--- 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: 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: - 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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} } ```