--- tags: - mteb model-index: - name: winberta results: - task: type: Clustering dataset: type: PL-MTEB/8tags-clustering name: MTEB 8TagsClustering config: default split: test revision: None metrics: - type: v_measure value: 4.6762575299584555 - task: type: STS dataset: type: C-MTEB/AFQMC name: MTEB AFQMC config: default split: validation revision: None metrics: - type: cos_sim_pearson value: 39.92944665836267 - type: cos_sim_spearman value: 44.25208147787637 - type: euclidean_pearson value: 42.772842908404925 - type: euclidean_spearman value: 44.25208147787637 - type: manhattan_pearson value: 42.600565541302124 - type: manhattan_spearman value: 44.10077657065955 - task: type: STS dataset: type: C-MTEB/ATEC name: MTEB ATEC config: default split: test revision: None metrics: - type: cos_sim_pearson value: 40.99236789888241 - type: cos_sim_spearman value: 48.23930486989189 - type: euclidean_pearson value: 48.58722571676781 - type: euclidean_spearman value: 48.23930486989189 - type: manhattan_pearson value: 48.46099247089918 - type: manhattan_spearman value: 48.146434253428446 - task: type: Classification dataset: type: PL-MTEB/allegro-reviews name: MTEB AllegroReviews config: default split: test revision: None metrics: - type: accuracy value: 24.890656063618295 - type: f1 value: 22.302214664290936 - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 69.91044776119402 - type: ap value: 31.66723912472561 - type: f1 value: 63.421139457970746 - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (de) config: de split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 54.111349036402565 - type: ap value: 71.1991959997261 - type: f1 value: 51.56958434326653 - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en-ext) config: en-ext split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 70.38230884557721 - type: ap value: 19.909214544678782 - type: f1 value: 57.875461279657294 - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (ja) config: ja split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 53.9507494646681 - type: ap value: 11.599932987437649 - type: f1 value: 43.985879202841346 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 72.94987499999999 - type: ap value: 67.05052265683933 - type: f1 value: 72.74508057235695 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (zh) config: zh split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 39.681999999999995 - type: f1 value: 37.89870143785791 - task: type: Classification dataset: type: DDSC/angry-tweets name: MTEB AngryTweetsClassification config: default split: test revision: 20b0e6081892e78179356fada741b7afa381443d metrics: - type: accuracy value: 46.170009551098374 - type: f1 value: 45.00796485732147 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 33.69909330263927 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 23.04252711340139 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 53.987091172373944 - type: mrr value: 67.65840038693224 - task: type: STS dataset: type: C-MTEB/BQ name: MTEB BQ config: default split: test revision: None metrics: - type: cos_sim_pearson value: 54.56093256747345 - type: cos_sim_spearman value: 56.27367976851523 - type: euclidean_pearson value: 55.38528627937832 - type: euclidean_spearman value: 56.27367284031196 - type: manhattan_pearson value: 55.30402898692059 - type: manhattan_spearman value: 56.19811385550433 - 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: 9.384133611691023 - type: f1 value: 9.25678496868476 - type: precision value: 9.204791728800078 - type: recall value: 9.384133611691023 - 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: 17.719568567026194 - type: f1 value: 17.413603345806735 - type: precision value: 17.284183459067894 - type: recall value: 17.719568567026194 - 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: 52.70523034291652 - type: f1 value: 51.97355963514606 - type: precision value: 51.642562994485395 - type: recall value: 52.70523034291652 - 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: 89.0995260663507 - type: f1 value: 88.70458135860979 - type: precision value: 88.5202738283307 - type: recall value: 89.0995260663507 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 64.12337662337661 - type: f1 value: 62.35908261257942 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 32.70437969303962 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 23.27850834359782 - task: type: Clustering dataset: type: slvnwhrl/blurbs-clustering-p2p name: MTEB BlurbsClusteringP2P config: default split: test revision: a2dd5b02a77de3466a3eaa98ae586b5610314496 metrics: - type: v_measure value: 17.471535040494018 - task: type: Clustering dataset: type: slvnwhrl/blurbs-clustering-s2s name: MTEB BlurbsClusteringS2S config: default split: test revision: 9bfff9a7f8f6dc6ffc9da71c48dd48b68696471d metrics: - type: v_measure value: 7.957798776861661 - task: type: Classification dataset: type: PL-MTEB/cbd name: MTEB CBD config: default split: test revision: None metrics: - type: accuracy value: 53.78000000000001 - type: ap value: 16.030265142358818 - type: f1 value: 46.39936854646567 - task: type: PairClassification dataset: type: PL-MTEB/cdsce-pairclassification name: MTEB CDSC-E config: default split: test revision: None metrics: - type: cos_sim_accuracy value: 82.69999999999999 - type: cos_sim_ap value: 43.50726455006939 - type: cos_sim_f1 value: 55.21472392638037 - type: cos_sim_precision value: 45.1505016722408 - type: cos_sim_recall value: 71.05263157894737 - type: dot_accuracy value: 82.69999999999999 - type: dot_ap value: 43.50726455006939 - type: dot_f1 value: 55.21472392638037 - type: dot_precision value: 45.1505016722408 - type: dot_recall value: 71.05263157894737 - type: euclidean_accuracy value: 82.69999999999999 - type: euclidean_ap value: 43.50726455006939 - type: euclidean_f1 value: 55.21472392638037 - type: euclidean_precision value: 45.1505016722408 - type: euclidean_recall value: 71.05263157894737 - type: manhattan_accuracy value: 83.1 - type: manhattan_ap value: 43.95534719205733 - type: manhattan_f1 value: 55.34351145038169 - type: manhattan_precision value: 43.41317365269461 - type: manhattan_recall value: 76.31578947368422 - type: max_accuracy value: 83.1 - type: max_ap value: 43.95534719205733 - type: max_f1 value: 55.34351145038169 - task: type: Clustering dataset: type: C-MTEB/CLSClusteringP2P name: MTEB CLSClusteringP2P config: default split: test revision: None metrics: - type: v_measure value: 42.20892953002924 - task: type: Clustering dataset: type: C-MTEB/CLSClusteringS2S name: MTEB CLSClusteringS2S config: default split: test revision: None metrics: - type: v_measure value: 40.33286164241634 - task: type: Reranking dataset: type: C-MTEB/CMedQAv1-reranking name: MTEB CMedQAv1 config: default split: test revision: None metrics: - type: map value: 76.47170720756812 - type: mrr value: 79.89289682539682 - task: type: Reranking dataset: type: C-MTEB/CMedQAv2-reranking name: MTEB CMedQAv2 config: default split: test revision: None metrics: - type: map value: 77.43675520157939 - type: mrr value: 81.11420634920636 - task: type: Retrieval dataset: type: C-MTEB/CmedqaRetrieval name: MTEB CmedqaRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 17.308 - type: map_at_10 value: 26.144000000000002 - type: map_at_100 value: 27.864 - type: map_at_1000 value: 28.032 - type: map_at_3 value: 23.058999999999997 - type: map_at_5 value: 24.724 - type: mrr_at_1 value: 27.206999999999997 - type: mrr_at_10 value: 34.287 - type: mrr_at_100 value: 35.375 - type: mrr_at_1000 value: 35.449999999999996 - type: mrr_at_3 value: 31.912000000000003 - type: mrr_at_5 value: 33.222 - type: ndcg_at_1 value: 27.206999999999997 - type: ndcg_at_10 value: 31.789 - type: ndcg_at_100 value: 39.251000000000005 - type: ndcg_at_1000 value: 42.536 - type: ndcg_at_3 value: 27.503 - type: ndcg_at_5 value: 29.226999999999997 - type: precision_at_1 value: 27.206999999999997 - type: precision_at_10 value: 7.3069999999999995 - type: precision_at_100 value: 1.345 - type: precision_at_1000 value: 0.17700000000000002 - type: precision_at_3 value: 15.854 - type: precision_at_5 value: 11.593 - type: recall_at_1 value: 17.308 - type: recall_at_10 value: 40.474 - type: recall_at_100 value: 71.897 - type: recall_at_1000 value: 94.375 - type: recall_at_3 value: 27.563 - type: recall_at_5 value: 32.944 - task: type: PairClassification dataset: type: C-MTEB/CMNLI name: MTEB Cmnli config: default split: validation revision: None metrics: - type: cos_sim_accuracy value: 76.11545399879735 - type: cos_sim_ap value: 84.09842598179311 - type: cos_sim_f1 value: 77.66760077602932 - type: cos_sim_precision value: 72.04559088182364 - type: cos_sim_recall value: 84.24129062426935 - type: dot_accuracy value: 76.11545399879735 - type: dot_ap value: 84.11185112340806 - type: dot_f1 value: 77.66760077602932 - type: dot_precision value: 72.04559088182364 - type: dot_recall value: 84.24129062426935 - type: euclidean_accuracy value: 76.11545399879735 - type: euclidean_ap value: 84.09842259671359 - type: euclidean_f1 value: 77.66760077602932 - type: euclidean_precision value: 72.04559088182364 - type: euclidean_recall value: 84.24129062426935 - type: manhattan_accuracy value: 76.12748045700542 - type: manhattan_ap value: 84.07246090513767 - type: manhattan_f1 value: 77.41864555848726 - type: manhattan_precision value: 73.064951234696 - type: manhattan_recall value: 82.3240589198036 - type: max_accuracy value: 76.12748045700542 - type: max_ap value: 84.11185112340806 - type: max_f1 value: 77.66760077602932 - task: type: Retrieval dataset: type: C-MTEB/CovidRetrieval name: MTEB CovidRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 53.266999999999996 - type: map_at_10 value: 61.807 - type: map_at_100 value: 62.342 - type: map_at_1000 value: 62.36000000000001 - type: map_at_3 value: 59.255 - type: map_at_5 value: 60.757000000000005 - type: mrr_at_1 value: 53.21399999999999 - type: mrr_at_10 value: 61.760999999999996 - type: mrr_at_100 value: 62.283 - type: mrr_at_1000 value: 62.300999999999995 - type: mrr_at_3 value: 59.272999999999996 - type: mrr_at_5 value: 60.727 - type: ndcg_at_1 value: 53.319 - type: ndcg_at_10 value: 66.334 - type: ndcg_at_100 value: 69.128 - type: ndcg_at_1000 value: 69.651 - type: ndcg_at_3 value: 61.105 - type: ndcg_at_5 value: 63.806 - type: precision_at_1 value: 53.319 - type: precision_at_10 value: 8.145 - type: precision_at_100 value: 0.9530000000000001 - type: precision_at_1000 value: 0.099 - type: precision_at_3 value: 22.234 - type: precision_at_5 value: 14.668000000000001 - type: recall_at_1 value: 53.266999999999996 - type: recall_at_10 value: 80.717 - type: recall_at_100 value: 94.204 - type: recall_at_1000 value: 98.419 - type: recall_at_3 value: 66.359 - type: recall_at_5 value: 72.94500000000001 - task: type: Classification dataset: type: DDSC/dkhate name: MTEB DKHateClassification config: default split: test revision: 59d12749a3c91a186063c7d729ec392fda94681c metrics: - type: accuracy value: 55.89665653495442 - type: ap value: 13.442306681200666 - type: f1 value: 45.52792790494033 - task: type: Classification dataset: type: AI-Sweden/SuperLim name: MTEB DalajClassification config: default split: test revision: 7ebf0b4caa7b2ae39698a889de782c09e6f5ee56 metrics: - type: accuracy value: 49.77477477477478 - type: ap value: 49.891019810950006 - type: f1 value: 49.271004191082156 - task: type: Classification dataset: type: danish_political_comments name: MTEB DanishPoliticalCommentsClassification config: default split: train revision: edbb03726c04a0efab14fc8c3b8b79e4d420e5a1 metrics: - type: accuracy value: 28.334721065778517 - type: f1 value: 25.604541019064698 - task: type: Retrieval dataset: type: C-MTEB/DuRetrieval name: MTEB DuRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 21.575 - type: map_at_10 value: 65.302 - type: map_at_100 value: 68.85 - type: map_at_1000 value: 68.94200000000001 - type: map_at_3 value: 44.824000000000005 - type: map_at_5 value: 56.303000000000004 - type: mrr_at_1 value: 77.9 - type: mrr_at_10 value: 84.612 - type: mrr_at_100 value: 84.774 - type: mrr_at_1000 value: 84.78099999999999 - type: mrr_at_3 value: 84.05 - type: mrr_at_5 value: 84.42699999999999 - type: ndcg_at_1 value: 77.9 - type: ndcg_at_10 value: 75.247 - type: ndcg_at_100 value: 80.252 - type: ndcg_at_1000 value: 81.21000000000001 - type: ndcg_at_3 value: 73.664 - type: ndcg_at_5 value: 72.36200000000001 - type: precision_at_1 value: 77.9 - type: precision_at_10 value: 36.875 - type: precision_at_100 value: 4.607 - type: precision_at_1000 value: 0.483 - type: precision_at_3 value: 66.567 - type: precision_at_5 value: 55.97 - type: recall_at_1 value: 21.575 - type: recall_at_10 value: 77.268 - type: recall_at_100 value: 92.706 - type: recall_at_1000 value: 97.721 - type: recall_at_3 value: 48.42 - type: recall_at_5 value: 62.92 - task: type: Retrieval dataset: type: C-MTEB/EcomRetrieval name: MTEB EcomRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 41.199999999999996 - type: map_at_10 value: 52.12 - type: map_at_100 value: 52.878 - type: map_at_1000 value: 52.898 - type: map_at_3 value: 49.6 - type: map_at_5 value: 51.23 - type: mrr_at_1 value: 41.199999999999996 - type: mrr_at_10 value: 52.12 - type: mrr_at_100 value: 52.878 - type: mrr_at_1000 value: 52.898 - type: mrr_at_3 value: 49.6 - type: mrr_at_5 value: 51.23 - type: ndcg_at_1 value: 41.199999999999996 - type: ndcg_at_10 value: 57.321 - type: ndcg_at_100 value: 61.019 - type: ndcg_at_1000 value: 61.638000000000005 - type: ndcg_at_3 value: 52.20399999999999 - type: ndcg_at_5 value: 55.177 - type: precision_at_1 value: 41.199999999999996 - type: precision_at_10 value: 7.359999999999999 - type: precision_at_100 value: 0.909 - type: precision_at_1000 value: 0.096 - type: precision_at_3 value: 19.900000000000002 - type: precision_at_5 value: 13.4 - type: recall_at_1 value: 41.199999999999996 - type: recall_at_10 value: 73.6 - type: recall_at_100 value: 90.9 - type: recall_at_1000 value: 95.89999999999999 - type: recall_at_3 value: 59.699999999999996 - type: recall_at_5 value: 67.0 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 31.514999999999997 - type: f1 value: 26.58222460337632 - task: type: Classification dataset: type: C-MTEB/IFlyTek-classification name: MTEB IFlyTek config: default split: validation revision: None metrics: - type: accuracy value: 47.00269334359369 - type: f1 value: 35.35096851514498 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 65.1704 - type: ap value: 59.97217670850408 - type: f1 value: 64.92509757731281 - task: type: Classification dataset: type: C-MTEB/JDReview-classification name: MTEB JDReview config: default split: test revision: None metrics: - type: accuracy value: 77.33583489681051 - type: ap value: 39.86267586660359 - type: f1 value: 71.07975139386433 - task: type: STS dataset: type: C-MTEB/LCQMC name: MTEB LCQMC config: default split: test revision: None metrics: - type: cos_sim_pearson value: 68.22943962011342 - type: cos_sim_spearman value: 74.09285052519111 - type: euclidean_pearson value: 72.99465307442854 - type: euclidean_spearman value: 74.09285052519111 - type: manhattan_pearson value: 73.00139084439715 - type: manhattan_spearman value: 74.07472412844967 - task: type: Classification dataset: type: DDSC/lcc name: MTEB LccSentimentClassification config: default split: test revision: de7ba3406ee55ea2cc52a0a41408fa6aede6d3c6 metrics: - type: accuracy value: 42.266666666666666 - type: f1 value: 40.963628523464294 - task: type: Reranking dataset: type: C-MTEB/Mmarco-reranking name: MTEB MMarcoReranking config: default split: dev revision: None metrics: - type: map value: 24.311577701296468 - type: mrr value: 23.545238095238094 - task: type: Retrieval dataset: type: C-MTEB/MMarcoRetrieval name: MTEB MMarcoRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 55.757 - type: map_at_10 value: 64.866 - type: map_at_100 value: 65.398 - type: map_at_1000 value: 65.41900000000001 - type: map_at_3 value: 62.634 - type: map_at_5 value: 63.993 - type: mrr_at_1 value: 57.794000000000004 - type: mrr_at_10 value: 65.661 - type: mrr_at_100 value: 66.137 - type: mrr_at_1000 value: 66.156 - type: mrr_at_3 value: 63.625 - type: mrr_at_5 value: 64.863 - type: ndcg_at_1 value: 57.794000000000004 - type: ndcg_at_10 value: 69.107 - type: ndcg_at_100 value: 71.56700000000001 - type: ndcg_at_1000 value: 72.146 - type: ndcg_at_3 value: 64.756 - type: ndcg_at_5 value: 67.094 - type: precision_at_1 value: 57.794000000000004 - type: precision_at_10 value: 8.656 - type: precision_at_100 value: 0.989 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 24.623 - type: precision_at_5 value: 15.991 - type: recall_at_1 value: 55.757 - type: recall_at_10 value: 81.55799999999999 - type: recall_at_100 value: 92.826 - type: recall_at_1000 value: 97.38900000000001 - type: recall_at_3 value: 69.903 - type: recall_at_5 value: 75.497 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 81.20611035111718 - type: f1 value: 80.7763576575655 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (de) config: de split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 57.22175260636799 - 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