguana |
|
name: MTEB ArguAna |
|
config: default |
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split: test |
|
revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3 |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.96 |
|
- type: map_at_10 |
|
value: 41.619 |
|
- type: map_at_100 |
|
value: 42.673 |
|
- type: map_at_1000 |
|
value: 42.684 |
|
- type: map_at_3 |
|
value: 36.569 |
|
- type: map_at_5 |
|
value: 39.397 |
|
- type: mrr_at_1 |
|
value: 26.316 |
|
- type: mrr_at_10 |
|
value: 41.772 |
|
- type: mrr_at_100 |
|
value: 42.82 |
|
- type: mrr_at_1000 |
|
value: 42.83 |
|
- type: mrr_at_3 |
|
value: 36.724000000000004 |
|
- type: mrr_at_5 |
|
value: 39.528999999999996 |
|
- type: ndcg_at_1 |
|
value: 25.96 |
|
- type: ndcg_at_10 |
|
value: 50.491 |
|
- type: ndcg_at_100 |
|
value: 54.864999999999995 |
|
- type: ndcg_at_1000 |
|
value: 55.10699999999999 |
|
- type: ndcg_at_3 |
|
value: 40.053 |
|
- type: ndcg_at_5 |
|
value: 45.134 |
|
- type: precision_at_1 |
|
value: 25.96 |
|
- type: precision_at_10 |
|
value: 7.8950000000000005 |
|
- type: precision_at_100 |
|
value: 0.9780000000000001 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 16.714000000000002 |
|
- type: precision_at_5 |
|
value: 12.489 |
|
- type: recall_at_1 |
|
value: 25.96 |
|
- type: recall_at_10 |
|
value: 78.947 |
|
- type: recall_at_100 |
|
value: 97.795 |
|
- type: recall_at_1000 |
|
value: 99.644 |
|
- type: recall_at_3 |
|
value: 50.141999999999996 |
|
- type: recall_at_5 |
|
value: 62.446999999999996 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-p2p |
|
name: MTEB ArxivClusteringP2P |
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config: default |
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split: test |
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revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8 |
|
metrics: |
|
- type: v_measure |
|
value: 44.72125714642202 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3 |
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metrics: |
|
- type: v_measure |
|
value: 35.081451519142064 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/askubuntudupquestions-reranking |
|
name: MTEB AskUbuntuDupQuestions |
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config: default |
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split: test |
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revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c |
|
metrics: |
|
- type: map |
|
value: 59.634661990392054 |
|
- type: mrr |
|
value: 73.6813525040672 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/biosses-sts |
|
name: MTEB BIOSSES |
|
config: default |
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split: test |
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revision: 9ee918f184421b6bd48b78f6c714d86546106103 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.42754550496836 |
|
- type: cos_sim_spearman |
|
value: 84.84289705838664 |
|
- type: euclidean_pearson |
|
value: 85.59331970450859 |
|
- type: euclidean_spearman |
|
value: 85.8525586184271 |
|
- type: manhattan_pearson |
|
value: 85.41233134466698 |
|
- type: manhattan_spearman |
|
value: 85.52303303767404 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
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revision: 44fa15921b4c889113cc5df03dd4901b49161ab7 |
|
metrics: |
|
- type: accuracy |
|
value: 83.21753246753246 |
|
- type: f1 |
|
value: 83.15394543120915 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
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split: test |
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revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55 |
|
metrics: |
|
- type: v_measure |
|
value: 34.41414219680629 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
|
name: MTEB BiorxivClusteringS2S |
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config: default |
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split: test |
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revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1 |
|
metrics: |
|
- type: v_measure |
|
value: 30.533275862270028 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackAndroidRetrieval |
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config: default |
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split: test |
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revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
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metrics: |
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- type: map_at_1 |
|
value: 30.808999999999997 |
|
- type: map_at_10 |
|
value: 40.617 |
|
- type: map_at_100 |
|
value: 41.894999999999996 |
|
- type: map_at_1000 |
|
value: 42.025 |
|
- type: map_at_3 |
|
value: 37.0 |
|
- type: map_at_5 |
|
value: 38.993 |
|
- type: mrr_at_1 |
|
value: 37.482 |
|
- type: mrr_at_10 |
|
value: 46.497 |
|
- type: mrr_at_100 |
|
value: 47.144000000000005 |
|
- type: mrr_at_1000 |
|
value: 47.189 |
|
- type: mrr_at_3 |
|
value: 43.705 |
|
- type: mrr_at_5 |
|
value: 45.193 |
|
- type: ndcg_at_1 |
|
value: 37.482 |
|
- type: ndcg_at_10 |
|
value: 46.688 |
|
- type: ndcg_at_100 |
|
value: 51.726000000000006 |
|
- type: ndcg_at_1000 |
|
value: 53.825 |
|
- type: ndcg_at_3 |
|
value: 41.242000000000004 |
|
- type: ndcg_at_5 |
|
value: 43.657000000000004 |
|
- type: precision_at_1 |
|
value: 37.482 |
|
- type: precision_at_10 |
|
value: 8.827 |
|
- type: precision_at_100 |
|
value: 1.393 |
|
- type: precision_at_1000 |
|
value: 0.186 |
|
- type: precision_at_3 |
|
value: 19.361 |
|
- type: precision_at_5 |
|
value: 14.106 |
|
- type: recall_at_1 |
|
value: 30.808999999999997 |
|
- type: recall_at_10 |
|
value: 58.47 |
|
- type: recall_at_100 |
|
value: 80.51899999999999 |
|
- type: recall_at_1000 |
|
value: 93.809 |
|
- type: recall_at_3 |
|
value: 42.462 |
|
- type: recall_at_5 |
|
value: 49.385 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.962000000000003 |
|
- type: map_at_10 |
|
value: 36.93 |
|
- type: map_at_100 |
|
value: 38.102000000000004 |
|
- type: map_at_1000 |
|
value: 38.22 |
|
- type: map_at_3 |
|
value: 34.065 |
|
- type: map_at_5 |
|
value: 35.72 |
|
- type: mrr_at_1 |
|
value: 33.567 |
|
- type: mrr_at_10 |
|
value: 42.269 |
|
- type: mrr_at_100 |
|
value: 42.99 |
|
- type: mrr_at_1000 |
|
value: 43.033 |
|
- type: mrr_at_3 |
|
value: 40.064 |
|
- type: mrr_at_5 |
|
value: 41.258 |
|
- type: ndcg_at_1 |
|
value: 33.567 |
|
- type: ndcg_at_10 |
|
value: 42.405 |
|
- type: ndcg_at_100 |
|
value: 46.847 |
|
- type: ndcg_at_1000 |
|
value: 48.951 |
|
- type: ndcg_at_3 |
|
value: 38.312000000000005 |
|
- type: ndcg_at_5 |
|
value: 40.242 |
|
- type: precision_at_1 |
|
value: 33.567 |
|
- type: precision_at_10 |
|
value: 8.032 |
|
- type: precision_at_100 |
|
value: 1.295 |
|
- type: precision_at_1000 |
|
value: 0.17600000000000002 |
|
- type: precision_at_3 |
|
value: 18.662 |
|
- type: precision_at_5 |
|
value: 13.299 |
|
- type: recall_at_1 |
|
value: 26.962000000000003 |
|
- type: recall_at_10 |
|
value: 52.489 |
|
- type: recall_at_100 |
|
value: 71.635 |
|
- type: recall_at_1000 |
|
value: 85.141 |
|
- type: recall_at_3 |
|
value: 40.28 |
|
- type: recall_at_5 |
|
value: 45.757 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 36.318 |
|
- type: map_at_10 |
|
value: 47.97 |
|
- type: map_at_100 |
|
value: 49.003 |
|
- type: map_at_1000 |
|
value: 49.065999999999995 |
|
- type: map_at_3 |
|
value: 45.031 |
|
- type: map_at_5 |
|
value: 46.633 |
|
- type: mrr_at_1 |
|
value: 41.504999999999995 |
|
- type: mrr_at_10 |
|
value: 51.431000000000004 |
|
- type: mrr_at_100 |
|
value: 52.129000000000005 |
|
- type: mrr_at_1000 |
|
value: 52.161 |
|
- type: mrr_at_3 |
|
value: 48.934 |
|
- type: mrr_at_5 |
|
value: 50.42 |
|
- type: ndcg_at_1 |
|
value: 41.504999999999995 |
|
- type: ndcg_at_10 |
|
value: 53.676 |
|
- type: ndcg_at_100 |
|
value: 57.867000000000004 |
|
- type: ndcg_at_1000 |
|
value: 59.166 |
|
- type: ndcg_at_3 |
|
value: 48.516 |
|
- type: ndcg_at_5 |
|
value: 50.983999999999995 |
|
- type: precision_at_1 |
|
value: 41.504999999999995 |
|
- type: precision_at_10 |
|
value: 8.608 |
|
- type: precision_at_100 |
|
value: 1.1560000000000001 |
|
- type: precision_at_1000 |
|
value: 0.133 |
|
- type: precision_at_3 |
|
value: 21.462999999999997 |
|
- type: precision_at_5 |
|
value: 14.721 |
|
- type: recall_at_1 |
|
value: 36.318 |
|
- type: recall_at_10 |
|
value: 67.066 |
|
- type: recall_at_100 |
|
value: 85.34 |
|
- type: recall_at_1000 |
|
value: 94.491 |
|
- type: recall_at_3 |
|
value: 53.215999999999994 |
|
- type: recall_at_5 |
|
value: 59.214 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.167 |
|
- type: map_at_10 |
|
value: 29.543999999999997 |
|
- type: map_at_100 |
|
value: 30.579 |
|
- type: map_at_1000 |
|
value: 30.669999999999998 |
|
- type: map_at_3 |
|
value: 26.982 |
|
- type: map_at_5 |
|
value: 28.474 |
|
- type: mrr_at_1 |
|
value: 24.068 |
|
- type: mrr_at_10 |
|
value: 31.237 |
|
- type: mrr_at_100 |
|
value: 32.222 |
|
- type: mrr_at_1000 |
|
value: 32.292 |
|
- type: mrr_at_3 |
|
value: 28.776000000000003 |
|
- type: mrr_at_5 |
|
value: 30.233999999999998 |
|
- type: ndcg_at_1 |
|
value: 24.068 |
|
- type: ndcg_at_10 |
|
value: 33.973 |
|
- type: ndcg_at_100 |
|
value: 39.135 |
|
- type: ndcg_at_1000 |
|
value: 41.443999999999996 |
|
- type: ndcg_at_3 |
|
value: 29.018 |
|
- type: ndcg_at_5 |
|
value: 31.558999999999997 |
|
- type: precision_at_1 |
|
value: 24.068 |
|
- type: precision_at_10 |
|
value: 5.299 |
|
- type: precision_at_100 |
|
value: 0.823 |
|
- type: precision_at_1000 |
|
value: 0.106 |
|
- type: precision_at_3 |
|
value: 12.166 |
|
- type: precision_at_5 |
|
value: 8.767999999999999 |
|
- type: recall_at_1 |
|
value: 22.167 |
|
- type: recall_at_10 |
|
value: 46.115 |
|
- type: recall_at_100 |
|
value: 69.867 |
|
- type: recall_at_1000 |
|
value: 87.234 |
|
- type: recall_at_3 |
|
value: 32.798 |
|
- type: recall_at_5 |
|
value: 38.951 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.033000000000001 |
|
- type: map_at_10 |
|
value: 19.314 |
|
- type: map_at_100 |
|
value: 20.562 |
|
- type: map_at_1000 |
|
value: 20.695 |
|
- type: map_at_3 |
|
value: 16.946 |
|
- type: map_at_5 |
|
value: 18.076999999999998 |
|
- type: mrr_at_1 |
|
value: 14.801 |
|
- type: mrr_at_10 |
|
value: 22.74 |
|
- type: mrr_at_100 |
|
value: 23.876 |
|
- type: mrr_at_1000 |
|
value: 23.949 |
|
- type: mrr_at_3 |
|
value: 20.211000000000002 |
|
- type: mrr_at_5 |
|
value: 21.573 |
|
- type: ndcg_at_1 |
|
value: 14.801 |
|
- type: ndcg_at_10 |
|
value: 24.038 |
|
- type: ndcg_at_100 |
|
value: 30.186 |
|
- type: ndcg_at_1000 |
|
value: 33.321 |
|
- type: ndcg_at_3 |
|
value: 19.431 |
|
- type: ndcg_at_5 |
|
value: 21.34 |
|
- type: precision_at_1 |
|
value: 14.801 |
|
- type: precision_at_10 |
|
value: 4.776 |
|
- type: precision_at_100 |
|
value: 0.897 |
|
- type: precision_at_1000 |
|
value: 0.133 |
|
- type: precision_at_3 |
|
value: 9.66 |
|
- type: precision_at_5 |
|
value: 7.239 |
|
- type: recall_at_1 |
|
value: 12.033000000000001 |
|
- type: recall_at_10 |
|
value: 35.098 |
|
- type: recall_at_100 |
|
value: 62.175000000000004 |
|
- type: recall_at_1000 |
|
value: 84.17099999999999 |
|
- type: recall_at_3 |
|
value: 22.61 |
|
- type: recall_at_5 |
|
value: 27.278999999999996 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.651000000000003 |
|
- type: map_at_10 |
|
value: 36.901 |
|
- type: map_at_100 |
|
value: 38.249 |
|
- type: map_at_1000 |
|
value: 38.361000000000004 |
|
- type: map_at_3 |
|
value: 33.891 |
|
- type: map_at_5 |
|
value: 35.439 |
|
- type: mrr_at_1 |
|
value: 32.724 |
|
- type: mrr_at_10 |
|
value: 42.504 |
|
- type: mrr_at_100 |
|
value: 43.391999999999996 |
|
- type: mrr_at_1000 |
|
value: 43.436 |
|
- type: mrr_at_3 |
|
value: 39.989999999999995 |
|
- type: mrr_at_5 |
|
value: 41.347 |
|
- type: ndcg_at_1 |
|
value: 32.724 |
|
- type: ndcg_at_10 |
|
value: 43.007 |
|
- type: ndcg_at_100 |
|
value: 48.601 |
|
- type: ndcg_at_1000 |
|
value: 50.697 |
|
- type: ndcg_at_3 |
|
value: 37.99 |
|
- type: ndcg_at_5 |
|
value: 40.083999999999996 |
|
- type: precision_at_1 |
|
value: 32.724 |
|
- type: precision_at_10 |
|
value: 7.872999999999999 |
|
- type: precision_at_100 |
|
value: 1.247 |
|
- type: precision_at_1000 |
|
value: 0.16199999999999998 |
|
- type: precision_at_3 |
|
value: 18.062 |
|
- type: precision_at_5 |
|
value: 12.666 |
|
- type: recall_at_1 |
|
value: 26.651000000000003 |
|
- type: recall_at_10 |
|
value: 55.674 |
|
- type: recall_at_100 |
|
value: 78.904 |
|
- type: recall_at_1000 |
|
value: 92.55799999999999 |
|
- type: recall_at_3 |
|
value: 41.36 |
|
- type: recall_at_5 |
|
value: 46.983999999999995 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.589000000000002 |
|
- type: map_at_10 |
|
value: 32.244 |
|
- type: map_at_100 |
|
value: 33.46 |
|
- type: map_at_1000 |
|
value: 33.593 |
|
- type: map_at_3 |
|
value: 29.21 |
|
- type: map_at_5 |
|
value: 31.019999999999996 |
|
- type: mrr_at_1 |
|
value: 28.425 |
|
- type: mrr_at_10 |
|
value: 37.282 |
|
- type: mrr_at_100 |
|
value: 38.187 |
|
- type: mrr_at_1000 |
|
value: 38.248 |
|
- type: mrr_at_3 |
|
value: 34.684 |
|
- type: mrr_at_5 |
|
value: 36.123 |
|
- type: ndcg_at_1 |
|
value: 28.425 |
|
- type: ndcg_at_10 |
|
value: 37.942 |
|
- type: ndcg_at_100 |
|
value: 43.443 |
|
- type: ndcg_at_1000 |
|
value: 45.995999999999995 |
|
- type: ndcg_at_3 |
|
value: 32.873999999999995 |
|
- type: ndcg_at_5 |
|
value: 35.325 |
|
- type: precision_at_1 |
|
value: 28.425 |
|
- type: precision_at_10 |
|
value: 7.1 |
|
- type: precision_at_100 |
|
value: 1.166 |
|
- type: precision_at_1000 |
|
value: 0.158 |
|
- type: precision_at_3 |
|
value: 16.02 |
|
- type: precision_at_5 |
|
value: 11.644 |
|
- type: recall_at_1 |
|
value: 22.589000000000002 |
|
- type: recall_at_10 |
|
value: 50.03999999999999 |
|
- type: recall_at_100 |
|
value: 73.973 |
|
- type: recall_at_1000 |
|
value: 91.128 |
|
- type: recall_at_3 |
|
value: 35.882999999999996 |
|
- type: recall_at_5 |
|
value: 42.187999999999995 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.190833333333334 |
|
- type: map_at_10 |
|
value: 31.504916666666666 |
|
- type: map_at_100 |
|
value: 32.64908333333334 |
|
- type: map_at_1000 |
|
value: 32.77075 |
|
- type: map_at_3 |
|
value: 28.82575 |
|
- type: map_at_5 |
|
value: 30.2755 |
|
- type: mrr_at_1 |
|
value: 27.427499999999995 |
|
- type: mrr_at_10 |
|
value: 35.36483333333334 |
|
- type: mrr_at_100 |
|
value: 36.23441666666666 |
|
- type: mrr_at_1000 |
|
value: 36.297583333333336 |
|
- type: mrr_at_3 |
|
value: 32.97966666666667 |
|
- type: mrr_at_5 |
|
value: 34.294583333333335 |
|
- type: ndcg_at_1 |
|
value: 27.427499999999995 |
|
- type: ndcg_at_10 |
|
value: 36.53358333333333 |
|
- type: ndcg_at_100 |
|
value: 41.64508333333333 |
|
- type: ndcg_at_1000 |
|
value: 44.14499999999999 |
|
- type: ndcg_at_3 |
|
value: 31.88908333333333 |
|
- type: ndcg_at_5 |
|
value: 33.98433333333333 |
|
- type: precision_at_1 |
|
value: 27.427499999999995 |
|
- type: precision_at_10 |
|
value: 6.481083333333333 |
|
- type: precision_at_100 |
|
value: 1.0610833333333334 |
|
- type: precision_at_1000 |
|
value: 0.14691666666666667 |
|
- type: precision_at_3 |
|
value: 14.656749999999999 |
|
- type: precision_at_5 |
|
value: 10.493583333333332 |
|
- type: recall_at_1 |
|
value: 23.190833333333334 |
|
- type: recall_at_10 |
|
value: 47.65175 |
|
- type: recall_at_100 |
|
value: 70.41016666666667 |
|
- type: recall_at_1000 |
|
value: 87.82708333333332 |
|
- type: recall_at_3 |
|
value: 34.637583333333325 |
|
- type: recall_at_5 |
|
value: 40.05008333333333 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.409 |
|
- type: map_at_10 |
|
value: 26.794 |
|
- type: map_at_100 |
|
value: 27.682000000000002 |
|
- type: map_at_1000 |
|
value: 27.783 |
|
- type: map_at_3 |
|
value: 24.461 |
|
- type: map_at_5 |
|
value: 25.668000000000003 |
|
- type: mrr_at_1 |
|
value: 22.853 |
|
- type: mrr_at_10 |
|
value: 29.296 |
|
- type: mrr_at_100 |
|
value: 30.103 |
|
- type: mrr_at_1000 |
|
value: 30.179000000000002 |
|
- type: mrr_at_3 |
|
value: 27.173000000000002 |
|
- type: mrr_at_5 |
|
value: 28.223 |
|
- type: ndcg_at_1 |
|
value: 22.853 |
|
- type: ndcg_at_10 |
|
value: 31.007 |
|
- type: ndcg_at_100 |
|
value: 35.581 |
|
- type: ndcg_at_1000 |
|
value: 38.147 |
|
- type: ndcg_at_3 |
|
value: 26.590999999999998 |
|
- type: ndcg_at_5 |
|
value: 28.43 |
|
- type: precision_at_1 |
|
value: 22.853 |
|
- type: precision_at_10 |
|
value: 5.031 |
|
- type: precision_at_100 |
|
value: 0.7939999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11 |
|
- type: precision_at_3 |
|
value: 11.401 |
|
- type: precision_at_5 |
|
value: 8.16 |
|
- type: recall_at_1 |
|
value: 20.409 |
|
- type: recall_at_10 |
|
value: 41.766 |
|
- type: recall_at_100 |
|
value: 62.964 |
|
- type: recall_at_1000 |
|
value: 81.682 |
|
- type: recall_at_3 |
|
value: 29.281000000000002 |
|
- type: recall_at_5 |
|
value: 33.83 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.549000000000001 |
|
- type: map_at_10 |
|
value: 20.315 |
|
- type: map_at_100 |
|
value: 21.301000000000002 |
|
- type: map_at_1000 |
|
value: 21.425 |
|
- type: map_at_3 |
|
value: 18.132 |
|
- type: map_at_5 |
|
value: 19.429 |
|
- type: mrr_at_1 |
|
value: 17.86 |
|
- type: mrr_at_10 |
|
value: 23.860999999999997 |
|
- type: mrr_at_100 |
|
value: 24.737000000000002 |
|
- type: mrr_at_1000 |
|
value: 24.82 |
|
- type: mrr_at_3 |
|
value: 21.685 |
|
- type: mrr_at_5 |
|
value: 23.008 |
|
- type: ndcg_at_1 |
|
value: 17.86 |
|
- type: ndcg_at_10 |
|
value: 24.396 |
|
- type: ndcg_at_100 |
|
value: 29.328 |
|
- type: ndcg_at_1000 |
|
value: 32.486 |
|
- type: ndcg_at_3 |
|
value: 20.375 |
|
- type: ndcg_at_5 |
|
value: 22.411 |
|
- type: precision_at_1 |
|
value: 17.86 |
|
- type: precision_at_10 |
|
value: 4.47 |
|
- type: precision_at_100 |
|
value: 0.8099999999999999 |
|
- type: precision_at_1000 |
|
value: 0.125 |
|
- type: precision_at_3 |
|
value: 9.475 |
|
- type: precision_at_5 |
|
value: 7.170999999999999 |
|
- type: recall_at_1 |
|
value: 14.549000000000001 |
|
- type: recall_at_10 |
|
value: 33.365 |
|
- type: recall_at_100 |
|
value: 55.797 |
|
- type: recall_at_1000 |
|
value: 78.632 |
|
- type: recall_at_3 |
|
value: 22.229 |
|
- type: recall_at_5 |
|
value: 27.339000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.286 |
|
- type: map_at_10 |
|
value: 30.728 |
|
- type: map_at_100 |
|
value: 31.840000000000003 |
|
- type: map_at_1000 |
|
value: 31.953 |
|
- type: map_at_3 |
|
value: 28.302 |
|
- type: map_at_5 |
|
value: 29.615000000000002 |
|
- type: mrr_at_1 |
|
value: 27.239 |
|
- type: mrr_at_10 |
|
value: 34.408 |
|
- type: mrr_at_100 |
|
value: 35.335 |
|
- type: mrr_at_1000 |
|
value: 35.405 |
|
- type: mrr_at_3 |
|
value: 32.151999999999994 |
|
- type: mrr_at_5 |
|
value: 33.355000000000004 |
|
- type: ndcg_at_1 |
|
value: 27.239 |
|
- type: ndcg_at_10 |
|
value: 35.324 |
|
- type: ndcg_at_100 |
|
value: 40.866 |
|
- type: ndcg_at_1000 |
|
value: 43.584 |
|
- type: ndcg_at_3 |
|
value: 30.898999999999997 |
|
- type: ndcg_at_5 |
|
value: 32.812999999999995 |
|
- type: precision_at_1 |
|
value: 27.239 |
|
- type: precision_at_10 |
|
value: 5.896 |
|
- type: precision_at_100 |
|
value: 0.979 |
|
- type: precision_at_1000 |
|
value: 0.133 |
|
- type: precision_at_3 |
|
value: 13.713000000000001 |
|
- type: precision_at_5 |
|
value: 9.683 |
|
- type: recall_at_1 |
|
value: 23.286 |
|
- type: recall_at_10 |
|
value: 45.711 |
|
- type: recall_at_100 |
|
value: 70.611 |
|
- type: recall_at_1000 |
|
value: 90.029 |
|
- type: recall_at_3 |
|
value: 33.615 |
|
- type: recall_at_5 |
|
value: 38.41 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.962 |
|
- type: map_at_10 |
|
value: 31.942999999999998 |
|
- type: map_at_100 |
|
value: 33.384 |
|
- type: map_at_1000 |
|
value: 33.611000000000004 |
|
- type: map_at_3 |
|
value: 29.243000000000002 |
|
- type: map_at_5 |
|
value: 30.446 |
|
- type: mrr_at_1 |
|
value: 28.458 |
|
- type: mrr_at_10 |
|
value: 36.157000000000004 |
|
- type: mrr_at_100 |
|
value: 37.092999999999996 |
|
- type: mrr_at_1000 |
|
value: 37.163000000000004 |
|
- type: mrr_at_3 |
|
value: 33.86 |
|
- type: mrr_at_5 |
|
value: 35.086 |
|
- type: ndcg_at_1 |
|
value: 28.458 |
|
- type: ndcg_at_10 |
|
value: 37.201 |
|
- type: ndcg_at_100 |
|
value: 42.591 |
|
- type: ndcg_at_1000 |
|
value: 45.539 |
|
- type: ndcg_at_3 |
|
value: 32.889 |
|
- type: ndcg_at_5 |
|
value: 34.483000000000004 |
|
- type: precision_at_1 |
|
value: 28.458 |
|
- type: precision_at_10 |
|
value: 7.332 |
|
- type: precision_at_100 |
|
value: 1.437 |
|
- type: precision_at_1000 |
|
value: 0.233 |
|
- type: precision_at_3 |
|
value: 15.547 |
|
- type: precision_at_5 |
|
value: 11.146 |
|
- type: recall_at_1 |
|
value: 23.962 |
|
- type: recall_at_10 |
|
value: 46.751 |
|
- type: recall_at_100 |
|
value: 71.626 |
|
- type: recall_at_1000 |
|
value: 90.93900000000001 |
|
- type: recall_at_3 |
|
value: 34.138000000000005 |
|
- type: recall_at_5 |
|
value: 38.673 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.555 |
|
- type: map_at_10 |
|
value: 24.759 |
|
- type: map_at_100 |
|
value: 25.732 |
|
- type: map_at_1000 |
|
value: 25.846999999999998 |
|
- type: map_at_3 |
|
value: 22.646 |
|
- type: map_at_5 |
|
value: 23.791999999999998 |
|
- type: mrr_at_1 |
|
value: 20.148 |
|
- type: mrr_at_10 |
|
value: 26.695999999999998 |
|
- type: mrr_at_100 |
|
value: 27.605 |
|
- type: mrr_at_1000 |
|
value: 27.695999999999998 |
|
- type: mrr_at_3 |
|
value: 24.522 |
|
- type: mrr_at_5 |
|
value: 25.715 |
|
- type: ndcg_at_1 |
|
value: 20.148 |
|
- type: ndcg_at_10 |
|
value: 28.746 |
|
- type: ndcg_at_100 |
|
value: 33.57 |
|
- type: ndcg_at_1000 |
|
value: 36.584 |
|
- type: ndcg_at_3 |
|
value: 24.532 |
|
- type: ndcg_at_5 |
|
value: 26.484 |
|
- type: precision_at_1 |
|
value: 20.148 |
|
- type: precision_at_10 |
|
value: 4.529 |
|
- type: precision_at_100 |
|
value: 0.736 |
|
- type: precision_at_1000 |
|
value: 0.108 |
|
- type: precision_at_3 |
|
value: 10.351 |
|
- type: precision_at_5 |
|
value: 7.32 |
|
- type: recall_at_1 |
|
value: 18.555 |
|
- type: recall_at_10 |
|
value: 39.275999999999996 |
|
- type: recall_at_100 |
|
value: 61.511 |
|
- type: recall_at_1000 |
|
value: 84.111 |
|
- type: recall_at_3 |
|
value: 27.778999999999996 |
|
- type: recall_at_5 |
|
value: 32.591 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: climate-fever |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: 392b78eb68c07badcd7c2cd8f39af108375dfcce |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.366999999999999 |
|
- type: map_at_10 |
|
value: 18.953999999999997 |
|
- type: map_at_100 |
|
value: 20.674999999999997 |
|
- type: map_at_1000 |
|
value: 20.868000000000002 |
|
- type: map_at_3 |
|
value: 15.486 |
|
- type: map_at_5 |
|
value: 17.347 |
|
- type: mrr_at_1 |
|
value: 23.257 |
|
- type: mrr_at_10 |
|
value: 35.419 |
|
- type: mrr_at_100 |
|
value: 36.361 |
|
- type: mrr_at_1000 |
|
value: 36.403 |
|
- type: mrr_at_3 |
|
value: 31.747999999999998 |
|
- type: mrr_at_5 |
|
value: 34.077 |
|
- type: ndcg_at_1 |
|
value: 23.257 |
|
- type: ndcg_at_10 |
|
value: 27.11 |
|
- type: ndcg_at_100 |
|
value: 33.981 |
|
- type: ndcg_at_1000 |
|
value: 37.444 |
|
- type: ndcg_at_3 |
|
value: 21.471999999999998 |
|
- type: ndcg_at_5 |
|
value: 23.769000000000002 |
|
- type: precision_at_1 |
|
value: 23.257 |
|
- type: precision_at_10 |
|
value: 8.704 |
|
- type: precision_at_100 |
|
value: 1.606 |
|
- type: precision_at_1000 |
|
value: 0.22499999999999998 |
|
- type: precision_at_3 |
|
value: 16.287 |
|
- type: precision_at_5 |
|
value: 13.068 |
|
- type: recall_at_1 |
|
value: 10.366999999999999 |
|
- type: recall_at_10 |
|
value: 33.706 |
|
- type: recall_at_100 |
|
value: 57.375 |
|
- type: recall_at_1000 |
|
value: 76.79 |
|
- type: recall_at_3 |
|
value: 20.18 |
|
- type: recall_at_5 |
|
value: 26.215 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: dbpedia-entity |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: f097057d03ed98220bc7309ddb10b71a54d667d6 |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.246 |
|
- type: map_at_10 |
|
value: 15.979 |
|
- type: map_at_100 |
|
value: 21.025 |
|
- type: map_at_1000 |
|
value: 22.189999999999998 |
|
- type: map_at_3 |
|
value: 11.997 |
|
- type: map_at_5 |
|
value: 13.697000000000001 |
|
- type: mrr_at_1 |
|
value: 60.75000000000001 |
|
- type: mrr_at_10 |
|
value: 68.70100000000001 |
|
- type: mrr_at_100 |
|
value: 69.1 |
|
- type: mrr_at_1000 |
|
value: 69.111 |
|
- type: mrr_at_3 |
|
value: 66.583 |
|
- type: mrr_at_5 |
|
value: 67.87100000000001 |
|
- type: ndcg_at_1 |
|
value: 49.75 |
|
- type: ndcg_at_10 |
|
value: 34.702 |
|
- type: ndcg_at_100 |
|
value: 37.607 |
|
- type: ndcg_at_1000 |
|
value: 44.322 |
|
- type: ndcg_at_3 |
|
value: 39.555 |
|
- type: ndcg_at_5 |
|
value: 36.684 |
|
- type: precision_at_1 |
|
value: 60.75000000000001 |
|
- type: precision_at_10 |
|
value: 26.625 |
|
- type: precision_at_100 |
|
value: 7.969999999999999 |
|
- type: precision_at_1000 |
|
value: 1.678 |
|
- type: precision_at_3 |
|
value: 41.833 |
|
- type: precision_at_5 |
|
value: 34.5 |
|
- type: recall_at_1 |
|
value: 8.246 |
|
- type: recall_at_10 |
|
value: 20.968 |
|
- type: recall_at_100 |
|
value: 42.065000000000005 |
|
- type: recall_at_1000 |
|
value: 63.671 |
|
- type: recall_at_3 |
|
value: 13.039000000000001 |
|
- type: recall_at_5 |
|
value: 16.042 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 829147f8f75a25f005913200eb5ed41fae320aa1 |
|
metrics: |
|
- type: accuracy |
|
value: 49.214999999999996 |
|
- type: f1 |
|
value: 44.85952451163755 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fever |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: 1429cf27e393599b8b359b9b72c666f96b2525f9 |
|
metrics: |
|
- type: map_at_1 |
|
value: 56.769000000000005 |
|
- type: map_at_10 |
|
value: 67.30199999999999 |
|
- type: map_at_100 |
|
value: 67.692 |
|
- type: map_at_1000 |
|
value: 67.712 |
|
- type: map_at_3 |
|
value: 65.346 |
|
- type: map_at_5 |
|
value: 66.574 |
|
- type: mrr_at_1 |
|
value: 61.370999999999995 |
|
- type: mrr_at_10 |
|
value: 71.875 |
|
- type: mrr_at_100 |
|
value: 72.195 |
|
- type: mrr_at_1000 |
|
value: 72.206 |
|
- type: mrr_at_3 |
|
value: 70.04 |
|
- type: mrr_at_5 |
|
value: 71.224 |
|
- type: ndcg_at_1 |
|
value: 61.370999999999995 |
|
- type: ndcg_at_10 |
|
value: 72.731 |
|
- type: ndcg_at_100 |
|
value: 74.468 |
|
- type: ndcg_at_1000 |
|
value: 74.91600000000001 |
|
- type: ndcg_at_3 |
|
value: 69.077 |
|
- type: ndcg_at_5 |
|
value: 71.111 |
|
- type: precision_at_1 |
|
value: 61.370999999999995 |
|
- type: precision_at_10 |
|
value: 9.325999999999999 |
|
- type: precision_at_100 |
|
value: 1.03 |
|
- type: precision_at_1000 |
|
value: 0.108 |
|
- type: precision_at_3 |
|
value: 27.303 |
|
- type: precision_at_5 |
|
value: 17.525 |
|
- type: recall_at_1 |
|
value: 56.769000000000005 |
|
- type: recall_at_10 |
|
value: 85.06 |
|
- type: recall_at_100 |
|
value: 92.767 |
|
- type: recall_at_1000 |
|
value: 95.933 |
|
- type: recall_at_3 |
|
value: 75.131 |
|
- type: recall_at_5 |
|
value: 80.17 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fiqa |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: 41b686a7f28c59bcaaa5791efd47c67c8ebe28be |
|
metrics: |
|
- type: map_at_1 |
|
value: 15.753 |
|
- type: map_at_10 |
|
value: 25.875999999999998 |
|
- type: map_at_100 |
|
value: 27.415 |
|
- type: map_at_1000 |
|
value: 27.590999999999998 |
|
- type: map_at_3 |
|
value: 22.17 |
|
- type: map_at_5 |
|
value: 24.236 |
|
- type: mrr_at_1 |
|
value: 31.019000000000002 |
|
- type: mrr_at_10 |
|
value: 39.977000000000004 |
|
- type: mrr_at_100 |
|
value: 40.788999999999994 |
|
- type: mrr_at_1000 |
|
value: 40.832 |
|
- type: mrr_at_3 |
|
value: 37.088 |
|
- type: mrr_at_5 |
|
value: 38.655 |
|
- type: ndcg_at_1 |
|
value: 31.019000000000002 |
|
- type: ndcg_at_10 |
|
value: 33.286 |
|
- type: ndcg_at_100 |
|
value: 39.528999999999996 |
|
- type: ndcg_at_1000 |
|
value: 42.934 |
|
- type: ndcg_at_3 |
|
value: 29.29 |
|
- type: ndcg_at_5 |
|
value: 30.615 |
|
- type: precision_at_1 |
|
value: 31.019000000000002 |
|
- type: precision_at_10 |
|
value: 9.383 |
|
- type: precision_at_100 |
|
value: 1.6019999999999999 |
|
- type: precision_at_1000 |
|
value: 0.22200000000000003 |
|
- type: precision_at_3 |
|
value: 19.753 |
|
- type: precision_at_5 |
|
value: 14.815000000000001 |
|
- type: recall_at_1 |
|
value: 15.753 |
|
- type: recall_at_10 |
|
value: 40.896 |
|
- type: recall_at_100 |
|
value: 64.443 |
|
- type: recall_at_1000 |
|
value: 85.218 |
|
- type: recall_at_3 |
|
value: 26.526 |
|
- type: recall_at_5 |
|
value: 32.452999999999996 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: hotpotqa |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: 766870b35a1b9ca65e67a0d1913899973551fc6c |
|
metrics: |
|
- type: map_at_1 |
|
value: 32.153999999999996 |
|
- type: map_at_10 |
|
value: 43.651 |
|
- type: map_at_100 |
|
value: 44.41 |
|
- type: map_at_1000 |
|
value: 44.487 |
|
- type: map_at_3 |
|
value: 41.239 |
|
- type: map_at_5 |
|
value: 42.659000000000006 |
|
- type: mrr_at_1 |
|
value: 64.30799999999999 |
|
- type: mrr_at_10 |
|
value: 71.22500000000001 |
|
- type: mrr_at_100 |
|
value: 71.57 |
|
- type: mrr_at_1000 |
|
value: 71.59100000000001 |
|
- type: mrr_at_3 |
|
value: 69.95 |
|
- type: mrr_at_5 |
|
value: 70.738 |
|
- type: ndcg_at_1 |
|
value: 64.30799999999999 |
|
- type: ndcg_at_10 |
|
value: 52.835 |
|
- type: ndcg_at_100 |
|
value: 55.840999999999994 |
|
- type: ndcg_at_1000 |
|
value: 57.484 |
|
- type: ndcg_at_3 |
|
value: 49.014 |
|
- type: ndcg_at_5 |
|
value: 51.01599999999999 |
|
- type: precision_at_1 |
|
value: 64.30799999999999 |
|
- type: precision_at_10 |
|
value: 10.77 |
|
- type: precision_at_100 |
|
value: 1.315 |
|
- type: precision_at_1000 |
|
value: 0.153 |
|
- type: precision_at_3 |
|
value: 30.223 |
|
- type: precision_at_5 |
|
value: 19.716 |
|
- type: recall_at_1 |
|
value: 32.153999999999996 |
|
- type: recall_at_10 |
|
value: 53.849000000000004 |
|
- type: recall_at_100 |
|
value: 65.75999999999999 |
|
- type: recall_at_1000 |
|
value: 76.705 |
|
- type: recall_at_3 |
|
value: 45.334 |
|
- type: recall_at_5 |
|
value: 49.291000000000004 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 8d743909f834c38949e8323a8a6ce8721ea6c7f4 |
|
metrics: |
|
- type: accuracy |
|
value: 63.5316 |
|
- type: ap |
|
value: 58.90084300359825 |
|
- type: f1 |
|
value: 63.35727889030892 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: msmarco |
|
name: MTEB MSMARCO |
|
config: default |
|
split: validation |
|
revision: e6838a846e2408f22cf5cc337ebc83e0bcf77849 |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.566000000000003 |
|
- type: map_at_10 |
|
value: 32.229 |
|
- type: map_at_100 |
|
value: 33.445 |
|
- type: map_at_1000 |
|
value: 33.501 |
|
- type: map_at_3 |
|
value: 28.504 |
|
- type: map_at_5 |
|
value: 30.681000000000004 |
|
- type: mrr_at_1 |
|
value: 21.218 |
|
- type: mrr_at_10 |
|
value: 32.816 |
|
- type: mrr_at_100 |
|
value: 33.986 |
|
- type: mrr_at_1000 |
|
value: 34.035 |
|
- type: mrr_at_3 |
|
value: 29.15 |
|
- type: mrr_at_5 |
|
value: 31.290000000000003 |
|
- type: ndcg_at_1 |
|
value: 21.218 |
|
- type: ndcg_at_10 |
|
value: 38.832 |
|
- type: ndcg_at_100 |
|
value: 44.743 |
|
- type: ndcg_at_1000 |
|
value: 46.138 |
|
- type: ndcg_at_3 |
|
value: 31.232 |
|
- type: ndcg_at_5 |
|
value: 35.099999999999994 |
|
- type: precision_at_1 |
|
value: 21.218 |
|
- type: precision_at_10 |
|
value: 6.186 |
|
- type: precision_at_100 |
|
value: 0.914 |
|
- type: precision_at_1000 |
|
value: 0.10300000000000001 |
|
- type: precision_at_3 |
|
value: 13.314 |
|
- type: precision_at_5 |
|
value: 9.943 |
|
- type: recall_at_1 |
|
value: 20.566000000000003 |
|
- type: recall_at_10 |
|
value: 59.192 |
|
- type: recall_at_100 |
|
value: 86.626 |
|
- type: recall_at_1000 |
|
value: 97.283 |
|
- type: recall_at_3 |
|
value: 38.492 |
|
- type: recall_at_5 |
|
value: 47.760000000000005 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 |
|
metrics: |
|
- type: accuracy |
|
value: 92.56269949840402 |
|
- type: f1 |
|
value: 92.1020975473988 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 6299947a7777084cc2d4b64235bf7190381ce755 |
|
metrics: |
|
- type: accuracy |
|
value: 71.8467852257182 |
|
- type: f1 |
|
value: 53.652719348592015 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea |
|
metrics: |
|
- type: accuracy |
|
value: 69.00806993947546 |
|
- type: f1 |
|
value: 67.41429618885515 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 75.90114324142569 |
|
- type: f1 |
|
value: 76.25183590651454 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: dcefc037ef84348e49b0d29109e891c01067226b |
|
metrics: |
|
- type: v_measure |
|
value: 31.350109978273395 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 3cd0e71dfbe09d4de0f9e5ecba43e7ce280959dc |
|
metrics: |
|
- type: v_measure |
|
value: 28.768923695767327 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 31.716396735210754 |
|
- type: mrr |
|
value: 32.88970538547634 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nfcorpus |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: 7eb63cc0c1eb59324d709ebed25fcab851fa7610 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.604 |
|
- type: map_at_10 |
|
value: 12.379999999999999 |
|
- type: map_at_100 |
|
value: 15.791 |
|
- type: map_at_1000 |
|
value: 17.327 |
|
- type: map_at_3 |
|
value: 9.15 |
|
- type: map_at_5 |
|
value: 10.599 |
|
- type: mrr_at_1 |
|
value: 45.201 |
|
- type: mrr_at_10 |
|
value: 53.374 |
|
- type: mrr_at_100 |
|
value: 54.089 |
|
- type: mrr_at_1000 |
|
value: 54.123 |
|
- type: mrr_at_3 |
|
value: 51.44499999999999 |
|
- type: mrr_at_5 |
|
value: 52.59 |
|
- type: ndcg_at_1 |
|
value: 42.879 |
|
- type: ndcg_at_10 |
|
value: 33.891 |
|
- type: ndcg_at_100 |
|
value: 31.391999999999996 |
|
- type: ndcg_at_1000 |
|
value: 40.36 |
|
- type: ndcg_at_3 |
|
value: 39.076 |
|
- type: ndcg_at_5 |
|
value: 37.047000000000004 |
|
- type: precision_at_1 |
|
value: 44.582 |
|
- type: precision_at_10 |
|
value: 25.294 |
|
- type: precision_at_100 |
|
value: 8.285 |
|
- type: precision_at_1000 |
|
value: 2.1479999999999997 |
|
- type: precision_at_3 |
|
value: 36.120000000000005 |
|
- type: precision_at_5 |
|
value: 31.95 |
|
- type: recall_at_1 |
|
value: 5.604 |
|
- type: recall_at_10 |
|
value: 16.239 |
|
- type: recall_at_100 |
|
value: 32.16 |
|
- type: recall_at_1000 |
|
value: 64.513 |
|
- type: recall_at_3 |
|
value: 10.406 |
|
- type: recall_at_5 |
|
value: 12.684999999999999 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nq |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: 6062aefc120bfe8ece5897809fb2e53bfe0d128c |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.881 |
|
- type: map_at_10 |
|
value: 39.501 |
|
- type: map_at_100 |
|
value: 40.615 |
|
- type: map_at_1000 |
|
value: 40.661 |
|
- type: map_at_3 |
|
value: 35.559000000000005 |
|
- type: map_at_5 |
|
value: 37.773 |
|
- type: mrr_at_1 |
|
value: 29.229 |
|
- type: mrr_at_10 |
|
value: 41.955999999999996 |
|
- type: mrr_at_100 |
|
value: 42.86 |
|
- type: mrr_at_1000 |
|
value: 42.893 |
|
- type: mrr_at_3 |
|
value: 38.562000000000005 |
|
- type: mrr_at_5 |
|
value: 40.542 |
|
- type: ndcg_at_1 |
|
value: 29.2 |
|
- type: ndcg_at_10 |
|
value: 46.703 |
|
- type: ndcg_at_100 |
|
value: 51.644 |
|
- type: ndcg_at_1000 |
|
value: 52.771 |
|
- type: ndcg_at_3 |
|
value: 39.141999999999996 |
|
- type: ndcg_at_5 |
|
value: 42.892 |
|
- type: precision_at_1 |
|
value: 29.2 |
|
- type: precision_at_10 |
|
value: 7.920000000000001 |
|
- type: precision_at_100 |
|
value: 1.0659999999999998 |
|
- type: precision_at_1000 |
|
value: 0.117 |
|
- type: precision_at_3 |
|
value: 18.105 |
|
- type: precision_at_5 |
|
value: 13.036 |
|
- type: recall_at_1 |
|
value: 25.881 |
|
- type: recall_at_10 |
|
value: 66.266 |
|
- type: recall_at_100 |
|
value: 88.116 |
|
- type: recall_at_1000 |
|
value: 96.58200000000001 |
|
- type: recall_at_3 |
|
value: 46.526 |
|
- type: recall_at_5 |
|
value: 55.154 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: quora |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: 6205996560df11e3a3da9ab4f926788fc30a7db4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 67.553 |
|
- type: map_at_10 |
|
value: 81.34 |
|
- type: map_at_100 |
|
value: 82.002 |
|
- type: map_at_1000 |
|
value: 82.027 |
|
- type: map_at_3 |
|
value: 78.281 |
|
- type: map_at_5 |
|
value: 80.149 |
|
- type: mrr_at_1 |
|
value: 77.72 |
|
- type: mrr_at_10 |
|
value: 84.733 |
|
- type: mrr_at_100 |
|
value: 84.878 |
|
- type: mrr_at_1000 |
|
value: 84.879 |
|
- type: mrr_at_3 |
|
value: 83.587 |
|
- type: mrr_at_5 |
|
value: 84.32600000000001 |
|
- type: ndcg_at_1 |
|
value: 77.75 |
|
- type: ndcg_at_10 |
|
value: 85.603 |
|
- type: ndcg_at_100 |
|
value: 87.069 |
|
- type: ndcg_at_1000 |
|
value: 87.25 |
|
- type: ndcg_at_3 |
|
value: 82.303 |
|
- type: ndcg_at_5 |
|
value: 84.03699999999999 |
|
- type: precision_at_1 |
|
value: 77.75 |
|
- type: precision_at_10 |
|
value: 13.04 |
|
- type: precision_at_100 |
|
value: 1.5070000000000001 |
|
- type: precision_at_1000 |
|
value: 0.156 |
|
- type: precision_at_3 |
|
value: 35.903 |
|
- type: precision_at_5 |
|
value: 23.738 |
|
- type: recall_at_1 |
|
value: 67.553 |
|
- type: recall_at_10 |
|
value: 93.903 |
|
- type: recall_at_100 |
|
value: 99.062 |
|
- type: recall_at_1000 |
|
value: 99.935 |
|
- type: recall_at_3 |
|
value: 84.58099999999999 |
|
- type: recall_at_5 |
|
value: 89.316 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: b2805658ae38990172679479369a78b86de8c390 |
|
metrics: |
|
- type: v_measure |
|
value: 46.46887711230235 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 |
|
metrics: |
|
- type: v_measure |
|
value: 54.166876298246926 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scidocs |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: 5c59ef3e437a0a9651c8fe6fde943e7dce59fba5 |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.053 |
|
- type: map_at_10 |
|
value: 9.693999999999999 |
|
- type: map_at_100 |
|
value: 11.387 |
|
- type: map_at_1000 |
|
value: 11.654 |
|
- type: map_at_3 |
|
value: 7.053 |
|
- type: map_at_5 |
|
value: 8.439 |
|
- type: mrr_at_1 |
|
value: 19.900000000000002 |
|
- type: mrr_at_10 |
|
value: 29.359 |
|
- type: mrr_at_100 |
|
value: 30.484 |
|
- type: mrr_at_1000 |
|
value: 30.553 |
|
- type: mrr_at_3 |
|
value: 26.200000000000003 |
|
- type: mrr_at_5 |
|
value: 28.115000000000002 |
|
- type: ndcg_at_1 |
|
value: 19.900000000000002 |
|
- type: ndcg_at_10 |
|
value: 16.575 |
|
- type: ndcg_at_100 |
|
value: 23.655 |
|
- type: ndcg_at_1000 |
|
value: 28.853 |
|
- type: ndcg_at_3 |
|
value: 15.848 |
|
- type: ndcg_at_5 |
|
value: 14.026 |
|
- type: precision_at_1 |
|
value: 19.900000000000002 |
|
- type: precision_at_10 |
|
value: 8.450000000000001 |
|
- type: precision_at_100 |
|
value: 1.872 |
|
- type: precision_at_1000 |
|
value: 0.313 |
|
- type: precision_at_3 |
|
value: 14.667 |
|
- type: precision_at_5 |
|
value: 12.32 |
|
- type: recall_at_1 |
|
value: 4.053 |
|
- type: recall_at_10 |
|
value: 17.169999999999998 |
|
- type: recall_at_100 |
|
value: 38.025 |
|
- type: recall_at_1000 |
|
value: 63.571999999999996 |
|
- type: recall_at_3 |
|
value: 8.903 |
|
- type: recall_at_5 |
|
value: 12.477 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.7548748519677 |
|
- type: cos_sim_spearman |
|
value: 68.19926431966059 |
|
- type: euclidean_pearson |
|
value: 71.69016204991725 |
|
- type: euclidean_spearman |
|
value: 66.98099673026834 |
|
- type: manhattan_pearson |
|
value: 71.62994072488664 |
|
- type: manhattan_spearman |
|
value: 67.03435950744577 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: fdf84275bb8ce4b49c971d02e84dd1abc677a50f |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.91051402657887 |
|
- type: cos_sim_spearman |
|
value: 66.99390786191645 |
|
- type: euclidean_pearson |
|
value: 71.54128036454578 |
|
- type: euclidean_spearman |
|
value: 69.25605675649068 |
|
- type: manhattan_pearson |
|
value: 71.60981030780171 |
|
- type: manhattan_spearman |
|
value: 69.27513670128046 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 1591bfcbe8c69d4bf7fe2a16e2451017832cafb9 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.23835466417793 |
|
- type: cos_sim_spearman |
|
value: 77.57623085766706 |
|
- type: euclidean_pearson |
|
value: 77.5090992200725 |
|
- type: euclidean_spearman |
|
value: 77.88601688144924 |
|
- type: manhattan_pearson |
|
value: 77.39045060647423 |
|
- type: manhattan_spearman |
|
value: 77.77552718279098 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: e2125984e7df8b7871f6ae9949cf6b6795e7c54b |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.91692485139602 |
|
- type: cos_sim_spearman |
|
value: 72.78258293483495 |
|
- type: euclidean_pearson |
|
value: 74.64773017077789 |
|
- type: euclidean_spearman |
|
value: 71.81662299104619 |
|
- type: manhattan_pearson |
|
value: 74.71043337995533 |
|
- type: manhattan_spearman |
|
value: 71.83960860845646 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: 1cd7298cac12a96a373b6a2f18738bb3e739a9b6 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.13422113617578 |
|
- type: cos_sim_spearman |
|
value: 82.61707296911949 |
|
- type: euclidean_pearson |
|
value: 81.42487480400861 |
|
- type: euclidean_spearman |
|
value: 82.17970991273835 |
|
- type: manhattan_pearson |
|
value: 81.41985055477845 |
|
- type: manhattan_spearman |
|
value: 82.15823204362937 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 360a0b2dff98700d09e634a01e1cc1624d3e42cd |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.07989542843826 |
|
- type: cos_sim_spearman |
|
value: 80.09839524406284 |
|
- type: euclidean_pearson |
|
value: 76.43186028364195 |
|
- type: euclidean_spearman |
|
value: 76.76720323266471 |
|
- type: manhattan_pearson |
|
value: 76.4674747409161 |
|
- type: manhattan_spearman |
|
value: 76.81797407068667 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.0420983224933 |
|
- type: cos_sim_spearman |
|
value: 87.25017540413702 |
|
- type: euclidean_pearson |
|
value: 84.56384596473421 |
|
- type: euclidean_spearman |
|
value: 84.72557417564886 |
|
- type: manhattan_pearson |
|
value: 84.7329954474549 |
|
- type: manhattan_spearman |
|
value: 84.75071371008909 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 68.47031320016424 |
|
- type: cos_sim_spearman |
|
value: 68.7486910762485 |
|
- type: euclidean_pearson |
|
value: 71.30330985913915 |
|
- type: euclidean_spearman |
|
value: 71.59666258520735 |
|
- type: manhattan_pearson |
|
value: 71.4423884279027 |
|
- type: manhattan_spearman |
|
value: 71.67460706861044 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: 8913289635987208e6e7c72789e4be2fe94b6abd |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.79514366062675 |
|
- type: cos_sim_spearman |
|
value: 79.20585637461048 |
|
- type: euclidean_pearson |
|
value: 78.6591557395699 |
|
- type: euclidean_spearman |
|
value: 77.86455794285718 |
|
- type: manhattan_pearson |
|
value: 78.67754806486865 |
|
- type: manhattan_spearman |
|
value: 77.88178687200732 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: 56a6d0140cf6356659e2a7c1413286a774468d44 |
|
metrics: |
|
- type: map |
|
value: 77.71580844366375 |
|
- type: mrr |
|
value: 93.04215845882513 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scifact |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: a75ae049398addde9b70f6b268875f5cbce99089 |
|
metrics: |
|
- type: map_at_1 |
|
value: 56.39999999999999 |
|
- type: map_at_10 |
|
value: 65.701 |
|
- type: map_at_100 |
|
value: 66.32000000000001 |
|
- type: map_at_1000 |
|
value: 66.34100000000001 |
|
- type: map_at_3 |
|
value: 62.641999999999996 |
|
- type: map_at_5 |
|
value: 64.342 |
|
- type: mrr_at_1 |
|
value: 58.667 |
|
- type: mrr_at_10 |
|
value: 66.45299999999999 |
|
- type: mrr_at_100 |
|
value: 66.967 |
|
- type: mrr_at_1000 |
|
value: 66.988 |
|
- type: mrr_at_3 |
|
value: 64.11099999999999 |
|
- type: mrr_at_5 |
|
value: 65.411 |
|
- type: ndcg_at_1 |
|
value: 58.667 |
|
- type: ndcg_at_10 |
|
value: 70.165 |
|
- type: ndcg_at_100 |
|
value: 72.938 |
|
- type: ndcg_at_1000 |
|
value: 73.456 |
|
- type: ndcg_at_3 |
|
value: 64.79 |
|
- type: ndcg_at_5 |
|
value: 67.28 |
|
- type: precision_at_1 |
|
value: 58.667 |
|
- type: precision_at_10 |
|
value: 9.4 |
|
- type: precision_at_100 |
|
value: 1.087 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 24.889 |
|
- type: precision_at_5 |
|
value: 16.667 |
|
- type: recall_at_1 |
|
value: 56.39999999999999 |
|
- type: recall_at_10 |
|
value: 83.122 |
|
- type: recall_at_100 |
|
value: 95.667 |
|
- type: recall_at_1000 |
|
value: 99.667 |
|
- type: recall_at_3 |
|
value: 68.378 |
|
- type: recall_at_5 |
|
value: 74.68299999999999 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: 5a8256d0dff9c4bd3be3ba3e67e4e70173f802ea |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.76831683168317 |
|
- type: cos_sim_ap |
|
value: 93.47124923047998 |
|
- type: cos_sim_f1 |
|
value: 88.06122448979592 |
|
- type: cos_sim_precision |
|
value: 89.89583333333333 |
|
- type: cos_sim_recall |
|
value: 86.3 |
|
- type: dot_accuracy |
|
value: 99.57326732673268 |
|
- type: dot_ap |
|
value: 84.06577868167207 |
|
- type: dot_f1 |
|
value: 77.82629791363416 |
|
- type: dot_precision |
|
value: 75.58906691800189 |
|
- type: dot_recall |
|
value: 80.2 |
|
- type: euclidean_accuracy |
|
value: 99.74257425742574 |
|
- type: euclidean_ap |
|
value: 92.1904681653555 |
|
- type: euclidean_f1 |
|
value: 86.74821610601427 |
|
- type: euclidean_precision |
|
value: 88.46153846153845 |
|
- type: euclidean_recall |
|
value: 85.1 |
|
- type: manhattan_accuracy |
|
value: 99.74554455445545 |
|
- type: manhattan_ap |
|
value: 92.4337790809948 |
|
- type: manhattan_f1 |
|
value: 86.86765457332653 |
|
- type: manhattan_precision |
|
value: 88.81922675026124 |
|
- type: manhattan_recall |
|
value: 85.0 |
|
- type: max_accuracy |
|
value: 99.76831683168317 |
|
- type: max_ap |
|
value: 93.47124923047998 |
|
- type: max_f1 |
|
value: 88.06122448979592 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 70a89468f6dccacc6aa2b12a6eac54e74328f235 |
|
metrics: |
|
- type: v_measure |
|
value: 59.194098673976484 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: d88009ab563dd0b16cfaf4436abaf97fa3550cf0 |
|
metrics: |
|
- type: v_measure |
|
value: 32.5744032578115 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: ef807ea29a75ec4f91b50fd4191cb4ee4589a9f9 |
|
metrics: |
|
- type: map |
|
value: 49.61186384154483 |
|
- type: mrr |
|
value: 50.55424253034547 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: mteb/summeval |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: 8753c2788d36c01fc6f05d03fe3f7268d63f9122 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.027210161713946 |
|
- type: cos_sim_spearman |
|
value: 31.030178065751735 |
|
- type: dot_pearson |
|
value: 30.09179785685587 |
|
- type: dot_spearman |
|
value: 30.408303252207813 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: trec-covid |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: 2c8041b2c07a79b6f7ba8fe6acc72e5d9f92d217 |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.22300000000000003 |
|
- type: map_at_10 |
|
value: 1.762 |
|
- type: map_at_100 |
|
value: 9.984 |
|
- type: map_at_1000 |
|
value: 24.265 |
|
- type: map_at_3 |
|
value: 0.631 |
|
- type: map_at_5 |
|
value: 0.9950000000000001 |
|
- type: mrr_at_1 |
|
value: 88.0 |
|
- type: mrr_at_10 |
|
value: 92.833 |
|
- type: mrr_at_100 |
|
value: 92.833 |
|
- type: mrr_at_1000 |
|
value: 92.833 |
|
- type: mrr_at_3 |
|
value: 92.333 |
|
- type: mrr_at_5 |
|
value: 92.833 |
|
- type: ndcg_at_1 |
|
value: 83.0 |
|
- type: ndcg_at_10 |
|
value: 75.17 |
|
- type: ndcg_at_100 |
|
value: 55.432 |
|
- type: ndcg_at_1000 |
|
value: 49.482 |
|
- type: ndcg_at_3 |
|
value: 82.184 |
|
- type: ndcg_at_5 |
|
value: 79.712 |
|
- type: precision_at_1 |
|
value: 88.0 |
|
- type: precision_at_10 |
|
value: 78.60000000000001 |
|
- type: precision_at_100 |
|
value: 56.56 |
|
- type: precision_at_1000 |
|
value: 22.334 |
|
- type: precision_at_3 |
|
value: 86.667 |
|
- type: precision_at_5 |
|
value: 83.6 |
|
- type: recall_at_1 |
|
value: 0.22300000000000003 |
|
- type: recall_at_10 |
|
value: 1.9879999999999998 |
|
- type: recall_at_100 |
|
value: 13.300999999999998 |
|
- type: recall_at_1000 |
|
value: 46.587 |
|
- type: recall_at_3 |
|
value: 0.6629999999999999 |
|
- type: recall_at_5 |
|
value: 1.079 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: webis-touche2020 |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: 527b7d77e16e343303e68cb6af11d6e18b9f7b3b |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.047 |
|
- type: map_at_10 |
|
value: 8.792 |
|
- type: map_at_100 |
|
value: 14.631 |
|
- type: map_at_1000 |
|
value: 16.127 |
|
- type: map_at_3 |
|
value: 4.673 |
|
- type: map_at_5 |
|
value: 5.897 |
|
- type: mrr_at_1 |
|
value: 38.775999999999996 |
|
- type: mrr_at_10 |
|
value: 49.271 |
|
- type: mrr_at_100 |
|
value: 50.181 |
|
- type: mrr_at_1000 |
|
value: 50.2 |
|
- type: mrr_at_3 |
|
value: 44.558 |
|
- type: mrr_at_5 |
|
value: 47.925000000000004 |
|
- type: ndcg_at_1 |
|
value: 35.714 |
|
- type: ndcg_at_10 |
|
value: 23.44 |
|
- type: ndcg_at_100 |
|
value: 35.345 |
|
- type: ndcg_at_1000 |
|
value: 46.495 |
|
- type: ndcg_at_3 |
|
value: 26.146 |
|
- type: ndcg_at_5 |
|
value: 24.878 |
|
- type: precision_at_1 |
|
value: 38.775999999999996 |
|
- type: precision_at_10 |
|
value: 20.816000000000003 |
|
- type: precision_at_100 |
|
value: 7.428999999999999 |
|
- type: precision_at_1000 |
|
value: 1.494 |
|
- type: precision_at_3 |
|
value: 25.85 |
|
- type: precision_at_5 |
|
value: 24.082 |
|
- type: recall_at_1 |
|
value: 3.047 |
|
- type: recall_at_10 |
|
value: 14.975 |
|
- type: recall_at_100 |
|
value: 45.943 |
|
- type: recall_at_1000 |
|
value: 80.31099999999999 |
|
- type: recall_at_3 |
|
value: 5.478000000000001 |
|
- type: recall_at_5 |
|
value: 8.294 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de |
|
metrics: |
|
- type: accuracy |
|
value: 68.84080000000002 |
|
- type: ap |
|
value: 13.135219251019848 |
|
- type: f1 |
|
value: 52.849999421995506 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: 62146448f05be9e52a36b8ee9936447ea787eede |
|
metrics: |
|
- type: accuracy |
|
value: 56.68647425014149 |
|
- type: f1 |
|
value: 56.97981427365949 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 091a54f9a36281ce7d6590ec8c75dd485e7e01d4 |
|
metrics: |
|
- type: v_measure |
|
value: 40.8911707239219 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 83.04226023722954 |
|
- type: cos_sim_ap |
|
value: 63.681339908301325 |
|
- type: cos_sim_f1 |
|
value: 60.349184470480125 |
|
- type: cos_sim_precision |
|
value: 53.437754271765655 |
|
- type: cos_sim_recall |
|
value: 69.31398416886545 |
|
- type: dot_accuracy |
|
value: 81.46271681468677 |
|
- type: dot_ap |
|
value: 57.78072296265885 |
|
- type: dot_f1 |
|
value: 56.28769265132901 |
|
- type: dot_precision |
|
value: 48.7993803253292 |
|
- type: dot_recall |
|
value: 66.49076517150397 |
|
- type: euclidean_accuracy |
|
value: 82.16606067830959 |
|
- type: euclidean_ap |
|
value: 59.974530371203514 |
|
- type: euclidean_f1 |
|
value: 56.856023506366306 |
|
- type: euclidean_precision |
|
value: 53.037916857012334 |
|
- type: euclidean_recall |
|
value: 61.2664907651715 |
|
- type: manhattan_accuracy |
|
value: 82.16606067830959 |
|
- type: manhattan_ap |
|
value: 59.98962379571767 |
|
- type: manhattan_f1 |
|
value: 56.98153158451947 |
|
- type: manhattan_precision |
|
value: 51.41158989598811 |
|
- type: manhattan_recall |
|
value: 63.90501319261214 |
|
- type: max_accuracy |
|
value: 83.04226023722954 |
|
- type: max_ap |
|
value: 63.681339908301325 |
|
- type: max_f1 |
|
value: 60.349184470480125 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.56871191834517 |
|
- type: cos_sim_ap |
|
value: 84.80240716354544 |
|
- type: cos_sim_f1 |
|
value: 77.07765285922385 |
|
- type: cos_sim_precision |
|
value: 74.84947406601378 |
|
- type: cos_sim_recall |
|
value: 79.44256236526024 |
|
- type: dot_accuracy |
|
value: 86.00923662048356 |
|
- type: dot_ap |
|
value: 78.6556459012073 |
|
- type: dot_f1 |
|
value: 72.7583749109052 |
|
- type: dot_precision |
|
value: 67.72823779193206 |
|
- type: dot_recall |
|
value: 78.59562673236834 |
|
- type: euclidean_accuracy |
|
value: 87.84103698529127 |
|
- type: euclidean_ap |
|
value: 83.50424424952834 |
|
- type: euclidean_f1 |
|
value: 75.74496544549307 |
|
- type: euclidean_precision |
|
value: 73.19402556369381 |
|
- type: euclidean_recall |
|
value: 78.48013550970127 |
|
- type: manhattan_accuracy |
|
value: 87.9225365777933 |
|
- type: manhattan_ap |
|
value: 83.49479248597825 |
|
- type: manhattan_f1 |
|
value: 75.67748162447101 |
|
- type: manhattan_precision |
|
value: 73.06810035842294 |
|
- type: manhattan_recall |
|
value: 78.48013550970127 |
|
- type: max_accuracy |
|
value: 88.56871191834517 |
|
- type: max_ap |
|
value: 84.80240716354544 |
|
- type: max_f1 |
|
value: 77.07765285922385 |
|
--- |
|
|
|
# SGPT-2.7B-weightedmean-msmarco-specb-bitfit |
|
|
|
## Usage |
|
|
|
For usage instructions, refer to our codebase: https://github.com/Muennighoff/sgpt |
|
|
|
## Evaluation Results |
|
|
|
For eval results, refer to the eval folder or our paper: https://arxiv.org/abs/2202.08904 |
|
|
|
## Training |
|
The model was trained with the parameters: |
|
|
|
**DataLoader**: |
|
|
|
`torch.utils.data.dataloader.DataLoader` of length 124796 with parameters: |
|
``` |
|
{'batch_size': 4, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'} |
|
``` |
|
|
|
**Loss**: |
|
|
|
`sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss` with parameters: |
|
``` |
|
{'scale': 20.0, 'similarity_fct': 'cos_sim'} |
|
``` |
|
|
|
Parameters of the fit()-Method: |
|
``` |
|
{ |
|
"epochs": 10, |
|
"evaluation_steps": 0, |
|
"evaluator": "NoneType", |
|
"max_grad_norm": 1, |
|
"optimizer_class": "<class 'transformers.optimization.AdamW'>", |
|
"optimizer_params": { |
|
"lr": 7.5e-05 |
|
}, |
|
"scheduler": "WarmupLinear", |
|
"steps_per_epoch": null, |
|
"warmup_steps": 1000, |
|
"weight_decay": 0.01 |
|
} |
|
``` |
|
|
|
|
|
## Full Model Architecture |
|
``` |
|
SentenceTransformer( |
|
(0): Transformer({'max_seq_length': 300, 'do_lower_case': False}) with Transformer model: GPTNeoModel |
|
(1): Pooling({'word_embedding_dimension': 2560, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': True, 'pooling_mode_lasttoken': False}) |
|
) |
|
``` |
|
|
|
## Citing & Authors |
|
|
|
```bibtex |
|
@article{muennighoff2022sgpt, |
|
title={SGPT: GPT Sentence Embeddings for Semantic Search}, |
|
author={Muennighoff, Niklas}, |
|
journal={arXiv preprint arXiv:2202.08904}, |
|
year={2022} |
|
} |
|
``` |
