diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -4,6 +4,7 @@ tags: - sentence-transformers - feature-extraction - sentence-similarity +- mteb language: en license: apache-2.0 datasets: @@ -28,7 +29,4495 @@ datasets: - embedding-data/SPECTER - embedding-data/PAQ_pairs - embedding-data/WikiAnswers - +model-index: +- name: all-MiniLM-L12-v2 + results: + - task: + type: Classification + dataset: + type: mteb/amazon_counterfactual + name: MTEB AmazonCounterfactualClassification (en) + config: en + split: test + metrics: + - type: accuracy + value: 65.28358208955224 + - type: ap + value: 28.02247873560022 + - type: f1 + value: 59.09977445939425 + - task: + type: Classification + dataset: + type: mteb/amazon_counterfactual + name: MTEB AmazonCounterfactualClassification (de) + config: de + split: test + metrics: + - type: accuracy + value: 57.09850107066381 + - type: ap + value: 73.38224986285773 + - type: f1 + value: 55.183322516223434 + - task: + type: Classification + dataset: + type: mteb/amazon_counterfactual + name: MTEB AmazonCounterfactualClassification (en-ext) + config: en-ext + split: test + metrics: + - type: accuracy + value: 67.24137931034483 + - type: ap + value: 17.93337056203553 + - type: f1 + value: 55.200711090858846 + - task: + type: Classification + dataset: + type: mteb/amazon_counterfactual + name: MTEB AmazonCounterfactualClassification (ja) + config: ja + split: test + metrics: + - type: accuracy + value: 59.91434689507494 + - type: ap + value: 13.610920446878454 + - type: f1 + value: 48.70464699796398 + - task: + type: Classification + dataset: + type: mteb/amazon_polarity + name: MTEB AmazonPolarityClassification + config: default + split: test + metrics: + - type: accuracy + value: 62.984899999999996 + - type: ap + value: 58.19701547898307 + - type: f1 + value: 62.704020410756144 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (en) + config: en + split: test + metrics: + - type: accuracy + value: 30.792 + - type: f1 + value: 30.254565315575437 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (de) + config: de + split: test + metrics: + - type: accuracy + value: 25.907999999999998 + - type: f1 + value: 25.538149526380543 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (es) + config: es + split: test + metrics: + - type: accuracy + value: 27.634000000000004 + - type: f1 + value: 27.287076320171728 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (fr) + config: fr + split: test + metrics: + - type: accuracy + value: 27.540000000000003 + - type: f1 + value: 27.21486019130574 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (ja) + config: ja + split: test + metrics: + - type: accuracy + value: 23.566000000000003 + - type: f1 + value: 23.3492650771905 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (zh) + config: zh + split: test + metrics: + - type: accuracy + value: 22.99 + - type: f1 + value: 22.47175043426865 + - task: + type: Retrieval + dataset: + type: arguana + name: MTEB ArguAna + config: default + split: test + metrics: + - type: map_at_1 + value: 23.257 + - type: map_at_10 + value: 38.083 + - type: map_at_100 + value: 39.263999999999996 + - type: map_at_1000 + value: 39.273 + - type: map_at_3 + value: 32.574999999999996 + - type: map_at_5 + value: 35.669000000000004 + - type: mrr_at_1 + value: 23.613 + - type: mrr_at_10 + value: 38.243 + - type: mrr_at_100 + value: 39.410000000000004 + - type: mrr_at_1000 + value: 39.419 + - type: mrr_at_3 + value: 32.883 + - type: mrr_at_5 + value: 35.766999999999996 + - type: ndcg_at_1 + value: 23.257 + - type: ndcg_at_10 + value: 47.128 + - type: ndcg_at_100 + value: 52.093 + - type: ndcg_at_1000 + value: 52.315999999999995 + - type: ndcg_at_3 + value: 35.794 + - type: ndcg_at_5 + value: 41.364000000000004 + - type: precision_at_1 + value: 23.257 + - type: precision_at_10 + value: 7.632 + - type: precision_at_100 + value: 0.979 + - type: precision_at_1000 + value: 0.1 + - type: precision_at_3 + value: 15.055 + - type: precision_at_5 + value: 11.735 + - type: recall_at_1 + value: 23.257 + - type: recall_at_10 + value: 76.31599999999999 + - type: recall_at_100 + value: 97.866 + - type: recall_at_1000 + value: 99.57300000000001 + - type: recall_at_3 + value: 45.164 + - type: recall_at_5 + value: 58.677 + - task: + type: Clustering + dataset: + type: mteb/arxiv-clustering-p2p + name: MTEB ArxivClusteringP2P + config: default + split: test + metrics: + - type: v_measure + value: 46.06982724111873 + - task: + type: Clustering + dataset: + type: mteb/arxiv-clustering-s2s + name: MTEB ArxivClusteringS2S + config: default + split: test + metrics: + - type: v_measure + value: 37.501829188148264 + - task: + type: Reranking + dataset: + type: mteb/askubuntudupquestions-reranking + name: MTEB AskUbuntuDupQuestions + config: default + split: test + metrics: + - type: map + value: 64.06160552465775 + - type: mrr + value: 77.40029899309677 + - task: + type: STS + dataset: + type: mteb/biosses-sts + name: MTEB BIOSSES + config: default + split: test + metrics: + - type: cos_sim_pearson + value: 86.73300462416691 + - type: cos_sim_spearman + value: 83.56756679430214 + - type: euclidean_pearson + value: 84.35153960397948 + - type: euclidean_spearman + value: 83.56756679430214 + - type: manhattan_pearson + value: 84.10087673223914 + - type: manhattan_spearman + value: 83.58383222516198 + - task: + type: Classification + dataset: + type: mteb/banking77 + name: MTEB Banking77Classification + config: default + split: test + metrics: + - type: accuracy + value: 80.40259740259741 + - type: f1 + value: 79.7932665380276 + - task: + type: Clustering + dataset: + type: mteb/biorxiv-clustering-p2p + name: MTEB BiorxivClusteringP2P + config: default + split: test + metrics: + - type: v_measure + value: 36.985834019439366 + - task: + type: Clustering + dataset: + type: mteb/biorxiv-clustering-s2s + name: MTEB BiorxivClusteringS2S + config: default + split: test + metrics: + - type: v_measure + value: 33.207831360185644 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackAndroidRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 34.975 + - type: map_at_10 + value: 47.227999999999994 + - type: map_at_100 + value: 48.91 + - type: map_at_1000 + value: 49.016 + - type: map_at_3 + value: 43.334 + - type: map_at_5 + value: 45.353 + - type: mrr_at_1 + value: 43.348 + - type: mrr_at_10 + value: 53.744 + - type: mrr_at_100 + value: 54.432 + - type: mrr_at_1000 + value: 54.458 + - type: mrr_at_3 + value: 51.359 + - type: mrr_at_5 + value: 52.825 + - type: ndcg_at_1 + value: 43.348 + - type: ndcg_at_10 + value: 54.118 + - type: ndcg_at_100 + value: 59.496 + - type: ndcg_at_1000 + value: 60.846999999999994 + - type: ndcg_at_3 + value: 49.001 + - type: ndcg_at_5 + value: 51.245 + - type: precision_at_1 + value: 43.348 + - type: precision_at_10 + value: 10.658 + - type: precision_at_100 + value: 1.701 + - type: precision_at_1000 + value: 0.214 + - type: precision_at_3 + value: 23.701 + - type: precision_at_5 + value: 17.082 + - type: recall_at_1 + value: 34.975 + - type: recall_at_10 + value: 66.291 + - type: recall_at_100 + value: 88.727 + - type: recall_at_1000 + value: 97.26700000000001 + - type: recall_at_3 + value: 51.505 + - type: recall_at_5 + value: 57.833 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackEnglishRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 31.509999999999998 + - type: map_at_10 + value: 43.401 + - type: map_at_100 + value: 44.762 + - type: map_at_1000 + value: 44.906 + - type: map_at_3 + value: 39.83 + - type: map_at_5 + value: 41.784 + - type: mrr_at_1 + value: 39.936 + - type: mrr_at_10 + value: 49.534 + - type: mrr_at_100 + value: 50.126000000000005 + - type: mrr_at_1000 + value: 50.163999999999994 + - type: mrr_at_3 + value: 46.996 + - type: mrr_at_5 + value: 48.508 + - type: ndcg_at_1 + value: 39.936 + - type: ndcg_at_10 + value: 49.845 + - type: ndcg_at_100 + value: 54.25600000000001 + - type: ndcg_at_1000 + value: 56.227000000000004 + - type: ndcg_at_3 + value: 44.982 + - type: ndcg_at_5 + value: 47.187 + - type: precision_at_1 + value: 39.936 + - type: precision_at_10 + value: 9.771 + - type: precision_at_100 + value: 1.575 + - type: precision_at_1000 + value: 0.20600000000000002 + - type: precision_at_3 + value: 22.314 + - type: precision_at_5 + value: 15.975 + - type: recall_at_1 + value: 31.509999999999998 + - type: recall_at_10 + value: 61.468 + - type: recall_at_100 + value: 80.023 + - type: recall_at_1000 + value: 92.267 + - type: recall_at_3 + value: 46.698 + - type: recall_at_5 + value: 53.03600000000001 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackGamingRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 38.577 + - type: map_at_10 + value: 51.041000000000004 + - type: map_at_100 + value: 52.141000000000005 + - type: map_at_1000 + value: 52.190000000000005 + - type: map_at_3 + value: 47.904 + - type: map_at_5 + value: 49.645 + - type: mrr_at_1 + value: 44.138 + - type: mrr_at_10 + value: 54.36 + - type: mrr_at_100 + value: 55.05799999999999 + - type: mrr_at_1000 + value: 55.084 + - type: mrr_at_3 + value: 52.017 + - type: mrr_at_5 + value: 53.321 + - type: ndcg_at_1 + value: 44.138 + - type: ndcg_at_10 + value: 56.855999999999995 + - type: ndcg_at_100 + value: 61.133 + - type: ndcg_at_1000 + value: 62.17399999999999 + - type: ndcg_at_3 + value: 51.624 + - type: ndcg_at_5 + value: 54.108999999999995 + - type: precision_at_1 + value: 44.138 + - type: precision_at_10 + value: 9.16 + - type: precision_at_100 + value: 1.2309999999999999 + - type: precision_at_1000 + value: 0.135 + - type: precision_at_3 + value: 23.156 + - type: precision_at_5 + value: 15.762 + - type: recall_at_1 + value: 38.577 + - type: recall_at_10 + value: 70.638 + - type: recall_at_100 + value: 89.01 + - type: recall_at_1000 + value: 96.53699999999999 + - type: recall_at_3 + value: 56.635000000000005 + - type: recall_at_5 + value: 62.731 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackGisRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 27.038 + - type: map_at_10 + value: 36.108000000000004 + - type: map_at_100 + value: 37.316 + - type: map_at_1000 + value: 37.396 + - type: map_at_3 + value: 33.206 + - type: map_at_5 + value: 34.674 + - type: mrr_at_1 + value: 29.04 + - type: mrr_at_10 + value: 37.979 + - type: mrr_at_100 + value: 39.056000000000004 + - type: mrr_at_1000 + value: 39.11 + - type: mrr_at_3 + value: 35.348 + - type: mrr_at_5 + value: 36.675999999999995 + - type: ndcg_at_1 + value: 29.04 + - type: ndcg_at_10 + value: 41.408 + - type: ndcg_at_100 + value: 46.918 + - type: ndcg_at_1000 + value: 48.827 + - type: ndcg_at_3 + value: 35.699999999999996 + - type: ndcg_at_5 + value: 38.112 + - type: precision_at_1 + value: 29.04 + - type: precision_at_10 + value: 6.463000000000001 + - type: precision_at_100 + value: 0.9570000000000001 + - type: precision_at_1000 + value: 0.116 + - type: precision_at_3 + value: 15.104000000000001 + - type: precision_at_5 + value: 10.508000000000001 + - type: recall_at_1 + value: 27.038 + - type: recall_at_10 + value: 55.989 + - type: recall_at_100 + value: 80.418 + - type: recall_at_1000 + value: 94.506 + - type: recall_at_3 + value: 40.388000000000005 + - type: recall_at_5 + value: 46.085 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackMathematicaRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 17.264 + - type: map_at_10 + value: 26.157000000000004 + - type: map_at_100 + value: 27.503 + - type: map_at_1000 + value: 27.617000000000004 + - type: map_at_3 + value: 23.247999999999998 + - type: map_at_5 + value: 24.81 + - type: mrr_at_1 + value: 21.144 + - type: mrr_at_10 + value: 30.516 + - type: mrr_at_100 + value: 31.607000000000003 + - type: mrr_at_1000 + value: 31.673000000000002 + - type: mrr_at_3 + value: 27.716 + - type: mrr_at_5 + value: 29.357 + - type: ndcg_at_1 + value: 21.144 + - type: ndcg_at_10 + value: 31.86 + - type: ndcg_at_100 + value: 38.12 + - type: ndcg_at_1000 + value: 40.699000000000005 + - type: ndcg_at_3 + value: 26.411 + - type: ndcg_at_5 + value: 28.896 + - type: precision_at_1 + value: 21.144 + - type: precision_at_10 + value: 5.995 + - type: precision_at_100 + value: 1.058 + - type: precision_at_1000 + value: 0.14100000000000001 + - type: precision_at_3 + value: 12.894 + - type: precision_at_5 + value: 9.428 + - type: recall_at_1 + value: 17.264 + - type: recall_at_10 + value: 45.074 + - type: recall_at_100 + value: 71.817 + - type: recall_at_1000 + value: 89.846 + - type: recall_at_3 + value: 30.031000000000002 + - type: recall_at_5 + value: 36.233 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackPhysicsRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 28.668 + - type: map_at_10 + value: 40.382 + - type: map_at_100 + value: 41.836 + - type: map_at_1000 + value: 41.954 + - type: map_at_3 + value: 37.136 + - type: map_at_5 + value: 38.755 + - type: mrr_at_1 + value: 35.13 + - type: mrr_at_10 + value: 45.928999999999995 + - type: mrr_at_100 + value: 46.814 + - type: mrr_at_1000 + value: 46.854 + - type: mrr_at_3 + value: 43.423 + - type: mrr_at_5 + value: 44.79 + - type: ndcg_at_1 + value: 35.13 + - type: ndcg_at_10 + value: 46.81 + - type: ndcg_at_100 + value: 52.552 + - type: ndcg_at_1000 + value: 54.493 + - type: ndcg_at_3 + value: 41.732 + - type: ndcg_at_5 + value: 43.847 + - type: precision_at_1 + value: 35.13 + - type: precision_at_10 + value: 8.738999999999999 + - type: precision_at_100 + value: 1.373 + - type: precision_at_1000 + value: 0.174 + - type: precision_at_3 + value: 20.372 + - type: precision_at_5 + value: 14.302000000000001 + - type: recall_at_1 + value: 28.668 + - type: recall_at_10 + value: 60.038000000000004 + - type: recall_at_100 + value: 83.736 + - type: recall_at_1000 + value: 96.184 + - type: recall_at_3 + value: 45.647999999999996 + - type: recall_at_5 + value: 51.212 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackProgrammersRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 25.287 + - type: map_at_10 + value: 35.351 + - type: map_at_100 + value: 36.867 + - type: map_at_1000 + value: 36.973 + - type: map_at_3 + value: 32.176 + - type: map_at_5 + value: 33.894999999999996 + - type: mrr_at_1 + value: 31.735000000000003 + - type: mrr_at_10 + value: 40.832 + - type: mrr_at_100 + value: 41.812 + - type: mrr_at_1000 + value: 41.864000000000004 + - type: mrr_at_3 + value: 38.489000000000004 + - type: mrr_at_5 + value: 39.654 + - type: ndcg_at_1 + value: 31.735000000000003 + - type: ndcg_at_10 + value: 41.327999999999996 + - type: ndcg_at_100 + value: 47.565000000000005 + - type: ndcg_at_1000 + value: 49.708000000000006 + - type: ndcg_at_3 + value: 36.391 + - type: ndcg_at_5 + value: 38.489000000000004 + - type: precision_at_1 + value: 31.735000000000003 + - type: precision_at_10 + value: 7.7170000000000005 + - type: precision_at_100 + value: 1.2670000000000001 + - type: precision_at_1000 + value: 0.16199999999999998 + - type: precision_at_3 + value: 17.808 + - type: precision_at_5 + value: 12.534 + - type: recall_at_1 + value: 25.287 + - type: recall_at_10 + value: 53.735 + - type: recall_at_100 + value: 80.149 + - type: recall_at_1000 + value: 94.756 + - type: recall_at_3 + value: 39.475 + - type: recall_at_5 + value: 45.532000000000004 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 26.613 + - type: map_at_10 + value: 36.747416666666666 + - type: map_at_100 + value: 38.091416666666674 + - type: map_at_1000 + value: 38.2075 + - type: map_at_3 + value: 33.630833333333335 + - type: map_at_5 + value: 35.28225 + - type: mrr_at_1 + value: 31.654 + - type: mrr_at_10 + value: 40.94166666666666 + - type: mrr_at_100 + value: 41.85883333333334 + - type: mrr_at_1000 + value: 41.910666666666664 + - type: mrr_at_3 + value: 38.44458333333334 + - type: mrr_at_5 + value: 39.84525000000001 + - type: ndcg_at_1 + value: 31.654 + - type: ndcg_at_10 + value: 42.533 + - type: ndcg_at_100 + value: 48.09741666666667 + - type: ndcg_at_1000 + value: 50.170166666666674 + - type: ndcg_at_3 + value: 37.37858333333333 + - type: ndcg_at_5 + value: 39.666666666666664 + - type: precision_at_1 + value: 31.654 + - type: precision_at_10 + value: 7.649500000000001 + - type: precision_at_100 + value: 1.2425 + - type: precision_at_1000 + value: 0.16175 + - type: precision_at_3 + value: 17.49625 + - type: precision_at_5 + value: 12.410333333333332 + - type: recall_at_1 + value: 26.613 + - type: recall_at_10 + value: 55.33375 + - type: recall_at_100 + value: 79.52791666666667 + - type: recall_at_1000 + value: 93.73391666666667 + - type: recall_at_3 + value: 40.861333333333334 + - type: recall_at_5 + value: 46.84675 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackStatsRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 26.079 + - type: map_at_10 + value: 33.481 + - type: map_at_100 + value: 34.494 + - type: map_at_1000 + value: 34.589999999999996 + - type: map_at_3 + value: 31.165 + - type: map_at_5 + value: 32.482 + - type: mrr_at_1 + value: 29.293999999999997 + - type: mrr_at_10 + value: 36.303000000000004 + - type: mrr_at_100 + value: 37.183 + - type: mrr_at_1000 + value: 37.254 + - type: mrr_at_3 + value: 34.33 + - type: mrr_at_5 + value: 35.519 + - type: ndcg_at_1 + value: 29.293999999999997 + - type: ndcg_at_10 + value: 37.817 + - type: ndcg_at_100 + value: 42.91 + - type: ndcg_at_1000 + value: 45.342 + - type: ndcg_at_3 + value: 33.695 + - type: ndcg_at_5 + value: 35.747 + - type: precision_at_1 + value: 29.293999999999997 + - type: precision_at_10 + value: 5.951 + - type: precision_at_100 + value: 0.9400000000000001 + - type: precision_at_1000 + value: 0.121 + - type: precision_at_3 + value: 14.519000000000002 + - type: precision_at_5 + value: 10.123 + - type: recall_at_1 + value: 26.079 + - type: recall_at_10 + value: 48.27 + - type: recall_at_100 + value: 71.64 + - type: recall_at_1000 + value: 89.775 + - type: recall_at_3 + value: 36.858000000000004 + - type: recall_at_5 + value: 42.013 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackTexRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 18.17 + - type: map_at_10 + value: 26.483 + - type: map_at_100 + value: 27.732 + - type: map_at_1000 + value: 27.864 + - type: map_at_3 + value: 23.76 + - type: map_at_5 + value: 25.290000000000003 + - type: mrr_at_1 + value: 22.436 + - type: mrr_at_10 + value: 30.448999999999998 + - type: mrr_at_100 + value: 31.476 + - type: mrr_at_1000 + value: 31.548 + - type: mrr_at_3 + value: 28.051 + - type: mrr_at_5 + value: 29.421999999999997 + - type: ndcg_at_1 + value: 22.436 + - type: ndcg_at_10 + value: 31.662000000000003 + - type: ndcg_at_100 + value: 37.611 + - type: ndcg_at_1000 + value: 40.439 + - type: ndcg_at_3 + value: 26.939999999999998 + - type: ndcg_at_5 + value: 29.177999999999997 + - type: precision_at_1 + value: 22.436 + - type: precision_at_10 + value: 5.908 + - type: precision_at_100 + value: 1.056 + - type: precision_at_1000 + value: 0.149 + - type: precision_at_3 + value: 12.962000000000002 + - type: precision_at_5 + value: 9.476999999999999 + - type: recall_at_1 + value: 18.17 + - type: recall_at_10 + value: 43.219 + - type: recall_at_100 + value: 70.106 + - type: recall_at_1000 + value: 90.04100000000001 + - type: recall_at_3 + value: 30.023 + - type: recall_at_5 + value: 35.845 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackUnixRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 28.016999999999996 + - type: map_at_10 + value: 38.123000000000005 + - type: map_at_100 + value: 39.367000000000004 + - type: map_at_1000 + value: 39.467999999999996 + - type: map_at_3 + value: 34.836 + - type: map_at_5 + value: 36.661 + - type: mrr_at_1 + value: 33.116 + - type: mrr_at_10 + value: 42.211 + - type: mrr_at_100 + value: 43.118 + - type: mrr_at_1000 + value: 43.169000000000004 + - type: mrr_at_3 + value: 39.521 + - type: mrr_at_5 + value: 41.154 + - type: ndcg_at_1 + value: 33.116 + - type: ndcg_at_10 + value: 43.86 + - type: ndcg_at_100 + value: 49.486000000000004 + - type: ndcg_at_1000 + value: 51.487 + - type: ndcg_at_3 + value: 38.303 + - type: ndcg_at_5 + value: 40.927 + - type: precision_at_1 + value: 33.116 + - type: precision_at_10 + value: 7.649 + - type: precision_at_100 + value: 1.165 + - type: precision_at_1000 + value: 0.145 + - type: precision_at_3 + value: 17.724 + - type: precision_at_5 + value: 12.668 + - type: recall_at_1 + value: 28.016999999999996 + - type: recall_at_10 + value: 57.032000000000004 + - type: recall_at_100 + value: 81.828 + - type: recall_at_1000 + value: 95.273 + - type: recall_at_3 + value: 41.733 + - type: recall_at_5 + value: 48.496 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackWebmastersRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 24.295 + - type: map_at_10 + value: 34.94 + - type: map_at_100 + value: 36.659000000000006 + - type: map_at_1000 + value: 36.902 + - type: map_at_3 + value: 31.562 + - type: map_at_5 + value: 33.28 + - type: mrr_at_1 + value: 29.644 + - type: mrr_at_10 + value: 39.467999999999996 + - type: mrr_at_100 + value: 40.561 + - type: mrr_at_1000 + value: 40.61 + - type: mrr_at_3 + value: 36.759 + - type: mrr_at_5 + value: 38.251000000000005 + - type: ndcg_at_1 + value: 29.644 + - type: ndcg_at_10 + value: 41.376000000000005 + - type: ndcg_at_100 + value: 47.701 + - type: ndcg_at_1000 + value: 49.925999999999995 + - type: ndcg_at_3 + value: 36.009 + - type: ndcg_at_5 + value: 38.23 + - type: precision_at_1 + value: 29.644 + - type: precision_at_10 + value: 8.182 + - type: precision_at_100 + value: 1.672 + - type: precision_at_1000 + value: 0.253 + - type: precision_at_3 + value: 17.325 + - type: precision_at_5 + value: 12.450999999999999 + - type: recall_at_1 + value: 24.295 + - type: recall_at_10 + value: 54.478 + - type: recall_at_100 + value: 81.85 + - type: recall_at_1000 + value: 95.395 + - type: recall_at_3 + value: 39.121 + - type: recall_at_5 + value: 45.465 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackWordpressRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 19.476 + - type: map_at_10 + value: 28.274 + - type: map_at_100 + value: 29.509999999999998 + - type: map_at_1000 + value: 29.614 + - type: map_at_3 + value: 25.413000000000004 + - type: map_at_5 + value: 26.758 + - type: mrr_at_1 + value: 20.887 + - type: mrr_at_10 + value: 29.975 + - type: mrr_at_100 + value: 31.063000000000002 + - type: mrr_at_1000 + value: 31.14 + - type: mrr_at_3 + value: 27.326 + - type: mrr_at_5 + value: 28.666000000000004 + - type: ndcg_at_1 + value: 20.887 + - type: ndcg_at_10 + value: 33.456 + - type: ndcg_at_100 + value: 39.421 + - type: ndcg_at_1000 + value: 41.873 + - type: ndcg_at_3 + value: 27.755000000000003 + - type: ndcg_at_5 + value: 30.032999999999998 + - type: precision_at_1 + value: 20.887 + - type: precision_at_10 + value: 5.601 + - type: precision_at_100 + value: 0.915 + - type: precision_at_1000 + value: 0.125 + - type: precision_at_3 + value: 12.076 + - type: precision_at_5 + value: 8.613999999999999 + - type: recall_at_1 + value: 19.476 + - type: recall_at_10 + value: 47.772999999999996 + - type: recall_at_100 + value: 75.031 + - type: recall_at_1000 + value: 92.96 + - type: recall_at_3 + value: 32.221 + - type: recall_at_5 + value: 37.68 + - task: + type: Retrieval + dataset: + type: climate-fever + name: MTEB ClimateFEVER + config: default + split: test + metrics: + - type: map_at_1 + value: 8.341999999999999 + - type: map_at_10 + value: 14.524000000000001 + - type: map_at_100 + value: 16.114 + - type: map_at_1000 + value: 16.301 + - type: map_at_3 + value: 11.904 + - type: map_at_5 + value: 13.175 + - type: mrr_at_1 + value: 18.892999999999997 + - type: mrr_at_10 + value: 29.185 + - type: mrr_at_100 + value: 30.368000000000002 + - type: mrr_at_1000 + value: 30.418 + - type: mrr_at_3 + value: 25.548 + - type: mrr_at_5 + value: 27.708 + - type: ndcg_at_1 + value: 18.892999999999997 + - type: ndcg_at_10 + value: 21.572 + - type: ndcg_at_100 + value: 28.51 + - type: ndcg_at_1000 + value: 32.204 + - type: ndcg_at_3 + value: 16.753 + - type: ndcg_at_5 + value: 18.5 + - type: precision_at_1 + value: 18.892999999999997 + - type: precision_at_10 + value: 6.997000000000001 + - type: precision_at_100 + value: 1.433 + - type: precision_at_1000 + value: 0.211 + - type: precision_at_3 + value: 12.53 + - type: precision_at_5 + value: 10.098 + - type: recall_at_1 + value: 8.341999999999999 + - type: recall_at_10 + value: 27.215 + - type: recall_at_100 + value: 51.534 + - type: recall_at_1000 + value: 72.655 + - type: recall_at_3 + value: 15.634 + - type: recall_at_5 + value: 20.227 + - task: + type: Retrieval + dataset: + type: dbpedia-entity + name: MTEB DBPedia + config: default + split: test + metrics: + - type: map_at_1 + value: 7.5920000000000005 + - type: map_at_10 + value: 15.42 + - type: map_at_100 + value: 21.269 + - type: map_at_1000 + value: 22.55 + - type: map_at_3 + value: 11.221 + - type: map_at_5 + value: 13.225999999999999 + - type: mrr_at_1 + value: 58.25 + - type: mrr_at_10 + value: 66.237 + - type: mrr_at_100 + value: 66.74799999999999 + - type: mrr_at_1000 + value: 66.762 + - type: mrr_at_3 + value: 64.167 + - type: mrr_at_5 + value: 65.229 + - type: ndcg_at_1 + value: 45.625 + - type: ndcg_at_10 + value: 33.355000000000004 + - type: ndcg_at_100 + value: 37.484 + - type: ndcg_at_1000 + value: 44.523 + - type: ndcg_at_3 + value: 37.879000000000005 + - type: ndcg_at_5 + value: 35.841 + - type: precision_at_1 + value: 58.25 + - type: precision_at_10 + value: 26.450000000000003 + - type: precision_at_100 + value: 8.290000000000001 + - type: precision_at_1000 + value: 1.744 + - type: precision_at_3 + value: 40.75 + - type: precision_at_5 + value: 35.0 + - type: recall_at_1 + value: 7.5920000000000005 + - type: recall_at_10 + value: 20.064 + - type: recall_at_100 + value: 43.187 + - type: recall_at_1000 + value: 66.154 + - type: recall_at_3 + value: 12.366000000000001 + - type: recall_at_5 + value: 15.631 + - task: + type: Classification + dataset: + type: mteb/emotion + name: MTEB EmotionClassification + config: default + split: test + metrics: + - type: accuracy + value: 41.17 + - type: f1 + value: 36.961926373935974 + - task: + type: Retrieval + dataset: + type: fever + name: MTEB FEVER + config: default + split: test + metrics: + - type: map_at_1 + value: 37.361 + - type: map_at_10 + value: 49.407000000000004 + - type: map_at_100 + value: 50.11600000000001 + - type: map_at_1000 + value: 50.151999999999994 + - type: map_at_3 + value: 46.608 + - type: map_at_5 + value: 48.286 + - type: mrr_at_1 + value: 40.204 + - type: mrr_at_10 + value: 52.714000000000006 + - type: mrr_at_100 + value: 53.347 + - type: mrr_at_1000 + value: 53.373000000000005 + - type: mrr_at_3 + value: 49.935 + - type: mrr_at_5 + value: 51.626000000000005 + - type: ndcg_at_1 + value: 40.204 + - type: ndcg_at_10 + value: 55.905 + - type: ndcg_at_100 + value: 59.229 + - type: ndcg_at_1000 + value: 60.077000000000005 + - type: ndcg_at_3 + value: 50.367 + - type: ndcg_at_5 + value: 53.291999999999994 + - type: precision_at_1 + value: 40.204 + - type: precision_at_10 + value: 8.0 + - type: precision_at_100 + value: 0.979 + - type: precision_at_1000 + value: 0.106 + - type: precision_at_3 + value: 20.997 + - type: precision_at_5 + value: 14.215 + - type: recall_at_1 + value: 37.361 + - type: recall_at_10 + value: 72.775 + - type: recall_at_100 + value: 87.883 + - type: recall_at_1000 + value: 94.204 + - type: recall_at_3 + value: 57.830000000000005 + - type: recall_at_5 + value: 64.888 + - task: + type: Retrieval + dataset: + type: fiqa + name: MTEB FiQA2018 + config: default + split: test + metrics: + - type: map_at_1 + value: 18.257 + - type: map_at_10 + value: 29.694 + - type: map_at_100 + value: 31.593 + - type: map_at_1000 + value: 31.795 + - type: map_at_3 + value: 25.778000000000002 + - type: map_at_5 + value: 27.901999999999997 + - type: mrr_at_1 + value: 36.574 + - type: mrr_at_10 + value: 45.562000000000005 + - type: mrr_at_100 + value: 46.479 + - type: mrr_at_1000 + value: 46.52 + - type: mrr_at_3 + value: 43.184 + - type: mrr_at_5 + value: 44.558 + - type: ndcg_at_1 + value: 36.574 + - type: ndcg_at_10 + value: 37.274 + - type: ndcg_at_100 + value: 44.379000000000005 + - type: ndcg_at_1000 + value: 47.803000000000004 + - type: ndcg_at_3 + value: 33.999 + - type: ndcg_at_5 + value: 34.927 + - type: precision_at_1 + value: 36.574 + - type: precision_at_10 + value: 10.571 + - type: precision_at_100 + value: 1.779 + - type: precision_at_1000 + value: 0.23700000000000002 + - type: precision_at_3 + value: 22.942 + - type: precision_at_5 + value: 16.944 + - type: recall_at_1 + value: 18.257 + - type: recall_at_10 + value: 43.46 + - type: recall_at_100 + value: 70.017 + - type: recall_at_1000 + value: 90.838 + - type: recall_at_3 + value: 30.520999999999997 + - type: recall_at_5 + value: 35.977 + - task: + type: Retrieval + dataset: + type: hotpotqa + name: MTEB HotpotQA + config: default + split: test + metrics: + - type: map_at_1 + value: 25.935000000000002 + - type: map_at_10 + value: 35.96 + - type: map_at_100 + value: 36.811 + - type: map_at_1000 + value: 36.894 + - type: map_at_3 + value: 33.479 + - type: map_at_5 + value: 34.93 + - type: mrr_at_1 + value: 51.870000000000005 + - type: mrr_at_10 + value: 59.671 + - type: mrr_at_100 + value: 60.153 + - type: mrr_at_1000 + value: 60.183 + - type: mrr_at_3 + value: 57.815000000000005 + - type: mrr_at_5 + value: 58.965999999999994 + - type: ndcg_at_1 + value: 51.870000000000005 + - type: ndcg_at_10 + value: 44.589 + - type: ndcg_at_100 + value: 48.113 + - type: ndcg_at_1000 + value: 49.962 + - type: ndcg_at_3 + value: 40.304 + - type: ndcg_at_5 + value: 42.543 + - type: precision_at_1 + value: 51.870000000000005 + - type: precision_at_10 + value: 9.454 + - type: precision_at_100 + value: 1.225 + - type: precision_at_1000 + value: 0.147 + - type: precision_at_3 + value: 25.131999999999998 + - type: precision_at_5 + value: 16.851 + - type: recall_at_1 + value: 25.935000000000002 + - type: recall_at_10 + value: 47.272 + - type: recall_at_100 + value: 61.229 + - type: recall_at_1000 + value: 73.55199999999999 + - type: recall_at_3 + value: 37.698 + - type: recall_at_5 + value: 42.126999999999995 + - task: + type: Classification + dataset: + type: mteb/imdb + name: MTEB ImdbClassification + config: default + split: test + metrics: + - type: accuracy + value: 59.76079999999999 + - type: ap + value: 55.90381572041755 + - type: f1 + value: 58.99832553463791 + - task: + type: Retrieval + dataset: + type: msmarco + name: MTEB MSMARCO + config: default + split: dev + metrics: + - type: map_at_1 + value: 20.666999999999998 + - type: map_at_10 + value: 32.425 + - type: map_at_100 + value: 33.586 + - type: map_at_1000 + value: 33.643 + - type: map_at_3 + value: 28.836000000000002 + - type: map_at_5 + value: 30.847 + - type: mrr_at_1 + value: 21.275 + - type: mrr_at_10 + value: 33.062999999999995 + - type: mrr_at_100 + value: 34.168 + - type: mrr_at_1000 + value: 34.217999999999996 + - type: mrr_at_3 + value: 29.491 + - type: mrr_at_5 + value: 31.502999999999997 + - type: ndcg_at_1 + value: 21.246000000000002 + - type: ndcg_at_10 + value: 39.034 + - type: ndcg_at_100 + value: 44.768 + - type: ndcg_at_1000 + value: 46.2 + - type: ndcg_at_3 + value: 31.652 + - type: ndcg_at_5 + value: 35.257 + - type: precision_at_1 + value: 21.246000000000002 + - type: precision_at_10 + value: 6.196 + - type: precision_at_100 + value: 0.909 + - type: precision_at_1000 + value: 0.10300000000000001 + - type: precision_at_3 + value: 13.547999999999998 + - type: precision_at_5 + value: 9.946000000000002 + - type: recall_at_1 + value: 20.666999999999998 + - type: recall_at_10 + value: 59.321999999999996 + - type: recall_at_100 + value: 86.158 + - type: recall_at_1000 + value: 97.154 + - type: recall_at_3 + value: 39.160000000000004 + - type: recall_at_5 + value: 47.82 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (en) + config: en + split: test + metrics: + - type: accuracy + value: 91.89922480620154 + - type: f1 + value: 91.66762682851963 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (de) + config: de + split: test + metrics: + - type: accuracy + value: 72.03719357565511 + - type: f1 + value: 68.75742308679864 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (es) + config: es + split: test + metrics: + - type: accuracy + value: 72.98532354903269 + - type: f1 + value: 71.33173021994274 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (fr) + config: fr + split: test + metrics: + - type: accuracy + value: 75.59348575007829 + - type: f1 + value: 73.1511918522243 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (hi) + config: hi + split: test + metrics: + - type: accuracy + value: 40.36213696665471 + - type: f1 + value: 37.865703085609475 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (th) + config: th + split: test + metrics: + - type: accuracy + value: 17.099457504520796 + - type: f1 + value: 12.86835498185132 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (en) + config: en + split: test + metrics: + - type: accuracy + value: 62.83629730962153 + - type: f1 + value: 44.241027031016735 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (de) + config: de + split: test + metrics: + - type: accuracy + value: 43.412228796844175 + - type: f1 + value: 25.96122949091921 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (es) + config: es + split: test + metrics: + - type: accuracy + value: 41.8812541694463 + - type: f1 + value: 27.93481154758236 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (fr) + config: fr + split: test + metrics: + - type: accuracy + value: 38.93830253679925 + - type: f1 + value: 25.820783392796052 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (hi) + config: hi + split: test + metrics: + - type: accuracy + value: 17.7518823951237 + - type: f1 + value: 11.681226129204576 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (th) + config: th + split: test + metrics: + - type: accuracy + value: 5.631103074141048 + - type: f1 + value: 2.046543337618445 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (af) + config: af + split: test + metrics: + - type: accuracy + value: 38.94082044384667 + - type: f1 + value: 36.222023448848596 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (am) + config: am + split: test + metrics: + - type: accuracy + value: 2.451244115669133 + - type: f1 + value: 1.1859369824825732 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (ar) + config: ar + split: test + metrics: + - type: accuracy + value: 20.938130464021523 + - type: f1 + value: 17.984223607695032 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (az) + config: az + split: test + metrics: + - type: accuracy + value: 34.25016812373907 + - type: f1 + value: 33.954933856088616 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (bn) + config: bn + split: test + metrics: + - type: accuracy + value: 13.665097511768659 + - type: f1 + value: 12.091606412618153 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (cy) + config: cy + split: test + metrics: + - type: accuracy + value: 35.7128446536651 + - type: f1 + value: 33.62071051640523 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (da) + config: da + split: test + metrics: + - type: accuracy + value: 44.425016812373904 + - type: f1 + value: 41.20770166767181 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (de) + config: de + split: test + metrics: + - type: accuracy + value: 44.1661062542031 + - type: f1 + value: 40.374580049860995 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (el) + config: el + split: test + metrics: + - type: accuracy + value: 28.698722259583054 + - type: f1 + value: 24.131330009557754 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (en) + config: en + split: test + metrics: + - type: accuracy + value: 67.14862138533961 + - type: f1 + value: 65.29267177342918 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (es) + config: es + split: test + metrics: + - type: accuracy + value: 40.907868190988566 + - type: f1 + value: 39.705805513162154 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (fa) + config: fa + split: test + metrics: + - type: accuracy + value: 23.517148621385342 + - type: f1 + value: 20.450403227141454 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (fi) + config: fi + split: test + metrics: + - type: accuracy + value: 39.27370544720915 + - type: f1 + value: 36.44557663703388 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (fr) + config: fr + split: test + metrics: + - type: accuracy + value: 44.81506388702085 + - type: f1 + value: 42.61335088326293 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (he) + config: he + split: test + metrics: + - type: accuracy + value: 23.648285137861468 + - type: f1 + value: 19.948568467541378 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (hi) + config: hi + split: test + metrics: + - type: accuracy + value: 17.97579018157364 + - type: f1 + value: 16.06739661356912 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (hu) + config: hu + split: test + metrics: + - type: accuracy + value: 37.995965030262276 + - type: f1 + value: 35.26841971527663 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (hy) + config: hy + split: test + metrics: + - type: accuracy + value: 8.691997310020176 + - type: f1 + value: 7.237344584036491 + - 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type: accuracy + value: 18.31540013449899 + - type: f1 + value: 13.491482848005418 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (tl) + config: tl + split: test + metrics: + - type: accuracy + value: 48.305312710154666 + - type: f1 + value: 45.48790821413181 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (tr) + config: tr + split: test + metrics: + - type: accuracy + value: 41.792199058507066 + - type: f1 + value: 41.24552662271258 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (ur) + config: ur + split: test + metrics: + - type: accuracy + value: 24.462004034969738 + - type: f1 + value: 22.270575649981797 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (vi) + config: vi + split: test + metrics: + - type: accuracy + value: 40.94149293880296 + - type: f1 + value: 39.08540872012287 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (zh-CN) + config: zh-CN + split: test + metrics: + - type: accuracy + value: 33.17753866845998 + - type: f1 + value: 31.64001182395128 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (zh-TW) + config: zh-TW + split: test + metrics: + - type: accuracy + value: 31.15669132481506 + - type: f1 + value: 30.89137619124565 + - task: + type: Clustering + dataset: + type: mteb/medrxiv-clustering-p2p + name: MTEB MedrxivClusteringP2P + config: default + split: test + metrics: + - type: v_measure + value: 34.24621118290122 + - task: + type: Clustering + dataset: + type: mteb/medrxiv-clustering-s2s + name: MTEB MedrxivClusteringS2S + config: default + split: test + metrics: + - type: v_measure + value: 32.24202424478886 + - task: + type: Reranking + dataset: + type: mteb/mind_small + name: MTEB MindSmallReranking + config: default + split: test + metrics: + - type: map + value: 31.024522945679166 + - type: mrr + value: 32.018722362966635 + - task: + type: Retrieval + dataset: + type: nfcorpus + name: MTEB NFCorpus + config: default + split: test + metrics: + - type: map_at_1 + value: 5.156000000000001 + - type: map_at_10 + value: 11.551 + - type: map_at_100 + value: 14.938 + - type: map_at_1000 + value: 16.366 + - type: map_at_3 + value: 8.118 + - type: map_at_5 + value: 9.918000000000001 + - type: mrr_at_1 + value: 42.415000000000006 + - type: mrr_at_10 + value: 51.571999999999996 + - type: mrr_at_100 + value: 52.126 + - type: mrr_at_1000 + value: 52.171 + - type: mrr_at_3 + value: 49.02 + - type: mrr_at_5 + value: 50.50599999999999 + - type: ndcg_at_1 + value: 39.783 + - type: ndcg_at_10 + value: 32.25 + - type: ndcg_at_100 + value: 30.089 + - type: ndcg_at_1000 + value: 38.86 + - type: ndcg_at_3 + value: 36.962 + - type: ndcg_at_5 + value: 35.292 + - type: precision_at_1 + value: 41.796 + - type: precision_at_10 + value: 24.272 + - type: precision_at_100 + value: 7.963000000000001 + - type: precision_at_1000 + value: 2.07 + - type: precision_at_3 + value: 35.397 + - type: precision_at_5 + value: 31.022 + - type: recall_at_1 + value: 5.156000000000001 + - type: recall_at_10 + value: 15.468000000000002 + - type: recall_at_100 + value: 31.049 + - type: recall_at_1000 + value: 63.148 + - type: recall_at_3 + value: 9.078999999999999 + - type: recall_at_5 + value: 12.275 + - task: + type: Retrieval + dataset: + type: nq + name: MTEB NQ + config: default + split: test + metrics: + - type: map_at_1 + value: 23.672 + - type: map_at_10 + value: 38.452 + - type: map_at_100 + value: 39.705 + - type: map_at_1000 + value: 39.742 + - type: map_at_3 + value: 33.806999999999995 + - type: map_at_5 + value: 36.576 + - type: mrr_at_1 + value: 26.854 + - type: mrr_at_10 + value: 40.822 + - type: mrr_at_100 + value: 41.801 + - type: mrr_at_1000 + value: 41.827999999999996 + - type: mrr_at_3 + value: 36.824 + - type: mrr_at_5 + value: 39.312000000000005 + - type: ndcg_at_1 + value: 26.854 + - type: ndcg_at_10 + value: 46.469 + - type: ndcg_at_100 + value: 51.756 + - type: ndcg_at_1000 + value: 52.601 + - type: ndcg_at_3 + value: 37.623 + - type: ndcg_at_5 + value: 42.324 + - type: precision_at_1 + value: 26.854 + - type: precision_at_10 + value: 8.189 + - type: precision_at_100 + value: 1.11 + - type: precision_at_1000 + value: 0.11900000000000001 + - type: precision_at_3 + value: 17.718999999999998 + - type: precision_at_5 + value: 13.291 + - type: recall_at_1 + value: 23.672 + - type: recall_at_10 + value: 68.639 + - type: recall_at_100 + value: 91.546 + - type: recall_at_1000 + value: 97.794 + - type: recall_at_3 + value: 45.643 + - type: recall_at_5 + value: 56.523 + - task: + type: Retrieval + dataset: + type: quora + name: MTEB QuoraRetrieval + config: default + split: test + metrics: + - type: map_at_1 + value: 69.667 + - type: map_at_10 + value: 83.83500000000001 + - type: map_at_100 + value: 84.479 + - type: map_at_1000 + value: 84.494 + - type: map_at_3 + value: 80.759 + - type: map_at_5 + value: 82.657 + - type: mrr_at_1 + value: 80.46 + - type: mrr_at_10 + value: 86.83800000000001 + - type: mrr_at_100 + value: 86.944 + - type: mrr_at_1000 + value: 86.945 + - type: mrr_at_3 + value: 85.815 + - type: mrr_at_5 + value: 86.508 + - type: ndcg_at_1 + value: 80.46 + - type: ndcg_at_10 + value: 87.752 + - type: ndcg_at_100 + value: 88.973 + - type: ndcg_at_1000 + value: 89.072 + - type: ndcg_at_3 + value: 84.735 + - type: ndcg_at_5 + value: 86.371 + - type: precision_at_1 + value: 80.46 + - type: precision_at_10 + value: 13.452 + - type: precision_at_100 + value: 1.532 + - type: precision_at_1000 + value: 0.157 + - type: precision_at_3 + value: 37.187 + - type: precision_at_5 + value: 24.5 + - type: recall_at_1 + value: 69.667 + - type: recall_at_10 + value: 95.329 + - type: recall_at_100 + value: 99.52 + - type: recall_at_1000 + value: 99.991 + - type: recall_at_3 + value: 86.696 + - type: recall_at_5 + value: 91.346 + - task: + type: Clustering + dataset: + type: mteb/reddit-clustering + name: MTEB RedditClustering + config: default + split: test + metrics: + - type: v_measure + value: 51.177545122684634 + - task: + type: Clustering + dataset: + type: mteb/reddit-clustering-p2p + name: MTEB RedditClusteringP2P + config: default + split: test + metrics: + - type: v_measure + value: 54.804652123126985 + - task: + type: Retrieval + dataset: + type: scidocs + name: MTEB SCIDOCS + config: default + split: test + metrics: + - type: map_at_1 + value: 5.162 + - type: map_at_10 + value: 13.168 + - type: map_at_100 + value: 15.766 + - type: map_at_1000 + value: 16.136 + - type: map_at_3 + value: 9.180000000000001 + - type: map_at_5 + value: 11.205 + - type: mrr_at_1 + value: 25.5 + - type: mrr_at_10 + value: 36.617 + - type: mrr_at_100 + value: 37.814 + - type: mrr_at_1000 + value: 37.86 + - type: mrr_at_3 + value: 33.15 + - type: mrr_at_5 + value: 35.29 + - type: ndcg_at_1 + value: 25.5 + - type: ndcg_at_10 + value: 21.818 + - type: ndcg_at_100 + value: 31.302999999999997 + - type: ndcg_at_1000 + value: 37.175000000000004 + - type: ndcg_at_3 + value: 20.358999999999998 + - type: ndcg_at_5 + value: 18.169 + - type: precision_at_1 + value: 25.5 + - type: precision_at_10 + value: 11.32 + - type: precision_at_100 + value: 2.495 + - type: precision_at_1000 + value: 0.38899999999999996 + - type: precision_at_3 + value: 18.833 + - type: precision_at_5 + value: 16.06 + - type: recall_at_1 + value: 5.162 + - type: recall_at_10 + value: 22.932 + - type: recall_at_100 + value: 50.598 + - type: recall_at_1000 + value: 79.053 + - type: recall_at_3 + value: 11.442 + - type: recall_at_5 + value: 16.272000000000002 + - task: + type: STS + dataset: + type: mteb/sickr-sts + name: MTEB SICK-R + config: default + split: test + metrics: + - type: cos_sim_pearson + value: 84.73414727754201 + - type: cos_sim_spearman + value: 79.3180820145488 + - type: euclidean_pearson + value: 81.33251162244008 + - type: euclidean_spearman + value: 79.31808410123591 + - type: manhattan_pearson + value: 81.24535628962194 + - type: manhattan_spearman + value: 79.18643136990889 + - task: + type: STS + dataset: + type: mteb/sts12-sts + name: MTEB STS12 + config: default + split: test + metrics: + - type: cos_sim_pearson + value: 82.89241604274538 + - type: cos_sim_spearman + value: 73.08329002776462 + - type: euclidean_pearson + value: 78.75856902522398 + - type: euclidean_spearman + value: 73.0808569122323 + - type: manhattan_pearson + value: 78.81165127939924 + - type: manhattan_spearman + value: 73.13358160467396 + - task: + type: STS + dataset: + type: mteb/sts13-sts + name: MTEB STS13 + config: default + split: test + metrics: + - type: cos_sim_pearson + value: 81.65439991719452 + - type: cos_sim_spearman + value: 82.13398891011764 + - type: euclidean_pearson + value: 81.63807492339613 + - type: euclidean_spearman + value: 82.13398891011764 + - type: manhattan_pearson + value: 81.5983078333819 + - type: manhattan_spearman + value: 82.11893098949203 + - task: + type: STS + dataset: + type: mteb/sts14-sts + name: MTEB STS14 + config: default + split: test + metrics: + - type: cos_sim_pearson + value: 81.66945263546415 + - type: cos_sim_spearman + value: 76.7342099954029 + - type: euclidean_pearson + value: 79.98454905286438 + - type: euclidean_spearman + value: 76.73420731947648 + - type: manhattan_pearson + value: 79.98121513026915 + - type: manhattan_spearman + value: 76.74818574618494 + - task: + type: STS + dataset: + type: mteb/sts15-sts + name: MTEB STS15 + config: default + split: test + metrics: + - type: cos_sim_pearson + value: 84.80085528616004 + - type: cos_sim_spearman + value: 85.57752600637704 + - type: euclidean_pearson + value: 84.88803602633503 + - type: euclidean_spearman + value: 85.57753174543699 + - type: manhattan_pearson + value: 84.77107707460819 + - type: manhattan_spearman + value: 85.4531691739887 + - task: + type: STS + dataset: + type: mteb/sts16-sts + name: MTEB STS16 + config: default + split: test + metrics: + - type: cos_sim_pearson + value: 79.32666585707851 + - type: cos_sim_spearman + value: 80.22692417222228 + - type: euclidean_pearson + value: 79.847799005588 + - type: euclidean_spearman + value: 80.22692417222228 + - type: manhattan_pearson + value: 79.86640649752613 + - type: manhattan_spearman + value: 80.25939898948658 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (ko-ko) + config: ko-ko + split: test + metrics: + - type: cos_sim_pearson + value: 36.97351108396674 + - type: cos_sim_spearman + value: 43.373159642451846 + - type: euclidean_pearson + value: 42.343251342924724 + - type: euclidean_spearman + value: 43.37383732365708 + - type: manhattan_pearson + value: 42.21420013714062 + - type: manhattan_spearman + value: 43.27093471564943 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (ar-ar) + config: ar-ar + split: test + metrics: + - type: cos_sim_pearson + value: 54.25766812232355 + - type: cos_sim_spearman + value: 58.70907752953121 + - type: euclidean_pearson + value: 57.74925638384565 + - type: euclidean_spearman + value: 58.70907752953121 + - type: manhattan_pearson + value: 57.53107164585081 + - type: manhattan_spearman + value: 58.18399071690873 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (en-ar) + config: en-ar + split: test + metrics: + - type: cos_sim_pearson + value: 2.000902150291317 + - type: cos_sim_spearman + value: 0.5442319876381565 + - type: euclidean_pearson + value: 2.0061692624223886 + - type: euclidean_spearman + value: 0.5442319876381565 + - type: manhattan_pearson + value: 1.6005243901065973 + - type: manhattan_spearman + value: 0.8261501538578374 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (en-de) + config: en-de + split: test + metrics: + - type: cos_sim_pearson + value: 31.103076250241756 + - type: cos_sim_spearman + value: 27.538399556865983 + - type: euclidean_pearson + value: 31.299966953719917 + - type: euclidean_spearman + value: 27.538399556865983 + - type: manhattan_pearson + value: 29.252983940152795 + - type: manhattan_spearman + value: 24.545142053308506 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (en-en) + config: en-en + split: test + metrics: + - type: cos_sim_pearson + value: 88.92662843843466 + - type: cos_sim_spearman + value: 88.6282754793921 + - type: euclidean_pearson + value: 88.9663425476392 + - type: euclidean_spearman + value: 88.6282754793921 + - type: manhattan_pearson + value: 89.04213757202741 + - type: manhattan_spearman + value: 88.8029452722001 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (en-tr) + config: en-tr + split: test + metrics: + - type: cos_sim_pearson + value: 6.699439791440673 + - type: cos_sim_spearman + value: 0.42741621491041054 + - type: euclidean_pearson + value: 7.0939749740816485 + - type: euclidean_spearman + value: 0.42741621491041054 + - type: manhattan_pearson + value: 3.7604205840813005 + - type: manhattan_spearman + value: -1.7995925853478083 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (es-en) + config: es-en + split: test + metrics: + - type: cos_sim_pearson + value: 22.332768127048812 + - type: cos_sim_spearman + value: 22.011862055263386 + - type: euclidean_pearson + value: 22.275743114886957 + - type: euclidean_spearman + value: 22.011862055263386 + - type: manhattan_pearson + value: 21.382471306976754 + - type: manhattan_spearman + value: 20.5220742340821 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (es-es) + config: es-es + split: test + metrics: + - type: cos_sim_pearson + value: 78.59529102081041 + - type: cos_sim_spearman + value: 78.36515013988296 + - type: euclidean_pearson + value: 79.6578967101581 + - type: euclidean_spearman + value: 78.36388790924713 + - type: manhattan_pearson + value: 79.54080618487365 + - type: manhattan_spearman + value: 78.03366107978795 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (fr-en) + config: fr-en + split: test + metrics: + - type: cos_sim_pearson + value: 34.19498070710533 + - type: cos_sim_spearman + value: 30.702559767030923 + - type: euclidean_pearson + value: 34.28061977250095 + - type: euclidean_spearman + value: 30.702559767030923 + - type: manhattan_pearson + value: 34.8122111793038 + - type: manhattan_spearman + value: 31.40796587790667 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (it-en) + config: it-en + split: test + metrics: + - type: cos_sim_pearson + value: 25.84186641167081 + - type: cos_sim_spearman + value: 24.28452119168039 + - type: euclidean_pearson + value: 25.866557000478302 + - type: euclidean_spearman + value: 24.28452119168039 + - type: manhattan_pearson + value: 24.273876016721925 + - type: manhattan_spearman + value: 23.66844883927423 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (nl-en) + config: nl-en + split: test + metrics: + - type: cos_sim_pearson + value: 31.68262883322153 + - type: cos_sim_spearman + value: 24.508086225784982 + - type: euclidean_pearson + value: 32.07775246994894 + - type: euclidean_spearman + value: 24.508086225784982 + - type: manhattan_pearson + value: 33.20196765495327 + - type: manhattan_spearman + value: 27.383641505403627 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (en) + config: en + split: test + metrics: + - type: cos_sim_pearson + value: 66.82398288868168 + - type: cos_sim_spearman + value: 65.6697261994716 + - type: euclidean_pearson + value: 66.84746542331361 + - type: euclidean_spearman + value: 65.6697261994716 + - type: manhattan_pearson + value: 66.89947196080837 + - type: manhattan_spearman + value: 65.61734245758937 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (de) + config: de + split: test + metrics: + - type: cos_sim_pearson + value: 18.956935297479266 + - type: cos_sim_spearman + value: 22.525438836468805 + - type: euclidean_pearson + value: 13.676185827963197 + - type: euclidean_spearman + value: 22.525438836468805 + - type: manhattan_pearson + value: 13.749488574260106 + - type: manhattan_spearman + value: 22.49725541226794 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (es) + config: es + split: test + metrics: + - type: cos_sim_pearson + value: 43.159634114474954 + - type: cos_sim_spearman + value: 43.97530387822291 + - type: euclidean_pearson + value: 42.45018759035119 + - type: euclidean_spearman + value: 43.97530387822291 + - type: manhattan_pearson + value: 43.88212906018782 + - type: manhattan_spearman + value: 44.2344991447187 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (pl) + config: pl + split: test + metrics: + - type: cos_sim_pearson + value: 2.9506287366804567 + - type: cos_sim_spearman + value: 19.21860340477442 + - type: euclidean_pearson + value: 6.306031200912426 + - type: euclidean_spearman + value: 19.21860340477442 + - type: manhattan_pearson + value: 5.968058806485322 + - type: manhattan_spearman + value: 18.496966556101356 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (tr) + config: tr + split: test + metrics: + - type: cos_sim_pearson + value: 17.494702940326327 + - type: cos_sim_spearman + value: 21.600665598855933 + - type: euclidean_pearson + value: 19.949878763475876 + - type: euclidean_spearman + value: 21.600665598855933 + - type: manhattan_pearson + value: 20.562737979747386 + - type: manhattan_spearman + value: 21.548415116687096 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (ar) + config: ar + split: test + metrics: + - type: cos_sim_pearson + value: 21.455304899947475 + - type: cos_sim_spearman + value: 17.54247841644246 + - type: euclidean_pearson + value: 19.954769470444862 + - type: euclidean_spearman + value: 17.54247841644246 + - type: manhattan_pearson + value: 20.491628523649304 + - type: manhattan_spearman + value: 17.984509706975498 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (ru) + config: ru + split: test + metrics: + - type: cos_sim_pearson + value: 5.725870260172754 + - type: cos_sim_spearman + value: 11.187514830423046 + - type: euclidean_pearson + value: 5.917124931676964 + - type: euclidean_spearman + value: 11.187514830423046 + - type: manhattan_pearson + value: 6.374841892742465 + - type: manhattan_spearman + value: 10.769670996439327 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (zh) + config: zh + split: test + metrics: + - type: cos_sim_pearson + value: 23.644675903928903 + - type: cos_sim_spearman + value: 33.1476054705555 + - type: euclidean_pearson + value: 27.486723401317015 + - type: euclidean_spearman + value: 33.14559867176513 + - type: manhattan_pearson + value: 28.905530853992335 + - type: manhattan_spearman + value: 32.97179552695711 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (fr) + config: fr + split: test + metrics: + - type: cos_sim_pearson + value: 68.19096417445061 + - type: cos_sim_spearman + value: 69.51402658537921 + - type: euclidean_pearson + value: 65.89836450895854 + - type: euclidean_spearman + value: 69.51402658537921 + - type: manhattan_pearson + value: 65.95918282706997 + - type: manhattan_spearman + value: 69.66631782067878 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (de-en) + config: de-en + split: test + metrics: + - type: cos_sim_pearson + value: 47.02727261965111 + - type: cos_sim_spearman + value: 42.85739641224728 + - type: euclidean_pearson + value: 47.55857919944314 + - type: euclidean_spearman + value: 42.85739641224728 + - type: manhattan_pearson + value: 50.24947623020984 + - type: manhattan_spearman + value: 44.34581665268886 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (es-en) + config: es-en + split: test + metrics: + - type: cos_sim_pearson + value: 52.54253509229287 + - type: cos_sim_spearman + value: 53.98864875959218 + - type: euclidean_pearson + value: 52.771474843725464 + - type: euclidean_spearman + value: 53.98864875959218 + - type: manhattan_pearson + value: 53.39728391060008 + - type: manhattan_spearman + value: 54.65413858996554 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (it) + config: it + split: test + metrics: + - type: cos_sim_pearson + value: 48.017241684543656 + - type: cos_sim_spearman + value: 47.47536430344332 + - type: euclidean_pearson + value: 46.94098755337956 + - type: euclidean_spearman + value: 47.47536430344332 + - type: manhattan_pearson + value: 47.27489495136295 + - type: manhattan_spearman + value: 47.75408075281176 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (pl-en) + config: pl-en + split: test + metrics: + - type: cos_sim_pearson + value: 43.16723254329198 + - type: cos_sim_spearman + value: 42.6695846628273 + - type: euclidean_pearson + value: 43.37634781317223 + - type: euclidean_spearman + value: 42.6695846628273 + - type: manhattan_pearson + value: 46.43632735525556 + - type: manhattan_spearman + value: 44.399080708250175 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (zh-en) + config: zh-en + split: test + metrics: + - type: cos_sim_pearson + value: 42.614472380988 + - type: cos_sim_spearman + value: 44.386615916921755 + - type: euclidean_pearson + value: 42.602921485579536 + - type: euclidean_spearman + value: 44.386615916921755 + - type: manhattan_pearson + value: 39.57742966805997 + - type: manhattan_spearman + value: 41.12937281700849 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (es-it) + config: es-it + split: test + metrics: + - type: cos_sim_pearson + value: 41.19025498086497 + - type: cos_sim_spearman + value: 40.70511339346037 + - type: euclidean_pearson + value: 41.757361379987536 + - type: euclidean_spearman + value: 40.70511339346037 + - type: manhattan_pearson + value: 42.12654868854391 + - type: manhattan_spearman + value: 40.16977290096036 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (de-fr) + config: de-fr + split: test + metrics: + - type: cos_sim_pearson + value: 42.58930629526249 + - type: cos_sim_spearman + value: 43.51970789091437 + - type: euclidean_pearson + value: 42.79780567751299 + - type: euclidean_spearman + value: 43.51970789091437 + - type: manhattan_pearson + value: 43.11190678703615 + - type: manhattan_spearman + value: 43.921331076552214 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (de-pl) + config: de-pl + split: test + metrics: + - type: cos_sim_pearson + value: 9.14354524166508 + - type: cos_sim_spearman + value: 1.632087485480262 + - type: euclidean_pearson + value: 9.808059926397586 + - type: euclidean_spearman + value: 1.632087485480262 + - type: manhattan_pearson + value: 15.655877492684972 + - type: manhattan_spearman + value: 9.084260532390138 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (fr-pl) + config: fr-pl + split: test + metrics: + - type: cos_sim_pearson + value: 16.116974803470246 + - type: cos_sim_spearman + value: 16.903085094570333 + - type: euclidean_pearson + value: 16.277560475636694 + - type: euclidean_spearman + value: 16.903085094570333 + - type: manhattan_pearson + value: 20.321632312194925 + - type: manhattan_spearman + value: 28.17180849095055 + - task: + type: STS + dataset: + type: mteb/stsbenchmark-sts + name: MTEB STSBenchmark + config: default + split: test + metrics: + - type: cos_sim_pearson + value: 83.75945741541354 + - type: cos_sim_spearman + value: 83.08944658809418 + - type: euclidean_pearson + value: 83.5587988852494 + - type: euclidean_spearman + value: 83.08938533093635 + - type: manhattan_pearson + value: 83.56896467262781 + - type: manhattan_spearman + value: 83.11516183577004 + - task: + type: Reranking + dataset: + type: mteb/scidocs-reranking + name: MTEB SciDocsRR + config: default + split: test + metrics: + - type: map + value: 87.20127714147824 + - type: mrr + value: 96.44415315983943 + - task: + type: Retrieval + dataset: + type: scifact + name: MTEB SciFact + config: default + split: test + metrics: + - type: map_at_1 + value: 47.483 + - type: map_at_10 + value: 57.18600000000001 + - type: map_at_100 + value: 57.863 + - type: map_at_1000 + value: 57.901 + - type: map_at_3 + value: 53.909 + - type: map_at_5 + value: 55.57299999999999 + - type: mrr_at_1 + value: 50.0 + - type: mrr_at_10 + value: 58.607 + - type: mrr_at_100 + value: 59.169000000000004 + - type: mrr_at_1000 + value: 59.207 + - type: mrr_at_3 + value: 56.056 + - type: mrr_at_5 + value: 57.422 + - type: ndcg_at_1 + value: 50.0 + - type: ndcg_at_10 + value: 62.639 + - type: ndcg_at_100 + value: 65.549 + - type: ndcg_at_1000 + value: 66.497 + - type: ndcg_at_3 + value: 56.602 + - type: ndcg_at_5 + value: 59.270999999999994 + - type: precision_at_1 + value: 50.0 + - type: precision_at_10 + value: 8.833 + - type: precision_at_100 + value: 1.0370000000000001 + - type: precision_at_1000 + value: 0.11100000000000002 + - type: precision_at_3 + value: 22.222 + - type: precision_at_5 + value: 15.0 + - type: recall_at_1 + value: 47.483 + - type: recall_at_10 + value: 78.233 + - type: recall_at_100 + value: 91.167 + - type: recall_at_1000 + value: 98.333 + - type: recall_at_3 + value: 61.956 + - type: recall_at_5 + value: 68.43900000000001 + - task: + type: PairClassification + dataset: + type: mteb/sprintduplicatequestions-pairclassification + name: MTEB SprintDuplicateQuestions + config: default + split: test + metrics: + - type: cos_sim_accuracy + value: 99.72871287128713 + - type: cos_sim_ap + value: 92.44554820122362 + - type: cos_sim_f1 + value: 85.89083419155509 + - type: cos_sim_precision + value: 88.53503184713377 + - type: cos_sim_recall + value: 83.39999999999999 + - type: dot_accuracy + value: 99.72871287128713 + - type: dot_ap + value: 92.44554820122363 + - type: dot_f1 + value: 85.89083419155509 + - type: dot_precision + value: 88.53503184713377 + - type: dot_recall + value: 83.39999999999999 + - type: euclidean_accuracy + value: 99.72871287128713 + - type: euclidean_ap + value: 92.44554820122362 + - type: euclidean_f1 + value: 85.89083419155509 + - type: euclidean_precision + value: 88.53503184713377 + - type: euclidean_recall + value: 83.39999999999999 + - type: manhattan_accuracy + value: 99.73267326732673 + - type: manhattan_ap + value: 92.57860510428624 + - type: manhattan_f1 + value: 86.20170597089813 + - type: manhattan_precision + value: 86.5055387713998 + - type: manhattan_recall + value: 85.9 + - type: max_accuracy + value: 99.73267326732673 + - type: max_ap + value: 92.57860510428624 + - type: max_f1 + value: 86.20170597089813 + - task: + type: Clustering + dataset: + type: mteb/stackexchange-clustering + name: MTEB StackExchangeClustering + config: default + split: test + metrics: + - type: v_measure + value: 53.04887987709521 + - task: + type: Clustering + dataset: + type: mteb/stackexchange-clustering-p2p + name: MTEB StackExchangeClusteringP2P + config: default + split: test + metrics: + - type: v_measure + value: 33.133116286225686 + - task: + type: Reranking + dataset: + type: mteb/stackoverflowdupquestions-reranking + name: MTEB StackOverflowDupQuestions + config: default + split: test + metrics: + - type: map + value: 51.4732035634667 + - type: mrr + value: 52.263880931160344 + - task: + type: Summarization + dataset: + type: mteb/summeval + name: MTEB SummEval + config: default + split: test + metrics: + - type: cos_sim_pearson + value: 29.365093191497525 + - type: cos_sim_spearman + value: 27.90160600683062 + - type: dot_pearson + value: 29.36509564650472 + - type: dot_spearman + value: 27.90160600683062 + - task: + type: Retrieval + dataset: + type: trec-covid + name: MTEB TRECCOVID + config: default + split: test + metrics: + - type: map_at_1 + value: 0.17600000000000002 + - type: map_at_10 + value: 1.164 + - type: map_at_100 + value: 6.048 + - type: map_at_1000 + value: 14.913000000000002 + - type: map_at_3 + value: 0.44799999999999995 + - type: map_at_5 + value: 0.658 + - type: mrr_at_1 + value: 64.0 + - type: mrr_at_10 + value: 73.538 + - type: mrr_at_100 + value: 73.752 + - type: mrr_at_1000 + value: 73.752 + - type: mrr_at_3 + value: 70.667 + - type: mrr_at_5 + value: 72.467 + - type: ndcg_at_1 + value: 59.0 + - type: ndcg_at_10 + value: 50.815999999999995 + - type: ndcg_at_100 + value: 37.662 + - type: ndcg_at_1000 + value: 35.907 + - type: ndcg_at_3 + value: 54.112 + - type: ndcg_at_5 + value: 51.19200000000001 + - type: precision_at_1 + value: 64.0 + - type: precision_at_10 + value: 55.400000000000006 + - type: precision_at_100 + value: 38.48 + - type: precision_at_1000 + value: 16.012 + - type: precision_at_3 + value: 57.99999999999999 + - type: precision_at_5 + value: 54.800000000000004 + - type: recall_at_1 + value: 0.17600000000000002 + - type: recall_at_10 + value: 1.435 + - type: recall_at_100 + value: 9.122 + - type: recall_at_1000 + value: 34.378 + - type: recall_at_3 + value: 0.47400000000000003 + - type: recall_at_5 + value: 0.736 + - task: + type: Retrieval + dataset: + type: webis-touche2020 + name: MTEB Touche2020 + config: default + split: test + metrics: + - type: map_at_1 + value: 1.813 + - type: map_at_10 + value: 6.632000000000001 + - type: map_at_100 + value: 11.485 + - type: map_at_1000 + value: 13.031 + - type: map_at_3 + value: 3.5069999999999997 + - type: map_at_5 + value: 5.183 + - type: mrr_at_1 + value: 18.367 + - type: mrr_at_10 + value: 33.035 + - type: mrr_at_100 + value: 34.117 + - type: mrr_at_1000 + value: 34.168 + - type: mrr_at_3 + value: 27.551 + - type: mrr_at_5 + value: 31.326999999999998 + - type: ndcg_at_1 + value: 15.306000000000001 + - type: ndcg_at_10 + value: 17.224 + - type: ndcg_at_100 + value: 29.287999999999997 + - type: ndcg_at_1000 + value: 41.613 + - type: ndcg_at_3 + value: 15.786 + - type: ndcg_at_5 + value: 16.985 + - type: precision_at_1 + value: 18.367 + - type: precision_at_10 + value: 15.714 + - type: precision_at_100 + value: 6.4079999999999995 + - type: precision_at_1000 + value: 1.451 + - type: precision_at_3 + value: 17.687 + - type: precision_at_5 + value: 18.776 + - type: recall_at_1 + value: 1.813 + - type: recall_at_10 + value: 12.006 + - type: recall_at_100 + value: 41.016999999999996 + - type: recall_at_1000 + value: 78.632 + - type: recall_at_3 + value: 4.476999999999999 + - type: recall_at_5 + value: 7.904999999999999 + - task: + type: Classification + dataset: + type: mteb/toxic_conversations_50k + name: MTEB ToxicConversationsClassification + config: default + split: test + metrics: + - type: accuracy + value: 67.4694 + - type: ap + value: 12.602604676283388 + - type: f1 + value: 51.82471949507483 + - task: + type: Classification + dataset: + type: mteb/tweet_sentiment_extraction + name: MTEB TweetSentimentExtractionClassification + config: default + split: test + metrics: + - type: accuracy + value: 54.25297113752122 + - type: f1 + value: 54.50148311546008 + - task: + type: Clustering + dataset: + type: mteb/twentynewsgroups-clustering + name: MTEB TwentyNewsgroupsClustering + config: default + split: test + metrics: + - type: v_measure + value: 47.467044776612376 + - task: + type: PairClassification + dataset: + type: mteb/twittersemeval2015-pairclassification + name: MTEB TwitterSemEval2015 + config: default + split: test + metrics: + - type: cos_sim_accuracy + value: 84.78869881385229 + - type: cos_sim_ap + value: 70.01722500181003 + - type: cos_sim_f1 + value: 65.943384461903 + - type: cos_sim_precision + value: 62.52069047056041 + - type: cos_sim_recall + value: 69.76253298153034 + - type: dot_accuracy + value: 84.78869881385229 + - type: dot_ap + value: 70.01721947474665 + - type: dot_f1 + value: 65.943384461903 + - type: dot_precision + value: 62.52069047056041 + - type: dot_recall + value: 69.76253298153034 + - type: euclidean_accuracy + value: 84.78869881385229 + - type: euclidean_ap + value: 70.01721811552584 + - type: euclidean_f1 + value: 65.943384461903 + - type: euclidean_precision + value: 62.52069047056041 + - type: euclidean_recall + value: 69.76253298153034 + - type: manhattan_accuracy + value: 84.68140907194373 + - type: manhattan_ap + value: 69.90669388421887 + - type: manhattan_f1 + value: 66.00842865743527 + - type: manhattan_precision + value: 60.70874861572536 + - type: manhattan_recall + value: 72.32189973614776 + - type: max_accuracy + value: 84.78869881385229 + - type: max_ap + value: 70.01722500181003 + - type: max_f1 + value: 66.00842865743527 + - task: + type: PairClassification + dataset: + type: mteb/twitterurlcorpus-pairclassification + name: MTEB TwitterURLCorpus + config: default + split: test + metrics: + - type: cos_sim_accuracy + value: 88.4367601971514 + - type: cos_sim_ap + value: 84.77318195783158 + - type: cos_sim_f1 + value: 77.13502703503444 + - type: cos_sim_precision + value: 74.31140288283146 + - type: cos_sim_recall + value: 80.18170619032954 + - type: dot_accuracy + value: 88.4367601971514 + - type: dot_ap + value: 84.77317449778201 + - type: dot_f1 + value: 77.13502703503444 + - type: dot_precision + value: 74.31140288283146 + - type: dot_recall + value: 80.18170619032954 + - type: euclidean_accuracy + value: 88.4367601971514 + - type: euclidean_ap + value: 84.77314948093711 + - type: euclidean_f1 + value: 77.13502703503444 + - type: euclidean_precision + value: 74.31140288283146 + - type: euclidean_recall + value: 80.18170619032954 + - type: manhattan_accuracy + value: 88.43287926417511 + - type: manhattan_ap + value: 84.71097141640011 + - type: manhattan_f1 + value: 77.08356453223837 + - type: manhattan_precision + value: 74.18298326806692 + - type: manhattan_recall + value: 80.2202032645519 + - type: max_accuracy + value: 88.4367601971514 + - type: max_ap + value: 84.77318195783158 + - type: max_f1 + value: 77.13502703503444 ---