--- pipeline_tag: sentence-similarity tags: - sentence-transformers - feature-extraction - sentence-similarity - mteb model-index: - name: SGPT-125M-weightedmean-nli-bitfit results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 metrics: - type: accuracy value: 65.88059701492537 - type: ap value: 28.685493163579785 - type: f1 value: 59.79951005816335 - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (de) config: de split: test revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 metrics: - type: accuracy value: 59.07922912205568 - type: ap value: 73.91887421019034 - type: f1 value: 56.6316368658711 - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en-ext) config: en-ext split: test revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 metrics: - type: accuracy value: 64.91754122938531 - type: ap value: 16.360681214864226 - type: f1 value: 53.126592061523766 - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (ja) config: ja split: test revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 metrics: - type: accuracy value: 56.423982869378996 - type: ap value: 12.143003571907899 - type: f1 value: 45.76363777987471 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1 metrics: - type: accuracy value: 74.938225 - type: ap value: 69.58187110320567 - type: f1 value: 74.72744058439321 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 35.098 - type: f1 value: 34.73265651435726 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (de) config: de split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 24.516 - type: f1 value: 24.21748200448397 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (es) config: es split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 29.097999999999995 - type: f1 value: 28.620040162757093 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (fr) config: fr split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 27.395999999999997 - type: f1 value: 27.146888644986284 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (ja) config: ja split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 21.724 - type: f1 value: 21.37230564276654 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (zh) config: zh split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 23.976 - type: f1 value: 23.741137981755482 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3 metrics: - type: map_at_1 value: 13.442000000000002 - type: map_at_10 value: 24.275 - type: map_at_100 value: 25.588 - type: map_at_1000 value: 25.659 - type: map_at_3 value: 20.092 - type: map_at_5 value: 22.439999999999998 - type: ndcg_at_1 value: 13.442000000000002 - type: ndcg_at_10 value: 31.04 - type: ndcg_at_100 value: 37.529 - type: ndcg_at_1000 value: 39.348 - type: ndcg_at_3 value: 22.342000000000002 - type: ndcg_at_5 value: 26.595999999999997 - type: precision_at_1 value: 13.442000000000002 - type: precision_at_10 value: 5.299 - type: precision_at_100 value: 0.836 - type: precision_at_1000 value: 0.098 - type: precision_at_3 value: 9.625 - type: precision_at_5 value: 7.852 - type: recall_at_1 value: 13.442000000000002 - type: recall_at_10 value: 52.986999999999995 - type: recall_at_100 value: 83.64200000000001 - type: recall_at_1000 value: 97.795 - type: recall_at_3 value: 28.876 - type: recall_at_5 value: 39.26 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8 metrics: - type: v_measure value: 34.742482477870766 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3 metrics: - type: v_measure value: 24.67870651472156 - task: type: Clustering dataset: type: slvnwhrl/blurbs-clustering-s2s name: MTEB BlurbsClusteringS2S config: default split: test revision: 9bfff9a7f8f6dc6ffc9da71c48dd48b68696471d metrics: - type: v_measure value: 8.00311862863495 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c metrics: - type: map value: 52.63439984994702 - type: mrr value: 65.75704612408214 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: 9ee918f184421b6bd48b78f6c714d86546106103 metrics: - type: cos_sim_pearson value: 72.78000135012542 - type: cos_sim_spearman value: 70.92812216947605 - type: euclidean_pearson value: 77.1169214949292 - type: euclidean_spearman value: 77.10175681583313 - type: manhattan_pearson value: 76.84527031837595 - type: manhattan_spearman value: 77.0704308008438 - task: type: BitextMining dataset: type: mteb/bucc-bitext-mining name: MTEB BUCC (de-en) config: de-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 1.0960334029227559 - type: f1 value: 1.0925539318023658 - type: precision value: 1.0908141962421711 - type: recall value: 1.0960334029227559 - task: type: BitextMining dataset: type: mteb/bucc-bitext-mining name: MTEB BUCC (fr-en) config: fr-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 0.02201188641866608 - type: f1 value: 0.02201188641866608 - type: precision value: 0.02201188641866608 - type: recall value: 0.02201188641866608 - task: type: BitextMining dataset: type: mteb/bucc-bitext-mining name: MTEB BUCC (ru-en) config: ru-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 0.0 - type: f1 value: 0.0 - type: precision value: 0.0 - type: recall value: 0.0 - task: type: BitextMining dataset: type: mteb/bucc-bitext-mining name: MTEB BUCC (zh-en) config: zh-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 0.0 - type: f1 value: 0.0 - type: precision value: 0.0 - type: recall value: 0.0 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 44fa15921b4c889113cc5df03dd4901b49161ab7 metrics: - type: accuracy value: 74.67857142857142 - type: f1 value: 74.61743413995573 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55 metrics: - type: v_measure value: 28.93427045246491 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1 metrics: - type: v_measure value: 23.080939123955474 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 18.221999999999998 - type: map_at_10 value: 24.506 - type: map_at_100 value: 25.611 - type: map_at_1000 value: 25.758 - type: map_at_3 value: 22.264999999999997 - type: map_at_5 value: 23.698 - type: ndcg_at_1 value: 23.033 - type: ndcg_at_10 value: 28.719 - type: ndcg_at_100 value: 33.748 - type: ndcg_at_1000 value: 37.056 - type: ndcg_at_3 value: 25.240000000000002 - type: ndcg_at_5 value: 27.12 - type: precision_at_1 value: 23.033 - type: precision_at_10 value: 5.408 - type: precision_at_100 value: 1.004 - type: precision_at_1000 value: 0.158 - type: precision_at_3 value: 11.874 - type: precision_at_5 value: 8.927 - type: recall_at_1 value: 18.221999999999998 - type: recall_at_10 value: 36.355 - type: recall_at_100 value: 58.724 - type: recall_at_1000 value: 81.33500000000001 - type: recall_at_3 value: 26.334000000000003 - type: recall_at_5 value: 31.4 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 12.058 - type: map_at_10 value: 16.051000000000002 - type: map_at_100 value: 16.772000000000002 - type: map_at_1000 value: 16.871 - type: map_at_3 value: 14.78 - type: map_at_5 value: 15.5 - type: ndcg_at_1 value: 15.35 - type: ndcg_at_10 value: 18.804000000000002 - type: ndcg_at_100 value: 22.346 - type: ndcg_at_1000 value: 25.007 - type: ndcg_at_3 value: 16.768 - type: ndcg_at_5 value: 17.692 - type: precision_at_1 value: 15.35 - type: precision_at_10 value: 3.51 - type: precision_at_100 value: 0.664 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 7.983 - type: precision_at_5 value: 5.656 - type: recall_at_1 value: 12.058 - type: recall_at_10 value: 23.644000000000002 - type: recall_at_100 value: 39.76 - type: recall_at_1000 value: 58.56 - type: recall_at_3 value: 17.541999999999998 - type: recall_at_5 value: 20.232 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 21.183 - type: map_at_10 value: 28.9 - type: map_at_100 value: 29.858 - type: map_at_1000 value: 29.953999999999997 - type: map_at_3 value: 26.58 - type: map_at_5 value: 27.912 - type: ndcg_at_1 value: 24.765 - type: ndcg_at_10 value: 33.339999999999996 - type: ndcg_at_100 value: 37.997 - type: ndcg_at_1000 value: 40.416000000000004 - type: ndcg_at_3 value: 29.044999999999998 - type: ndcg_at_5 value: 31.121 - type: precision_at_1 value: 24.765 - type: precision_at_10 value: 5.599 - type: precision_at_100 value: 0.8699999999999999 - type: precision_at_1000 value: 0.11499999999999999 - type: precision_at_3 value: 13.270999999999999 - type: precision_at_5 value: 9.367 - type: recall_at_1 value: 21.183 - type: recall_at_10 value: 43.875 - type: recall_at_100 value: 65.005 - type: recall_at_1000 value: 83.017 - type: recall_at_3 value: 32.232 - type: recall_at_5 value: 37.308 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 11.350999999999999 - type: map_at_10 value: 14.953 - type: map_at_100 value: 15.623000000000001 - type: map_at_1000 value: 15.716 - type: map_at_3 value: 13.603000000000002 - type: map_at_5 value: 14.343 - type: ndcg_at_1 value: 12.429 - type: ndcg_at_10 value: 17.319000000000003 - type: ndcg_at_100 value: 20.990000000000002 - type: ndcg_at_1000 value: 23.899 - type: ndcg_at_3 value: 14.605 - type: ndcg_at_5 value: 15.89 - type: precision_at_1 value: 12.429 - type: precision_at_10 value: 2.701 - type: precision_at_100 value: 0.48700000000000004 - type: precision_at_1000 value: 0.078 - type: precision_at_3 value: 6.026 - type: precision_at_5 value: 4.3839999999999995 - type: recall_at_1 value: 11.350999999999999 - type: recall_at_10 value: 23.536 - type: recall_at_100 value: 40.942 - type: recall_at_1000 value: 64.05 - type: recall_at_3 value: 16.195 - type: recall_at_5 value: 19.264 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 8.08 - type: map_at_10 value: 11.691 - type: map_at_100 value: 12.312 - type: map_at_1000 value: 12.439 - type: map_at_3 value: 10.344000000000001 - type: map_at_5 value: 10.996 - type: ndcg_at_1 value: 10.697 - type: ndcg_at_10 value: 14.48 - type: ndcg_at_100 value: 18.160999999999998 - type: ndcg_at_1000 value: 21.886 - type: ndcg_at_3 value: 11.872 - type: ndcg_at_5 value: 12.834000000000001 - type: precision_at_1 value: 10.697 - type: precision_at_10 value: 2.811 - type: precision_at_100 value: 0.551 - type: precision_at_1000 value: 0.10200000000000001 - type: precision_at_3 value: 5.804 - type: precision_at_5 value: 4.154 - type: recall_at_1 value: 8.08 - type: recall_at_10 value: 20.235 - type: recall_at_100 value: 37.525999999999996 - type: recall_at_1000 value: 65.106 - type: recall_at_3 value: 12.803999999999998 - type: recall_at_5 value: 15.498999999999999 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 13.908999999999999 - type: map_at_10 value: 19.256 - type: map_at_100 value: 20.286 - type: map_at_1000 value: 20.429 - type: map_at_3 value: 17.399 - type: map_at_5 value: 18.398999999999997 - type: ndcg_at_1 value: 17.421 - type: ndcg_at_10 value: 23.105999999999998 - type: ndcg_at_100 value: 28.128999999999998 - type: ndcg_at_1000 value: 31.480999999999998 - type: ndcg_at_3 value: 19.789 - type: ndcg_at_5 value: 21.237000000000002 - type: precision_at_1 value: 17.421 - type: precision_at_10 value: 4.331 - type: precision_at_100 value: 0.839 - type: precision_at_1000 value: 0.131 - type: precision_at_3 value: 9.4 - type: precision_at_5 value: 6.776 - type: recall_at_1 value: 13.908999999999999 - type: recall_at_10 value: 31.086999999999996 - type: recall_at_100 value: 52.946000000000005 - type: recall_at_1000 value: 76.546 - type: recall_at_3 value: 21.351 - type: recall_at_5 value: 25.264999999999997 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 12.598 - type: map_at_10 value: 17.304 - type: map_at_100 value: 18.209 - type: map_at_1000 value: 18.328 - type: map_at_3 value: 15.784 - type: map_at_5 value: 16.669999999999998 - type: ndcg_at_1 value: 15.867999999999999 - type: ndcg_at_10 value: 20.623 - type: ndcg_at_100 value: 25.093 - type: ndcg_at_1000 value: 28.498 - type: ndcg_at_3 value: 17.912 - type: ndcg_at_5 value: 19.198 - type: precision_at_1 value: 15.867999999999999 - type: precision_at_10 value: 3.7670000000000003 - type: precision_at_100 value: 0.716 - type: precision_at_1000 value: 0.11800000000000001 - type: precision_at_3 value: 8.638 - type: precision_at_5 value: 6.21 - type: recall_at_1 value: 12.598 - type: recall_at_10 value: 27.144000000000002 - type: recall_at_100 value: 46.817 - type: recall_at_1000 value: 71.86099999999999 - type: recall_at_3 value: 19.231 - type: recall_at_5 value: 22.716 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 12.738416666666666 - type: map_at_10 value: 17.235916666666668 - type: map_at_100 value: 18.063333333333333 - type: map_at_1000 value: 18.18433333333333 - type: map_at_3 value: 15.74775 - type: map_at_5 value: 16.57825 - type: ndcg_at_1 value: 15.487416666666665 - type: ndcg_at_10 value: 20.290166666666668 - type: ndcg_at_100 value: 24.41291666666666 - type: ndcg_at_1000 value: 27.586333333333336 - type: ndcg_at_3 value: 17.622083333333332 - type: ndcg_at_5 value: 18.859916666666667 - type: precision_at_1 value: 15.487416666666665 - type: precision_at_10 value: 3.6226666666666665 - type: precision_at_100 value: 0.6820833333333334 - type: precision_at_1000 value: 0.11216666666666666 - type: precision_at_3 value: 8.163749999999999 - type: precision_at_5 value: 5.865416666666667 - type: recall_at_1 value: 12.738416666666666 - type: recall_at_10 value: 26.599416666666663 - type: recall_at_100 value: 45.41258333333334 - type: recall_at_1000 value: 68.7565 - type: recall_at_3 value: 19.008166666666668 - type: recall_at_5 value: 22.24991666666667 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 12.307 - type: map_at_10 value: 15.440000000000001 - type: map_at_100 value: 16.033 - type: map_at_1000 value: 16.14 - type: map_at_3 value: 14.393 - type: map_at_5 value: 14.856 - type: ndcg_at_1 value: 14.571000000000002 - type: ndcg_at_10 value: 17.685000000000002 - type: ndcg_at_100 value: 20.882 - type: ndcg_at_1000 value: 23.888 - type: ndcg_at_3 value: 15.739 - type: ndcg_at_5 value: 16.391 - type: precision_at_1 value: 14.571000000000002 - type: precision_at_10 value: 2.883 - type: precision_at_100 value: 0.49100000000000005 - type: precision_at_1000 value: 0.08 - type: precision_at_3 value: 7.0040000000000004 - type: precision_at_5 value: 4.693 - type: recall_at_1 value: 12.307 - type: recall_at_10 value: 22.566 - type: recall_at_100 value: 37.469 - type: recall_at_1000 value: 60.550000000000004 - type: recall_at_3 value: 16.742 - type: recall_at_5 value: 18.634 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 6.496 - type: map_at_10 value: 9.243 - type: map_at_100 value: 9.841 - type: map_at_1000 value: 9.946000000000002 - type: map_at_3 value: 8.395 - type: map_at_5 value: 8.872 - type: ndcg_at_1 value: 8.224 - type: ndcg_at_10 value: 11.24 - type: ndcg_at_100 value: 14.524999999999999 - type: ndcg_at_1000 value: 17.686 - type: ndcg_at_3 value: 9.617 - type: ndcg_at_5 value: 10.37 - type: precision_at_1 value: 8.224 - type: precision_at_10 value: 2.0820000000000003 - type: precision_at_100 value: 0.443 - type: precision_at_1000 value: 0.08499999999999999 - type: precision_at_3 value: 4.623 - type: precision_at_5 value: 3.331 - type: recall_at_1 value: 6.496 - type: recall_at_10 value: 15.310000000000002 - type: recall_at_100 value: 30.680000000000003 - type: recall_at_1000 value: 54.335 - type: recall_at_3 value: 10.691 - type: recall_at_5 value: 12.687999999999999 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 13.843 - type: map_at_10 value: 17.496000000000002 - type: map_at_100 value: 18.304000000000002 - type: map_at_1000 value: 18.426000000000002 - type: map_at_3 value: 16.225 - type: map_at_5 value: 16.830000000000002 - type: ndcg_at_1 value: 16.698 - type: ndcg_at_10 value: 20.301 - type: ndcg_at_100 value: 24.523 - type: ndcg_at_1000 value: 27.784 - type: ndcg_at_3 value: 17.822 - type: ndcg_at_5 value: 18.794 - type: precision_at_1 value: 16.698 - type: precision_at_10 value: 3.3579999999999997 - type: precision_at_100 value: 0.618 - type: precision_at_1000 value: 0.101 - type: precision_at_3 value: 7.898 - type: precision_at_5 value: 5.428999999999999 - type: recall_at_1 value: 13.843 - type: recall_at_10 value: 25.887999999999998 - type: recall_at_100 value: 45.028 - type: recall_at_1000 value: 68.991 - type: recall_at_3 value: 18.851000000000003 - type: recall_at_5 value: 21.462 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 13.757 - type: map_at_10 value: 19.27 - type: map_at_100 value: 20.461 - type: map_at_1000 value: 20.641000000000002 - type: map_at_3 value: 17.865000000000002 - type: map_at_5 value: 18.618000000000002 - type: ndcg_at_1 value: 16.996 - type: ndcg_at_10 value: 22.774 - type: ndcg_at_100 value: 27.675 - type: ndcg_at_1000 value: 31.145 - type: ndcg_at_3 value: 20.691000000000003 - type: ndcg_at_5 value: 21.741 - type: precision_at_1 value: 16.996 - type: precision_at_10 value: 4.545 - type: precision_at_100 value: 1.036 - type: precision_at_1000 value: 0.185 - type: precision_at_3 value: 10.145 - type: precision_at_5 value: 7.391 - type: recall_at_1 value: 13.757 - type: recall_at_10 value: 28.233999999999998 - type: recall_at_100 value: 51.05499999999999 - type: recall_at_1000 value: 75.35300000000001 - type: recall_at_3 value: 21.794 - type: recall_at_5 value: 24.614 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 9.057 - type: map_at_10 value: 12.720999999999998 - type: map_at_100 value: 13.450000000000001 - type: map_at_1000 value: 13.564000000000002 - type: map_at_3 value: 11.34 - type: map_at_5 value: 12.245000000000001 - type: ndcg_at_1 value: 9.797 - type: ndcg_at_10 value: 15.091 - type: ndcg_at_100 value: 18.886 - type: ndcg_at_1000 value: 22.29 - type: ndcg_at_3 value: 12.365 - type: ndcg_at_5 value: 13.931 - type: precision_at_1 value: 9.797 - type: precision_at_10 value: 2.477 - type: precision_at_100 value: 0.466 - type: precision_at_1000 value: 0.082 - type: precision_at_3 value: 5.299 - type: precision_at_5 value: 4.067 - type: recall_at_1 value: 9.057 - type: recall_at_10 value: 21.319 - type: recall_at_100 value: 38.999 - type: recall_at_1000 value: 65.374 - type: recall_at_3 value: 14.331 - type: recall_at_5 value: 17.916999999999998 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: 392b78eb68c07badcd7c2cd8f39af108375dfcce metrics: - type: map_at_1 value: 3.714 - type: map_at_10 value: 6.926 - type: map_at_100 value: 7.879 - type: map_at_1000 value: 8.032 - type: map_at_3 value: 5.504 - type: map_at_5 value: 6.357 - type: ndcg_at_1 value: 8.86 - type: ndcg_at_10 value: 11.007 - type: ndcg_at_100 value: 16.154 - type: ndcg_at_1000 value: 19.668 - type: ndcg_at_3 value: 8.103 - type: ndcg_at_5 value: 9.456000000000001 - type: precision_at_1 value: 8.86 - type: precision_at_10 value: 3.7199999999999998 - type: precision_at_100 value: 0.9169999999999999 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 6.254 - type: precision_at_5 value: 5.380999999999999 - type: recall_at_1 value: 3.714 - type: recall_at_10 value: 14.382 - type: recall_at_100 value: 33.166000000000004 - type: recall_at_1000 value: 53.444 - type: recall_at_3 value: 7.523000000000001 - type: recall_at_5 value: 10.91 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: f097057d03ed98220bc7309ddb10b71a54d667d6 metrics: - type: map_at_1 value: 1.764 - type: map_at_10 value: 3.8600000000000003 - type: map_at_100 value: 5.457 - type: map_at_1000 value: 5.938000000000001 - type: map_at_3 value: 2.667 - type: map_at_5 value: 3.2199999999999998 - type: ndcg_at_1 value: 14.000000000000002 - type: ndcg_at_10 value: 10.868 - type: ndcg_at_100 value: 12.866 - type: ndcg_at_1000 value: 17.43 - type: ndcg_at_3 value: 11.943 - type: ndcg_at_5 value: 11.66 - type: precision_at_1 value: 19.25 - type: precision_at_10 value: 10.274999999999999 - type: precision_at_100 value: 3.527 - type: precision_at_1000 value: 0.9119999999999999 - type: precision_at_3 value: 14.917 - type: precision_at_5 value: 13.5 - type: recall_at_1 value: 1.764 - type: recall_at_10 value: 6.609 - type: recall_at_100 value: 17.616 - type: recall_at_1000 value: 33.085 - type: recall_at_3 value: 3.115 - type: recall_at_5 value: 4.605 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 829147f8f75a25f005913200eb5ed41fae320aa1 metrics: - type: accuracy value: 42.225 - type: f1 value: 37.563516542112104 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: 1429cf27e393599b8b359b9b72c666f96b2525f9 metrics: - type: map_at_1 value: 11.497 - type: map_at_10 value: 15.744 - type: map_at_100 value: 16.3 - type: map_at_1000 value: 16.365 - type: map_at_3 value: 14.44 - type: map_at_5 value: 15.18 - type: ndcg_at_1 value: 12.346 - type: ndcg_at_10 value: 18.398999999999997 - type: ndcg_at_100 value: 21.399 - type: ndcg_at_1000 value: 23.442 - type: ndcg_at_3 value: 15.695 - type: ndcg_at_5 value: 17.027 - type: precision_at_1 value: 12.346 - type: precision_at_10 value: 2.798 - type: precision_at_100 value: 0.445 - type: precision_at_1000 value: 0.063 - type: precision_at_3 value: 6.586 - type: precision_at_5 value: 4.665 - type: recall_at_1 value: 11.497 - type: recall_at_10 value: 25.636 - type: recall_at_100 value: 39.894 - type: recall_at_1000 value: 56.181000000000004 - type: recall_at_3 value: 18.273 - type: recall_at_5 value: 21.474 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: 41b686a7f28c59bcaaa5791efd47c67c8ebe28be metrics: - type: map_at_1 value: 3.637 - type: map_at_10 value: 6.084 - type: map_at_100 value: 6.9190000000000005 - type: map_at_1000 value: 7.1080000000000005 - type: map_at_3 value: 5.071 - type: map_at_5 value: 5.5649999999999995 - type: ndcg_at_1 value: 7.407 - type: ndcg_at_10 value: 8.94 - type: ndcg_at_100 value: 13.594999999999999 - type: ndcg_at_1000 value: 18.29 - type: ndcg_at_3 value: 7.393 - type: ndcg_at_5 value: 7.854 - type: precision_at_1 value: 7.407 - type: precision_at_10 value: 2.778 - type: precision_at_100 value: 0.75 - type: precision_at_1000 value: 0.154 - type: precision_at_3 value: 5.144 - type: precision_at_5 value: 3.981 - type: recall_at_1 value: 3.637 - type: recall_at_10 value: 11.821 - type: recall_at_100 value: 30.18 - type: recall_at_1000 value: 60.207 - type: recall_at_3 value: 6.839 - type: recall_at_5 value: 8.649 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: 766870b35a1b9ca65e67a0d1913899973551fc6c metrics: - type: map_at_1 value: 9.676 - type: map_at_10 value: 13.350999999999999 - type: map_at_100 value: 13.919 - type: map_at_1000 value: 14.01 - type: map_at_3 value: 12.223 - type: map_at_5 value: 12.812000000000001 - type: ndcg_at_1 value: 19.352 - type: ndcg_at_10 value: 17.727 - type: ndcg_at_100 value: 20.837 - type: ndcg_at_1000 value: 23.412 - type: ndcg_at_3 value: 15.317 - type: ndcg_at_5 value: 16.436 - type: precision_at_1 value: 19.352 - type: precision_at_10 value: 3.993 - type: precision_at_100 value: 0.651 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 9.669 - type: precision_at_5 value: 6.69 - type: recall_at_1 value: 9.676 - type: recall_at_10 value: 19.966 - type: recall_at_100 value: 32.573 - type: recall_at_1000 value: 49.905 - type: recall_at_3 value: 14.504 - type: recall_at_5 value: 16.725 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 8d743909f834c38949e8323a8a6ce8721ea6c7f4 metrics: - type: accuracy value: 62.895999999999994 - type: ap value: 58.47769349850157 - type: f1 value: 62.67885149592086 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: validation revision: e6838a846e2408f22cf5cc337ebc83e0bcf77849 metrics: - type: map_at_1 value: 2.88 - type: map_at_10 value: 4.914000000000001 - type: map_at_100 value: 5.459 - type: map_at_1000 value: 5.538 - type: map_at_3 value: 4.087 - type: map_at_5 value: 4.518 - type: ndcg_at_1 value: 2.937 - type: ndcg_at_10 value: 6.273 - type: ndcg_at_100 value: 9.426 - type: ndcg_at_1000 value: 12.033000000000001 - type: ndcg_at_3 value: 4.513 - type: ndcg_at_5 value: 5.292 - type: precision_at_1 value: 2.937 - type: precision_at_10 value: 1.089 - type: precision_at_100 value: 0.27699999999999997 - type: precision_at_1000 value: 0.051000000000000004 - type: precision_at_3 value: 1.9290000000000003 - type: precision_at_5 value: 1.547 - type: recall_at_1 value: 2.88 - type: recall_at_10 value: 10.578 - type: recall_at_100 value: 26.267000000000003 - type: recall_at_1000 value: 47.589999999999996 - type: recall_at_3 value: 5.673 - type: recall_at_5 value: 7.545 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 metrics: - type: accuracy value: 81.51846785225717 - type: f1 value: 81.648869152345 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (de) config: de split: test revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 metrics: - type: accuracy value: 60.37475345167653 - type: f1 value: 58.452649375517026 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (es) config: es split: test revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 metrics: - type: accuracy value: 67.36824549699799 - type: f1 value: 65.35927434998516 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (fr) config: fr split: test revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 metrics: - type: accuracy value: 63.12871907297212 - type: f1 value: 61.37620329272278 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (hi) config: hi split: test revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 metrics: - type: accuracy value: 47.04553603442094 - type: f1 value: 46.20389912644561 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (th) config: th split: test revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 metrics: - type: accuracy value: 52.282097649186255 - type: f1 value: 50.75489206473579 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: 6299947a7777084cc2d4b64235bf7190381ce755 metrics: - type: accuracy value: 58.2421340629275 - type: f1 value: 40.11696046622642 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (de) config: de split: test revision: 6299947a7777084cc2d4b64235bf7190381ce755 metrics: - type: accuracy value: 45.069033530571986 - type: f1 value: 30.468468273374967 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (es) config: es split: test revision: 6299947a7777084cc2d4b64235bf7190381ce755 metrics: - type: accuracy value: 48.80920613742495 - type: f1 value: 32.65985375400447 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (fr) config: fr split: test revision: 6299947a7777084cc2d4b64235bf7190381ce755 metrics: - type: accuracy value: 44.337613529595984 - type: f1 value: 29.302047435606436 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (hi) config: hi split: test revision: 6299947a7777084cc2d4b64235bf7190381ce755 metrics: - type: accuracy value: 34.198637504481894 - type: f1 value: 22.063706032248408 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (th) config: th split: test revision: 6299947a7777084cc2d4b64235bf7190381ce755 metrics: - type: accuracy value: 43.11030741410488 - type: f1 value: 26.92408933648504 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (af) config: af split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 37.79421654337593 - type: f1 value: 36.81580701507746 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (am) config: am split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 23.722259583053127 - type: f1 value: 23.235269695764273 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ar) config: ar split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 29.64021519838601 - type: f1 value: 28.273175327650137 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (az) config: az split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 39.4754539340955 - type: f1 value: 39.25997361415121 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (bn) config: bn split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 26.550100874243444 - type: f1 value: 25.607924873522975 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (cy) config: cy split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 38.78278412911904 - type: f1 value: 37.64180582626517 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (da) config: da split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 43.557498318762605 - type: f1 value: 41.35305173800667 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (de) config: de split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 40.39340954942838 - type: f1 value: 38.33393219528934 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (el) config: el split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 37.28648285137861 - type: f1 value: 36.64005906680284 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 58.080026899798256 - type: f1 value: 56.49243881660991 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (es) config: es split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 41.176866173503704 - type: f1 value: 40.66779962225799 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (fa) config: fa split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 36.422326832548755 - type: f1 value: 34.6441738042885 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (fi) config: fi split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 38.75588433086752 - type: f1 value: 37.26725894668694 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (fr) config: fr split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 43.67182246133153 - type: f1 value: 42.351846624566605 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (he) config: he split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 31.980497646267658 - type: f1 value: 30.557928872809008 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (hi) config: hi split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 28.039677202420982 - type: f1 value: 28.428418145508306 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (hu) config: hu split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 38.13718897108272 - type: f1 value: 37.057406988196874 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (hy) config: hy split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 26.05245460659045 - type: f1 value: 25.25483953344816 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (id) config: id split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 41.156691324815064 - type: f1 value: 40.83715033247605 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (is) config: is split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 38.62811028917284 - type: f1 value: 37.67691901246032 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (it) config: it split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 44.0383322125084 - type: f1 value: 43.77259010877456 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ja) config: ja split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 46.20712844653666 - type: f1 value: 44.66632875940824 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (jv) config: jv split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 37.60591795561533 - type: f1 value: 36.581071742378015 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ka) config: ka split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 24.47209145931405 - type: f1 value: 24.238209697895606 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (km) config: km split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 26.23739071956961 - type: f1 value: 25.378783150845052 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (kn) config: kn split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 17.831203765971754 - type: f1 value: 17.275078420466343 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ko) config: ko split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 37.266308002689975 - type: f1 value: 36.92473791708214 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (lv) config: lv split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 40.93140551445864 - type: f1 value: 40.825227889641965 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ml) config: ml split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 17.88500336247478 - type: f1 value: 17.621569082971817 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (mn) config: mn split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 32.975790181573636 - type: f1 value: 33.402014633349665 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ms) config: ms split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 40.91123066577001 - type: f1 value: 40.09538559124075 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (my) config: my split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 17.834566240753194 - type: f1 value: 17.006381849454314 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (nb) config: nb split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 39.47881640887693 - type: f1 value: 37.819934317839305 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (nl) config: nl split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 41.76193678547412 - type: f1 value: 40.281991759509694 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (pl) config: pl split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 42.61936785474109 - type: f1 value: 40.83673914649905 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (pt) config: pt split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 44.54270342972427 - type: f1 value: 43.45243164278448 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ro) config: ro split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 39.96973772696705 - type: f1 value: 38.74209466530094 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ru) config: ru split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 37.461331540013454 - type: f1 value: 36.91132021821187 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (sl) config: sl split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 38.28850033624748 - type: f1 value: 37.37259394049676 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (sq) config: sq split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 40.95494283792872 - type: f1 value: 39.767707902869084 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (sv) config: sv split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 41.85272360457296 - type: f1 value: 40.42848260365438 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (sw) config: sw split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 38.328850033624754 - type: f1 value: 36.90334596675622 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ta) config: ta split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 19.031607262945528 - type: f1 value: 18.66510306325761 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (te) config: te split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 19.38466711499664 - type: f1 value: 19.186399376652535 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (th) config: th split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 34.088769334229994 - type: f1 value: 34.20383086009429 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (tl) config: tl split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 40.285810356422324 - type: f1 value: 39.361500249640414 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (tr) config: tr split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 38.860121049092136 - type: f1 value: 37.81916859627235 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ur) config: ur split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 27.834566240753194 - type: f1 value: 26.898389386106487 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (vi) config: vi split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 38.70544720914593 - type: f1 value: 38.280026442024415 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (zh-CN) config: zh-CN split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 45.78009414929387 - type: f1 value: 44.21526778674136 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (zh-TW) config: zh-TW split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 42.32010759919301 - type: f1 value: 42.25772977490916 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (af) config: af split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 40.24546065904506 - type: f1 value: 38.79924050989544 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (am) config: am split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 25.68930733019502 - type: f1 value: 25.488166279162712 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ar) config: ar split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 32.39744451916611 - type: f1 value: 31.863029579075775 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (az) config: az split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 40.53127101546738 - type: f1 value: 39.707079033948936 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (bn) config: bn split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 27.23268325487559 - type: f1 value: 26.443653281858793 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (cy) config: cy split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 38.69872225958305 - type: f1 value: 36.55930387892567 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (da) config: da split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 44.75453934095494 - type: f1 value: 42.87356484024154 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (de) config: de split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 41.355077336919976 - type: f1 value: 39.82365179458047 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (el) config: el split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 38.43981170141224 - type: f1 value: 37.02538368296387 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 66.33826496301278 - type: f1 value: 65.89634765029932 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (es) config: es split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 44.17955615332885 - type: f1 value: 43.10228811620319 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (fa) config: fa split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 34.82851378614661 - type: f1 value: 33.95952441502803 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (fi) config: fi split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 40.561533288500335 - type: f1 value: 38.04939011733627 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (fr) config: fr split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 45.917955615332886 - type: f1 value: 44.65741971572902 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (he) config: he split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 32.08473436449227 - type: f1 value: 29.53932929808133 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (hi) config: hi split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 28.369199731002016 - type: f1 value: 27.52902837981212 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (hu) config: hu split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 39.49226630800269 - type: f1 value: 37.3272340470504 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (hy) config: hy split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 25.904505716207133 - type: f1 value: 24.547396574853444 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (id) config: id split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 40.95830531271016 - type: f1 value: 40.177843177422226 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (is) config: is split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 38.564223268325485 - type: f1 value: 37.35307758495248 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (it) config: it split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 46.58708809683928 - type: f1 value: 44.103900526804985 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ja) config: ja split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 46.24747814391393 - type: f1 value: 45.4107101796664 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (jv) config: jv split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 39.6570275722932 - type: f1 value: 38.82737576832412 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ka) config: ka split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 25.279085406859448 - type: f1 value: 23.662661686788493 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (km) config: km split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 28.97108271687962 - type: f1 value: 27.195758324189246 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (kn) config: kn split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 19.27370544720915 - type: f1 value: 18.694271924323637 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ko) config: ko split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 35.729657027572294 - type: f1 value: 34.38287006177308 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (lv) config: lv split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 39.57296570275723 - type: f1 value: 38.074945140886925 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ml) config: ml split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 19.895763281775388 - type: f1 value: 20.00931364846829 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (mn) config: mn split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 32.431069266980494 - type: f1 value: 31.395958664782576 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ms) config: ms split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 42.32347007397445 - type: f1 value: 40.81374026314701 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (my) config: my split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 20.864156018829856 - type: f1 value: 20.409870408935436 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (nb) config: nb split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 40.47074646940148 - type: f1 value: 39.19044149415904 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (nl) config: nl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 43.591123066577 - type: f1 value: 41.43420363064241 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (pl) config: pl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 41.876260928043045 - type: f1 value: 41.192117676667614 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (pt) config: pt split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 46.30800268997983 - type: f1 value: 45.25536730126799 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ro) config: ro split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 42.525218560860786 - type: f1 value: 41.02418109296485 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ru) config: ru split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 35.94821788836584 - type: f1 value: 35.08598314806566 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (sl) config: sl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 38.69199731002017 - type: f1 value: 37.68119408674127 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (sq) config: sq split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 40.474108944182916 - type: f1 value: 39.480530387013594 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (sv) config: sv split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 41.523201075991935 - type: f1 value: 40.20097996024383 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (sw) config: sw split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 39.54942837928716 - type: f1 value: 38.185561243338064 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ta) config: ta split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 22.8782784129119 - type: f1 value: 22.239467186721456 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (te) config: te split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 20.51445864156019 - type: f1 value: 19.999047885530217 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (th) config: th split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 34.92602555480834 - type: f1 value: 33.24016717215723 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (tl) config: tl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 40.74983187626093 - type: f1 value: 39.30274328728882 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (tr) config: tr split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 39.06859448554136 - type: f1 value: 39.21542039662971 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ur) config: ur split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 29.747814391392062 - type: f1 value: 28.261836892220447 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (vi) config: vi split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 38.02286482851379 - type: f1 value: 37.8742438608697 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (zh-CN) config: zh-CN split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 48.550773369199725 - type: f1 value: 46.7399625882649 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (zh-TW) config: zh-TW split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 45.17821116341628 - type: f1 value: 44.84809741811729 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: dcefc037ef84348e49b0d29109e891c01067226b metrics: - type: v_measure value: 28.301902023313875 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 3cd0e71dfbe09d4de0f9e5ecba43e7ce280959dc metrics: - type: v_measure value: 24.932123582259287 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 29.269341041468326 - type: mrr value: 30.132140876875717 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: 7eb63cc0c1eb59324d709ebed25fcab851fa7610 metrics: - type: map_at_1 value: 1.2269999999999999 - type: map_at_10 value: 3.081 - type: map_at_100 value: 4.104 - type: map_at_1000 value: 4.989 - type: map_at_3 value: 2.221 - type: map_at_5 value: 2.535 - type: ndcg_at_1 value: 15.015 - type: ndcg_at_10 value: 11.805 - type: ndcg_at_100 value: 12.452 - type: ndcg_at_1000 value: 22.284000000000002 - type: ndcg_at_3 value: 13.257 - type: ndcg_at_5 value: 12.199 - type: precision_at_1 value: 16.409000000000002 - type: precision_at_10 value: 9.102 - type: precision_at_100 value: 3.678 - type: precision_at_1000 value: 1.609 - type: precision_at_3 value: 12.797 - type: precision_at_5 value: 10.464 - type: recall_at_1 value: 1.2269999999999999 - type: recall_at_10 value: 5.838 - type: recall_at_100 value: 15.716 - type: recall_at_1000 value: 48.837 - type: recall_at_3 value: 2.828 - type: recall_at_5 value: 3.697 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: 6062aefc120bfe8ece5897809fb2e53bfe0d128c metrics: - type: map_at_1 value: 3.515 - type: map_at_10 value: 5.884 - type: map_at_100 value: 6.510000000000001 - type: map_at_1000 value: 6.598999999999999 - type: map_at_3 value: 4.8919999999999995 - type: map_at_5 value: 5.391 - type: ndcg_at_1 value: 4.056 - type: ndcg_at_10 value: 7.6259999999999994 - type: ndcg_at_100 value: 11.08 - type: ndcg_at_1000 value: 13.793 - type: ndcg_at_3 value: 5.537 - type: ndcg_at_5 value: 6.45 - type: precision_at_1 value: 4.056 - type: precision_at_10 value: 1.4569999999999999 - type: precision_at_100 value: 0.347 - type: precision_at_1000 value: 0.061 - type: precision_at_3 value: 2.6069999999999998 - type: precision_at_5 value: 2.086 - type: recall_at_1 value: 3.515 - type: recall_at_10 value: 12.312 - type: recall_at_100 value: 28.713 - type: recall_at_1000 value: 50.027 - type: recall_at_3 value: 6.701 - type: recall_at_5 value: 8.816 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: 6205996560df11e3a3da9ab4f926788fc30a7db4 metrics: - type: map_at_1 value: 61.697 - type: map_at_10 value: 74.20400000000001 - type: map_at_100 value: 75.023 - type: map_at_1000 value: 75.059 - type: map_at_3 value: 71.265 - type: map_at_5 value: 73.001 - type: ndcg_at_1 value: 70.95 - type: ndcg_at_10 value: 78.96 - type: ndcg_at_100 value: 81.26 - type: ndcg_at_1000 value: 81.679 - type: ndcg_at_3 value: 75.246 - type: ndcg_at_5 value: 77.092 - type: precision_at_1 value: 70.95 - type: precision_at_10 value: 11.998000000000001 - type: precision_at_100 value: 1.451 - type: precision_at_1000 value: 0.154 - type: precision_at_3 value: 32.629999999999995 - type: precision_at_5 value: 21.573999999999998 - type: recall_at_1 value: 61.697 - type: recall_at_10 value: 88.23299999999999 - type: recall_at_100 value: 96.961 - type: recall_at_1000 value: 99.401 - type: recall_at_3 value: 77.689 - type: recall_at_5 value: 82.745 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: b2805658ae38990172679479369a78b86de8c390 metrics: - type: v_measure value: 33.75741018380938 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 metrics: - type: v_measure value: 41.00799910099266 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: 5c59ef3e437a0a9651c8fe6fde943e7dce59fba5 metrics: - type: map_at_1 value: 1.72 - type: map_at_10 value: 3.8240000000000003 - type: map_at_100 value: 4.727 - type: map_at_1000 value: 4.932 - type: map_at_3 value: 2.867 - type: map_at_5 value: 3.3230000000000004 - type: ndcg_at_1 value: 8.5 - type: ndcg_at_10 value: 7.133000000000001 - type: ndcg_at_100 value: 11.911 - type: ndcg_at_1000 value: 16.962 - type: ndcg_at_3 value: 6.763 - type: ndcg_at_5 value: 5.832 - type: precision_at_1 value: 8.5 - type: precision_at_10 value: 3.6799999999999997 - type: precision_at_100 value: 1.0670000000000002 - type: precision_at_1000 value: 0.22999999999999998 - type: precision_at_3 value: 6.2330000000000005 - type: precision_at_5 value: 5.0200000000000005 - type: recall_at_1 value: 1.72 - type: recall_at_10 value: 7.487000000000001 - type: recall_at_100 value: 21.683 - type: recall_at_1000 value: 46.688 - type: recall_at_3 value: 3.798 - type: recall_at_5 value: 5.113 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: 20a6d6f312dd54037fe07a32d58e5e168867909d metrics: - type: cos_sim_pearson value: 80.96286245858941 - type: cos_sim_spearman value: 74.57093488947429 - type: euclidean_pearson value: 75.50377970259402 - type: euclidean_spearman value: 71.7498004622999 - type: manhattan_pearson value: 75.3256836091382 - type: manhattan_spearman value: 71.80676733410375 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: fdf84275bb8ce4b49c971d02e84dd1abc677a50f metrics: - type: cos_sim_pearson value: 80.20938796088339 - type: cos_sim_spearman value: 69.16914010333394 - type: euclidean_pearson value: 79.33415250097545 - type: euclidean_spearman value: 71.46707320292745 - type: manhattan_pearson value: 79.73669837981976 - type: manhattan_spearman value: 71.87919511134902 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 1591bfcbe8c69d4bf7fe2a16e2451017832cafb9 metrics: - type: cos_sim_pearson value: 76.401935081936 - type: cos_sim_spearman value: 77.23446219694267 - type: euclidean_pearson value: 74.61017160439877 - type: euclidean_spearman value: 75.85871531365609 - type: manhattan_pearson value: 74.83034779539724 - type: manhattan_spearman value: 75.95948993588429 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: e2125984e7df8b7871f6ae9949cf6b6795e7c54b metrics: - type: cos_sim_pearson value: 75.35551963935667 - type: cos_sim_spearman value: 70.98892671568665 - type: euclidean_pearson value: 73.24467338564628 - type: euclidean_spearman value: 71.97533151639425 - type: manhattan_pearson value: 73.2776559359938 - type: manhattan_spearman value: 72.2221421456084 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: 1cd7298cac12a96a373b6a2f18738bb3e739a9b6 metrics: - type: cos_sim_pearson value: 79.05293131911803 - type: cos_sim_spearman value: 79.7379478259805 - type: euclidean_pearson value: 78.17016171851057 - type: euclidean_spearman value: 78.76038607583105 - type: manhattan_pearson value: 78.4994607532332 - type: manhattan_spearman value: 79.13026720132872 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 360a0b2dff98700d09e634a01e1cc1624d3e42cd metrics: - type: cos_sim_pearson value: 76.04750373932828 - type: cos_sim_spearman value: 77.93230986462234 - type: euclidean_pearson value: 75.8320302521164 - type: euclidean_spearman value: 76.83154481579385 - type: manhattan_pearson value: 75.98713517720608 - type: manhattan_spearman value: 76.95479705521507 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (ko-ko) config: ko-ko split: test revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 metrics: - type: cos_sim_pearson value: 43.0464619152799 - type: cos_sim_spearman value: 45.65606588928089 - type: euclidean_pearson value: 45.69437788355499 - type: euclidean_spearman value: 45.08552742346606 - type: manhattan_pearson value: 45.87166698903681 - type: manhattan_spearman value: 45.155963016434164 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (ar-ar) config: ar-ar split: test revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 metrics: - type: cos_sim_pearson value: 53.27469278912148 - type: cos_sim_spearman value: 54.16113207623789 - type: euclidean_pearson value: 55.97026429327157 - type: euclidean_spearman value: 54.71320909074608 - type: manhattan_pearson value: 56.12511774278802 - type: manhattan_spearman value: 55.22875659158676 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-ar) config: en-ar split: test revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 metrics: - type: cos_sim_pearson value: 1.5482997790039945 - type: cos_sim_spearman value: 1.7208386347363582 - type: euclidean_pearson value: 6.727915670345885 - type: euclidean_spearman value: 6.112826908474543 - type: manhattan_pearson value: 4.94386093060865 - type: manhattan_spearman value: 5.018174110623732 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-de) config: en-de split: test revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 metrics: - type: cos_sim_pearson value: 27.5420218362265 - type: cos_sim_spearman value: 25.483838431031007 - type: euclidean_pearson value: 6.268684143856358 - type: euclidean_spearman value: 5.877961421091679 - type: manhattan_pearson value: 2.667237739227861 - type: manhattan_spearman value: 2.5683839956554775 - 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: 85.32029757646663 - type: cos_sim_spearman value: 87.32720847297225 - type: euclidean_pearson value: 81.12594485791254 - type: euclidean_spearman value: 81.1531079489332 - type: manhattan_pearson value: 81.32899414704019 - type: manhattan_spearman value: 81.3897040261192 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-tr) config: en-tr split: test revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 metrics: - type: cos_sim_pearson value: 4.37162299241808 - type: cos_sim_spearman value: 2.0879072561774543 - type: euclidean_pearson value: 3.0725243785454595 - type: euclidean_spearman value: 5.3721339279483535 - type: manhattan_pearson value: 4.867795293367359 - type: manhattan_spearman value: 7.9397069840018775 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (es-en) config: es-en split: test revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 metrics: - type: cos_sim_pearson value: 20.306030448858603 - type: cos_sim_spearman value: 21.93220782551375 - type: euclidean_pearson value: 3.878631934602361 - type: euclidean_spearman value: 5.171796902725965 - type: manhattan_pearson value: 7.13020644036815 - type: manhattan_spearman value: 7.707315591498748 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (es-es) config: es-es split: test revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 metrics: - type: cos_sim_pearson value: 66.81873207478459 - type: cos_sim_spearman value: 67.80273445636502 - type: euclidean_pearson value: 70.60654682977268 - type: euclidean_spearman value: 69.4566208379486 - type: manhattan_pearson value: 70.9548461896642 - type: manhattan_spearman value: 69.78323323058773 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (fr-en) config: fr-en split: test revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 metrics: - type: cos_sim_pearson value: 21.366487281202602 - type: cos_sim_spearman value: 18.90627528698481 - type: euclidean_pearson value: 2.3390998579461995 - type: euclidean_spearman value: 4.151213674012541 - type: manhattan_pearson value: 2.234831868844863 - type: manhattan_spearman value: 4.555291328501442 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (it-en) config: it-en split: test revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 metrics: - type: cos_sim_pearson value: 20.73153177251085 - type: cos_sim_spearman value: 16.3855949033176 - type: euclidean_pearson value: 8.734648741714238 - type: euclidean_spearman value: 10.75672244732182 - type: manhattan_pearson value: 7.536654126608877 - type: manhattan_spearman value: 8.330065460047296 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (nl-en) config: nl-en split: test revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 metrics: - type: cos_sim_pearson value: 26.618435024084253 - type: cos_sim_spearman value: 23.488974089577816 - type: euclidean_pearson value: 3.1310350304707866 - type: euclidean_spearman value: 3.1242598481634665 - type: manhattan_pearson value: 1.1096752982707008 - type: manhattan_spearman value: 1.4591693078765848 - 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: 59.17638344661753 - type: cos_sim_spearman value: 59.636760071130865 - type: euclidean_pearson value: 56.68753290255448 - type: euclidean_spearman value: 57.613280258574484 - type: manhattan_pearson value: 56.92312052723706 - type: manhattan_spearman value: 57.76774918418505 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de) config: de split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 10.322254716987457 - type: cos_sim_spearman value: 11.0033092996862 - type: euclidean_pearson value: 6.006926471684402 - type: euclidean_spearman value: 10.972140246688376 - type: manhattan_pearson value: 5.933298751861177 - type: manhattan_spearman value: 11.030111585680233 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es) config: es split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 43.38031880545056 - type: cos_sim_spearman value: 43.05358201410913 - type: euclidean_pearson value: 42.72327196362553 - type: euclidean_spearman value: 42.55163899944477 - type: manhattan_pearson value: 44.01557499780587 - type: manhattan_spearman value: 43.12473221615855 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (pl) config: pl split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 4.291290504363136 - type: cos_sim_spearman value: 14.912727487893479 - type: euclidean_pearson value: 3.2855132112394485 - type: euclidean_spearman value: 16.575204463951025 - type: manhattan_pearson value: 3.2398776723465814 - type: manhattan_spearman value: 16.841985772913855 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (tr) config: tr split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 4.102739498555817 - type: cos_sim_spearman value: 3.818238576547375 - type: euclidean_pearson value: 2.3181033496453556 - type: euclidean_spearman value: 5.1826811802703565 - type: manhattan_pearson value: 4.8006179265256455 - type: manhattan_spearman value: 6.738401400306252 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (ar) config: ar split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 2.38765395226737 - type: cos_sim_spearman value: 5.173899391162327 - type: euclidean_pearson value: 3.0710263954769825 - type: euclidean_spearman value: 5.04922290903982 - type: manhattan_pearson value: 3.7826314109861703 - type: manhattan_spearman value: 5.042238232170212 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (ru) config: ru split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 7.6735490672676345 - type: cos_sim_spearman value: 3.3631215256878892 - type: euclidean_pearson value: 4.64331702652217 - type: euclidean_spearman value: 3.6129205171334324 - type: manhattan_pearson value: 4.011231736076196 - type: manhattan_spearman value: 3.233959766173701 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (zh) config: zh split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 0.06167614416104335 - type: cos_sim_spearman value: 6.521685391703255 - type: euclidean_pearson value: 4.884572579069032 - type: euclidean_spearman value: 5.59058032900239 - type: manhattan_pearson value: 6.139838096573897 - type: manhattan_spearman value: 5.0060884837066215 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (fr) config: fr split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 53.19490347682836 - type: cos_sim_spearman value: 54.56055727079527 - type: euclidean_pearson value: 52.55574442039842 - type: euclidean_spearman value: 52.94640154371587 - type: manhattan_pearson value: 53.275993040454196 - type: manhattan_spearman value: 53.174561503510155 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-en) config: de-en split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 51.151158530122146 - type: cos_sim_spearman value: 53.926925081736655 - type: euclidean_pearson value: 44.55629287737235 - type: euclidean_spearman value: 46.222372143731384 - type: manhattan_pearson value: 42.831322151459005 - type: manhattan_spearman value: 45.70991764985799 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es-en) config: es-en split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 30.36194885126792 - type: cos_sim_spearman value: 32.739632941633836 - type: euclidean_pearson value: 29.83135800843496 - type: euclidean_spearman value: 31.114406001326923 - type: manhattan_pearson value: 31.264502938148286 - type: manhattan_spearman value: 33.3112040753475 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (it) config: it split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 35.23883630335275 - type: cos_sim_spearman value: 33.67797082086704 - type: euclidean_pearson value: 34.878640693874544 - type: euclidean_spearman value: 33.525189235133496 - type: manhattan_pearson value: 34.22761246389947 - type: manhattan_spearman value: 32.713218497609176 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (pl-en) config: pl-en split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 19.809302548119547 - type: cos_sim_spearman value: 20.540370202115497 - type: euclidean_pearson value: 23.006803962133016 - type: euclidean_spearman value: 22.96270653079511 - type: manhattan_pearson value: 25.40168317585851 - type: manhattan_spearman value: 25.421508137540865 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (zh-en) config: zh-en split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 20.393500955410488 - type: cos_sim_spearman value: 26.705713693011603 - type: euclidean_pearson value: 18.168376767724585 - type: euclidean_spearman value: 19.260826601517245 - type: manhattan_pearson value: 18.302619990671527 - type: manhattan_spearman value: 19.4691037846159 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es-it) config: es-it split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 36.58919983075148 - type: cos_sim_spearman value: 35.989722099974045 - type: euclidean_pearson value: 41.045112547574206 - type: euclidean_spearman value: 39.322301680629835 - type: manhattan_pearson value: 41.36802503205308 - type: manhattan_spearman value: 40.76270030293609 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-fr) config: de-fr split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 26.350936227950083 - type: cos_sim_spearman value: 25.108218032460343 - type: euclidean_pearson value: 28.61681094744849 - type: euclidean_spearman value: 27.350990203943592 - type: manhattan_pearson value: 30.527977072984513 - type: manhattan_spearman value: 26.403339990640813 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-pl) config: de-pl split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 20.056269198600322 - type: cos_sim_spearman value: 20.939990379746757 - type: euclidean_pearson value: 18.942765438962198 - type: euclidean_spearman value: 21.709842967237446 - type: manhattan_pearson value: 23.643909798655123 - type: manhattan_spearman value: 23.58828328071473 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (fr-pl) config: fr-pl split: test revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 metrics: - type: cos_sim_pearson value: 19.563740271419395 - type: cos_sim_spearman value: 5.634361698190111 - type: euclidean_pearson value: 16.833522619239474 - type: euclidean_spearman value: 16.903085094570333 - type: manhattan_pearson value: 5.805392712660814 - type: manhattan_spearman value: 16.903085094570333 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: 8913289635987208e6e7c72789e4be2fe94b6abd metrics: - type: cos_sim_pearson value: 80.00905671833966 - type: cos_sim_spearman value: 79.54269211027272 - type: euclidean_pearson value: 79.51954544247441 - type: euclidean_spearman value: 78.93670303434288 - type: manhattan_pearson value: 79.47610653340678 - type: manhattan_spearman value: 79.07344156719613 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: 56a6d0140cf6356659e2a7c1413286a774468d44 metrics: - type: map value: 68.35710819755543 - type: mrr value: 88.05442832403617 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: a75ae049398addde9b70f6b268875f5cbce99089 metrics: - type: map_at_1 value: 21.556 - type: map_at_10 value: 27.982000000000003 - type: map_at_100 value: 28.937 - type: map_at_1000 value: 29.058 - type: map_at_3 value: 25.644 - type: map_at_5 value: 26.996 - type: ndcg_at_1 value: 23.333000000000002 - type: ndcg_at_10 value: 31.787 - type: ndcg_at_100 value: 36.647999999999996 - type: ndcg_at_1000 value: 39.936 - type: ndcg_at_3 value: 27.299 - type: ndcg_at_5 value: 29.659000000000002 - type: precision_at_1 value: 23.333000000000002 - type: precision_at_10 value: 4.867 - type: precision_at_100 value: 0.743 - type: precision_at_1000 value: 0.10200000000000001 - type: precision_at_3 value: 11.333 - type: precision_at_5 value: 8.133 - type: recall_at_1 value: 21.556 - type: recall_at_10 value: 42.333 - type: recall_at_100 value: 65.706 - type: recall_at_1000 value: 91.489 - type: recall_at_3 value: 30.361 - type: recall_at_5 value: 36.222 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: 5a8256d0dff9c4bd3be3ba3e67e4e70173f802ea metrics: - type: cos_sim_accuracy value: 99.49306930693069 - type: cos_sim_ap value: 77.7308550291728 - type: cos_sim_f1 value: 71.78978681209718 - type: cos_sim_precision value: 71.1897738446411 - type: cos_sim_recall value: 72.39999999999999 - type: dot_accuracy value: 99.08118811881188 - type: dot_ap value: 30.267748833368234 - type: dot_f1 value: 34.335201222618444 - type: dot_precision value: 34.994807892004154 - type: dot_recall value: 33.7 - type: euclidean_accuracy value: 99.51683168316832 - type: euclidean_ap value: 78.64498778235628 - type: euclidean_f1 value: 73.09149972929075 - type: euclidean_precision value: 79.69303423848878 - type: euclidean_recall value: 67.5 - type: manhattan_accuracy value: 99.53168316831683 - type: manhattan_ap value: 79.45274878693958 - type: manhattan_f1 value: 74.19863373620599 - type: manhattan_precision value: 78.18383167220377 - type: manhattan_recall value: 70.6 - type: max_accuracy value: 99.53168316831683 - type: max_ap value: 79.45274878693958 - type: max_f1 value: 74.19863373620599 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 70a89468f6dccacc6aa2b12a6eac54e74328f235 metrics: - type: v_measure value: 44.59127540530939 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: d88009ab563dd0b16cfaf4436abaf97fa3550cf0 metrics: - type: v_measure value: 28.230204578753636 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: ef807ea29a75ec4f91b50fd4191cb4ee4589a9f9 metrics: - type: map value: 39.96520488022785 - type: mrr value: 40.189248047703934 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: 8753c2788d36c01fc6f05d03fe3f7268d63f9122 metrics: - type: cos_sim_pearson value: 30.56303767714449 - type: cos_sim_spearman value: 30.256847004390487 - type: dot_pearson value: 29.453520030995005 - type: dot_spearman value: 29.561732550926777 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: 2c8041b2c07a79b6f7ba8fe6acc72e5d9f92d217 metrics: - type: map_at_1 value: 0.11299999999999999 - type: map_at_10 value: 0.733 - type: map_at_100 value: 3.313 - type: map_at_1000 value: 7.355 - type: map_at_3 value: 0.28200000000000003 - type: map_at_5 value: 0.414 - type: ndcg_at_1 value: 42.0 - type: ndcg_at_10 value: 39.31 - type: ndcg_at_100 value: 26.904 - type: ndcg_at_1000 value: 23.778 - type: ndcg_at_3 value: 42.775999999999996 - type: ndcg_at_5 value: 41.554 - type: precision_at_1 value: 48.0 - type: precision_at_10 value: 43.0 - type: precision_at_100 value: 27.08 - type: precision_at_1000 value: 11.014 - type: precision_at_3 value: 48.0 - type: precision_at_5 value: 45.6 - type: recall_at_1 value: 0.11299999999999999 - type: recall_at_10 value: 0.976 - type: recall_at_100 value: 5.888 - type: recall_at_1000 value: 22.634999999999998 - type: recall_at_3 value: 0.329 - type: recall_at_5 value: 0.518 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: 527b7d77e16e343303e68cb6af11d6e18b9f7b3b metrics: - type: map_at_1 value: 0.645 - type: map_at_10 value: 4.1160000000000005 - type: map_at_100 value: 7.527 - type: map_at_1000 value: 8.677999999999999 - type: map_at_3 value: 1.6019999999999999 - type: map_at_5 value: 2.6 - type: ndcg_at_1 value: 10.204 - type: ndcg_at_10 value: 12.27 - type: ndcg_at_100 value: 22.461000000000002 - type: ndcg_at_1000 value: 33.543 - type: ndcg_at_3 value: 9.982000000000001 - type: ndcg_at_5 value: 11.498 - type: precision_at_1 value: 10.204 - type: precision_at_10 value: 12.245000000000001 - type: precision_at_100 value: 5.286 - type: precision_at_1000 value: 1.2630000000000001 - type: precision_at_3 value: 10.884 - type: precision_at_5 value: 13.061 - type: recall_at_1 value: 0.645 - type: recall_at_10 value: 8.996 - type: recall_at_100 value: 33.666000000000004 - type: recall_at_1000 value: 67.704 - type: recall_at_3 value: 2.504 - type: recall_at_5 value: 4.95 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de metrics: - type: accuracy value: 62.7862 - type: ap value: 10.958454618347831 - type: f1 value: 48.37243417046763 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: 62146448f05be9e52a36b8ee9936447ea787eede metrics: - type: accuracy value: 54.821731748726656 - type: f1 value: 55.14729314789282 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 091a54f9a36281ce7d6590ec8c75dd485e7e01d4 metrics: - type: v_measure value: 28.24295128553035 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 81.5640460153782 - type: cos_sim_ap value: 57.094095366921536 - type: cos_sim_f1 value: 55.29607083563918 - type: cos_sim_precision value: 47.62631077216397 - type: cos_sim_recall value: 65.91029023746702 - type: dot_accuracy value: 78.81623651427549 - type: dot_ap value: 47.42989400382077 - type: dot_f1 value: 51.25944584382871 - type: dot_precision value: 42.55838271174625 - type: dot_recall value: 64.43271767810026 - type: euclidean_accuracy value: 80.29445073612685 - type: euclidean_ap value: 53.42012231336148 - type: euclidean_f1 value: 51.867783563504645 - type: euclidean_precision value: 45.4203013481364 - type: euclidean_recall value: 60.4485488126649 - type: manhattan_accuracy value: 80.2884901949097 - type: manhattan_ap value: 53.43205271323232 - type: manhattan_f1 value: 52.014165559982295 - type: manhattan_precision value: 44.796035074342356 - type: manhattan_recall value: 62.00527704485488 - type: max_accuracy value: 81.5640460153782 - type: max_ap value: 57.094095366921536 - type: max_f1 value: 55.29607083563918 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 86.63018589668955 - type: cos_sim_ap value: 80.51063771262909 - type: cos_sim_f1 value: 72.70810586950793 - type: cos_sim_precision value: 71.14123627790467 - type: cos_sim_recall value: 74.3455497382199 - type: dot_accuracy value: 82.41743315092948 - type: dot_ap value: 69.2393381283664 - type: dot_f1 value: 65.61346624814597 - type: dot_precision value: 59.43260638630257 - type: dot_recall value: 73.22913458577148 - type: euclidean_accuracy value: 86.49435324251951 - type: euclidean_ap value: 80.28100477250926 - type: euclidean_f1 value: 72.58242344489099 - type: euclidean_precision value: 67.44662568576906 - type: euclidean_recall value: 78.56482907299045 - type: manhattan_accuracy value: 86.59525749990297 - type: manhattan_ap value: 80.37850832566262 - type: manhattan_f1 value: 72.59435321233073 - type: manhattan_precision value: 68.19350473612991 - type: manhattan_recall value: 77.60240221743148 - type: max_accuracy value: 86.63018589668955 - type: max_ap value: 80.51063771262909 - type: max_f1 value: 72.70810586950793 --- # SGPT-125M-weightedmean-nli-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**: `sentence_transformers.datasets.NoDuplicatesDataLoader.NoDuplicatesDataLoader` of length 8807 with parameters: ``` {'batch_size': 64} ``` **Loss**: `sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss` with parameters: ``` {'scale': 20.0, 'similarity_fct': 'cos_sim'} ``` Parameters of the fit()-Method: ``` { "epochs": 1, "evaluation_steps": 880, "evaluator": "sentence_transformers.evaluation.EmbeddingSimilarityEvaluator.EmbeddingSimilarityEvaluator", "max_grad_norm": 1, "optimizer_class": "", "optimizer_params": { "lr": 0.0002 }, "scheduler": "WarmupLinear", "steps_per_epoch": null, "warmup_steps": 881, "weight_decay": 0.01 } ``` ## Full Model Architecture ``` SentenceTransformer( (0): Transformer({'max_seq_length': 75, 'do_lower_case': False}) with Transformer model: GPTNeoModel (1): Pooling({'word_embedding_dimension': 768, '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} } ```