--- tags: - sentence-transformers - feature-extraction - sentence-similarity - mteb model-index: - name: SGPT-1.3B-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: 65.20895522388061 - type: ap value: 29.59212705444778 - type: f1 value: 59.97099864321921 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1 metrics: - type: accuracy value: 73.20565 - type: ap value: 67.36680643550963 - type: f1 value: 72.90420520325125 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: c379a6705fec24a2493fa68e011692605f44e119 metrics: - type: accuracy value: 34.955999999999996 - type: f1 value: 34.719324437696955 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3 metrics: - type: map_at_1 value: 26.101999999999997 - type: map_at_10 value: 40.958 - type: map_at_100 value: 42.033 - type: map_at_1000 value: 42.042 - type: map_at_3 value: 36.332 - type: map_at_5 value: 38.608 - type: mrr_at_1 value: 26.387 - type: mrr_at_10 value: 41.051 - type: mrr_at_100 value: 42.118 - type: mrr_at_1000 value: 42.126999999999995 - type: mrr_at_3 value: 36.415 - type: mrr_at_5 value: 38.72 - type: ndcg_at_1 value: 26.101999999999997 - type: ndcg_at_10 value: 49.68 - type: ndcg_at_100 value: 54.257999999999996 - type: ndcg_at_1000 value: 54.486000000000004 - type: ndcg_at_3 value: 39.864 - type: ndcg_at_5 value: 43.980000000000004 - type: precision_at_1 value: 26.101999999999997 - type: precision_at_10 value: 7.781000000000001 - type: precision_at_100 value: 0.979 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 16.714000000000002 - type: precision_at_5 value: 12.034 - type: recall_at_1 value: 26.101999999999997 - type: recall_at_10 value: 77.809 - type: recall_at_100 value: 97.866 - type: recall_at_1000 value: 99.644 - type: recall_at_3 value: 50.141999999999996 - type: recall_at_5 value: 60.171 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8 metrics: - type: v_measure value: 43.384194916953774 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3 metrics: - type: v_measure value: 33.70962633433912 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c metrics: - type: map value: 58.133058996870076 - type: mrr value: 72.10922041946972 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: 9ee918f184421b6bd48b78f6c714d86546106103 metrics: - type: cos_sim_pearson value: 86.62153841660047 - type: cos_sim_spearman value: 83.01514456843276 - type: euclidean_pearson value: 86.00431518427241 - type: euclidean_spearman value: 83.85552516285783 - type: manhattan_pearson value: 85.83025803351181 - type: manhattan_spearman value: 83.86636878343106 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 44fa15921b4c889113cc5df03dd4901b49161ab7 metrics: - type: accuracy value: 82.05844155844156 - type: f1 value: 82.0185837884764 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55 metrics: - type: v_measure value: 35.05918333141837 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1 metrics: - type: v_measure value: 30.71055028830579 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 26.519 - type: map_at_10 value: 35.634 - type: map_at_100 value: 36.961 - type: map_at_1000 value: 37.088 - type: map_at_3 value: 32.254 - type: map_at_5 value: 34.22 - type: mrr_at_1 value: 32.332 - type: mrr_at_10 value: 41.168 - type: mrr_at_100 value: 41.977 - type: mrr_at_1000 value: 42.028999999999996 - type: mrr_at_3 value: 38.196999999999996 - type: mrr_at_5 value: 40.036 - type: ndcg_at_1 value: 32.332 - type: ndcg_at_10 value: 41.471000000000004 - type: ndcg_at_100 value: 46.955999999999996 - type: ndcg_at_1000 value: 49.262 - type: ndcg_at_3 value: 35.937999999999995 - type: ndcg_at_5 value: 38.702999999999996 - type: precision_at_1 value: 32.332 - type: precision_at_10 value: 7.7829999999999995 - type: precision_at_100 value: 1.29 - type: precision_at_1000 value: 0.178 - type: precision_at_3 value: 16.834 - type: precision_at_5 value: 12.418 - type: recall_at_1 value: 26.519 - type: recall_at_10 value: 53.190000000000005 - type: recall_at_100 value: 76.56500000000001 - type: recall_at_1000 value: 91.47800000000001 - type: recall_at_3 value: 38.034 - type: recall_at_5 value: 45.245999999999995 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 25.356 - type: map_at_10 value: 34.596 - type: map_at_100 value: 35.714 - type: map_at_1000 value: 35.839999999999996 - type: map_at_3 value: 32.073 - type: map_at_5 value: 33.475 - type: mrr_at_1 value: 31.274 - type: mrr_at_10 value: 39.592 - type: mrr_at_100 value: 40.284 - type: mrr_at_1000 value: 40.339999999999996 - type: mrr_at_3 value: 37.378 - type: mrr_at_5 value: 38.658 - type: ndcg_at_1 value: 31.274 - type: ndcg_at_10 value: 39.766 - type: ndcg_at_100 value: 44.028 - type: ndcg_at_1000 value: 46.445 - type: ndcg_at_3 value: 35.934 - type: ndcg_at_5 value: 37.751000000000005 - type: precision_at_1 value: 31.274 - type: precision_at_10 value: 7.452 - type: precision_at_100 value: 1.217 - type: precision_at_1000 value: 0.16999999999999998 - type: precision_at_3 value: 17.431 - type: precision_at_5 value: 12.306000000000001 - type: recall_at_1 value: 25.356 - type: recall_at_10 value: 49.344 - type: recall_at_100 value: 67.497 - type: recall_at_1000 value: 83.372 - type: recall_at_3 value: 38.227 - type: recall_at_5 value: 43.187999999999995 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 32.759 - type: map_at_10 value: 43.937 - type: map_at_100 value: 45.004 - type: map_at_1000 value: 45.07 - type: map_at_3 value: 40.805 - type: map_at_5 value: 42.497 - type: mrr_at_1 value: 37.367 - type: mrr_at_10 value: 47.237 - type: mrr_at_100 value: 47.973 - type: mrr_at_1000 value: 48.010999999999996 - type: mrr_at_3 value: 44.65 - type: mrr_at_5 value: 46.050999999999995 - type: ndcg_at_1 value: 37.367 - type: ndcg_at_10 value: 49.659 - type: ndcg_at_100 value: 54.069 - type: ndcg_at_1000 value: 55.552 - type: ndcg_at_3 value: 44.169000000000004 - type: ndcg_at_5 value: 46.726 - type: precision_at_1 value: 37.367 - type: precision_at_10 value: 8.163 - type: precision_at_100 value: 1.133 - type: precision_at_1000 value: 0.131 - type: precision_at_3 value: 19.707 - type: precision_at_5 value: 13.718 - type: recall_at_1 value: 32.759 - type: recall_at_10 value: 63.341 - type: recall_at_100 value: 82.502 - type: recall_at_1000 value: 93.259 - type: recall_at_3 value: 48.796 - type: recall_at_5 value: 54.921 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 18.962 - type: map_at_10 value: 25.863000000000003 - type: map_at_100 value: 26.817999999999998 - type: map_at_1000 value: 26.918 - type: map_at_3 value: 23.043 - type: map_at_5 value: 24.599 - type: mrr_at_1 value: 20.452 - type: mrr_at_10 value: 27.301 - type: mrr_at_100 value: 28.233000000000004 - type: mrr_at_1000 value: 28.310000000000002 - type: mrr_at_3 value: 24.539 - type: mrr_at_5 value: 26.108999999999998 - type: ndcg_at_1 value: 20.452 - type: ndcg_at_10 value: 30.354999999999997 - type: ndcg_at_100 value: 35.336 - type: ndcg_at_1000 value: 37.927 - type: ndcg_at_3 value: 24.705 - type: ndcg_at_5 value: 27.42 - type: precision_at_1 value: 20.452 - type: precision_at_10 value: 4.949 - type: precision_at_100 value: 0.7799999999999999 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 10.358 - type: precision_at_5 value: 7.774 - type: recall_at_1 value: 18.962 - type: recall_at_10 value: 43.056 - type: recall_at_100 value: 66.27300000000001 - type: recall_at_1000 value: 85.96000000000001 - type: recall_at_3 value: 27.776 - type: recall_at_5 value: 34.287 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 11.24 - type: map_at_10 value: 18.503 - type: map_at_100 value: 19.553 - type: map_at_1000 value: 19.689999999999998 - type: map_at_3 value: 16.150000000000002 - type: map_at_5 value: 17.254 - type: mrr_at_1 value: 13.806 - type: mrr_at_10 value: 21.939 - type: mrr_at_100 value: 22.827 - type: mrr_at_1000 value: 22.911 - type: mrr_at_3 value: 19.32 - type: mrr_at_5 value: 20.558 - type: ndcg_at_1 value: 13.806 - type: ndcg_at_10 value: 23.383000000000003 - type: ndcg_at_100 value: 28.834 - type: ndcg_at_1000 value: 32.175 - type: ndcg_at_3 value: 18.651999999999997 - type: ndcg_at_5 value: 20.505000000000003 - type: precision_at_1 value: 13.806 - type: precision_at_10 value: 4.714 - type: precision_at_100 value: 0.864 - type: precision_at_1000 value: 0.13 - type: precision_at_3 value: 9.328 - type: precision_at_5 value: 6.841 - type: recall_at_1 value: 11.24 - type: recall_at_10 value: 34.854 - type: recall_at_100 value: 59.50299999999999 - type: recall_at_1000 value: 83.25 - type: recall_at_3 value: 22.02 - type: recall_at_5 value: 26.715 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 23.012 - type: map_at_10 value: 33.048 - type: map_at_100 value: 34.371 - type: map_at_1000 value: 34.489 - type: map_at_3 value: 29.942999999999998 - type: map_at_5 value: 31.602000000000004 - type: mrr_at_1 value: 28.104000000000003 - type: mrr_at_10 value: 37.99 - type: mrr_at_100 value: 38.836 - type: mrr_at_1000 value: 38.891 - type: mrr_at_3 value: 35.226 - type: mrr_at_5 value: 36.693999999999996 - type: ndcg_at_1 value: 28.104000000000003 - type: ndcg_at_10 value: 39.037 - type: ndcg_at_100 value: 44.643 - type: ndcg_at_1000 value: 46.939 - type: ndcg_at_3 value: 33.784 - type: ndcg_at_5 value: 36.126000000000005 - type: precision_at_1 value: 28.104000000000003 - type: precision_at_10 value: 7.2669999999999995 - type: precision_at_100 value: 1.193 - type: precision_at_1000 value: 0.159 - type: precision_at_3 value: 16.298000000000002 - type: precision_at_5 value: 11.684 - type: recall_at_1 value: 23.012 - type: recall_at_10 value: 52.054 - type: recall_at_100 value: 75.622 - type: recall_at_1000 value: 90.675 - type: recall_at_3 value: 37.282 - type: recall_at_5 value: 43.307 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 21.624 - type: map_at_10 value: 30.209999999999997 - type: map_at_100 value: 31.52 - type: map_at_1000 value: 31.625999999999998 - type: map_at_3 value: 26.951000000000004 - type: map_at_5 value: 28.938999999999997 - type: mrr_at_1 value: 26.941 - type: mrr_at_10 value: 35.13 - type: mrr_at_100 value: 36.15 - type: mrr_at_1000 value: 36.204 - type: mrr_at_3 value: 32.42 - type: mrr_at_5 value: 34.155 - type: ndcg_at_1 value: 26.941 - type: ndcg_at_10 value: 35.726 - type: ndcg_at_100 value: 41.725 - type: ndcg_at_1000 value: 44.105 - type: ndcg_at_3 value: 30.184 - type: ndcg_at_5 value: 33.176 - type: precision_at_1 value: 26.941 - type: precision_at_10 value: 6.654999999999999 - type: precision_at_100 value: 1.1520000000000001 - type: precision_at_1000 value: 0.152 - type: precision_at_3 value: 14.346 - type: precision_at_5 value: 10.868 - type: recall_at_1 value: 21.624 - type: recall_at_10 value: 47.359 - type: recall_at_100 value: 73.436 - type: recall_at_1000 value: 89.988 - type: recall_at_3 value: 32.34 - type: recall_at_5 value: 39.856 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 20.67566666666667 - type: map_at_10 value: 28.479333333333333 - type: map_at_100 value: 29.612249999999996 - type: map_at_1000 value: 29.731166666666663 - type: map_at_3 value: 25.884 - type: map_at_5 value: 27.298916666666667 - type: mrr_at_1 value: 24.402583333333332 - type: mrr_at_10 value: 32.07041666666667 - type: mrr_at_100 value: 32.95841666666667 - type: mrr_at_1000 value: 33.025416666666665 - type: mrr_at_3 value: 29.677749999999996 - type: mrr_at_5 value: 31.02391666666667 - type: ndcg_at_1 value: 24.402583333333332 - type: ndcg_at_10 value: 33.326166666666666 - type: ndcg_at_100 value: 38.51566666666667 - type: ndcg_at_1000 value: 41.13791666666667 - type: ndcg_at_3 value: 28.687749999999994 - type: ndcg_at_5 value: 30.84766666666667 - type: precision_at_1 value: 24.402583333333332 - type: precision_at_10 value: 5.943749999999999 - type: precision_at_100 value: 1.0098333333333334 - type: precision_at_1000 value: 0.14183333333333334 - type: precision_at_3 value: 13.211500000000001 - type: precision_at_5 value: 9.548416666666668 - type: recall_at_1 value: 20.67566666666667 - type: recall_at_10 value: 44.245583333333336 - type: recall_at_100 value: 67.31116666666667 - type: recall_at_1000 value: 85.87841666666665 - type: recall_at_3 value: 31.49258333333333 - type: recall_at_5 value: 36.93241666666667 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 18.34 - type: map_at_10 value: 23.988 - type: map_at_100 value: 24.895 - type: map_at_1000 value: 24.992 - type: map_at_3 value: 21.831 - type: map_at_5 value: 23.0 - type: mrr_at_1 value: 20.399 - type: mrr_at_10 value: 26.186 - type: mrr_at_100 value: 27.017999999999997 - type: mrr_at_1000 value: 27.090999999999998 - type: mrr_at_3 value: 24.08 - type: mrr_at_5 value: 25.230000000000004 - type: ndcg_at_1 value: 20.399 - type: ndcg_at_10 value: 27.799000000000003 - type: ndcg_at_100 value: 32.579 - type: ndcg_at_1000 value: 35.209 - type: ndcg_at_3 value: 23.684 - type: ndcg_at_5 value: 25.521 - type: precision_at_1 value: 20.399 - type: precision_at_10 value: 4.585999999999999 - type: precision_at_100 value: 0.755 - type: precision_at_1000 value: 0.105 - type: precision_at_3 value: 10.276 - type: precision_at_5 value: 7.362 - type: recall_at_1 value: 18.34 - type: recall_at_10 value: 37.456 - type: recall_at_100 value: 59.86 - type: recall_at_1000 value: 79.703 - type: recall_at_3 value: 26.163999999999998 - type: recall_at_5 value: 30.652 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 12.327 - type: map_at_10 value: 17.572 - type: map_at_100 value: 18.534 - type: map_at_1000 value: 18.653 - type: map_at_3 value: 15.703 - type: map_at_5 value: 16.752 - type: mrr_at_1 value: 15.038000000000002 - type: mrr_at_10 value: 20.726 - type: mrr_at_100 value: 21.61 - type: mrr_at_1000 value: 21.695 - type: mrr_at_3 value: 18.829 - type: mrr_at_5 value: 19.885 - type: ndcg_at_1 value: 15.038000000000002 - type: ndcg_at_10 value: 21.241 - type: ndcg_at_100 value: 26.179000000000002 - type: ndcg_at_1000 value: 29.316 - type: ndcg_at_3 value: 17.762 - type: ndcg_at_5 value: 19.413 - type: precision_at_1 value: 15.038000000000002 - type: precision_at_10 value: 3.8920000000000003 - type: precision_at_100 value: 0.75 - type: precision_at_1000 value: 0.11800000000000001 - type: precision_at_3 value: 8.351 - type: precision_at_5 value: 6.187 - type: recall_at_1 value: 12.327 - type: recall_at_10 value: 29.342000000000002 - type: recall_at_100 value: 51.854 - type: recall_at_1000 value: 74.648 - type: recall_at_3 value: 19.596 - type: recall_at_5 value: 23.899 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 20.594 - type: map_at_10 value: 27.878999999999998 - type: map_at_100 value: 28.926000000000002 - type: map_at_1000 value: 29.041 - type: map_at_3 value: 25.668999999999997 - type: map_at_5 value: 26.773999999999997 - type: mrr_at_1 value: 23.694000000000003 - type: mrr_at_10 value: 31.335 - type: mrr_at_100 value: 32.218 - type: mrr_at_1000 value: 32.298 - type: mrr_at_3 value: 29.26 - type: mrr_at_5 value: 30.328 - type: ndcg_at_1 value: 23.694000000000003 - type: ndcg_at_10 value: 32.456 - type: ndcg_at_100 value: 37.667 - type: ndcg_at_1000 value: 40.571 - type: ndcg_at_3 value: 28.283 - type: ndcg_at_5 value: 29.986 - type: precision_at_1 value: 23.694000000000003 - type: precision_at_10 value: 5.448 - type: precision_at_100 value: 0.9119999999999999 - type: precision_at_1000 value: 0.127 - type: precision_at_3 value: 12.717999999999998 - type: precision_at_5 value: 8.843 - type: recall_at_1 value: 20.594 - type: recall_at_10 value: 43.004999999999995 - type: recall_at_100 value: 66.228 - type: recall_at_1000 value: 87.17099999999999 - type: recall_at_3 value: 31.554 - type: recall_at_5 value: 35.838 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 20.855999999999998 - type: map_at_10 value: 28.372000000000003 - type: map_at_100 value: 29.87 - type: map_at_1000 value: 30.075000000000003 - type: map_at_3 value: 26.054 - type: map_at_5 value: 27.128999999999998 - type: mrr_at_1 value: 25.494 - type: mrr_at_10 value: 32.735 - type: mrr_at_100 value: 33.794000000000004 - type: mrr_at_1000 value: 33.85 - type: mrr_at_3 value: 30.731 - type: mrr_at_5 value: 31.897 - type: ndcg_at_1 value: 25.494 - type: ndcg_at_10 value: 33.385 - type: ndcg_at_100 value: 39.436 - type: ndcg_at_1000 value: 42.313 - type: ndcg_at_3 value: 29.612 - type: ndcg_at_5 value: 31.186999999999998 - type: precision_at_1 value: 25.494 - type: precision_at_10 value: 6.422999999999999 - type: precision_at_100 value: 1.383 - type: precision_at_1000 value: 0.22399999999999998 - type: precision_at_3 value: 13.834 - type: precision_at_5 value: 10.0 - type: recall_at_1 value: 20.855999999999998 - type: recall_at_10 value: 42.678 - type: recall_at_100 value: 70.224 - type: recall_at_1000 value: 89.369 - type: recall_at_3 value: 31.957 - type: recall_at_5 value: 36.026 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db metrics: - type: map_at_1 value: 16.519000000000002 - type: map_at_10 value: 22.15 - type: map_at_100 value: 23.180999999999997 - type: map_at_1000 value: 23.291999999999998 - type: map_at_3 value: 20.132 - type: map_at_5 value: 21.346 - type: mrr_at_1 value: 17.93 - type: mrr_at_10 value: 23.506 - type: mrr_at_100 value: 24.581 - type: mrr_at_1000 value: 24.675 - type: mrr_at_3 value: 21.503 - type: mrr_at_5 value: 22.686 - type: ndcg_at_1 value: 17.93 - type: ndcg_at_10 value: 25.636 - type: ndcg_at_100 value: 30.736 - type: ndcg_at_1000 value: 33.841 - type: ndcg_at_3 value: 21.546000000000003 - type: ndcg_at_5 value: 23.658 - type: precision_at_1 value: 17.93 - type: precision_at_10 value: 3.993 - type: precision_at_100 value: 0.6890000000000001 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 9.057 - type: precision_at_5 value: 6.58 - type: recall_at_1 value: 16.519000000000002 - type: recall_at_10 value: 35.268 - type: recall_at_100 value: 58.17 - type: recall_at_1000 value: 81.66799999999999 - type: recall_at_3 value: 24.165 - type: recall_at_5 value: 29.254 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: 392b78eb68c07badcd7c2cd8f39af108375dfcce metrics: - type: map_at_1 value: 10.363 - type: map_at_10 value: 18.301000000000002 - type: map_at_100 value: 20.019000000000002 - type: map_at_1000 value: 20.207 - type: map_at_3 value: 14.877 - type: map_at_5 value: 16.544 - type: mrr_at_1 value: 22.866 - type: mrr_at_10 value: 34.935 - type: mrr_at_100 value: 35.802 - type: mrr_at_1000 value: 35.839999999999996 - type: mrr_at_3 value: 30.965999999999998 - type: mrr_at_5 value: 33.204 - type: ndcg_at_1 value: 22.866 - type: ndcg_at_10 value: 26.595000000000002 - type: ndcg_at_100 value: 33.513999999999996 - type: ndcg_at_1000 value: 36.872 - type: ndcg_at_3 value: 20.666999999999998 - type: ndcg_at_5 value: 22.728 - type: precision_at_1 value: 22.866 - type: precision_at_10 value: 8.632 - type: precision_at_100 value: 1.6119999999999999 - type: precision_at_1000 value: 0.22399999999999998 - type: precision_at_3 value: 15.504999999999999 - type: precision_at_5 value: 12.404 - type: recall_at_1 value: 10.363 - type: recall_at_10 value: 33.494 - type: recall_at_100 value: 57.593 - type: recall_at_1000 value: 76.342 - type: recall_at_3 value: 19.157 - type: recall_at_5 value: 24.637999999999998 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: f097057d03ed98220bc7309ddb10b71a54d667d6 metrics: - type: map_at_1 value: 7.436 - type: map_at_10 value: 14.760000000000002 - type: map_at_100 value: 19.206 - type: map_at_1000 value: 20.267 - type: map_at_3 value: 10.894 - type: map_at_5 value: 12.828999999999999 - type: mrr_at_1 value: 54.25 - type: mrr_at_10 value: 63.769 - type: mrr_at_100 value: 64.193 - type: mrr_at_1000 value: 64.211 - type: mrr_at_3 value: 61.458 - type: mrr_at_5 value: 63.096 - type: ndcg_at_1 value: 42.875 - type: ndcg_at_10 value: 31.507 - type: ndcg_at_100 value: 34.559 - type: ndcg_at_1000 value: 41.246 - type: ndcg_at_3 value: 35.058 - type: ndcg_at_5 value: 33.396 - type: precision_at_1 value: 54.25 - type: precision_at_10 value: 24.45 - type: precision_at_100 value: 7.383000000000001 - type: precision_at_1000 value: 1.582 - type: precision_at_3 value: 38.083 - type: precision_at_5 value: 32.6 - type: recall_at_1 value: 7.436 - type: recall_at_10 value: 19.862 - type: recall_at_100 value: 38.981 - type: recall_at_1000 value: 61.038000000000004 - type: recall_at_3 value: 11.949 - type: recall_at_5 value: 15.562000000000001 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 829147f8f75a25f005913200eb5ed41fae320aa1 metrics: - type: accuracy value: 46.39 - type: f1 value: 42.26424885856703 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: 1429cf27e393599b8b359b9b72c666f96b2525f9 metrics: - type: map_at_1 value: 50.916 - type: map_at_10 value: 62.258 - type: map_at_100 value: 62.741 - type: map_at_1000 value: 62.763000000000005 - type: map_at_3 value: 60.01800000000001 - type: map_at_5 value: 61.419999999999995 - type: mrr_at_1 value: 54.964999999999996 - type: mrr_at_10 value: 66.554 - type: mrr_at_100 value: 66.96600000000001 - type: mrr_at_1000 value: 66.97800000000001 - type: mrr_at_3 value: 64.414 - type: mrr_at_5 value: 65.77 - type: ndcg_at_1 value: 54.964999999999996 - type: ndcg_at_10 value: 68.12 - type: ndcg_at_100 value: 70.282 - type: ndcg_at_1000 value: 70.788 - type: ndcg_at_3 value: 63.861999999999995 - type: ndcg_at_5 value: 66.216 - type: precision_at_1 value: 54.964999999999996 - type: precision_at_10 value: 8.998000000000001 - type: precision_at_100 value: 1.016 - type: precision_at_1000 value: 0.107 - type: precision_at_3 value: 25.618000000000002 - type: precision_at_5 value: 16.676 - type: recall_at_1 value: 50.916 - type: recall_at_10 value: 82.04 - type: recall_at_100 value: 91.689 - type: recall_at_1000 value: 95.34899999999999 - type: recall_at_3 value: 70.512 - type: recall_at_5 value: 76.29899999999999 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: 41b686a7f28c59bcaaa5791efd47c67c8ebe28be metrics: - type: map_at_1 value: 13.568 - type: map_at_10 value: 23.264000000000003 - type: map_at_100 value: 24.823999999999998 - type: map_at_1000 value: 25.013999999999996 - type: map_at_3 value: 19.724 - type: map_at_5 value: 21.772 - type: mrr_at_1 value: 27.315 - type: mrr_at_10 value: 35.935 - type: mrr_at_100 value: 36.929 - type: mrr_at_1000 value: 36.985 - type: mrr_at_3 value: 33.591 - type: mrr_at_5 value: 34.848 - type: ndcg_at_1 value: 27.315 - type: ndcg_at_10 value: 29.988 - type: ndcg_at_100 value: 36.41 - type: ndcg_at_1000 value: 40.184999999999995 - type: ndcg_at_3 value: 26.342 - type: ndcg_at_5 value: 27.68 - type: precision_at_1 value: 27.315 - type: precision_at_10 value: 8.565000000000001 - type: precision_at_100 value: 1.508 - type: precision_at_1000 value: 0.219 - type: precision_at_3 value: 17.849999999999998 - type: precision_at_5 value: 13.672999999999998 - type: recall_at_1 value: 13.568 - type: recall_at_10 value: 37.133 - type: recall_at_100 value: 61.475 - type: recall_at_1000 value: 84.372 - type: recall_at_3 value: 24.112000000000002 - type: recall_at_5 value: 29.507 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: 766870b35a1b9ca65e67a0d1913899973551fc6c metrics: - type: map_at_1 value: 30.878 - type: map_at_10 value: 40.868 - type: map_at_100 value: 41.693999999999996 - type: map_at_1000 value: 41.775 - type: map_at_3 value: 38.56 - type: map_at_5 value: 39.947 - type: mrr_at_1 value: 61.756 - type: mrr_at_10 value: 68.265 - type: mrr_at_100 value: 68.671 - type: mrr_at_1000 value: 68.694 - type: mrr_at_3 value: 66.78399999999999 - type: mrr_at_5 value: 67.704 - type: ndcg_at_1 value: 61.756 - type: ndcg_at_10 value: 49.931 - type: ndcg_at_100 value: 53.179 - type: ndcg_at_1000 value: 54.94799999999999 - type: ndcg_at_3 value: 46.103 - type: ndcg_at_5 value: 48.147 - type: precision_at_1 value: 61.756 - type: precision_at_10 value: 10.163 - type: precision_at_100 value: 1.2710000000000001 - type: precision_at_1000 value: 0.151 - type: precision_at_3 value: 28.179 - type: precision_at_5 value: 18.528 - type: recall_at_1 value: 30.878 - type: recall_at_10 value: 50.817 - type: recall_at_100 value: 63.544999999999995 - type: recall_at_1000 value: 75.361 - type: recall_at_3 value: 42.269 - type: recall_at_5 value: 46.32 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 8d743909f834c38949e8323a8a6ce8721ea6c7f4 metrics: - type: accuracy value: 64.04799999999999 - type: ap value: 59.185251455339284 - type: f1 value: 63.947123181349255 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: validation revision: e6838a846e2408f22cf5cc337ebc83e0bcf77849 metrics: - type: map_at_1 value: 18.9 - type: map_at_10 value: 29.748 - type: map_at_100 value: 30.976 - type: map_at_1000 value: 31.041 - type: map_at_3 value: 26.112999999999996 - type: map_at_5 value: 28.197 - type: mrr_at_1 value: 19.413 - type: mrr_at_10 value: 30.322 - type: mrr_at_100 value: 31.497000000000003 - type: mrr_at_1000 value: 31.555 - type: mrr_at_3 value: 26.729000000000003 - type: mrr_at_5 value: 28.788999999999998 - type: ndcg_at_1 value: 19.413 - type: ndcg_at_10 value: 36.048 - type: ndcg_at_100 value: 42.152 - type: ndcg_at_1000 value: 43.772 - type: ndcg_at_3 value: 28.642 - type: ndcg_at_5 value: 32.358 - type: precision_at_1 value: 19.413 - type: precision_at_10 value: 5.785 - type: precision_at_100 value: 0.8869999999999999 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 12.192 - type: precision_at_5 value: 9.189 - type: recall_at_1 value: 18.9 - type: recall_at_10 value: 55.457 - type: recall_at_100 value: 84.09100000000001 - type: recall_at_1000 value: 96.482 - type: recall_at_3 value: 35.359 - type: recall_at_5 value: 44.275 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 metrics: - type: accuracy value: 92.07706338349293 - type: f1 value: 91.56680443236652 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: 6299947a7777084cc2d4b64235bf7190381ce755 metrics: - type: accuracy value: 71.18559051527589 - type: f1 value: 52.42887061726789 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea metrics: - type: accuracy value: 68.64828513786148 - type: f1 value: 66.54281381596097 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 76.04236718224612 - type: f1 value: 75.89170458655639 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: dcefc037ef84348e49b0d29109e891c01067226b metrics: - type: v_measure value: 32.0840369055247 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 3cd0e71dfbe09d4de0f9e5ecba43e7ce280959dc metrics: - type: v_measure value: 29.448729560244537 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 31.340856463122375 - type: mrr value: 32.398547669840916 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: 7eb63cc0c1eb59324d709ebed25fcab851fa7610 metrics: - type: map_at_1 value: 5.526 - type: map_at_10 value: 11.745 - type: map_at_100 value: 14.831 - type: map_at_1000 value: 16.235 - type: map_at_3 value: 8.716 - type: map_at_5 value: 10.101 - type: mrr_at_1 value: 43.653 - type: mrr_at_10 value: 51.06699999999999 - type: mrr_at_100 value: 51.881 - type: mrr_at_1000 value: 51.912000000000006 - type: mrr_at_3 value: 49.02 - type: mrr_at_5 value: 50.288999999999994 - type: ndcg_at_1 value: 41.949999999999996 - type: ndcg_at_10 value: 32.083 - type: ndcg_at_100 value: 30.049999999999997 - type: ndcg_at_1000 value: 38.661 - type: ndcg_at_3 value: 37.940000000000005 - type: ndcg_at_5 value: 35.455999999999996 - type: precision_at_1 value: 43.344 - type: precision_at_10 value: 23.437 - type: precision_at_100 value: 7.829999999999999 - type: precision_at_1000 value: 2.053 - type: precision_at_3 value: 35.501 - type: precision_at_5 value: 30.464000000000002 - type: recall_at_1 value: 5.526 - type: recall_at_10 value: 15.445999999999998 - type: recall_at_100 value: 31.179000000000002 - type: recall_at_1000 value: 61.578 - type: recall_at_3 value: 9.71 - type: recall_at_5 value: 12.026 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: 6062aefc120bfe8ece5897809fb2e53bfe0d128c metrics: - type: map_at_1 value: 23.467 - type: map_at_10 value: 36.041000000000004 - type: map_at_100 value: 37.268 - type: map_at_1000 value: 37.322 - type: map_at_3 value: 32.09 - type: map_at_5 value: 34.414 - type: mrr_at_1 value: 26.738 - type: mrr_at_10 value: 38.665 - type: mrr_at_100 value: 39.64 - type: mrr_at_1000 value: 39.681 - type: mrr_at_3 value: 35.207 - type: mrr_at_5 value: 37.31 - type: ndcg_at_1 value: 26.709 - type: ndcg_at_10 value: 42.942 - type: ndcg_at_100 value: 48.296 - type: ndcg_at_1000 value: 49.651 - type: ndcg_at_3 value: 35.413 - type: ndcg_at_5 value: 39.367999999999995 - type: precision_at_1 value: 26.709 - type: precision_at_10 value: 7.306 - type: precision_at_100 value: 1.0290000000000001 - type: precision_at_1000 value: 0.116 - type: precision_at_3 value: 16.348 - type: precision_at_5 value: 12.068 - type: recall_at_1 value: 23.467 - type: recall_at_10 value: 61.492999999999995 - type: recall_at_100 value: 85.01100000000001 - type: recall_at_1000 value: 95.261 - type: recall_at_3 value: 41.952 - type: recall_at_5 value: 51.105999999999995 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: 6205996560df11e3a3da9ab4f926788fc30a7db4 metrics: - type: map_at_1 value: 67.51700000000001 - type: map_at_10 value: 81.054 - type: map_at_100 value: 81.727 - type: map_at_1000 value: 81.75200000000001 - type: map_at_3 value: 78.018 - type: map_at_5 value: 79.879 - type: mrr_at_1 value: 77.52 - type: mrr_at_10 value: 84.429 - type: mrr_at_100 value: 84.58200000000001 - type: mrr_at_1000 value: 84.584 - type: mrr_at_3 value: 83.268 - type: mrr_at_5 value: 84.013 - type: ndcg_at_1 value: 77.53 - type: ndcg_at_10 value: 85.277 - type: ndcg_at_100 value: 86.80499999999999 - type: ndcg_at_1000 value: 87.01 - type: ndcg_at_3 value: 81.975 - type: ndcg_at_5 value: 83.723 - type: precision_at_1 value: 77.53 - type: precision_at_10 value: 12.961 - type: precision_at_100 value: 1.502 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 35.713 - type: precision_at_5 value: 23.574 - type: recall_at_1 value: 67.51700000000001 - type: recall_at_10 value: 93.486 - type: recall_at_100 value: 98.9 - type: recall_at_1000 value: 99.92999999999999 - type: recall_at_3 value: 84.17999999999999 - type: recall_at_5 value: 88.97500000000001 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: b2805658ae38990172679479369a78b86de8c390 metrics: - type: v_measure value: 48.225994608749915 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 metrics: - type: v_measure value: 53.17635557157765 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: 5c59ef3e437a0a9651c8fe6fde943e7dce59fba5 metrics: - type: map_at_1 value: 3.988 - type: map_at_10 value: 9.4 - type: map_at_100 value: 10.968 - type: map_at_1000 value: 11.257 - type: map_at_3 value: 7.123 - type: map_at_5 value: 8.221 - type: mrr_at_1 value: 19.7 - type: mrr_at_10 value: 29.098000000000003 - type: mrr_at_100 value: 30.247 - type: mrr_at_1000 value: 30.318 - type: mrr_at_3 value: 26.55 - type: mrr_at_5 value: 27.915 - type: ndcg_at_1 value: 19.7 - type: ndcg_at_10 value: 16.176 - type: ndcg_at_100 value: 22.931 - type: ndcg_at_1000 value: 28.301 - type: ndcg_at_3 value: 16.142 - type: ndcg_at_5 value: 13.633999999999999 - type: precision_at_1 value: 19.7 - type: precision_at_10 value: 8.18 - type: precision_at_100 value: 1.8010000000000002 - type: precision_at_1000 value: 0.309 - type: precision_at_3 value: 15.1 - type: precision_at_5 value: 11.74 - type: recall_at_1 value: 3.988 - type: recall_at_10 value: 16.625 - type: recall_at_100 value: 36.61 - type: recall_at_1000 value: 62.805 - type: recall_at_3 value: 9.168 - type: recall_at_5 value: 11.902 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: 20a6d6f312dd54037fe07a32d58e5e168867909d metrics: - type: cos_sim_pearson value: 77.29330379162072 - type: cos_sim_spearman value: 67.22953551111448 - type: euclidean_pearson value: 71.44682700059415 - type: euclidean_spearman value: 66.33178012153247 - type: manhattan_pearson value: 71.46941734657887 - 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type: max_f1 value: 75.94113995691386 --- # SGPT-1.3B-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 62398 with parameters: ``` {'batch_size': 8, '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': 2048, '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} } ```