--- pipeline_tag: sentence-similarity tags: - sentence-transformers - feature-extraction - sentence-similarity - mteb model-index: - name: SGPT-125M-weightedmean-msmarco-specb-bitfit results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 metrics: - type: accuracy value: 61.23880597014926 - type: ap value: 25.854431650388644 - type: f1 value: 55.751862762818604 - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (de) config: de split: test revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 metrics: - type: accuracy value: 56.88436830835117 - type: ap value: 72.67279104379772 - type: f1 value: 54.449840243786404 - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en-ext) config: en-ext split: test revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 metrics: - type: accuracy value: 58.27586206896551 - type: ap value: 14.067357642500387 - type: f1 value: 48.172318518691334 - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (ja) config: ja split: test revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 metrics: - type: accuracy value: 54.64668094218415 - type: ap value: 11.776694555054965 - type: f1 value: 44.526622834078765 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1 metrics: - type: accuracy value: 65.401225 - type: ap value: 60.22809958678552 - type: f1 value: 65.0251824898292 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 31.165999999999993 - type: f1 value: 30.908870050167437 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (de) config: de split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 24.79 - type: f1 value: 24.5833598854121 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (es) config: es split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 26.643999999999995 - type: f1 value: 26.39012792213563 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (fr) config: fr split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 26.386000000000003 - type: f1 value: 26.276867791454873 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (ja) config: ja split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 22.078000000000003 - type: f1 value: 21.797960290226843 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (zh) config: zh split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 24.274 - type: f1 value: 23.887054434822627 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3 metrics: - type: map_at_1 value: 22.404 - type: map_at_10 value: 36.845 - type: map_at_100 value: 37.945 - type: map_at_1000 value: 37.966 - type: map_at_3 value: 31.78 - type: map_at_5 value: 34.608 - type: mrr_at_1 value: 22.902 - type: mrr_at_10 value: 37.034 - type: mrr_at_100 value: 38.134 - type: mrr_at_1000 value: 38.155 - type: mrr_at_3 value: 31.935000000000002 - type: mrr_at_5 value: 34.812 - type: ndcg_at_1 value: 22.404 - type: ndcg_at_10 value: 45.425 - type: ndcg_at_100 value: 50.354 - type: ndcg_at_1000 value: 50.873999999999995 - type: ndcg_at_3 value: 34.97 - type: ndcg_at_5 value: 40.081 - type: precision_at_1 value: 22.404 - type: precision_at_10 value: 7.303999999999999 - type: precision_at_100 value: 0.951 - type: precision_at_1000 value: 0.099 - type: precision_at_3 value: 14.746 - type: precision_at_5 value: 11.337 - type: recall_at_1 value: 22.404 - type: recall_at_10 value: 73.044 - type: recall_at_100 value: 95.092 - type: recall_at_1000 value: 99.075 - type: recall_at_3 value: 44.239 - type: recall_at_5 value: 56.686 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8 metrics: - type: v_measure value: 39.70858340673288 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3 metrics: - type: v_measure value: 28.242847713721048 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c metrics: - type: map value: 55.83700395192393 - type: mrr value: 70.3891307215407 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: 9ee918f184421b6bd48b78f6c714d86546106103 metrics: - type: cos_sim_pearson value: 79.25366801756223 - type: cos_sim_spearman value: 75.20954502580506 - type: euclidean_pearson value: 78.79900722991617 - type: euclidean_spearman value: 77.79996549607588 - type: manhattan_pearson value: 78.18408109480399 - type: manhattan_spearman value: 76.85958262303106 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 44fa15921b4c889113cc5df03dd4901b49161ab7 metrics: - type: accuracy value: 77.70454545454545 - type: f1 value: 77.6929000113803 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55 metrics: - type: v_measure value: 33.63260395543984 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1 metrics: - type: v_measure value: 27.038042665369925 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 22.139 - type: map_at_10 value: 28.839 - type: map_at_100 value: 30.023 - type: map_at_1000 value: 30.153000000000002 - type: map_at_3 value: 26.521 - type: map_at_5 value: 27.775 - type: mrr_at_1 value: 26.466 - type: mrr_at_10 value: 33.495000000000005 - type: mrr_at_100 value: 34.416999999999994 - type: mrr_at_1000 value: 34.485 - type: mrr_at_3 value: 31.402 - type: mrr_at_5 value: 32.496 - type: ndcg_at_1 value: 26.466 - type: ndcg_at_10 value: 33.372 - type: ndcg_at_100 value: 38.7 - type: ndcg_at_1000 value: 41.696 - type: ndcg_at_3 value: 29.443 - type: ndcg_at_5 value: 31.121 - type: precision_at_1 value: 26.466 - type: precision_at_10 value: 6.037 - type: precision_at_100 value: 1.0670000000000002 - type: precision_at_1000 value: 0.16199999999999998 - type: precision_at_3 value: 13.782 - type: precision_at_5 value: 9.757 - type: recall_at_1 value: 22.139 - type: recall_at_10 value: 42.39 - type: recall_at_100 value: 65.427 - type: recall_at_1000 value: 86.04899999999999 - type: recall_at_3 value: 31.127 - type: recall_at_5 value: 35.717999999999996 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 20.652 - type: map_at_10 value: 27.558 - type: map_at_100 value: 28.473 - type: map_at_1000 value: 28.577 - type: map_at_3 value: 25.402 - type: map_at_5 value: 26.68 - type: mrr_at_1 value: 25.223000000000003 - type: mrr_at_10 value: 31.966 - type: mrr_at_100 value: 32.664 - type: mrr_at_1000 value: 32.724 - type: mrr_at_3 value: 30.074 - type: mrr_at_5 value: 31.249 - type: ndcg_at_1 value: 25.223000000000003 - type: ndcg_at_10 value: 31.694 - type: ndcg_at_100 value: 35.662 - type: ndcg_at_1000 value: 38.092 - type: ndcg_at_3 value: 28.294000000000004 - type: ndcg_at_5 value: 30.049 - type: precision_at_1 value: 25.223000000000003 - type: precision_at_10 value: 5.777 - type: precision_at_100 value: 0.9730000000000001 - type: precision_at_1000 value: 0.13999999999999999 - type: precision_at_3 value: 13.397 - type: precision_at_5 value: 9.605 - type: recall_at_1 value: 20.652 - type: recall_at_10 value: 39.367999999999995 - type: recall_at_100 value: 56.485 - type: recall_at_1000 value: 73.292 - type: recall_at_3 value: 29.830000000000002 - type: recall_at_5 value: 34.43 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 25.180000000000003 - type: map_at_10 value: 34.579 - type: map_at_100 value: 35.589999999999996 - type: map_at_1000 value: 35.68 - type: map_at_3 value: 31.735999999999997 - type: map_at_5 value: 33.479 - type: mrr_at_1 value: 29.467 - type: mrr_at_10 value: 37.967 - type: mrr_at_100 value: 38.800000000000004 - type: mrr_at_1000 value: 38.858 - type: mrr_at_3 value: 35.465 - type: mrr_at_5 value: 37.057 - type: ndcg_at_1 value: 29.467 - type: ndcg_at_10 value: 39.796 - type: ndcg_at_100 value: 44.531 - type: ndcg_at_1000 value: 46.666000000000004 - type: ndcg_at_3 value: 34.676 - type: ndcg_at_5 value: 37.468 - type: precision_at_1 value: 29.467 - type: precision_at_10 value: 6.601999999999999 - type: precision_at_100 value: 0.9900000000000001 - type: precision_at_1000 value: 0.124 - type: precision_at_3 value: 15.568999999999999 - type: precision_at_5 value: 11.172 - type: recall_at_1 value: 25.180000000000003 - type: recall_at_10 value: 52.269 - type: recall_at_100 value: 73.574 - type: recall_at_1000 value: 89.141 - type: recall_at_3 value: 38.522 - type: recall_at_5 value: 45.323 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 16.303 - type: map_at_10 value: 21.629 - type: map_at_100 value: 22.387999999999998 - type: map_at_1000 value: 22.489 - type: map_at_3 value: 19.608 - type: map_at_5 value: 20.774 - type: mrr_at_1 value: 17.740000000000002 - type: mrr_at_10 value: 23.214000000000002 - type: mrr_at_100 value: 23.97 - type: mrr_at_1000 value: 24.054000000000002 - type: mrr_at_3 value: 21.243000000000002 - type: mrr_at_5 value: 22.322 - type: ndcg_at_1 value: 17.740000000000002 - type: ndcg_at_10 value: 25.113000000000003 - type: ndcg_at_100 value: 29.287999999999997 - type: ndcg_at_1000 value: 32.204 - type: ndcg_at_3 value: 21.111 - type: ndcg_at_5 value: 23.061999999999998 - type: precision_at_1 value: 17.740000000000002 - type: precision_at_10 value: 3.955 - type: precision_at_100 value: 0.644 - type: precision_at_1000 value: 0.093 - type: precision_at_3 value: 8.851 - type: precision_at_5 value: 6.418 - type: recall_at_1 value: 16.303 - type: recall_at_10 value: 34.487 - type: recall_at_100 value: 54.413999999999994 - type: recall_at_1000 value: 77.158 - type: recall_at_3 value: 23.733 - type: recall_at_5 value: 28.381 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 10.133000000000001 - type: map_at_10 value: 15.665999999999999 - type: map_at_100 value: 16.592000000000002 - type: map_at_1000 value: 16.733999999999998 - type: map_at_3 value: 13.625000000000002 - type: map_at_5 value: 14.721 - type: mrr_at_1 value: 12.562000000000001 - type: mrr_at_10 value: 18.487000000000002 - type: mrr_at_100 value: 19.391 - type: mrr_at_1000 value: 19.487 - type: mrr_at_3 value: 16.418 - type: mrr_at_5 value: 17.599999999999998 - type: ndcg_at_1 value: 12.562000000000001 - type: ndcg_at_10 value: 19.43 - type: ndcg_at_100 value: 24.546 - type: ndcg_at_1000 value: 28.193 - type: ndcg_at_3 value: 15.509999999999998 - type: ndcg_at_5 value: 17.322000000000003 - type: precision_at_1 value: 12.562000000000001 - type: precision_at_10 value: 3.794 - type: precision_at_100 value: 0.74 - type: precision_at_1000 value: 0.122 - type: precision_at_3 value: 7.546 - type: precision_at_5 value: 5.721 - type: recall_at_1 value: 10.133000000000001 - type: recall_at_10 value: 28.261999999999997 - type: recall_at_100 value: 51.742999999999995 - type: recall_at_1000 value: 78.075 - type: recall_at_3 value: 17.634 - type: recall_at_5 value: 22.128999999999998 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 19.991999999999997 - type: map_at_10 value: 27.346999999999998 - type: map_at_100 value: 28.582 - type: map_at_1000 value: 28.716 - type: map_at_3 value: 24.907 - type: map_at_5 value: 26.1 - type: mrr_at_1 value: 23.773 - type: mrr_at_10 value: 31.647 - type: mrr_at_100 value: 32.639 - type: mrr_at_1000 value: 32.706 - type: mrr_at_3 value: 29.195 - type: mrr_at_5 value: 30.484 - type: ndcg_at_1 value: 23.773 - type: ndcg_at_10 value: 32.322 - type: ndcg_at_100 value: 37.996 - type: ndcg_at_1000 value: 40.819 - type: ndcg_at_3 value: 27.876 - type: ndcg_at_5 value: 29.664 - type: precision_at_1 value: 23.773 - type: precision_at_10 value: 5.976999999999999 - type: precision_at_100 value: 1.055 - type: precision_at_1000 value: 0.15 - type: precision_at_3 value: 13.122 - type: precision_at_5 value: 9.451 - type: recall_at_1 value: 19.991999999999997 - type: recall_at_10 value: 43.106 - type: recall_at_100 value: 67.264 - type: recall_at_1000 value: 86.386 - type: recall_at_3 value: 30.392000000000003 - type: recall_at_5 value: 34.910999999999994 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 17.896 - type: map_at_10 value: 24.644 - type: map_at_100 value: 25.790000000000003 - type: map_at_1000 value: 25.913999999999998 - type: map_at_3 value: 22.694 - type: map_at_5 value: 23.69 - type: mrr_at_1 value: 21.346999999999998 - type: mrr_at_10 value: 28.594 - type: mrr_at_100 value: 29.543999999999997 - type: mrr_at_1000 value: 29.621 - type: mrr_at_3 value: 26.807 - type: mrr_at_5 value: 27.669 - type: ndcg_at_1 value: 21.346999999999998 - type: ndcg_at_10 value: 28.833 - type: ndcg_at_100 value: 34.272000000000006 - type: ndcg_at_1000 value: 37.355 - type: ndcg_at_3 value: 25.373 - type: ndcg_at_5 value: 26.756 - type: precision_at_1 value: 21.346999999999998 - type: precision_at_10 value: 5.2170000000000005 - type: precision_at_100 value: 0.954 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 11.948 - type: precision_at_5 value: 8.425 - type: recall_at_1 value: 17.896 - type: recall_at_10 value: 37.291000000000004 - type: recall_at_100 value: 61.138000000000005 - type: recall_at_1000 value: 83.212 - type: recall_at_3 value: 27.705999999999996 - type: recall_at_5 value: 31.234 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 17.195166666666665 - type: map_at_10 value: 23.329083333333333 - type: map_at_100 value: 24.30308333333333 - type: map_at_1000 value: 24.422416666666667 - type: map_at_3 value: 21.327416666666664 - type: map_at_5 value: 22.419999999999998 - type: mrr_at_1 value: 19.999916666666667 - type: mrr_at_10 value: 26.390166666666666 - type: mrr_at_100 value: 27.230999999999998 - type: mrr_at_1000 value: 27.308333333333334 - type: mrr_at_3 value: 24.4675 - type: mrr_at_5 value: 25.541083333333336 - type: ndcg_at_1 value: 19.999916666666667 - type: ndcg_at_10 value: 27.248666666666665 - type: ndcg_at_100 value: 32.00258333333334 - type: ndcg_at_1000 value: 34.9465 - type: ndcg_at_3 value: 23.58566666666667 - type: ndcg_at_5 value: 25.26341666666666 - type: precision_at_1 value: 19.999916666666667 - type: precision_at_10 value: 4.772166666666666 - type: precision_at_100 value: 0.847 - type: precision_at_1000 value: 0.12741666666666668 - type: precision_at_3 value: 10.756166666666669 - type: precision_at_5 value: 7.725416666666667 - type: recall_at_1 value: 17.195166666666665 - type: recall_at_10 value: 35.99083333333334 - type: recall_at_100 value: 57.467999999999996 - type: recall_at_1000 value: 78.82366666666667 - type: recall_at_3 value: 25.898499999999995 - type: recall_at_5 value: 30.084333333333333 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 16.779 - type: map_at_10 value: 21.557000000000002 - type: map_at_100 value: 22.338 - type: map_at_1000 value: 22.421 - type: map_at_3 value: 19.939 - type: map_at_5 value: 20.903 - type: mrr_at_1 value: 18.404999999999998 - type: mrr_at_10 value: 23.435 - type: mrr_at_100 value: 24.179000000000002 - type: mrr_at_1000 value: 24.25 - type: mrr_at_3 value: 21.907 - type: mrr_at_5 value: 22.781000000000002 - type: ndcg_at_1 value: 18.404999999999998 - type: ndcg_at_10 value: 24.515 - type: ndcg_at_100 value: 28.721000000000004 - type: ndcg_at_1000 value: 31.259999999999998 - type: ndcg_at_3 value: 21.508 - type: ndcg_at_5 value: 23.01 - type: precision_at_1 value: 18.404999999999998 - type: precision_at_10 value: 3.834 - type: precision_at_100 value: 0.641 - type: precision_at_1000 value: 0.093 - type: precision_at_3 value: 9.151 - type: precision_at_5 value: 6.503 - type: recall_at_1 value: 16.779 - type: recall_at_10 value: 31.730000000000004 - type: recall_at_100 value: 51.673 - type: recall_at_1000 value: 71.17599999999999 - type: recall_at_3 value: 23.518 - type: recall_at_5 value: 27.230999999999998 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 9.279 - type: map_at_10 value: 13.822000000000001 - type: map_at_100 value: 14.533 - type: map_at_1000 value: 14.649999999999999 - type: map_at_3 value: 12.396 - type: map_at_5 value: 13.214 - type: mrr_at_1 value: 11.149000000000001 - type: mrr_at_10 value: 16.139 - type: mrr_at_100 value: 16.872 - type: mrr_at_1000 value: 16.964000000000002 - type: mrr_at_3 value: 14.613000000000001 - type: mrr_at_5 value: 15.486 - type: ndcg_at_1 value: 11.149000000000001 - type: ndcg_at_10 value: 16.82 - type: ndcg_at_100 value: 20.73 - type: ndcg_at_1000 value: 23.894000000000002 - type: ndcg_at_3 value: 14.11 - type: ndcg_at_5 value: 15.404000000000002 - type: precision_at_1 value: 11.149000000000001 - type: precision_at_10 value: 3.063 - type: precision_at_100 value: 0.587 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 6.699 - type: precision_at_5 value: 4.928 - type: recall_at_1 value: 9.279 - type: recall_at_10 value: 23.745 - type: recall_at_100 value: 41.873 - type: recall_at_1000 value: 64.982 - type: recall_at_3 value: 16.152 - type: recall_at_5 value: 19.409000000000002 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 16.36 - type: map_at_10 value: 21.927 - type: map_at_100 value: 22.889 - type: map_at_1000 value: 22.994 - type: map_at_3 value: 20.433 - type: map_at_5 value: 21.337 - type: mrr_at_1 value: 18.75 - type: mrr_at_10 value: 24.859 - type: mrr_at_100 value: 25.746999999999996 - type: mrr_at_1000 value: 25.829 - type: mrr_at_3 value: 23.383000000000003 - type: mrr_at_5 value: 24.297 - type: ndcg_at_1 value: 18.75 - type: ndcg_at_10 value: 25.372 - type: ndcg_at_100 value: 30.342999999999996 - type: ndcg_at_1000 value: 33.286 - type: ndcg_at_3 value: 22.627 - type: ndcg_at_5 value: 24.04 - type: precision_at_1 value: 18.75 - type: precision_at_10 value: 4.1419999999999995 - type: precision_at_100 value: 0.738 - 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type: max_f1 value: 73.64688856729379 --- # SGPT-125M-weightedmean-msmarco-specb-bitfit ## Usage For usage instructions, refer to our codebase: https://github.com/Muennighoff/sgpt ## Evaluation Results For eval results, refer to the eval folder or our paper: https://arxiv.org/abs/2202.08904 ## Training The model was trained with the parameters: **DataLoader**: `torch.utils.data.dataloader.DataLoader` of length 15600 with parameters: ``` {'batch_size': 32, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'} ``` **Loss**: `sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss` with parameters: ``` {'scale': 20.0, 'similarity_fct': 'cos_sim'} ``` Parameters of the fit()-Method: ``` { "epochs": 10, "evaluation_steps": 0, "evaluator": "NoneType", "max_grad_norm": 1, "optimizer_class": "", "optimizer_params": { "lr": 0.0002 }, "scheduler": "WarmupLinear", "steps_per_epoch": null, "warmup_steps": 1000, "weight_decay": 0.01 } ``` ## Full Model Architecture ``` SentenceTransformer( (0): Transformer({'max_seq_length': 300, 'do_lower_case': False}) with Transformer model: GPTNeoModel (1): Pooling({'word_embedding_dimension': 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} } ```