--- language: - multilingual - af - am - ar - as - az - be - bg - bn - br - bs - ca - cs - cy - da - de - el - en - eo - es - et - eu - fa - fi - fr - fy - ga - gd - gl - gu - ha - he - hi - hr - hu - hy - id - is - it - ja - jv - ka - kk - km - kn - ko - ku - ky - la - lo - lt - lv - mg - mk - ml - mn - mr - ms - my - ne - nl - 'no' - om - or - pa - pl - ps - pt - ro - ru - sa - sd - si - sk - sl - so - sq - sr - su - sv - sw - ta - te - th - tl - tr - ug - uk - ur - uz - vi - xh - yi - zh license: mit tags: - mteb - Sentence Transformers - sentence-similarity - sentence-transformers - mlx model-index: - name: multilingual-e5-small results: - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (en) type: mteb/amazon_counterfactual config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 73.79104477611939 - type: ap value: 36.9996434842022 - type: f1 value: 67.95453679103099 - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (de) type: mteb/amazon_counterfactual config: de split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 71.64882226980728 - type: ap value: 82.11942130026586 - type: f1 value: 69.87963421606715 - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (en-ext) type: mteb/amazon_counterfactual config: en-ext split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 75.8095952023988 - type: ap value: 24.46869495579561 - type: f1 value: 63.00108480037597 - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (ja) type: mteb/amazon_counterfactual config: ja split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 64.186295503212 - type: ap value: 15.496804690197042 - type: f1 value: 52.07153895475031 - task: type: Classification dataset: name: MTEB AmazonPolarityClassification type: mteb/amazon_polarity config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 88.699325 - type: ap value: 85.27039559917269 - type: f1 value: 88.65556295032513 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (en) type: mteb/amazon_reviews_multi config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 44.69799999999999 - type: f1 value: 43.73187348654165 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (de) type: mteb/amazon_reviews_multi config: de split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 40.245999999999995 - type: f1 value: 39.3863530637684 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (es) type: mteb/amazon_reviews_multi config: es split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 40.394 - type: f1 value: 39.301223469483446 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (fr) type: mteb/amazon_reviews_multi config: fr split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 38.864 - type: f1 value: 37.97974261868003 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (ja) type: mteb/amazon_reviews_multi config: ja split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 37.682 - type: f1 value: 37.07399369768313 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (zh) type: mteb/amazon_reviews_multi config: zh split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 37.504 - type: f1 value: 36.62317273874278 - task: type: Retrieval dataset: name: MTEB ArguAna type: arguana config: default split: test revision: None metrics: - type: map_at_1 value: 19.061 - type: map_at_10 value: 31.703 - type: map_at_100 value: 32.967 - type: map_at_1000 value: 33.001000000000005 - type: map_at_3 value: 27.466 - type: map_at_5 value: 29.564 - type: mrr_at_1 value: 19.559 - type: mrr_at_10 value: 31.874999999999996 - type: mrr_at_100 value: 33.146 - type: mrr_at_1000 value: 33.18 - type: mrr_at_3 value: 27.667 - type: mrr_at_5 value: 29.74 - type: ndcg_at_1 value: 19.061 - type: ndcg_at_10 value: 39.062999999999995 - type: ndcg_at_100 value: 45.184000000000005 - type: ndcg_at_1000 value: 46.115 - type: ndcg_at_3 value: 30.203000000000003 - type: ndcg_at_5 value: 33.953 - type: precision_at_1 value: 19.061 - type: precision_at_10 value: 6.279999999999999 - type: precision_at_100 value: 0.9129999999999999 - type: precision_at_1000 value: 0.099 - type: precision_at_3 value: 12.706999999999999 - type: precision_at_5 value: 9.431000000000001 - type: recall_at_1 value: 19.061 - type: recall_at_10 value: 62.802 - type: recall_at_100 value: 91.323 - type: recall_at_1000 value: 98.72 - type: recall_at_3 value: 38.122 - type: recall_at_5 value: 47.155 - task: type: Clustering dataset: name: MTEB ArxivClusteringP2P type: mteb/arxiv-clustering-p2p config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 39.22266660528253 - task: type: Clustering dataset: name: MTEB ArxivClusteringS2S type: mteb/arxiv-clustering-s2s config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 30.79980849482483 - task: type: Reranking dataset: name: MTEB AskUbuntuDupQuestions type: mteb/askubuntudupquestions-reranking config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 57.8790068352054 - type: mrr value: 71.78791276436706 - task: type: STS dataset: name: MTEB BIOSSES type: mteb/biosses-sts config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 82.36328364043163 - type: cos_sim_spearman value: 82.26211536195868 - type: euclidean_pearson value: 80.3183865039173 - type: euclidean_spearman value: 79.88495276296132 - type: manhattan_pearson value: 80.14484480692127 - type: manhattan_spearman value: 80.39279565980743 - task: type: BitextMining dataset: name: MTEB BUCC (de-en) type: mteb/bucc-bitext-mining config: de-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 98.0375782881002 - type: f1 value: 97.86012526096033 - type: precision value: 97.77139874739039 - type: recall value: 98.0375782881002 - task: type: BitextMining dataset: name: MTEB BUCC (fr-en) type: mteb/bucc-bitext-mining config: fr-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 93.35241030156286 - type: f1 value: 92.66050333846944 - type: precision value: 92.3306919069631 - type: recall value: 93.35241030156286 - task: type: BitextMining dataset: name: MTEB BUCC (ru-en) type: mteb/bucc-bitext-mining config: ru-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 94.0699688257707 - type: f1 value: 93.50236693222492 - type: precision value: 93.22791825424315 - type: recall value: 94.0699688257707 - task: type: BitextMining dataset: name: MTEB BUCC (zh-en) type: mteb/bucc-bitext-mining config: zh-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 89.25750394944708 - type: f1 value: 88.79234684921889 - type: precision value: 88.57293312269616 - type: recall value: 89.25750394944708 - task: type: Classification dataset: name: MTEB Banking77Classification type: mteb/banking77 config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 79.41558441558442 - type: f1 value: 79.25886487487219 - task: type: Clustering dataset: name: MTEB BiorxivClusteringP2P type: mteb/biorxiv-clustering-p2p config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 35.747820820329736 - task: type: Clustering dataset: name: MTEB BiorxivClusteringS2S type: mteb/biorxiv-clustering-s2s config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 27.045143830596146 - task: type: Retrieval dataset: name: MTEB CQADupstackRetrieval type: BeIR/cqadupstack config: default split: test revision: None metrics: - type: map_at_1 value: 24.252999999999997 - type: map_at_10 value: 31.655916666666666 - type: map_at_100 value: 32.680749999999996 - type: map_at_1000 value: 32.79483333333334 - type: map_at_3 value: 29.43691666666666 - type: map_at_5 value: 30.717416666666665 - type: mrr_at_1 value: 28.602750000000004 - type: mrr_at_10 value: 35.56875 - type: mrr_at_100 value: 36.3595 - type: mrr_at_1000 value: 36.427749999999996 - type: mrr_at_3 value: 33.586166666666664 - type: mrr_at_5 value: 34.73641666666666 - type: ndcg_at_1 value: 28.602750000000004 - type: ndcg_at_10 value: 36.06933333333334 - type: ndcg_at_100 value: 40.70141666666667 - type: ndcg_at_1000 value: 43.24341666666667 - type: ndcg_at_3 value: 32.307916666666664 - type: ndcg_at_5 value: 34.129999999999995 - type: precision_at_1 value: 28.602750000000004 - type: precision_at_10 value: 6.097666666666667 - type: precision_at_100 value: 0.9809166666666668 - type: precision_at_1000 value: 0.13766666666666663 - type: precision_at_3 value: 14.628166666666667 - type: precision_at_5 value: 10.266916666666667 - type: recall_at_1 value: 24.252999999999997 - type: recall_at_10 value: 45.31916666666667 - type: recall_at_100 value: 66.03575000000001 - type: recall_at_1000 value: 83.94708333333334 - type: recall_at_3 value: 34.71941666666666 - type: recall_at_5 value: 39.46358333333333 - task: type: Retrieval dataset: name: MTEB ClimateFEVER type: climate-fever config: default split: test revision: None metrics: - type: map_at_1 value: 9.024000000000001 - type: map_at_10 value: 15.644 - type: map_at_100 value: 17.154 - type: map_at_1000 value: 17.345 - type: map_at_3 value: 13.028 - type: map_at_5 value: 14.251 - type: mrr_at_1 value: 19.674 - type: mrr_at_10 value: 29.826999999999998 - type: mrr_at_100 value: 30.935000000000002 - type: mrr_at_1000 value: 30.987 - type: mrr_at_3 value: 26.645000000000003 - type: mrr_at_5 value: 28.29 - type: ndcg_at_1 value: 19.674 - type: ndcg_at_10 value: 22.545 - type: ndcg_at_100 value: 29.207 - type: ndcg_at_1000 value: 32.912 - type: ndcg_at_3 value: 17.952 - type: ndcg_at_5 value: 19.363 - type: precision_at_1 value: 19.674 - type: precision_at_10 value: 7.212000000000001 - type: precision_at_100 value: 1.435 - type: precision_at_1000 value: 0.212 - type: precision_at_3 value: 13.507 - type: precision_at_5 value: 10.397 - type: recall_at_1 value: 9.024000000000001 - type: recall_at_10 value: 28.077999999999996 - type: recall_at_100 value: 51.403 - type: recall_at_1000 value: 72.406 - type: recall_at_3 value: 16.768 - type: recall_at_5 value: 20.737 - task: type: Retrieval dataset: name: MTEB DBPedia type: dbpedia-entity config: default split: test revision: None metrics: - type: map_at_1 value: 8.012 - type: map_at_10 value: 17.138 - type: map_at_100 value: 24.146 - type: map_at_1000 value: 25.622 - type: map_at_3 value: 12.552 - type: map_at_5 value: 14.435 - type: mrr_at_1 value: 62.25000000000001 - type: mrr_at_10 value: 71.186 - type: mrr_at_100 value: 71.504 - type: mrr_at_1000 value: 71.514 - type: mrr_at_3 value: 69.333 - type: mrr_at_5 value: 70.408 - type: ndcg_at_1 value: 49.75 - type: ndcg_at_10 value: 37.76 - type: ndcg_at_100 value: 42.071 - type: ndcg_at_1000 value: 49.309 - type: ndcg_at_3 value: 41.644 - type: ndcg_at_5 value: 39.812999999999995 - type: precision_at_1 value: 62.25000000000001 - type: precision_at_10 value: 30.15 - type: precision_at_100 value: 9.753 - type: precision_at_1000 value: 1.9189999999999998 - type: precision_at_3 value: 45.667 - type: precision_at_5 value: 39.15 - type: recall_at_1 value: 8.012 - type: recall_at_10 value: 22.599 - type: recall_at_100 value: 48.068 - type: recall_at_1000 value: 71.328 - type: recall_at_3 value: 14.043 - type: recall_at_5 value: 17.124 - task: type: Classification dataset: name: MTEB EmotionClassification type: mteb/emotion config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 42.455 - type: f1 value: 37.59462649781862 - task: type: Retrieval dataset: name: MTEB FEVER type: fever config: default split: test revision: None metrics: - type: map_at_1 value: 58.092 - type: map_at_10 value: 69.586 - type: map_at_100 value: 69.968 - type: map_at_1000 value: 69.982 - type: map_at_3 value: 67.48100000000001 - type: map_at_5 value: 68.915 - type: mrr_at_1 value: 62.166 - type: mrr_at_10 value: 73.588 - type: mrr_at_100 value: 73.86399999999999 - type: mrr_at_1000 value: 73.868 - type: mrr_at_3 value: 71.6 - type: mrr_at_5 value: 72.99 - type: ndcg_at_1 value: 62.166 - type: ndcg_at_10 value: 75.27199999999999 - type: ndcg_at_100 value: 76.816 - type: ndcg_at_1000 value: 77.09700000000001 - type: ndcg_at_3 value: 71.36 - type: ndcg_at_5 value: 73.785 - type: precision_at_1 value: 62.166 - type: precision_at_10 value: 9.716 - type: precision_at_100 value: 1.065 - type: precision_at_1000 value: 0.11 - type: precision_at_3 value: 28.278 - type: precision_at_5 value: 18.343999999999998 - type: recall_at_1 value: 58.092 - type: recall_at_10 value: 88.73400000000001 - type: recall_at_100 value: 95.195 - type: recall_at_1000 value: 97.04599999999999 - type: recall_at_3 value: 78.45 - type: recall_at_5 value: 84.316 - task: type: Retrieval dataset: name: MTEB FiQA2018 type: fiqa config: default split: test revision: None metrics: - type: map_at_1 value: 16.649 - type: map_at_10 value: 26.457000000000004 - type: map_at_100 value: 28.169 - type: map_at_1000 value: 28.352 - type: map_at_3 value: 23.305 - type: map_at_5 value: 25.169000000000004 - type: mrr_at_1 value: 32.407000000000004 - type: mrr_at_10 value: 40.922 - type: mrr_at_100 value: 41.931000000000004 - type: mrr_at_1000 value: 41.983 - type: mrr_at_3 value: 38.786 - type: mrr_at_5 value: 40.205999999999996 - type: ndcg_at_1 value: 32.407000000000004 - type: ndcg_at_10 value: 33.314 - type: ndcg_at_100 value: 40.312 - type: ndcg_at_1000 value: 43.685 - type: ndcg_at_3 value: 30.391000000000002 - type: ndcg_at_5 value: 31.525 - type: precision_at_1 value: 32.407000000000004 - type: precision_at_10 value: 8.966000000000001 - type: precision_at_100 value: 1.6019999999999999 - type: precision_at_1000 value: 0.22200000000000003 - type: precision_at_3 value: 20.165 - type: precision_at_5 value: 14.722 - type: recall_at_1 value: 16.649 - type: recall_at_10 value: 39.117000000000004 - type: recall_at_100 value: 65.726 - type: recall_at_1000 value: 85.784 - type: recall_at_3 value: 27.914 - type: recall_at_5 value: 33.289 - task: type: Retrieval dataset: name: MTEB HotpotQA type: hotpotqa config: default split: test revision: None metrics: - type: map_at_1 value: 36.253 - type: map_at_10 value: 56.16799999999999 - type: map_at_100 value: 57.06099999999999 - type: map_at_1000 value: 57.126 - type: map_at_3 value: 52.644999999999996 - type: map_at_5 value: 54.909 - type: mrr_at_1 value: 72.505 - type: mrr_at_10 value: 79.66 - type: mrr_at_100 value: 79.869 - type: mrr_at_1000 value: 79.88 - type: mrr_at_3 value: 78.411 - type: mrr_at_5 value: 79.19800000000001 - type: ndcg_at_1 value: 72.505 - type: ndcg_at_10 value: 65.094 - type: ndcg_at_100 value: 68.219 - type: ndcg_at_1000 value: 69.515 - type: ndcg_at_3 value: 59.99 - type: ndcg_at_5 value: 62.909000000000006 - type: precision_at_1 value: 72.505 - type: precision_at_10 value: 13.749 - type: precision_at_100 value: 1.619 - type: precision_at_1000 value: 0.179 - type: precision_at_3 value: 38.357 - type: precision_at_5 value: 25.313000000000002 - type: recall_at_1 value: 36.253 - type: recall_at_10 value: 68.744 - type: recall_at_100 value: 80.925 - type: recall_at_1000 value: 89.534 - type: recall_at_3 value: 57.535000000000004 - type: recall_at_5 value: 63.282000000000004 - task: type: Classification dataset: name: MTEB ImdbClassification type: mteb/imdb config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 80.82239999999999 - type: ap value: 75.65895781725314 - type: f1 value: 80.75880969095746 - task: type: Retrieval dataset: name: MTEB MSMARCO type: msmarco config: default split: dev revision: None metrics: - type: map_at_1 value: 21.624 - type: map_at_10 value: 34.075 - type: map_at_100 value: 35.229 - type: map_at_1000 value: 35.276999999999994 - type: map_at_3 value: 30.245 - type: map_at_5 value: 32.42 - type: mrr_at_1 value: 22.264 - type: mrr_at_10 value: 34.638000000000005 - type: mrr_at_100 value: 35.744 - type: mrr_at_1000 value: 35.787 - type: mrr_at_3 value: 30.891000000000002 - type: mrr_at_5 value: 33.042 - type: ndcg_at_1 value: 22.264 - type: ndcg_at_10 value: 40.991 - type: ndcg_at_100 value: 46.563 - type: ndcg_at_1000 value: 47.743 - type: ndcg_at_3 value: 33.198 - type: ndcg_at_5 value: 37.069 - type: precision_at_1 value: 22.264 - type: precision_at_10 value: 6.5089999999999995 - type: precision_at_100 value: 0.9299999999999999 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 14.216999999999999 - type: precision_at_5 value: 10.487 - type: recall_at_1 value: 21.624 - type: recall_at_10 value: 62.303 - type: recall_at_100 value: 88.124 - type: recall_at_1000 value: 97.08 - type: recall_at_3 value: 41.099999999999994 - type: recall_at_5 value: 50.381 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (en) type: mteb/mtop_domain config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 91.06703146374831 - type: f1 value: 90.86867815863172 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (de) type: mteb/mtop_domain config: de split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 87.46970977740209 - type: f1 value: 86.36832872036588 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (es) type: mteb/mtop_domain config: es split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 89.26951300867245 - type: f1 value: 88.93561193959502 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (fr) type: mteb/mtop_domain config: fr split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 84.22799874725963 - type: f1 value: 84.30490069236556 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (hi) type: mteb/mtop_domain config: hi split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 86.02007888131948 - type: f1 value: 85.39376041027991 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (th) type: mteb/mtop_domain config: th split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 85.34900542495481 - type: f1 value: 85.39859673336713 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (en) type: mteb/mtop_intent config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 71.078431372549 - type: f1 value: 53.45071102002276 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (de) type: mteb/mtop_intent config: de split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 65.85798816568047 - type: f1 value: 46.53112748993529 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (es) type: mteb/mtop_intent config: es split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 67.96864576384256 - type: f1 value: 45.966703022829506 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (fr) type: mteb/mtop_intent config: fr split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 61.31537738803633 - type: f1 value: 45.52601712835461 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (hi) type: mteb/mtop_intent config: hi split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 66.29616349946218 - type: f1 value: 47.24166485726613 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (th) type: mteb/mtop_intent config: th split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 67.51537070524412 - type: f1 value: 49.463476319014276 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (af) type: mteb/amazon_massive_intent config: af split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 57.06792199058508 - type: f1 value: 54.094921857502285 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (am) type: mteb/amazon_massive_intent config: am split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 51.960322797579025 - type: f1 value: 48.547371223370945 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (ar) type: mteb/amazon_massive_intent config: ar split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 54.425016812373904 - type: f1 value: 50.47069202054312 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (az) type: mteb/amazon_massive_intent config: az split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 59.798251513113655 - type: f1 value: 57.05013069086648 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (bn) type: mteb/amazon_massive_intent config: bn split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 59.37794216543376 - type: f1 value: 56.3607992649805 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (cy) type: mteb/amazon_massive_intent config: cy split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 46.56018829858777 - type: f1 value: 43.87319715715134 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (da) type: mteb/amazon_massive_intent config: da split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 62.9724277067922 - type: f1 value: 59.36480066245562 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (de) type: mteb/amazon_massive_intent config: de split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 62.72696704774715 - type: f1 value: 59.143595966615855 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (el) type: mteb/amazon_massive_intent config: el split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 61.5971755211836 - type: f1 value: 59.169445724946726 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (en) type: mteb/amazon_massive_intent config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 70.29589778076665 - type: f1 value: 67.7577001808977 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (es) type: mteb/amazon_massive_intent config: es split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 66.31136516476126 - type: f1 value: 64.52032955983242 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (fa) type: mteb/amazon_massive_intent config: fa split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 65.54472091459314 - type: f1 value: 61.47903120066317 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (fi) type: mteb/amazon_massive_intent config: fi split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 61.45595158036314 - type: f1 value: 58.0891846024637 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (fr) type: mteb/amazon_massive_intent config: fr split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 65.47074646940149 - type: f1 value: 62.84830858877575 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (he) type: mteb/amazon_massive_intent config: he split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 58.046402151983855 - type: f1 value: 55.269074430533195 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (hi) type: mteb/amazon_massive_intent config: hi split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 64.06523201075991 - type: f1 value: 61.35339643021369 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (hu) type: mteb/amazon_massive_intent config: hu split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 60.954942837928726 - type: f1 value: 57.07035922704846 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (hy) type: mteb/amazon_massive_intent config: hy split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 57.404169468728995 - type: f1 value: 53.94259011839138 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (id) type: mteb/amazon_massive_intent config: id split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 64.16610625420309 - type: f1 value: 61.337103431499365 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (is) type: mteb/amazon_massive_intent config: is split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 52.262945527908535 - type: f1 value: 49.7610691598921 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (it) type: mteb/amazon_massive_intent config: it split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 65.54472091459314 - type: f1 value: 63.469099018440154 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (ja) type: mteb/amazon_massive_intent config: ja split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 68.22797579018157 - type: f1 value: 64.89098471083001 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (jv) type: mteb/amazon_massive_intent config: jv split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 50.847343644922674 - type: f1 value: 47.8536963168393 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (ka) type: mteb/amazon_massive_intent config: ka split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 48.45326160053799 - type: f1 value: 46.370078045805556 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (km) type: mteb/amazon_massive_intent config: km split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 42.83120376597175 - type: f1 value: 39.68948521599982 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (kn) type: mteb/amazon_massive_intent config: kn split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 57.5084061869536 - type: f1 value: 53.961876160401545 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (ko) type: mteb/amazon_massive_intent config: ko split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 63.7895090786819 - type: f1 value: 61.134223684676 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (lv) type: mteb/amazon_massive_intent config: lv split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 54.98991257565569 - type: f1 value: 52.579862862826296 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (ml) type: mteb/amazon_massive_intent config: ml split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 61.90316072629456 - type: f1 value: 58.203024538290336 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (mn) type: mteb/amazon_massive_intent config: mn split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 57.09818426361802 - type: f1 value: 54.22718458445455 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (ms) type: mteb/amazon_massive_intent config: ms split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 58.991257565568255 - type: f1 value: 55.84892781767421 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (my) type: mteb/amazon_massive_intent config: my split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 55.901143241425686 - type: f1 value: 52.25264332199797 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (nb) type: mteb/amazon_massive_intent config: nb split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 61.96368527236047 - type: f1 value: 58.927243876153454 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (nl) type: mteb/amazon_massive_intent config: nl split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 65.64223268325489 - type: f1 value: 62.340453718379706 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (pl) type: mteb/amazon_massive_intent config: pl split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 64.52589105581708 - type: f1 value: 61.661113187022174 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (pt) type: mteb/amazon_massive_intent config: pt split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 66.84599865501009 - type: f1 value: 64.59342572873005 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (ro) type: mteb/amazon_massive_intent config: ro split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 60.81035642232684 - type: f1 value: 57.5169089806797 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (ru) type: mteb/amazon_massive_intent config: ru split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 65.75991930060525 - type: f1 value: 62.89531115787938 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (sl) type: mteb/amazon_massive_intent config: sl split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 56.51647612642906 - type: f1 value: 54.33154780100043 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (sq) type: mteb/amazon_massive_intent config: sq split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 57.985877605917956 - type: f1 value: 54.46187524463802 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (sv) type: mteb/amazon_massive_intent config: sv split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 65.03026227303296 - type: f1 value: 62.34377392877748 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (sw) type: mteb/amazon_massive_intent config: sw split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 53.567585743106925 - type: f1 value: 50.73770655983206 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (ta) type: mteb/amazon_massive_intent config: ta split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 57.2595830531271 - type: f1 value: 53.657327291708626 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (te) type: mteb/amazon_massive_intent config: te split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 57.82784129119032 - type: f1 value: 54.82518072665301 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (th) type: mteb/amazon_massive_intent config: th split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 64.06859448554137 - type: f1 value: 63.00185280500495 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (tl) type: mteb/amazon_massive_intent config: tl split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 58.91055817081371 - type: f1 value: 55.54116301224262 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (tr) type: mteb/amazon_massive_intent config: tr split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 63.54404841963686 - type: f1 value: 59.57650946030184 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (ur) type: mteb/amazon_massive_intent config: ur split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 59.27706792199059 - type: f1 value: 56.50010066083435 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (vi) type: mteb/amazon_massive_intent config: vi split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 64.0719569603228 - type: f1 value: 61.817075925647956 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (zh-CN) type: mteb/amazon_massive_intent config: zh-CN split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 68.23806321452591 - type: f1 value: 65.24917026029749 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (zh-TW) type: mteb/amazon_massive_intent config: zh-TW split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 62.53530598520511 - type: f1 value: 61.71131132295768 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (af) type: mteb/amazon_massive_scenario config: af split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 63.04303967720243 - type: f1 value: 60.3950085685985 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (am) type: mteb/amazon_massive_scenario config: am split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 56.83591123066578 - type: f1 value: 54.95059828830849 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (ar) type: mteb/amazon_massive_scenario config: ar split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 59.62340282447881 - type: f1 value: 59.525159996498225 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (az) type: mteb/amazon_massive_scenario config: az split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 60.85406859448555 - type: f1 value: 59.129299095681276 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (bn) type: mteb/amazon_massive_scenario config: bn split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 62.76731674512441 - type: f1 value: 61.159560612627715 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (cy) type: mteb/amazon_massive_scenario config: cy split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 50.181573638197705 - type: f1 value: 46.98422176289957 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (da) type: mteb/amazon_massive_scenario config: da split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 68.92737054472092 - type: f1 value: 67.69135611952979 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (de) type: mteb/amazon_massive_scenario config: de split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 69.18964357767318 - type: f1 value: 68.46106138186214 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (el) type: mteb/amazon_massive_scenario config: el split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 67.0712844653665 - type: f1 value: 66.75545422473901 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (en) type: mteb/amazon_massive_scenario config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 74.4754539340955 - type: f1 value: 74.38427146553252 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (es) type: mteb/amazon_massive_scenario config: es split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 69.82515131136518 - type: f1 value: 69.63516462173847 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (fa) type: mteb/amazon_massive_scenario config: fa split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 68.70880968392737 - type: f1 value: 67.45420662567926 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (fi) type: mteb/amazon_massive_scenario config: fi split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 65.95494283792871 - type: f1 value: 65.06191009049222 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (fr) type: mteb/amazon_massive_scenario config: fr split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 68.75924680564896 - type: f1 value: 68.30833379585945 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (he) type: mteb/amazon_massive_scenario config: he split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 63.806321452589096 - type: f1 value: 63.273048243765054 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (hi) type: mteb/amazon_massive_scenario config: hi split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 67.68997982515133 - type: f1 value: 66.54703855381324 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (hu) type: mteb/amazon_massive_scenario config: hu split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 66.46940147948891 - type: f1 value: 65.91017343463396 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (hy) type: mteb/amazon_massive_scenario config: hy split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 59.49899125756556 - type: f1 value: 57.90333469917769 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (id) type: mteb/amazon_massive_scenario config: id split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 67.9219905850706 - type: f1 value: 67.23169403762938 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (is) type: mteb/amazon_massive_scenario config: is split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 56.486213853396094 - type: f1 value: 54.85282355583758 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (it) type: mteb/amazon_massive_scenario config: it split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 69.04169468728985 - type: f1 value: 68.83833333320462 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (ja) type: mteb/amazon_massive_scenario config: ja split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 73.88702084734365 - type: f1 value: 74.04474735232299 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (jv) type: mteb/amazon_massive_scenario config: jv split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 56.63416274377943 - type: f1 value: 55.11332211687954 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (ka) type: mteb/amazon_massive_scenario config: ka split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 52.23604572965702 - type: f1 value: 50.86529813991055 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (km) type: mteb/amazon_massive_scenario config: km split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 46.62407531943511 - type: f1 value: 43.63485467164535 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (kn) type: mteb/amazon_massive_scenario config: kn split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 59.15601882985878 - type: f1 value: 57.522837510959924 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (ko) type: mteb/amazon_massive_scenario config: ko split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 69.84532616005382 - type: f1 value: 69.60021127179697 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (lv) type: mteb/amazon_massive_scenario config: lv split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 56.65770006724949 - type: f1 value: 55.84219135523227 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (ml) type: mteb/amazon_massive_scenario config: ml split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 66.53665097511768 - type: f1 value: 65.09087787792639 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (mn) type: mteb/amazon_massive_scenario config: mn split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 59.31405514458642 - type: f1 value: 58.06135303831491 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (ms) type: mteb/amazon_massive_scenario config: ms split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 64.88231338264964 - type: f1 value: 62.751099407787926 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (my) type: mteb/amazon_massive_scenario config: my split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 58.86012104909213 - type: f1 value: 56.29118323058282 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (nb) type: mteb/amazon_massive_scenario config: nb split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 67.37390719569602 - type: f1 value: 66.27922244885102 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (nl) type: mteb/amazon_massive_scenario config: nl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 70.8675184936113 - type: f1 value: 70.22146529932019 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (pl) type: mteb/amazon_massive_scenario config: pl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 68.2212508406187 - type: f1 value: 67.77454802056282 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (pt) type: mteb/amazon_massive_scenario config: pt split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 68.18090114324143 - type: f1 value: 68.03737625431621 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (ro) type: mteb/amazon_massive_scenario config: ro split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 64.65030262273034 - type: f1 value: 63.792945486912856 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (ru) type: mteb/amazon_massive_scenario config: ru split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 69.48217888365838 - type: f1 value: 69.96028997292197 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (sl) type: mteb/amazon_massive_scenario config: sl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 60.17821116341627 - type: f1 value: 59.3935969827171 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (sq) type: mteb/amazon_massive_scenario config: sq split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 62.86146603900471 - type: f1 value: 60.133692735032376 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (sv) type: mteb/amazon_massive_scenario config: sv split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 70.89441829186282 - type: f1 value: 70.03064076194089 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (sw) type: mteb/amazon_massive_scenario config: sw split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 58.15063887020847 - type: f1 value: 56.23326278499678 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (ta) type: mteb/amazon_massive_scenario config: ta split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 59.43846671149966 - type: f1 value: 57.70440450281974 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (te) type: mteb/amazon_massive_scenario config: te split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 60.8507061197041 - type: f1 value: 59.22916396061171 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (th) type: mteb/amazon_massive_scenario config: th split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 70.65568258238063 - type: f1 value: 69.90736239440633 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (tl) type: mteb/amazon_massive_scenario config: tl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 60.8843308675185 - type: f1 value: 59.30332663713599 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (tr) type: mteb/amazon_massive_scenario config: tr split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 68.05312710154674 - type: f1 value: 67.44024062594775 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (ur) type: mteb/amazon_massive_scenario config: ur split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 62.111634162743776 - type: f1 value: 60.89083013084519 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (vi) type: mteb/amazon_massive_scenario config: vi split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 67.44115669132482 - type: f1 value: 67.92227541674552 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (zh-CN) type: mteb/amazon_massive_scenario config: zh-CN split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 74.4687289845326 - type: f1 value: 74.16376793486025 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (zh-TW) type: mteb/amazon_massive_scenario config: zh-TW split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 68.31876260928043 - type: f1 value: 68.5246745215607 - task: type: Clustering dataset: name: MTEB MedrxivClusteringP2P type: mteb/medrxiv-clustering-p2p config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 30.90431696479766 - task: type: Clustering dataset: name: MTEB MedrxivClusteringS2S type: mteb/medrxiv-clustering-s2s config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 27.259158476693774 - task: type: Reranking dataset: name: MTEB MindSmallReranking type: mteb/mind_small config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 30.28445330838555 - type: mrr value: 31.15758529581164 - task: type: Retrieval dataset: name: MTEB NFCorpus type: nfcorpus config: default split: test revision: None metrics: - type: map_at_1 value: 5.353 - type: map_at_10 value: 11.565 - type: map_at_100 value: 14.097000000000001 - type: map_at_1000 value: 15.354999999999999 - type: map_at_3 value: 8.749 - type: map_at_5 value: 9.974 - type: mrr_at_1 value: 42.105 - type: mrr_at_10 value: 50.589 - type: mrr_at_100 value: 51.187000000000005 - type: mrr_at_1000 value: 51.233 - type: mrr_at_3 value: 48.246 - type: mrr_at_5 value: 49.546 - type: ndcg_at_1 value: 40.402 - type: ndcg_at_10 value: 31.009999999999998 - type: ndcg_at_100 value: 28.026 - type: ndcg_at_1000 value: 36.905 - type: ndcg_at_3 value: 35.983 - type: ndcg_at_5 value: 33.764 - type: precision_at_1 value: 42.105 - type: precision_at_10 value: 22.786 - type: precision_at_100 value: 6.916 - type: precision_at_1000 value: 1.981 - type: precision_at_3 value: 33.333 - type: precision_at_5 value: 28.731 - type: recall_at_1 value: 5.353 - type: recall_at_10 value: 15.039 - type: recall_at_100 value: 27.348 - type: recall_at_1000 value: 59.453 - type: recall_at_3 value: 9.792 - type: recall_at_5 value: 11.882 - task: type: Retrieval dataset: name: MTEB NQ type: nq config: default split: test revision: None metrics: - type: map_at_1 value: 33.852 - type: map_at_10 value: 48.924 - type: map_at_100 value: 49.854 - type: map_at_1000 value: 49.886 - type: map_at_3 value: 44.9 - type: map_at_5 value: 47.387 - type: mrr_at_1 value: 38.035999999999994 - type: mrr_at_10 value: 51.644 - type: mrr_at_100 value: 52.339 - type: mrr_at_1000 value: 52.35999999999999 - type: mrr_at_3 value: 48.421 - type: mrr_at_5 value: 50.468999999999994 - type: ndcg_at_1 value: 38.007000000000005 - type: ndcg_at_10 value: 56.293000000000006 - type: ndcg_at_100 value: 60.167 - type: ndcg_at_1000 value: 60.916000000000004 - type: ndcg_at_3 value: 48.903999999999996 - type: ndcg_at_5 value: 52.978 - type: precision_at_1 value: 38.007000000000005 - type: precision_at_10 value: 9.041 - type: precision_at_100 value: 1.1199999999999999 - type: precision_at_1000 value: 0.11900000000000001 - type: precision_at_3 value: 22.084 - type: precision_at_5 value: 15.608 - type: recall_at_1 value: 33.852 - type: recall_at_10 value: 75.893 - type: recall_at_100 value: 92.589 - type: recall_at_1000 value: 98.153 - type: recall_at_3 value: 56.969 - type: recall_at_5 value: 66.283 - task: type: Retrieval dataset: name: MTEB QuoraRetrieval type: quora config: default split: test revision: None metrics: - type: map_at_1 value: 69.174 - type: map_at_10 value: 82.891 - type: map_at_100 value: 83.545 - type: map_at_1000 value: 83.56700000000001 - type: map_at_3 value: 79.944 - type: map_at_5 value: 81.812 - type: mrr_at_1 value: 79.67999999999999 - type: mrr_at_10 value: 86.279 - type: mrr_at_100 value: 86.39 - type: mrr_at_1000 value: 86.392 - type: mrr_at_3 value: 85.21 - type: mrr_at_5 value: 85.92999999999999 - type: ndcg_at_1 value: 79.69000000000001 - type: ndcg_at_10 value: 86.929 - type: ndcg_at_100 value: 88.266 - type: ndcg_at_1000 value: 88.428 - type: ndcg_at_3 value: 83.899 - type: ndcg_at_5 value: 85.56700000000001 - type: precision_at_1 value: 79.69000000000001 - type: precision_at_10 value: 13.161000000000001 - type: precision_at_100 value: 1.513 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 36.603 - type: precision_at_5 value: 24.138 - type: recall_at_1 value: 69.174 - type: recall_at_10 value: 94.529 - type: recall_at_100 value: 99.15 - type: recall_at_1000 value: 99.925 - type: recall_at_3 value: 85.86200000000001 - type: recall_at_5 value: 90.501 - task: type: Clustering dataset: name: MTEB RedditClustering type: mteb/reddit-clustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 39.13064340585255 - task: type: Clustering dataset: name: MTEB RedditClusteringP2P type: mteb/reddit-clustering-p2p config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 58.97884249325877 - task: type: Retrieval dataset: name: MTEB SCIDOCS type: scidocs config: default split: test revision: None metrics: - type: map_at_1 value: 3.4680000000000004 - type: map_at_10 value: 7.865 - type: map_at_100 value: 9.332 - type: map_at_1000 value: 9.587 - type: map_at_3 value: 5.800000000000001 - type: map_at_5 value: 6.8790000000000004 - type: mrr_at_1 value: 17.0 - type: mrr_at_10 value: 25.629 - type: mrr_at_100 value: 26.806 - type: mrr_at_1000 value: 26.889000000000003 - type: mrr_at_3 value: 22.8 - type: mrr_at_5 value: 24.26 - type: ndcg_at_1 value: 17.0 - type: ndcg_at_10 value: 13.895 - type: ndcg_at_100 value: 20.491999999999997 - type: ndcg_at_1000 value: 25.759999999999998 - type: ndcg_at_3 value: 13.347999999999999 - type: ndcg_at_5 value: 11.61 - type: precision_at_1 value: 17.0 - type: precision_at_10 value: 7.090000000000001 - type: precision_at_100 value: 1.669 - type: precision_at_1000 value: 0.294 - type: precision_at_3 value: 12.3 - type: precision_at_5 value: 10.02 - type: recall_at_1 value: 3.4680000000000004 - type: recall_at_10 value: 14.363000000000001 - type: recall_at_100 value: 33.875 - type: recall_at_1000 value: 59.711999999999996 - type: recall_at_3 value: 7.483 - type: recall_at_5 value: 10.173 - task: type: STS dataset: name: MTEB SICK-R type: mteb/sickr-sts config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 83.04084311714061 - type: cos_sim_spearman value: 77.51342467443078 - type: euclidean_pearson value: 80.0321166028479 - type: euclidean_spearman value: 77.29249114733226 - type: manhattan_pearson value: 80.03105964262431 - type: manhattan_spearman value: 77.22373689514794 - task: type: STS dataset: name: MTEB STS12 type: mteb/sts12-sts config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 84.1680158034387 - type: cos_sim_spearman value: 76.55983344071117 - type: euclidean_pearson value: 79.75266678300143 - type: euclidean_spearman value: 75.34516823467025 - type: manhattan_pearson value: 79.75959151517357 - type: manhattan_spearman value: 75.42330344141912 - task: type: STS dataset: name: MTEB STS13 type: mteb/sts13-sts config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 76.48898993209346 - type: cos_sim_spearman value: 76.96954120323366 - type: euclidean_pearson value: 76.94139109279668 - type: euclidean_spearman value: 76.85860283201711 - type: manhattan_pearson value: 76.6944095091912 - type: manhattan_spearman value: 76.61096912972553 - task: type: STS dataset: name: MTEB STS14 type: mteb/sts14-sts config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 77.85082366246944 - type: cos_sim_spearman value: 75.52053350101731 - type: euclidean_pearson value: 77.1165845070926 - type: euclidean_spearman value: 75.31216065884388 - type: manhattan_pearson value: 77.06193941833494 - type: manhattan_spearman value: 75.31003701700112 - task: type: STS dataset: name: MTEB STS15 type: mteb/sts15-sts config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 86.36305246526497 - type: cos_sim_spearman value: 87.11704613927415 - type: euclidean_pearson value: 86.04199125810939 - type: euclidean_spearman value: 86.51117572414263 - type: manhattan_pearson value: 86.0805106816633 - type: manhattan_spearman value: 86.52798366512229 - task: type: STS dataset: name: MTEB STS16 type: mteb/sts16-sts config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 82.18536255599724 - type: cos_sim_spearman value: 83.63377151025418 - type: euclidean_pearson value: 83.24657467993141 - type: euclidean_spearman value: 84.02751481993825 - type: manhattan_pearson value: 83.11941806582371 - type: manhattan_spearman value: 83.84251281019304 - task: type: STS dataset: name: MTEB STS17 (ko-ko) type: mteb/sts17-crosslingual-sts config: ko-ko split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 78.95816528475514 - type: cos_sim_spearman value: 78.86607380120462 - type: euclidean_pearson value: 78.51268699230545 - type: euclidean_spearman value: 79.11649316502229 - type: manhattan_pearson value: 78.32367302808157 - type: manhattan_spearman value: 78.90277699624637 - task: type: STS dataset: name: MTEB STS17 (ar-ar) type: mteb/sts17-crosslingual-sts config: ar-ar split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 72.89126914997624 - type: cos_sim_spearman value: 73.0296921832678 - type: euclidean_pearson value: 71.50385903677738 - type: euclidean_spearman value: 73.13368899716289 - type: manhattan_pearson value: 71.47421463379519 - type: manhattan_spearman value: 73.03383242946575 - task: type: STS dataset: name: MTEB STS17 (en-ar) type: mteb/sts17-crosslingual-sts config: en-ar split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 59.22923684492637 - type: cos_sim_spearman value: 57.41013211368396 - type: euclidean_pearson value: 61.21107388080905 - type: euclidean_spearman value: 60.07620768697254 - type: manhattan_pearson value: 59.60157142786555 - type: manhattan_spearman value: 59.14069604103739 - task: type: STS dataset: name: MTEB STS17 (en-de) type: mteb/sts17-crosslingual-sts config: en-de split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 76.24345978774299 - type: cos_sim_spearman value: 77.24225743830719 - type: euclidean_pearson value: 76.66226095469165 - type: euclidean_spearman value: 77.60708820493146 - type: manhattan_pearson value: 76.05303324760429 - type: manhattan_spearman value: 76.96353149912348 - task: type: STS dataset: name: MTEB STS17 (en-en) type: mteb/sts17-crosslingual-sts config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 85.50879160160852 - type: cos_sim_spearman value: 86.43594662965224 - type: euclidean_pearson value: 86.06846012826577 - type: euclidean_spearman value: 86.02041395794136 - type: manhattan_pearson value: 86.10916255616904 - type: manhattan_spearman value: 86.07346068198953 - task: type: STS dataset: name: MTEB STS17 (en-tr) type: mteb/sts17-crosslingual-sts config: en-tr split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 58.39803698977196 - type: cos_sim_spearman value: 55.96910950423142 - type: euclidean_pearson value: 58.17941175613059 - type: euclidean_spearman value: 55.03019330522745 - type: manhattan_pearson value: 57.333358138183286 - type: manhattan_spearman value: 54.04614023149965 - task: type: STS dataset: name: MTEB STS17 (es-en) type: mteb/sts17-crosslingual-sts config: es-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 70.98304089637197 - type: cos_sim_spearman value: 72.44071656215888 - type: euclidean_pearson value: 72.19224359033983 - type: euclidean_spearman value: 73.89871188913025 - type: manhattan_pearson value: 71.21098311547406 - type: manhattan_spearman value: 72.93405764824821 - task: type: STS dataset: name: MTEB STS17 (es-es) type: mteb/sts17-crosslingual-sts config: es-es split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 85.99792397466308 - type: cos_sim_spearman value: 84.83824377879495 - type: euclidean_pearson value: 85.70043288694438 - type: euclidean_spearman value: 84.70627558703686 - type: manhattan_pearson value: 85.89570850150801 - type: manhattan_spearman value: 84.95806105313007 - task: type: STS dataset: name: MTEB STS17 (fr-en) type: mteb/sts17-crosslingual-sts config: fr-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 72.21850322994712 - type: cos_sim_spearman value: 72.28669398117248 - type: euclidean_pearson value: 73.40082510412948 - type: euclidean_spearman value: 73.0326539281865 - type: manhattan_pearson value: 71.8659633964841 - type: manhattan_spearman value: 71.57817425823303 - task: type: STS dataset: name: MTEB STS17 (it-en) type: mteb/sts17-crosslingual-sts config: it-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 75.80921368595645 - type: cos_sim_spearman value: 77.33209091229315 - type: euclidean_pearson value: 76.53159540154829 - type: euclidean_spearman value: 78.17960842810093 - type: manhattan_pearson value: 76.13530186637601 - type: manhattan_spearman value: 78.00701437666875 - task: type: STS dataset: name: MTEB STS17 (nl-en) type: mteb/sts17-crosslingual-sts config: nl-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 74.74980608267349 - type: cos_sim_spearman value: 75.37597374318821 - type: euclidean_pearson value: 74.90506081911661 - type: euclidean_spearman value: 75.30151613124521 - type: manhattan_pearson value: 74.62642745918002 - type: manhattan_spearman value: 75.18619716592303 - task: type: STS dataset: name: MTEB STS22 (en) type: mteb/sts22-crosslingual-sts config: en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 59.632662289205584 - type: cos_sim_spearman value: 60.938543391610914 - type: euclidean_pearson value: 62.113200529767056 - type: euclidean_spearman value: 61.410312633261164 - type: manhattan_pearson value: 61.75494698945686 - type: manhattan_spearman value: 60.92726195322362 - task: type: STS dataset: name: MTEB STS22 (de) type: mteb/sts22-crosslingual-sts config: de split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 45.283470551557244 - type: cos_sim_spearman value: 53.44833015864201 - type: euclidean_pearson value: 41.17892011120893 - type: euclidean_spearman value: 53.81441383126767 - type: manhattan_pearson value: 41.17482200420659 - type: manhattan_spearman value: 53.82180269276363 - task: type: STS dataset: name: MTEB STS22 (es) type: mteb/sts22-crosslingual-sts config: es split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 60.5069165306236 - type: cos_sim_spearman value: 66.87803259033826 - type: euclidean_pearson value: 63.5428979418236 - type: euclidean_spearman value: 66.9293576586897 - type: manhattan_pearson value: 63.59789526178922 - type: manhattan_spearman value: 66.86555009875066 - task: type: STS dataset: name: MTEB STS22 (pl) type: mteb/sts22-crosslingual-sts config: pl split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 28.23026196280264 - type: cos_sim_spearman value: 35.79397812652861 - type: euclidean_pearson value: 17.828102102767353 - type: euclidean_spearman value: 35.721501145568894 - type: manhattan_pearson value: 17.77134274219677 - type: manhattan_spearman value: 35.98107902846267 - task: type: STS dataset: name: MTEB STS22 (tr) type: mteb/sts22-crosslingual-sts config: tr split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 56.51946541393812 - type: cos_sim_spearman value: 63.714686006214485 - type: euclidean_pearson value: 58.32104651305898 - type: euclidean_spearman value: 62.237110895702216 - type: manhattan_pearson value: 58.579416468759185 - type: manhattan_spearman value: 62.459738981727 - task: type: STS dataset: name: MTEB STS22 (ar) type: mteb/sts22-crosslingual-sts config: ar split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 48.76009839569795 - type: cos_sim_spearman value: 56.65188431953149 - type: euclidean_pearson value: 50.997682160915595 - type: euclidean_spearman value: 55.99910008818135 - type: manhattan_pearson value: 50.76220659606342 - type: manhattan_spearman value: 55.517347595391456 - task: type: STS dataset: name: MTEB STS22 (ru) type: mteb/sts22-crosslingual-sts config: ru split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 51.232731157702425 - type: cos_sim_spearman value: 59.89531877658345 - type: euclidean_pearson value: 49.937914570348376 - type: euclidean_spearman value: 60.220905659334036 - type: manhattan_pearson value: 50.00987996844193 - type: manhattan_spearman value: 60.081341480977926 - task: type: STS dataset: name: MTEB STS22 (zh) type: mteb/sts22-crosslingual-sts config: zh split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 54.717524559088005 - type: cos_sim_spearman value: 66.83570886252286 - type: euclidean_pearson value: 58.41338625505467 - type: euclidean_spearman value: 66.68991427704938 - type: manhattan_pearson value: 58.78638572916807 - type: manhattan_spearman value: 66.58684161046335 - task: type: STS dataset: name: MTEB STS22 (fr) type: mteb/sts22-crosslingual-sts config: fr split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 73.2962042954962 - type: cos_sim_spearman value: 76.58255504852025 - type: euclidean_pearson value: 75.70983192778257 - type: euclidean_spearman value: 77.4547684870542 - type: manhattan_pearson value: 75.75565853870485 - type: manhattan_spearman value: 76.90208974949428 - task: type: STS dataset: name: MTEB STS22 (de-en) type: mteb/sts22-crosslingual-sts config: de-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 54.47396266924846 - type: cos_sim_spearman value: 56.492267162048606 - type: euclidean_pearson value: 55.998505203070195 - type: euclidean_spearman value: 56.46447012960222 - type: manhattan_pearson value: 54.873172394430995 - type: manhattan_spearman value: 56.58111534551218 - task: type: STS dataset: name: MTEB STS22 (es-en) type: mteb/sts22-crosslingual-sts config: es-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 69.87177267688686 - type: cos_sim_spearman value: 74.57160943395763 - type: euclidean_pearson value: 70.88330406826788 - type: euclidean_spearman value: 74.29767636038422 - type: manhattan_pearson value: 71.38245248369536 - type: manhattan_spearman value: 74.53102232732175 - task: type: STS dataset: name: MTEB STS22 (it) type: mteb/sts22-crosslingual-sts config: it split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 72.80225656959544 - type: cos_sim_spearman value: 76.52646173725735 - type: euclidean_pearson value: 73.95710720200799 - type: euclidean_spearman value: 76.54040031984111 - type: manhattan_pearson value: 73.89679971946774 - type: manhattan_spearman value: 76.60886958161574 - task: type: STS dataset: name: MTEB STS22 (pl-en) type: mteb/sts22-crosslingual-sts config: pl-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 70.70844249898789 - type: cos_sim_spearman value: 72.68571783670241 - type: euclidean_pearson value: 72.38800772441031 - type: euclidean_spearman value: 72.86804422703312 - type: manhattan_pearson value: 71.29840508203515 - type: manhattan_spearman value: 71.86264441749513 - task: type: STS dataset: name: MTEB STS22 (zh-en) type: mteb/sts22-crosslingual-sts config: zh-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 58.647478923935694 - type: cos_sim_spearman value: 63.74453623540931 - type: euclidean_pearson value: 59.60138032437505 - type: euclidean_spearman value: 63.947930832166065 - type: manhattan_pearson value: 58.59735509491861 - type: manhattan_spearman value: 62.082503844627404 - task: type: STS dataset: name: MTEB STS22 (es-it) type: mteb/sts22-crosslingual-sts config: es-it split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 65.8722516867162 - type: cos_sim_spearman value: 71.81208592523012 - type: euclidean_pearson value: 67.95315252165956 - type: euclidean_spearman value: 73.00749822046009 - type: manhattan_pearson value: 68.07884688638924 - type: manhattan_spearman value: 72.34210325803069 - task: type: STS dataset: name: MTEB STS22 (de-fr) type: mteb/sts22-crosslingual-sts config: de-fr split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 54.5405814240949 - type: cos_sim_spearman value: 60.56838649023775 - type: euclidean_pearson value: 53.011731611314104 - type: euclidean_spearman value: 58.533194841668426 - type: manhattan_pearson value: 53.623067729338494 - type: manhattan_spearman value: 58.018756154446926 - task: type: STS dataset: name: MTEB STS22 (de-pl) type: mteb/sts22-crosslingual-sts config: de-pl split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 13.611046866216112 - type: cos_sim_spearman value: 28.238192909158492 - type: euclidean_pearson value: 22.16189199885129 - type: euclidean_spearman value: 35.012895679076564 - type: manhattan_pearson value: 21.969771178698387 - type: manhattan_spearman value: 32.456985088607475 - task: type: STS dataset: name: MTEB STS22 (fr-pl) type: mteb/sts22-crosslingual-sts config: fr-pl split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 74.58077407011655 - type: cos_sim_spearman value: 84.51542547285167 - type: euclidean_pearson value: 74.64613843596234 - type: euclidean_spearman value: 84.51542547285167 - type: manhattan_pearson value: 75.15335973101396 - type: manhattan_spearman value: 84.51542547285167 - task: type: STS dataset: name: MTEB STSBenchmark type: mteb/stsbenchmark-sts config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 82.0739825531578 - type: cos_sim_spearman value: 84.01057479311115 - type: euclidean_pearson value: 83.85453227433344 - type: euclidean_spearman value: 84.01630226898655 - type: manhattan_pearson value: 83.75323603028978 - type: manhattan_spearman value: 83.89677983727685 - task: type: Reranking dataset: name: MTEB SciDocsRR type: mteb/scidocs-reranking config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 78.12945623123957 - type: mrr value: 93.87738713719106 - task: type: Retrieval dataset: name: MTEB SciFact type: scifact config: default split: test revision: None metrics: - type: map_at_1 value: 52.983000000000004 - type: map_at_10 value: 62.946000000000005 - type: map_at_100 value: 63.514 - type: map_at_1000 value: 63.554 - type: map_at_3 value: 60.183 - type: map_at_5 value: 61.672000000000004 - type: mrr_at_1 value: 55.667 - type: mrr_at_10 value: 64.522 - type: mrr_at_100 value: 64.957 - type: mrr_at_1000 value: 64.995 - type: mrr_at_3 value: 62.388999999999996 - type: mrr_at_5 value: 63.639 - type: ndcg_at_1 value: 55.667 - type: ndcg_at_10 value: 67.704 - type: ndcg_at_100 value: 70.299 - type: ndcg_at_1000 value: 71.241 - type: ndcg_at_3 value: 62.866 - type: ndcg_at_5 value: 65.16999999999999 - type: precision_at_1 value: 55.667 - type: precision_at_10 value: 9.033 - type: precision_at_100 value: 1.053 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 24.444 - type: precision_at_5 value: 16.133 - type: recall_at_1 value: 52.983000000000004 - type: recall_at_10 value: 80.656 - type: recall_at_100 value: 92.5 - type: recall_at_1000 value: 99.667 - type: recall_at_3 value: 67.744 - type: recall_at_5 value: 73.433 - task: type: PairClassification dataset: name: MTEB SprintDuplicateQuestions type: mteb/sprintduplicatequestions-pairclassification config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.72772277227723 - type: cos_sim_ap value: 92.17845897992215 - type: cos_sim_f1 value: 85.9746835443038 - type: cos_sim_precision value: 87.07692307692308 - type: cos_sim_recall value: 84.89999999999999 - type: dot_accuracy value: 99.3039603960396 - type: dot_ap value: 60.70244020124878 - type: dot_f1 value: 59.92742353551063 - type: dot_precision value: 62.21743810548978 - type: dot_recall value: 57.8 - type: euclidean_accuracy value: 99.71683168316832 - type: euclidean_ap value: 91.53997039964659 - type: euclidean_f1 value: 84.88372093023257 - type: euclidean_precision value: 90.02242152466367 - type: euclidean_recall value: 80.30000000000001 - type: manhattan_accuracy value: 99.72376237623763 - type: manhattan_ap value: 91.80756777790289 - type: manhattan_f1 value: 85.48468106479157 - type: manhattan_precision value: 85.8728557013118 - type: manhattan_recall value: 85.1 - type: max_accuracy value: 99.72772277227723 - type: max_ap value: 92.17845897992215 - type: max_f1 value: 85.9746835443038 - task: type: Clustering dataset: name: MTEB StackExchangeClustering type: mteb/stackexchange-clustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 53.52464042600003 - task: type: Clustering dataset: name: MTEB StackExchangeClusteringP2P type: mteb/stackexchange-clustering-p2p config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 32.071631948736 - task: type: Reranking dataset: name: MTEB StackOverflowDupQuestions type: mteb/stackoverflowdupquestions-reranking config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 49.19552407604654 - type: mrr value: 49.95269130379425 - task: type: Summarization dataset: name: MTEB SummEval type: mteb/summeval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 29.345293033095427 - type: cos_sim_spearman value: 29.976931423258403 - type: dot_pearson value: 27.047078008958408 - type: dot_spearman value: 27.75894368380218 - task: type: Retrieval dataset: name: MTEB TRECCOVID type: trec-covid config: default split: test revision: None metrics: - type: map_at_1 value: 0.22 - type: map_at_10 value: 1.706 - type: map_at_100 value: 9.634 - type: map_at_1000 value: 23.665 - type: map_at_3 value: 0.5950000000000001 - type: map_at_5 value: 0.95 - type: mrr_at_1 value: 86.0 - type: mrr_at_10 value: 91.8 - type: mrr_at_100 value: 91.8 - type: mrr_at_1000 value: 91.8 - type: mrr_at_3 value: 91.0 - type: mrr_at_5 value: 91.8 - type: ndcg_at_1 value: 80.0 - type: ndcg_at_10 value: 72.573 - type: ndcg_at_100 value: 53.954 - type: ndcg_at_1000 value: 47.760999999999996 - type: ndcg_at_3 value: 76.173 - type: ndcg_at_5 value: 75.264 - type: precision_at_1 value: 86.0 - type: precision_at_10 value: 76.4 - type: precision_at_100 value: 55.50000000000001 - type: precision_at_1000 value: 21.802 - type: precision_at_3 value: 81.333 - type: precision_at_5 value: 80.4 - type: recall_at_1 value: 0.22 - type: recall_at_10 value: 1.925 - type: recall_at_100 value: 12.762 - type: recall_at_1000 value: 44.946000000000005 - type: recall_at_3 value: 0.634 - type: recall_at_5 value: 1.051 - task: type: BitextMining dataset: name: MTEB Tatoeba (sqi-eng) type: mteb/tatoeba-bitext-mining config: sqi-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 91.0 - type: f1 value: 88.55666666666666 - type: precision value: 87.46166666666667 - type: recall value: 91.0 - task: type: BitextMining dataset: name: MTEB Tatoeba (fry-eng) type: mteb/tatoeba-bitext-mining config: fry-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 57.22543352601156 - type: f1 value: 51.03220478943021 - type: precision value: 48.8150289017341 - type: recall value: 57.22543352601156 - task: type: BitextMining dataset: name: MTEB Tatoeba (kur-eng) type: mteb/tatoeba-bitext-mining config: kur-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 46.58536585365854 - type: f1 value: 39.66870798578116 - type: precision value: 37.416085946573745 - type: recall value: 46.58536585365854 - task: type: BitextMining dataset: name: MTEB Tatoeba (tur-eng) type: mteb/tatoeba-bitext-mining config: tur-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 89.7 - type: f1 value: 86.77999999999999 - type: precision value: 85.45333333333332 - type: recall value: 89.7 - task: type: BitextMining dataset: name: MTEB Tatoeba (deu-eng) type: mteb/tatoeba-bitext-mining config: deu-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 97.39999999999999 - type: f1 value: 96.58333333333331 - type: precision value: 96.2 - type: recall value: 97.39999999999999 - task: type: BitextMining dataset: name: MTEB Tatoeba (nld-eng) type: mteb/tatoeba-bitext-mining config: nld-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 92.4 - type: f1 value: 90.3 - type: precision value: 89.31666666666668 - type: recall value: 92.4 - task: type: BitextMining dataset: name: MTEB Tatoeba (ron-eng) type: mteb/tatoeba-bitext-mining config: ron-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 86.9 - type: f1 value: 83.67190476190476 - type: precision value: 82.23333333333332 - type: recall value: 86.9 - task: type: BitextMining dataset: name: MTEB Tatoeba (ang-eng) type: mteb/tatoeba-bitext-mining config: ang-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 50.0 - type: f1 value: 42.23229092632078 - type: precision value: 39.851634683724235 - type: recall value: 50.0 - task: type: BitextMining dataset: name: MTEB Tatoeba (ido-eng) type: mteb/tatoeba-bitext-mining config: ido-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 76.3 - type: f1 value: 70.86190476190477 - type: precision value: 68.68777777777777 - type: recall value: 76.3 - task: type: BitextMining dataset: name: MTEB Tatoeba (jav-eng) type: mteb/tatoeba-bitext-mining config: jav-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 57.073170731707314 - type: f1 value: 50.658958927251604 - type: precision value: 48.26480836236933 - type: recall value: 57.073170731707314 - task: type: BitextMining dataset: name: MTEB Tatoeba (isl-eng) type: mteb/tatoeba-bitext-mining config: isl-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 68.2 - type: f1 value: 62.156507936507936 - type: precision value: 59.84964285714286 - type: recall value: 68.2 - task: type: BitextMining dataset: name: MTEB Tatoeba (slv-eng) type: mteb/tatoeba-bitext-mining config: slv-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 77.52126366950182 - type: f1 value: 72.8496210148701 - type: precision value: 70.92171498003819 - type: recall value: 77.52126366950182 - task: type: BitextMining dataset: name: MTEB Tatoeba (cym-eng) type: mteb/tatoeba-bitext-mining config: cym-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 70.78260869565217 - type: f1 value: 65.32422360248447 - type: precision value: 63.063067367415194 - type: recall value: 70.78260869565217 - task: type: BitextMining dataset: name: MTEB Tatoeba (kaz-eng) type: mteb/tatoeba-bitext-mining config: kaz-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 78.43478260869566 - type: f1 value: 73.02608695652172 - type: precision value: 70.63768115942028 - type: recall value: 78.43478260869566 - task: type: BitextMining dataset: name: MTEB Tatoeba (est-eng) type: mteb/tatoeba-bitext-mining config: est-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 60.9 - type: f1 value: 55.309753694581275 - type: precision value: 53.130476190476195 - type: recall value: 60.9 - task: type: BitextMining dataset: name: MTEB Tatoeba (heb-eng) type: mteb/tatoeba-bitext-mining config: heb-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 72.89999999999999 - type: f1 value: 67.92023809523809 - type: precision value: 65.82595238095237 - type: recall value: 72.89999999999999 - task: type: BitextMining dataset: name: MTEB Tatoeba (gla-eng) type: mteb/tatoeba-bitext-mining config: gla-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 46.80337756332931 - type: f1 value: 39.42174900558496 - type: precision value: 36.97101116280851 - type: recall value: 46.80337756332931 - task: type: BitextMining dataset: name: MTEB Tatoeba (mar-eng) type: mteb/tatoeba-bitext-mining config: mar-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 89.8 - type: f1 value: 86.79 - type: precision value: 85.375 - type: recall value: 89.8 - task: type: BitextMining dataset: name: MTEB Tatoeba (lat-eng) type: mteb/tatoeba-bitext-mining config: lat-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 47.199999999999996 - type: f1 value: 39.95484348984349 - type: precision value: 37.561071428571424 - type: recall value: 47.199999999999996 - task: type: BitextMining dataset: name: MTEB Tatoeba (bel-eng) type: mteb/tatoeba-bitext-mining config: bel-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 87.8 - type: f1 value: 84.68190476190475 - type: precision value: 83.275 - type: recall value: 87.8 - task: type: BitextMining dataset: name: MTEB Tatoeba (pms-eng) type: mteb/tatoeba-bitext-mining config: pms-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 48.76190476190476 - type: f1 value: 42.14965986394558 - type: precision value: 39.96743626743626 - type: recall value: 48.76190476190476 - task: type: BitextMining dataset: name: MTEB Tatoeba (gle-eng) type: mteb/tatoeba-bitext-mining config: gle-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 66.10000000000001 - type: f1 value: 59.58580086580086 - type: precision value: 57.150238095238095 - type: recall value: 66.10000000000001 - task: type: BitextMining dataset: name: MTEB Tatoeba (pes-eng) type: mteb/tatoeba-bitext-mining config: pes-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 87.3 - type: f1 value: 84.0 - type: precision value: 82.48666666666666 - type: recall value: 87.3 - task: type: BitextMining dataset: name: MTEB Tatoeba (nob-eng) type: mteb/tatoeba-bitext-mining config: nob-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 90.4 - type: f1 value: 87.79523809523809 - type: precision value: 86.6 - type: recall value: 90.4 - task: type: BitextMining dataset: name: MTEB Tatoeba (bul-eng) type: mteb/tatoeba-bitext-mining config: bul-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 87.0 - type: f1 value: 83.81 - type: precision value: 82.36666666666666 - type: recall value: 87.0 - task: type: BitextMining dataset: name: MTEB Tatoeba (cbk-eng) type: mteb/tatoeba-bitext-mining config: cbk-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 63.9 - type: f1 value: 57.76533189033189 - type: precision value: 55.50595238095239 - type: recall value: 63.9 - task: type: BitextMining dataset: name: MTEB Tatoeba (hun-eng) type: mteb/tatoeba-bitext-mining config: hun-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 76.1 - type: f1 value: 71.83690476190478 - type: precision value: 70.04928571428573 - type: recall value: 76.1 - task: type: BitextMining dataset: name: MTEB Tatoeba (uig-eng) type: mteb/tatoeba-bitext-mining config: uig-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 66.3 - type: f1 value: 59.32626984126984 - type: precision value: 56.62535714285713 - type: recall value: 66.3 - task: type: BitextMining dataset: name: MTEB Tatoeba (rus-eng) type: mteb/tatoeba-bitext-mining config: rus-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 90.60000000000001 - type: f1 value: 87.96333333333334 - type: precision value: 86.73333333333333 - type: recall value: 90.60000000000001 - task: type: BitextMining dataset: name: MTEB Tatoeba (spa-eng) type: mteb/tatoeba-bitext-mining config: spa-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 93.10000000000001 - type: f1 value: 91.10000000000001 - type: precision value: 90.16666666666666 - type: recall value: 93.10000000000001 - task: type: BitextMining dataset: name: MTEB Tatoeba (hye-eng) type: mteb/tatoeba-bitext-mining config: hye-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 85.71428571428571 - type: f1 value: 82.29142600436403 - type: precision value: 80.8076626877166 - type: recall value: 85.71428571428571 - task: type: BitextMining dataset: name: MTEB Tatoeba (tel-eng) type: mteb/tatoeba-bitext-mining config: tel-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 88.88888888888889 - type: f1 value: 85.7834757834758 - type: precision value: 84.43732193732193 - type: recall value: 88.88888888888889 - task: type: BitextMining dataset: name: MTEB Tatoeba (afr-eng) type: mteb/tatoeba-bitext-mining config: afr-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 88.5 - type: f1 value: 85.67190476190476 - type: precision value: 84.43333333333332 - type: recall value: 88.5 - task: type: BitextMining dataset: name: MTEB Tatoeba (mon-eng) type: mteb/tatoeba-bitext-mining config: mon-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 82.72727272727273 - type: f1 value: 78.21969696969695 - type: precision value: 76.18181818181819 - type: recall value: 82.72727272727273 - task: type: BitextMining dataset: name: MTEB Tatoeba (arz-eng) type: mteb/tatoeba-bitext-mining config: arz-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 61.0062893081761 - type: f1 value: 55.13976240391334 - type: precision value: 52.92112499659669 - type: recall value: 61.0062893081761 - task: type: BitextMining dataset: name: MTEB Tatoeba (hrv-eng) type: mteb/tatoeba-bitext-mining config: hrv-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 89.5 - type: f1 value: 86.86666666666666 - type: precision value: 85.69166666666668 - type: recall value: 89.5 - task: type: BitextMining dataset: name: MTEB Tatoeba (nov-eng) type: mteb/tatoeba-bitext-mining config: nov-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 73.54085603112841 - type: f1 value: 68.56031128404669 - type: precision value: 66.53047989623866 - type: recall value: 73.54085603112841 - task: type: BitextMining dataset: name: MTEB Tatoeba (gsw-eng) type: mteb/tatoeba-bitext-mining config: gsw-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 43.58974358974359 - type: f1 value: 36.45299145299145 - type: precision value: 33.81155881155882 - type: recall value: 43.58974358974359 - task: type: BitextMining dataset: name: MTEB Tatoeba (nds-eng) type: mteb/tatoeba-bitext-mining config: nds-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 59.599999999999994 - type: f1 value: 53.264689754689755 - type: precision value: 50.869166666666665 - type: recall value: 59.599999999999994 - task: type: BitextMining dataset: name: MTEB Tatoeba (ukr-eng) type: mteb/tatoeba-bitext-mining config: ukr-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 85.2 - type: f1 value: 81.61666666666665 - type: precision value: 80.02833333333335 - type: recall value: 85.2 - task: type: BitextMining dataset: name: MTEB Tatoeba (uzb-eng) type: mteb/tatoeba-bitext-mining config: uzb-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 63.78504672897196 - type: f1 value: 58.00029669188548 - type: precision value: 55.815809968847354 - type: recall value: 63.78504672897196 - task: type: BitextMining dataset: name: MTEB Tatoeba (lit-eng) type: mteb/tatoeba-bitext-mining config: lit-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 66.5 - type: f1 value: 61.518333333333345 - type: precision value: 59.622363699102834 - type: recall value: 66.5 - task: type: BitextMining dataset: name: MTEB Tatoeba (ina-eng) type: mteb/tatoeba-bitext-mining config: ina-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 88.6 - type: f1 value: 85.60222222222221 - type: precision value: 84.27916666666665 - type: recall value: 88.6 - task: type: BitextMining dataset: name: MTEB Tatoeba (lfn-eng) type: mteb/tatoeba-bitext-mining config: lfn-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 58.699999999999996 - type: f1 value: 52.732375957375965 - type: precision value: 50.63214035964035 - type: recall value: 58.699999999999996 - task: type: BitextMining dataset: name: MTEB Tatoeba (zsm-eng) type: mteb/tatoeba-bitext-mining config: zsm-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 92.10000000000001 - type: f1 value: 89.99666666666667 - type: precision value: 89.03333333333333 - type: recall value: 92.10000000000001 - task: type: BitextMining dataset: name: MTEB Tatoeba (ita-eng) type: mteb/tatoeba-bitext-mining config: ita-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 90.10000000000001 - type: f1 value: 87.55666666666667 - type: precision value: 86.36166666666668 - type: recall value: 90.10000000000001 - task: type: BitextMining dataset: name: MTEB Tatoeba (cmn-eng) type: mteb/tatoeba-bitext-mining config: cmn-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 91.4 - type: f1 value: 88.89000000000001 - type: precision value: 87.71166666666666 - type: recall value: 91.4 - task: type: BitextMining dataset: name: MTEB Tatoeba (lvs-eng) type: mteb/tatoeba-bitext-mining config: lvs-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 65.7 - type: f1 value: 60.67427750410509 - type: precision value: 58.71785714285714 - type: recall value: 65.7 - task: type: BitextMining dataset: name: MTEB Tatoeba (glg-eng) type: mteb/tatoeba-bitext-mining config: glg-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 85.39999999999999 - type: f1 value: 81.93190476190475 - type: precision value: 80.37833333333333 - type: recall value: 85.39999999999999 - task: type: BitextMining dataset: name: MTEB Tatoeba (ceb-eng) type: mteb/tatoeba-bitext-mining config: ceb-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 47.833333333333336 - type: f1 value: 42.006625781625786 - type: precision value: 40.077380952380956 - type: recall value: 47.833333333333336 - task: type: BitextMining dataset: name: MTEB Tatoeba (bre-eng) type: mteb/tatoeba-bitext-mining config: bre-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 10.4 - type: f1 value: 8.24465007215007 - type: precision value: 7.664597069597071 - type: recall value: 10.4 - task: type: BitextMining dataset: name: MTEB Tatoeba (ben-eng) type: mteb/tatoeba-bitext-mining config: ben-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 82.6 - type: f1 value: 77.76333333333334 - type: precision value: 75.57833333333332 - type: recall value: 82.6 - task: type: BitextMining dataset: name: MTEB Tatoeba (swg-eng) type: mteb/tatoeba-bitext-mining config: swg-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 52.67857142857143 - type: f1 value: 44.302721088435376 - type: precision value: 41.49801587301587 - type: recall value: 52.67857142857143 - task: type: BitextMining dataset: name: MTEB Tatoeba (arq-eng) type: mteb/tatoeba-bitext-mining config: arq-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 28.3205268935236 - type: f1 value: 22.426666605171157 - type: precision value: 20.685900116470915 - type: recall value: 28.3205268935236 - task: type: BitextMining dataset: name: MTEB Tatoeba (kab-eng) type: mteb/tatoeba-bitext-mining config: kab-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 22.7 - type: f1 value: 17.833970473970474 - type: precision value: 16.407335164835164 - type: recall value: 22.7 - task: type: BitextMining dataset: name: MTEB Tatoeba (fra-eng) type: mteb/tatoeba-bitext-mining config: fra-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 92.2 - type: f1 value: 89.92999999999999 - type: precision value: 88.87 - type: recall value: 92.2 - task: type: BitextMining dataset: name: MTEB Tatoeba (por-eng) type: mteb/tatoeba-bitext-mining config: por-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 91.4 - type: f1 value: 89.25 - type: precision value: 88.21666666666667 - type: recall value: 91.4 - task: type: BitextMining dataset: name: MTEB Tatoeba (tat-eng) type: mteb/tatoeba-bitext-mining config: tat-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 69.19999999999999 - type: f1 value: 63.38269841269841 - type: precision value: 61.14773809523809 - type: recall value: 69.19999999999999 - task: type: BitextMining dataset: name: MTEB Tatoeba (oci-eng) type: mteb/tatoeba-bitext-mining config: oci-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 48.8 - type: f1 value: 42.839915639915645 - type: precision value: 40.770287114845935 - type: recall value: 48.8 - task: type: BitextMining dataset: name: MTEB Tatoeba (pol-eng) type: mteb/tatoeba-bitext-mining config: pol-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 88.8 - type: f1 value: 85.90666666666668 - type: precision value: 84.54166666666666 - type: recall value: 88.8 - task: type: BitextMining dataset: name: MTEB Tatoeba (war-eng) type: mteb/tatoeba-bitext-mining config: war-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 46.6 - type: f1 value: 40.85892920804686 - type: precision value: 38.838223114604695 - type: recall value: 46.6 - task: type: BitextMining dataset: name: MTEB Tatoeba (aze-eng) type: mteb/tatoeba-bitext-mining config: aze-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 84.0 - type: f1 value: 80.14190476190475 - type: precision value: 78.45333333333333 - type: recall value: 84.0 - task: type: BitextMining dataset: name: MTEB Tatoeba (vie-eng) type: mteb/tatoeba-bitext-mining config: vie-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 90.5 - type: f1 value: 87.78333333333333 - type: precision value: 86.5 - type: recall value: 90.5 - task: type: BitextMining dataset: name: MTEB Tatoeba (nno-eng) type: mteb/tatoeba-bitext-mining config: nno-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 74.5 - type: f1 value: 69.48397546897547 - type: precision value: 67.51869047619049 - type: recall value: 74.5 - task: type: BitextMining dataset: name: MTEB Tatoeba (cha-eng) type: mteb/tatoeba-bitext-mining config: cha-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 32.846715328467155 - type: f1 value: 27.828177499710343 - type: precision value: 26.63451511991658 - type: recall value: 32.846715328467155 - task: type: BitextMining dataset: name: MTEB Tatoeba (mhr-eng) type: mteb/tatoeba-bitext-mining config: mhr-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 8.0 - type: f1 value: 6.07664116764988 - type: precision value: 5.544177607179943 - type: recall value: 8.0 - task: type: BitextMining dataset: name: MTEB Tatoeba (dan-eng) type: mteb/tatoeba-bitext-mining config: dan-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 87.6 - type: f1 value: 84.38555555555554 - type: precision value: 82.91583333333334 - type: recall value: 87.6 - task: type: BitextMining dataset: name: MTEB Tatoeba (ell-eng) type: mteb/tatoeba-bitext-mining config: ell-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 87.5 - type: f1 value: 84.08333333333331 - type: precision value: 82.47333333333333 - type: recall value: 87.5 - task: type: BitextMining dataset: name: MTEB Tatoeba (amh-eng) type: mteb/tatoeba-bitext-mining config: amh-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 80.95238095238095 - type: f1 value: 76.13095238095238 - type: precision value: 74.05753968253967 - type: recall value: 80.95238095238095 - task: type: BitextMining dataset: name: MTEB Tatoeba (pam-eng) type: mteb/tatoeba-bitext-mining config: pam-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 8.799999999999999 - type: f1 value: 6.971422975172975 - type: precision value: 6.557814916172301 - type: recall value: 8.799999999999999 - task: type: BitextMining dataset: name: MTEB Tatoeba (hsb-eng) type: mteb/tatoeba-bitext-mining config: hsb-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 44.099378881987576 - type: f1 value: 37.01649742022413 - type: precision value: 34.69420618488942 - type: recall value: 44.099378881987576 - task: type: BitextMining dataset: name: MTEB Tatoeba (srp-eng) type: mteb/tatoeba-bitext-mining config: srp-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 84.3 - type: f1 value: 80.32666666666667 - type: precision value: 78.60666666666665 - type: recall value: 84.3 - task: type: BitextMining dataset: name: MTEB Tatoeba (epo-eng) type: mteb/tatoeba-bitext-mining config: epo-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 92.5 - type: f1 value: 90.49666666666666 - type: precision value: 89.56666666666668 - type: recall value: 92.5 - task: type: BitextMining dataset: name: MTEB Tatoeba (kzj-eng) type: mteb/tatoeba-bitext-mining config: kzj-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 10.0 - type: f1 value: 8.268423529875141 - type: precision value: 7.878118605532398 - type: recall value: 10.0 - task: type: BitextMining dataset: name: MTEB Tatoeba (awa-eng) type: mteb/tatoeba-bitext-mining config: awa-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 79.22077922077922 - type: f1 value: 74.27128427128426 - type: precision value: 72.28715728715729 - type: recall value: 79.22077922077922 - task: type: BitextMining dataset: name: MTEB Tatoeba (fao-eng) type: mteb/tatoeba-bitext-mining config: fao-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 65.64885496183206 - type: f1 value: 58.87495456197747 - type: precision value: 55.992366412213734 - type: recall value: 65.64885496183206 - task: type: BitextMining dataset: name: MTEB Tatoeba (mal-eng) type: mteb/tatoeba-bitext-mining config: mal-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 96.06986899563319 - type: f1 value: 94.78408539543909 - type: precision value: 94.15332362930616 - type: recall value: 96.06986899563319 - task: type: BitextMining dataset: name: MTEB Tatoeba (ile-eng) type: mteb/tatoeba-bitext-mining config: ile-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 77.2 - type: f1 value: 71.72571428571428 - type: precision value: 69.41000000000001 - type: recall value: 77.2 - task: type: BitextMining dataset: name: MTEB Tatoeba (bos-eng) type: mteb/tatoeba-bitext-mining config: bos-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 86.4406779661017 - type: f1 value: 83.2391713747646 - type: precision value: 81.74199623352166 - type: recall value: 86.4406779661017 - task: type: BitextMining dataset: name: MTEB Tatoeba (cor-eng) type: mteb/tatoeba-bitext-mining config: cor-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 8.4 - type: f1 value: 6.017828743398003 - type: precision value: 5.4829865484756795 - type: recall value: 8.4 - task: type: BitextMining dataset: name: MTEB Tatoeba (cat-eng) type: mteb/tatoeba-bitext-mining config: cat-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 83.5 - type: f1 value: 79.74833333333333 - type: precision value: 78.04837662337664 - type: recall value: 83.5 - task: type: BitextMining dataset: name: MTEB Tatoeba (eus-eng) type: mteb/tatoeba-bitext-mining config: eus-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 60.4 - type: f1 value: 54.467301587301584 - type: precision value: 52.23242424242424 - type: recall value: 60.4 - task: type: BitextMining dataset: name: MTEB Tatoeba (yue-eng) type: mteb/tatoeba-bitext-mining config: yue-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 74.9 - type: f1 value: 69.68699134199134 - type: precision value: 67.59873015873016 - type: recall value: 74.9 - task: type: BitextMining dataset: name: MTEB Tatoeba (swe-eng) type: mteb/tatoeba-bitext-mining config: swe-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 88.0 - type: f1 value: 84.9652380952381 - type: precision value: 83.66166666666666 - type: recall value: 88.0 - task: type: BitextMining dataset: name: MTEB Tatoeba (dtp-eng) type: mteb/tatoeba-bitext-mining config: dtp-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 9.1 - type: f1 value: 7.681244588744588 - type: precision value: 7.370043290043291 - type: recall value: 9.1 - task: type: BitextMining dataset: name: MTEB Tatoeba (kat-eng) type: mteb/tatoeba-bitext-mining config: kat-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 80.9651474530831 - type: f1 value: 76.84220605132133 - type: precision value: 75.19606398962966 - type: recall value: 80.9651474530831 - task: type: BitextMining dataset: name: MTEB Tatoeba (jpn-eng) type: mteb/tatoeba-bitext-mining config: jpn-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 86.9 - type: f1 value: 83.705 - type: precision value: 82.3120634920635 - type: recall value: 86.9 - task: type: BitextMining dataset: name: MTEB Tatoeba (csb-eng) type: mteb/tatoeba-bitext-mining config: csb-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 29.64426877470356 - type: f1 value: 23.98763072676116 - type: precision value: 22.506399397703746 - type: recall value: 29.64426877470356 - task: type: BitextMining dataset: name: MTEB Tatoeba (xho-eng) type: mteb/tatoeba-bitext-mining config: xho-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 70.4225352112676 - type: f1 value: 62.84037558685445 - type: precision value: 59.56572769953053 - type: recall value: 70.4225352112676 - task: type: BitextMining dataset: name: MTEB Tatoeba (orv-eng) type: mteb/tatoeba-bitext-mining config: orv-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 19.64071856287425 - type: f1 value: 15.125271011207756 - type: precision value: 13.865019261197494 - type: recall value: 19.64071856287425 - task: type: BitextMining dataset: name: MTEB Tatoeba (ind-eng) type: mteb/tatoeba-bitext-mining config: ind-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 90.2 - type: f1 value: 87.80666666666666 - type: precision value: 86.70833333333331 - type: recall value: 90.2 - task: type: BitextMining dataset: name: MTEB Tatoeba (tuk-eng) type: mteb/tatoeba-bitext-mining config: tuk-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 23.15270935960591 - type: f1 value: 18.407224958949097 - type: precision value: 16.982385430661292 - type: recall value: 23.15270935960591 - task: type: BitextMining dataset: name: MTEB Tatoeba (max-eng) type: mteb/tatoeba-bitext-mining config: max-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 55.98591549295775 - type: f1 value: 49.94718309859154 - type: precision value: 47.77864154624717 - type: recall value: 55.98591549295775 - task: type: BitextMining dataset: name: MTEB Tatoeba (swh-eng) type: mteb/tatoeba-bitext-mining config: swh-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 73.07692307692307 - type: f1 value: 66.74358974358974 - type: precision value: 64.06837606837607 - type: recall value: 73.07692307692307 - task: type: BitextMining dataset: name: MTEB Tatoeba (hin-eng) type: mteb/tatoeba-bitext-mining config: hin-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 94.89999999999999 - type: f1 value: 93.25 - type: precision value: 92.43333333333332 - type: recall value: 94.89999999999999 - task: type: BitextMining dataset: name: MTEB Tatoeba (dsb-eng) type: mteb/tatoeba-bitext-mining config: dsb-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 37.78705636743215 - type: f1 value: 31.63899658680452 - type: precision value: 29.72264397629742 - type: recall value: 37.78705636743215 - task: type: BitextMining dataset: name: MTEB Tatoeba (ber-eng) type: mteb/tatoeba-bitext-mining config: ber-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 21.6 - type: f1 value: 16.91697302697303 - type: precision value: 15.71225147075147 - type: recall value: 21.6 - task: type: BitextMining dataset: name: MTEB Tatoeba (tam-eng) type: mteb/tatoeba-bitext-mining config: tam-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 85.01628664495115 - type: f1 value: 81.38514037536838 - type: precision value: 79.83170466883823 - type: recall value: 85.01628664495115 - task: type: BitextMining dataset: name: MTEB Tatoeba (slk-eng) type: mteb/tatoeba-bitext-mining config: slk-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 83.39999999999999 - type: f1 value: 79.96380952380952 - type: precision value: 78.48333333333333 - type: recall value: 83.39999999999999 - task: type: BitextMining dataset: name: MTEB Tatoeba (tgl-eng) type: mteb/tatoeba-bitext-mining config: tgl-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 83.2 - type: f1 value: 79.26190476190476 - type: precision value: 77.58833333333334 - type: recall value: 83.2 - task: type: BitextMining dataset: name: MTEB Tatoeba (ast-eng) type: mteb/tatoeba-bitext-mining config: ast-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 75.59055118110236 - type: f1 value: 71.66854143232096 - type: precision value: 70.30183727034121 - type: recall value: 75.59055118110236 - task: type: BitextMining dataset: name: MTEB Tatoeba (mkd-eng) type: mteb/tatoeba-bitext-mining config: mkd-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 65.5 - type: f1 value: 59.26095238095238 - type: precision value: 56.81909090909092 - type: recall value: 65.5 - task: type: BitextMining dataset: name: MTEB Tatoeba (khm-eng) type: mteb/tatoeba-bitext-mining config: khm-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 55.26315789473685 - type: f1 value: 47.986523325858506 - type: precision value: 45.33950006595436 - type: recall value: 55.26315789473685 - task: type: BitextMining dataset: name: MTEB Tatoeba (ces-eng) type: mteb/tatoeba-bitext-mining config: ces-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 82.89999999999999 - type: f1 value: 78.835 - type: precision value: 77.04761904761905 - type: recall value: 82.89999999999999 - task: type: BitextMining dataset: name: MTEB Tatoeba (tzl-eng) type: mteb/tatoeba-bitext-mining config: tzl-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 43.269230769230774 - type: f1 value: 36.20421245421245 - type: precision value: 33.57371794871795 - type: recall value: 43.269230769230774 - task: type: BitextMining dataset: name: MTEB Tatoeba (urd-eng) type: mteb/tatoeba-bitext-mining config: urd-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 88.0 - type: f1 value: 84.70666666666666 - type: precision value: 83.23166666666665 - type: recall value: 88.0 - task: type: BitextMining dataset: name: MTEB Tatoeba (ara-eng) type: mteb/tatoeba-bitext-mining config: ara-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 77.4 - type: f1 value: 72.54666666666667 - type: precision value: 70.54318181818181 - type: recall value: 77.4 - task: type: BitextMining dataset: name: MTEB Tatoeba (kor-eng) type: mteb/tatoeba-bitext-mining config: kor-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 78.60000000000001 - type: f1 value: 74.1588888888889 - type: precision value: 72.30250000000001 - type: recall value: 78.60000000000001 - task: type: BitextMining dataset: name: MTEB Tatoeba (yid-eng) type: mteb/tatoeba-bitext-mining config: yid-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 72.40566037735849 - type: f1 value: 66.82587328813744 - type: precision value: 64.75039308176099 - type: recall value: 72.40566037735849 - task: type: BitextMining dataset: name: MTEB Tatoeba (fin-eng) type: mteb/tatoeba-bitext-mining config: fin-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 73.8 - type: f1 value: 68.56357142857144 - type: precision value: 66.3178822055138 - type: recall value: 73.8 - task: type: BitextMining dataset: name: MTEB Tatoeba (tha-eng) type: mteb/tatoeba-bitext-mining config: tha-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 91.78832116788321 - type: f1 value: 89.3552311435523 - type: precision value: 88.20559610705597 - type: recall value: 91.78832116788321 - task: type: BitextMining dataset: name: MTEB Tatoeba (wuu-eng) type: mteb/tatoeba-bitext-mining config: wuu-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics: - type: accuracy value: 74.3 - type: f1 value: 69.05085581085581 - type: precision value: 66.955 - type: recall value: 74.3 - task: type: Retrieval dataset: name: MTEB Touche2020 type: webis-touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 2.896 - type: map_at_10 value: 8.993 - type: map_at_100 value: 14.133999999999999 - type: map_at_1000 value: 15.668000000000001 - type: map_at_3 value: 5.862 - type: map_at_5 value: 7.17 - type: mrr_at_1 value: 34.694 - type: mrr_at_10 value: 42.931000000000004 - type: mrr_at_100 value: 44.81 - type: mrr_at_1000 value: 44.81 - type: mrr_at_3 value: 38.435 - type: mrr_at_5 value: 41.701 - type: ndcg_at_1 value: 31.633 - type: ndcg_at_10 value: 21.163 - type: ndcg_at_100 value: 33.306000000000004 - type: ndcg_at_1000 value: 45.275999999999996 - type: ndcg_at_3 value: 25.685999999999996 - type: ndcg_at_5 value: 23.732 - type: precision_at_1 value: 34.694 - type: precision_at_10 value: 17.755000000000003 - type: precision_at_100 value: 6.938999999999999 - type: precision_at_1000 value: 1.48 - type: precision_at_3 value: 25.85 - type: precision_at_5 value: 23.265 - type: recall_at_1 value: 2.896 - type: recall_at_10 value: 13.333999999999998 - type: recall_at_100 value: 43.517 - type: recall_at_1000 value: 79.836 - type: recall_at_3 value: 6.306000000000001 - type: recall_at_5 value: 8.825 - task: type: Classification dataset: name: MTEB ToxicConversationsClassification type: mteb/toxic_conversations_50k config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 69.3874 - type: ap value: 13.829909072469423 - type: f1 value: 53.54534203543492 - task: type: Classification dataset: name: MTEB TweetSentimentExtractionClassification type: mteb/tweet_sentiment_extraction config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 62.62026032823995 - type: f1 value: 62.85251350485221 - task: type: Clustering dataset: name: MTEB TwentyNewsgroupsClustering type: mteb/twentynewsgroups-clustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 33.21527881409797 - task: type: PairClassification dataset: name: MTEB TwitterSemEval2015 type: mteb/twittersemeval2015-pairclassification config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 84.97943613280086 - type: cos_sim_ap value: 70.75454316885921 - type: cos_sim_f1 value: 65.38274012676743 - type: cos_sim_precision value: 60.761214318078835 - type: cos_sim_recall value: 70.76517150395777 - type: dot_accuracy value: 79.0546581629612 - type: dot_ap value: 47.3197121792147 - type: dot_f1 value: 49.20106524633821 - type: dot_precision value: 42.45499808502489 - type: dot_recall value: 58.49604221635884 - type: euclidean_accuracy value: 85.08076533349228 - type: euclidean_ap value: 70.95016106374474 - type: euclidean_f1 value: 65.43987900176455 - type: euclidean_precision value: 62.64478764478765 - type: euclidean_recall value: 68.49604221635884 - type: manhattan_accuracy value: 84.93771234428085 - type: manhattan_ap value: 70.63668388755362 - type: manhattan_f1 value: 65.23895401262398 - type: manhattan_precision value: 56.946084218811485 - type: manhattan_recall value: 76.35883905013192 - type: max_accuracy value: 85.08076533349228 - type: max_ap value: 70.95016106374474 - type: max_f1 value: 65.43987900176455 - task: type: PairClassification dataset: name: MTEB TwitterURLCorpus type: mteb/twitterurlcorpus-pairclassification config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.69096130709822 - type: cos_sim_ap value: 84.82526278228542 - type: cos_sim_f1 value: 77.65485060585536 - type: cos_sim_precision value: 75.94582658619167 - type: cos_sim_recall value: 79.44256236526024 - type: dot_accuracy value: 80.97954748321496 - type: dot_ap value: 64.81642914145866 - type: dot_f1 value: 60.631996987229975 - type: dot_precision value: 54.5897293631712 - type: dot_recall value: 68.17831844779796 - type: euclidean_accuracy value: 88.6987231730508 - type: euclidean_ap value: 84.80003825477253 - type: euclidean_f1 value: 77.67194179854496 - type: euclidean_precision value: 75.7128235122094 - type: euclidean_recall value: 79.73514012935017 - type: manhattan_accuracy value: 88.62692591298949 - type: manhattan_ap value: 84.80451408255276 - type: manhattan_f1 value: 77.69888949572183 - type: manhattan_precision value: 73.70311528631622 - type: manhattan_recall value: 82.15275639051433 - type: max_accuracy value: 88.6987231730508 - type: max_ap value: 84.82526278228542 - type: max_f1 value: 77.69888949572183 --- # multilingual-e5-small-mlx This model was converted to MLX format from [`intfloat/multilingual-e5-small`](). Refer to the [original model card](https://huggingface.co/intfloat/multilingual-e5-small) for more details on the model. ## Use with mlx ```bash pip install mlx git clone https://github.com/ml-explore/mlx-examples.git cd mlx-examples/llms/hf_llm python generate.py --model mlx-community/multilingual-e5-small-mlx --prompt "My name is" ```