--- license: apache-2.0 pipeline_tag: sentence-similarity inference: false tags: - sentence-transformers - feature-extraction - sentence-similarity - mteb language: en datasets: - s2orc - flax-sentence-embeddings/stackexchange_title_body_jsonl - flax-sentence-embeddings/stackexchange_titlebody_best_voted_answer_jsonl - flax-sentence-embeddings/stackexchange_title_best_voted_answer_jsonl - flax-sentence-embeddings/stackexchange_titlebody_best_and_down_voted_answer_jsonl - sentence-transformers/reddit-title-body - msmarco - gooaq - yahoo_answers_topics - code_search_net - search_qa - eli5 - snli - multi_nli - wikihow - natural_questions - trivia_qa - embedding-data/sentence-compression - embedding-data/flickr30k-captions - embedding-data/altlex - embedding-data/simple-wiki - embedding-data/QQP - embedding-data/SPECTER - embedding-data/PAQ_pairs - embedding-data/WikiAnswers - sentence-transformers/embedding-training-data model-index: - name: lodestone-base-4096-v1 results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 69.7313432835821 - type: ap value: 31.618259511417733 - type: f1 value: 63.30313825394228 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 86.89837499999999 - type: ap value: 82.39500885672128 - type: f1 value: 86.87317947399657 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 44.05 - type: f1 value: 42.67624383248947 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 26.173999999999996 - type: map_at_10 value: 40.976 - type: map_at_100 value: 42.067 - type: map_at_1000 value: 42.075 - type: map_at_3 value: 35.917 - type: map_at_5 value: 38.656 - type: mrr_at_1 value: 26.814 - type: mrr_at_10 value: 41.252 - type: mrr_at_100 value: 42.337 - type: mrr_at_1000 value: 42.345 - type: mrr_at_3 value: 36.226 - type: mrr_at_5 value: 38.914 - type: ndcg_at_1 value: 26.173999999999996 - type: ndcg_at_10 value: 49.819 - type: ndcg_at_100 value: 54.403999999999996 - type: ndcg_at_1000 value: 54.59 - type: ndcg_at_3 value: 39.231 - type: ndcg_at_5 value: 44.189 - type: precision_at_1 value: 26.173999999999996 - type: precision_at_10 value: 7.838000000000001 - type: precision_at_100 value: 0.9820000000000001 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 16.287 - type: precision_at_5 value: 12.191 - type: recall_at_1 value: 26.173999999999996 - type: recall_at_10 value: 78.378 - type: recall_at_100 value: 98.222 - type: recall_at_1000 value: 99.644 - type: recall_at_3 value: 48.862 - type: recall_at_5 value: 60.953 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 42.31689035788179 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 31.280245136660984 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 58.79109720839415 - type: mrr value: 71.79615705931495 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 76.44918756608115 - type: cos_sim_spearman value: 70.86607256286257 - type: euclidean_pearson value: 74.12154678100815 - type: euclidean_spearman value: 70.86607256286257 - type: manhattan_pearson value: 74.0078626964417 - type: manhattan_spearman value: 70.68353828321327 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 75.40584415584415 - type: f1 value: 74.29514617572676 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 37.41860080664014 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 29.319217023090705 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.595000000000002 - type: map_at_10 value: 36.556 - type: map_at_100 value: 37.984 - type: map_at_1000 value: 38.134 - type: map_at_3 value: 33.417 - type: map_at_5 value: 35.160000000000004 - type: mrr_at_1 value: 32.761 - type: mrr_at_10 value: 41.799 - type: mrr_at_100 value: 42.526 - type: mrr_at_1000 value: 42.582 - type: mrr_at_3 value: 39.39 - type: mrr_at_5 value: 40.727000000000004 - type: ndcg_at_1 value: 32.761 - type: ndcg_at_10 value: 42.549 - type: ndcg_at_100 value: 47.915 - type: ndcg_at_1000 value: 50.475 - type: ndcg_at_3 value: 37.93 - type: ndcg_at_5 value: 39.939 - type: precision_at_1 value: 32.761 - type: precision_at_10 value: 8.312 - type: precision_at_100 value: 1.403 - type: precision_at_1000 value: 0.197 - type: precision_at_3 value: 18.741 - type: precision_at_5 value: 13.447999999999999 - type: recall_at_1 value: 26.595000000000002 - type: recall_at_10 value: 54.332 - type: recall_at_100 value: 76.936 - type: recall_at_1000 value: 93.914 - type: recall_at_3 value: 40.666000000000004 - type: recall_at_5 value: 46.513 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.528000000000002 - type: map_at_10 value: 30.751 - type: map_at_100 value: 31.855 - type: map_at_1000 value: 31.972 - type: map_at_3 value: 28.465 - type: map_at_5 value: 29.738 - type: mrr_at_1 value: 28.662 - type: mrr_at_10 value: 35.912 - type: mrr_at_100 value: 36.726 - type: mrr_at_1000 value: 36.777 - type: mrr_at_3 value: 34.013 - type: mrr_at_5 value: 35.156 - type: ndcg_at_1 value: 28.662 - type: ndcg_at_10 value: 35.452 - type: ndcg_at_100 value: 40.1 - type: ndcg_at_1000 value: 42.323 - type: ndcg_at_3 value: 32.112 - type: ndcg_at_5 value: 33.638 - type: precision_at_1 value: 28.662 - type: precision_at_10 value: 6.688 - type: precision_at_100 value: 1.13 - type: precision_at_1000 value: 0.16 - type: precision_at_3 value: 15.562999999999999 - type: precision_at_5 value: 11.019 - type: recall_at_1 value: 22.528000000000002 - type: recall_at_10 value: 43.748 - type: recall_at_100 value: 64.235 - type: recall_at_1000 value: 78.609 - type: recall_at_3 value: 33.937 - type: recall_at_5 value: 38.234 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 33.117999999999995 - type: map_at_10 value: 44.339 - type: map_at_100 value: 45.367000000000004 - type: map_at_1000 value: 45.437 - type: map_at_3 value: 41.195 - type: map_at_5 value: 42.922 - type: mrr_at_1 value: 38.37 - type: mrr_at_10 value: 47.786 - type: mrr_at_100 value: 48.522 - type: mrr_at_1000 value: 48.567 - type: mrr_at_3 value: 45.371 - type: mrr_at_5 value: 46.857 - type: ndcg_at_1 value: 38.37 - type: ndcg_at_10 value: 50.019999999999996 - type: ndcg_at_100 value: 54.36299999999999 - type: ndcg_at_1000 value: 55.897 - type: ndcg_at_3 value: 44.733000000000004 - type: ndcg_at_5 value: 47.292 - type: precision_at_1 value: 38.37 - type: precision_at_10 value: 8.288 - type: precision_at_100 value: 1.139 - type: precision_at_1000 value: 0.132 - type: precision_at_3 value: 20.293 - type: precision_at_5 value: 14.107 - type: recall_at_1 value: 33.117999999999995 - type: recall_at_10 value: 63.451 - type: recall_at_100 value: 82.767 - type: recall_at_1000 value: 93.786 - type: recall_at_3 value: 48.964999999999996 - type: recall_at_5 value: 55.358 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 16.028000000000002 - type: map_at_10 value: 23.186999999999998 - type: map_at_100 value: 24.236 - type: map_at_1000 value: 24.337 - type: map_at_3 value: 20.816000000000003 - type: map_at_5 value: 22.311 - type: mrr_at_1 value: 17.514 - type: mrr_at_10 value: 24.84 - type: mrr_at_100 value: 25.838 - type: mrr_at_1000 value: 25.924999999999997 - type: mrr_at_3 value: 22.542 - type: mrr_at_5 value: 24.04 - type: ndcg_at_1 value: 17.514 - type: ndcg_at_10 value: 27.391 - type: ndcg_at_100 value: 32.684999999999995 - type: ndcg_at_1000 value: 35.367 - type: ndcg_at_3 value: 22.820999999999998 - type: ndcg_at_5 value: 25.380999999999997 - type: precision_at_1 value: 17.514 - type: precision_at_10 value: 4.463 - type: precision_at_100 value: 0.745 - type: precision_at_1000 value: 0.101 - type: precision_at_3 value: 10.019 - type: precision_at_5 value: 7.457999999999999 - type: recall_at_1 value: 16.028000000000002 - type: recall_at_10 value: 38.81 - type: recall_at_100 value: 63.295 - type: recall_at_1000 value: 83.762 - type: recall_at_3 value: 26.604 - type: recall_at_5 value: 32.727000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 11.962 - type: map_at_10 value: 17.218 - type: map_at_100 value: 18.321 - type: map_at_1000 value: 18.455 - type: map_at_3 value: 15.287999999999998 - type: map_at_5 value: 16.417 - type: mrr_at_1 value: 14.677000000000001 - type: mrr_at_10 value: 20.381 - type: mrr_at_100 value: 21.471999999999998 - type: mrr_at_1000 value: 21.566 - type: mrr_at_3 value: 18.448999999999998 - type: mrr_at_5 value: 19.587 - type: ndcg_at_1 value: 14.677000000000001 - type: ndcg_at_10 value: 20.86 - type: ndcg_at_100 value: 26.519 - type: ndcg_at_1000 value: 30.020000000000003 - type: ndcg_at_3 value: 17.208000000000002 - type: ndcg_at_5 value: 19.037000000000003 - type: precision_at_1 value: 14.677000000000001 - type: precision_at_10 value: 3.856 - type: precision_at_100 value: 0.7889999999999999 - type: precision_at_1000 value: 0.124 - type: precision_at_3 value: 8.043 - type: precision_at_5 value: 6.069999999999999 - type: recall_at_1 value: 11.962 - type: recall_at_10 value: 28.994999999999997 - type: recall_at_100 value: 54.071999999999996 - type: recall_at_1000 value: 79.309 - type: recall_at_3 value: 19.134999999999998 - type: recall_at_5 value: 23.727999999999998 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.764 - type: map_at_10 value: 31.744 - type: map_at_100 value: 33.037 - type: map_at_1000 value: 33.156 - type: map_at_3 value: 29.015 - type: map_at_5 value: 30.434 - type: mrr_at_1 value: 28.296 - type: mrr_at_10 value: 37.03 - type: mrr_at_100 value: 37.902 - type: mrr_at_1000 value: 37.966 - type: mrr_at_3 value: 34.568 - type: mrr_at_5 value: 35.786 - type: ndcg_at_1 value: 28.296 - type: ndcg_at_10 value: 37.289 - type: ndcg_at_100 value: 42.787 - type: ndcg_at_1000 value: 45.382 - type: ndcg_at_3 value: 32.598 - type: ndcg_at_5 value: 34.521 - type: precision_at_1 value: 28.296 - type: precision_at_10 value: 6.901 - type: precision_at_100 value: 1.135 - type: precision_at_1000 value: 0.152 - type: precision_at_3 value: 15.367 - type: precision_at_5 value: 11.03 - type: recall_at_1 value: 22.764 - type: recall_at_10 value: 48.807 - type: recall_at_100 value: 71.859 - type: recall_at_1000 value: 89.606 - type: recall_at_3 value: 35.594 - type: recall_at_5 value: 40.541 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 19.742 - type: map_at_10 value: 27.741 - type: map_at_100 value: 29.323 - type: map_at_1000 value: 29.438 - type: map_at_3 value: 25.217 - type: map_at_5 value: 26.583000000000002 - type: mrr_at_1 value: 24.657999999999998 - type: mrr_at_10 value: 32.407000000000004 - type: mrr_at_100 value: 33.631 - type: mrr_at_1000 value: 33.686 - type: mrr_at_3 value: 30.194 - type: mrr_at_5 value: 31.444 - type: ndcg_at_1 value: 24.657999999999998 - type: ndcg_at_10 value: 32.614 - type: ndcg_at_100 value: 39.61 - type: ndcg_at_1000 value: 42.114000000000004 - type: ndcg_at_3 value: 28.516000000000002 - type: ndcg_at_5 value: 30.274 - type: precision_at_1 value: 24.657999999999998 - type: precision_at_10 value: 6.176 - type: precision_at_100 value: 1.1400000000000001 - type: precision_at_1000 value: 0.155 - type: precision_at_3 value: 13.927 - type: precision_at_5 value: 9.954 - type: recall_at_1 value: 19.742 - type: recall_at_10 value: 42.427 - type: recall_at_100 value: 72.687 - type: recall_at_1000 value: 89.89 - type: recall_at_3 value: 30.781 - type: recall_at_5 value: 35.606 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 19.72608333333333 - type: map_at_10 value: 27.165333333333336 - type: map_at_100 value: 28.292499999999997 - type: map_at_1000 value: 28.416333333333327 - type: map_at_3 value: 24.783833333333334 - type: map_at_5 value: 26.101750000000003 - type: mrr_at_1 value: 23.721500000000002 - type: mrr_at_10 value: 30.853333333333328 - type: mrr_at_100 value: 31.741750000000003 - type: mrr_at_1000 value: 31.812999999999995 - type: mrr_at_3 value: 28.732249999999997 - type: mrr_at_5 value: 29.945166666666665 - type: ndcg_at_1 value: 23.721500000000002 - type: ndcg_at_10 value: 31.74883333333333 - type: ndcg_at_100 value: 36.883583333333334 - type: ndcg_at_1000 value: 39.6145 - type: ndcg_at_3 value: 27.639583333333334 - type: ndcg_at_5 value: 29.543666666666667 - type: precision_at_1 value: 23.721500000000002 - type: precision_at_10 value: 5.709083333333333 - type: precision_at_100 value: 0.9859166666666666 - type: precision_at_1000 value: 0.1413333333333333 - type: precision_at_3 value: 12.85683333333333 - type: precision_at_5 value: 9.258166666666668 - type: recall_at_1 value: 19.72608333333333 - type: recall_at_10 value: 41.73583333333334 - type: recall_at_100 value: 64.66566666666668 - type: recall_at_1000 value: 84.09833333333336 - type: recall_at_3 value: 30.223083333333328 - type: recall_at_5 value: 35.153083333333335 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.582 - type: map_at_10 value: 22.803 - type: map_at_100 value: 23.503 - type: map_at_1000 value: 23.599999999999998 - type: map_at_3 value: 21.375 - type: map_at_5 value: 22.052 - type: mrr_at_1 value: 20.399 - type: mrr_at_10 value: 25.369999999999997 - type: mrr_at_100 value: 26.016000000000002 - type: mrr_at_1000 value: 26.090999999999998 - type: mrr_at_3 value: 23.952 - type: mrr_at_5 value: 24.619 - type: ndcg_at_1 value: 20.399 - type: ndcg_at_10 value: 25.964 - type: ndcg_at_100 value: 29.607 - type: ndcg_at_1000 value: 32.349 - type: ndcg_at_3 value: 23.177 - type: ndcg_at_5 value: 24.276 - type: precision_at_1 value: 20.399 - type: precision_at_10 value: 4.018 - type: precision_at_100 value: 0.629 - type: precision_at_1000 value: 0.093 - type: precision_at_3 value: 9.969 - type: precision_at_5 value: 6.748 - type: recall_at_1 value: 17.582 - type: recall_at_10 value: 33.35 - type: recall_at_100 value: 50.219 - type: recall_at_1000 value: 71.06099999999999 - type: recall_at_3 value: 25.619999999999997 - type: recall_at_5 value: 28.291 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 11.071 - type: map_at_10 value: 16.201999999999998 - type: map_at_100 value: 17.112 - type: map_at_1000 value: 17.238 - type: map_at_3 value: 14.508 - type: map_at_5 value: 15.440999999999999 - type: mrr_at_1 value: 13.833 - type: mrr_at_10 value: 19.235 - type: mrr_at_100 value: 20.108999999999998 - type: mrr_at_1000 value: 20.196 - type: mrr_at_3 value: 17.515 - type: mrr_at_5 value: 18.505 - type: ndcg_at_1 value: 13.833 - type: ndcg_at_10 value: 19.643 - type: ndcg_at_100 value: 24.298000000000002 - type: ndcg_at_1000 value: 27.614 - type: ndcg_at_3 value: 16.528000000000002 - type: ndcg_at_5 value: 17.991 - type: precision_at_1 value: 13.833 - type: precision_at_10 value: 3.6990000000000003 - type: precision_at_100 value: 0.713 - type: precision_at_1000 value: 0.116 - type: precision_at_3 value: 7.9030000000000005 - type: precision_at_5 value: 5.891 - type: recall_at_1 value: 11.071 - type: recall_at_10 value: 27.019 - type: recall_at_100 value: 48.404 - type: recall_at_1000 value: 72.641 - type: recall_at_3 value: 18.336 - type: recall_at_5 value: 21.991 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 18.573 - type: map_at_10 value: 25.008999999999997 - type: map_at_100 value: 26.015 - type: map_at_1000 value: 26.137 - type: map_at_3 value: 22.798 - type: map_at_5 value: 24.092 - type: mrr_at_1 value: 22.108 - type: mrr_at_10 value: 28.646 - type: mrr_at_100 value: 29.477999999999998 - type: mrr_at_1000 value: 29.57 - type: mrr_at_3 value: 26.415 - type: mrr_at_5 value: 27.693 - type: ndcg_at_1 value: 22.108 - type: ndcg_at_10 value: 29.42 - type: ndcg_at_100 value: 34.385 - type: ndcg_at_1000 value: 37.572 - type: ndcg_at_3 value: 25.274 - type: ndcg_at_5 value: 27.315 - type: precision_at_1 value: 22.108 - type: precision_at_10 value: 5.093 - type: precision_at_100 value: 0.859 - type: precision_at_1000 value: 0.124 - type: precision_at_3 value: 11.474 - type: precision_at_5 value: 8.321000000000002 - type: recall_at_1 value: 18.573 - type: recall_at_10 value: 39.433 - type: recall_at_100 value: 61.597 - type: recall_at_1000 value: 84.69 - type: recall_at_3 value: 27.849 - type: recall_at_5 value: 33.202999999999996 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.807 - type: map_at_10 value: 30.014000000000003 - type: map_at_100 value: 31.422 - type: map_at_1000 value: 31.652 - type: map_at_3 value: 27.447 - type: map_at_5 value: 28.711 - type: mrr_at_1 value: 27.668 - type: mrr_at_10 value: 34.489 - type: mrr_at_100 value: 35.453 - type: mrr_at_1000 value: 35.526 - type: mrr_at_3 value: 32.477000000000004 - type: mrr_at_5 value: 33.603 - type: ndcg_at_1 value: 27.668 - type: ndcg_at_10 value: 34.983 - type: ndcg_at_100 value: 40.535 - type: ndcg_at_1000 value: 43.747 - type: ndcg_at_3 value: 31.026999999999997 - type: ndcg_at_5 value: 32.608 - type: precision_at_1 value: 27.668 - type: precision_at_10 value: 6.837999999999999 - type: precision_at_100 value: 1.411 - type: precision_at_1000 value: 0.23600000000000002 - type: precision_at_3 value: 14.295 - type: precision_at_5 value: 10.435 - type: recall_at_1 value: 22.807 - type: recall_at_10 value: 43.545 - type: recall_at_100 value: 69.39800000000001 - type: recall_at_1000 value: 90.706 - type: recall_at_3 value: 32.183 - type: recall_at_5 value: 36.563 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 13.943 - type: map_at_10 value: 20.419999999999998 - type: map_at_100 value: 21.335 - type: map_at_1000 value: 21.44 - type: map_at_3 value: 17.865000000000002 - type: map_at_5 value: 19.36 - type: mrr_at_1 value: 15.712000000000002 - type: mrr_at_10 value: 22.345000000000002 - type: mrr_at_100 value: 23.227999999999998 - type: mrr_at_1000 value: 23.304 - type: mrr_at_3 value: 19.901 - type: mrr_at_5 value: 21.325 - type: ndcg_at_1 value: 15.712000000000002 - type: ndcg_at_10 value: 24.801000000000002 - type: ndcg_at_100 value: 29.799 - type: ndcg_at_1000 value: 32.513999999999996 - type: ndcg_at_3 value: 19.750999999999998 - type: ndcg_at_5 value: 22.252 - type: precision_at_1 value: 15.712000000000002 - type: precision_at_10 value: 4.1770000000000005 - type: precision_at_100 value: 0.738 - type: precision_at_1000 value: 0.106 - type: precision_at_3 value: 8.688 - type: precision_at_5 value: 6.617000000000001 - type: recall_at_1 value: 13.943 - type: recall_at_10 value: 36.913000000000004 - type: recall_at_100 value: 60.519 - type: recall_at_1000 value: 81.206 - type: recall_at_3 value: 23.006999999999998 - type: recall_at_5 value: 29.082 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 9.468 - type: map_at_10 value: 16.029 - type: map_at_100 value: 17.693 - type: map_at_1000 value: 17.886 - type: map_at_3 value: 13.15 - type: map_at_5 value: 14.568 - type: mrr_at_1 value: 21.173000000000002 - type: mrr_at_10 value: 31.028 - type: mrr_at_100 value: 32.061 - type: mrr_at_1000 value: 32.119 - type: mrr_at_3 value: 27.534999999999997 - type: mrr_at_5 value: 29.431 - type: ndcg_at_1 value: 21.173000000000002 - type: ndcg_at_10 value: 23.224 - type: ndcg_at_100 value: 30.225 - type: ndcg_at_1000 value: 33.961000000000006 - type: ndcg_at_3 value: 18.174 - type: ndcg_at_5 value: 19.897000000000002 - type: precision_at_1 value: 21.173000000000002 - type: precision_at_10 value: 7.4719999999999995 - type: precision_at_100 value: 1.5010000000000001 - type: precision_at_1000 value: 0.219 - type: precision_at_3 value: 13.312 - type: precision_at_5 value: 10.619 - type: recall_at_1 value: 9.468 - type: recall_at_10 value: 28.823 - type: recall_at_100 value: 53.26499999999999 - type: recall_at_1000 value: 74.536 - type: recall_at_3 value: 16.672 - type: recall_at_5 value: 21.302 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 6.343 - type: map_at_10 value: 12.717 - type: map_at_100 value: 16.48 - type: map_at_1000 value: 17.381 - type: map_at_3 value: 9.568999999999999 - type: map_at_5 value: 11.125 - type: mrr_at_1 value: 48.75 - type: mrr_at_10 value: 58.425000000000004 - type: mrr_at_100 value: 59.075 - type: mrr_at_1000 value: 59.095 - type: mrr_at_3 value: 56.291999999999994 - type: mrr_at_5 value: 57.679 - type: ndcg_at_1 value: 37.875 - type: ndcg_at_10 value: 27.77 - type: ndcg_at_100 value: 30.288999999999998 - type: ndcg_at_1000 value: 36.187999999999995 - type: ndcg_at_3 value: 31.385999999999996 - type: ndcg_at_5 value: 29.923 - type: precision_at_1 value: 48.75 - type: precision_at_10 value: 22.375 - type: precision_at_100 value: 6.3420000000000005 - type: precision_at_1000 value: 1.4489999999999998 - type: precision_at_3 value: 35.5 - type: precision_at_5 value: 30.55 - type: recall_at_1 value: 6.343 - type: recall_at_10 value: 16.936 - type: recall_at_100 value: 35.955999999999996 - type: recall_at_1000 value: 55.787 - type: recall_at_3 value: 10.771 - type: recall_at_5 value: 13.669999999999998 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 41.99 - type: f1 value: 36.823402174564954 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 40.088 - type: map_at_10 value: 52.69200000000001 - type: map_at_100 value: 53.296 - type: map_at_1000 value: 53.325 - type: map_at_3 value: 49.905 - type: map_at_5 value: 51.617000000000004 - type: mrr_at_1 value: 43.009 - type: mrr_at_10 value: 56.203 - type: mrr_at_100 value: 56.75 - type: mrr_at_1000 value: 56.769000000000005 - type: mrr_at_3 value: 53.400000000000006 - type: mrr_at_5 value: 55.163 - type: ndcg_at_1 value: 43.009 - type: ndcg_at_10 value: 59.39 - type: ndcg_at_100 value: 62.129999999999995 - type: ndcg_at_1000 value: 62.793 - type: ndcg_at_3 value: 53.878 - type: ndcg_at_5 value: 56.887 - type: precision_at_1 value: 43.009 - type: precision_at_10 value: 8.366 - type: precision_at_100 value: 0.983 - type: precision_at_1000 value: 0.105 - type: precision_at_3 value: 22.377 - type: precision_at_5 value: 15.035000000000002 - type: recall_at_1 value: 40.088 - type: recall_at_10 value: 76.68700000000001 - type: recall_at_100 value: 88.91 - type: recall_at_1000 value: 93.782 - type: recall_at_3 value: 61.809999999999995 - type: recall_at_5 value: 69.131 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 10.817 - type: map_at_10 value: 18.9 - type: map_at_100 value: 20.448 - type: map_at_1000 value: 20.660999999999998 - type: map_at_3 value: 15.979 - type: map_at_5 value: 17.415 - type: mrr_at_1 value: 23.148 - type: mrr_at_10 value: 31.208000000000002 - type: mrr_at_100 value: 32.167 - type: mrr_at_1000 value: 32.242 - type: mrr_at_3 value: 28.498 - type: mrr_at_5 value: 29.964000000000002 - type: ndcg_at_1 value: 23.148 - type: ndcg_at_10 value: 25.325999999999997 - type: ndcg_at_100 value: 31.927 - type: ndcg_at_1000 value: 36.081 - type: ndcg_at_3 value: 21.647 - type: ndcg_at_5 value: 22.762999999999998 - type: precision_at_1 value: 23.148 - type: precision_at_10 value: 7.546 - type: precision_at_100 value: 1.415 - type: precision_at_1000 value: 0.216 - type: precision_at_3 value: 14.969 - type: precision_at_5 value: 11.327 - type: recall_at_1 value: 10.817 - type: recall_at_10 value: 32.164 - type: recall_at_100 value: 57.655 - type: recall_at_1000 value: 82.797 - type: recall_at_3 value: 19.709 - type: recall_at_5 value: 24.333 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 25.380999999999997 - type: map_at_10 value: 33.14 - type: map_at_100 value: 33.948 - type: map_at_1000 value: 34.028000000000006 - type: map_at_3 value: 31.019999999999996 - type: map_at_5 value: 32.23 - type: mrr_at_1 value: 50.763000000000005 - type: mrr_at_10 value: 57.899 - type: mrr_at_100 value: 58.426 - type: mrr_at_1000 value: 58.457 - type: mrr_at_3 value: 56.093 - type: mrr_at_5 value: 57.116 - type: ndcg_at_1 value: 50.763000000000005 - type: ndcg_at_10 value: 41.656 - type: ndcg_at_100 value: 45.079 - type: ndcg_at_1000 value: 46.916999999999994 - type: ndcg_at_3 value: 37.834 - type: ndcg_at_5 value: 39.732 - type: precision_at_1 value: 50.763000000000005 - type: precision_at_10 value: 8.648 - type: precision_at_100 value: 1.135 - type: precision_at_1000 value: 0.13799999999999998 - type: precision_at_3 value: 23.105999999999998 - type: precision_at_5 value: 15.363 - type: recall_at_1 value: 25.380999999999997 - type: recall_at_10 value: 43.241 - type: recall_at_100 value: 56.745000000000005 - type: recall_at_1000 value: 69.048 - type: recall_at_3 value: 34.659 - type: recall_at_5 value: 38.406 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 79.544 - type: ap value: 73.82920133396664 - type: f1 value: 79.51048124883265 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 11.174000000000001 - type: map_at_10 value: 19.451999999999998 - type: map_at_100 value: 20.612 - type: map_at_1000 value: 20.703 - type: map_at_3 value: 16.444 - type: map_at_5 value: 18.083 - type: mrr_at_1 value: 11.447000000000001 - type: mrr_at_10 value: 19.808 - type: mrr_at_100 value: 20.958 - type: mrr_at_1000 value: 21.041999999999998 - type: mrr_at_3 value: 16.791 - type: mrr_at_5 value: 18.459 - type: ndcg_at_1 value: 11.447000000000001 - type: ndcg_at_10 value: 24.556 - type: ndcg_at_100 value: 30.637999999999998 - type: ndcg_at_1000 value: 33.14 - type: ndcg_at_3 value: 18.325 - type: ndcg_at_5 value: 21.278 - type: precision_at_1 value: 11.447000000000001 - type: precision_at_10 value: 4.215 - type: precision_at_100 value: 0.732 - type: precision_at_1000 value: 0.095 - type: precision_at_3 value: 8.052 - type: precision_at_5 value: 6.318 - type: recall_at_1 value: 11.174000000000001 - type: recall_at_10 value: 40.543 - type: recall_at_100 value: 69.699 - type: recall_at_1000 value: 89.403 - type: recall_at_3 value: 23.442 - type: recall_at_5 value: 30.536 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 89.6671226630187 - type: f1 value: 89.57660424361246 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 60.284997720018254 - type: f1 value: 40.30637400152823 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 63.33557498318763 - type: f1 value: 60.24039910680179 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 72.37390719569603 - type: f1 value: 72.33097333477316 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 34.68158939060552 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 30.340061711905236 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 32.01814326295803 - type: mrr value: 33.20555240055367 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 3.3910000000000005 - type: map_at_10 value: 7.7219999999999995 - type: map_at_100 value: 10.286 - type: map_at_1000 value: 11.668000000000001 - type: map_at_3 value: 5.552 - type: map_at_5 value: 6.468 - type: mrr_at_1 value: 34.365 - type: mrr_at_10 value: 42.555 - type: mrr_at_100 value: 43.295 - type: mrr_at_1000 value: 43.357 - type: mrr_at_3 value: 40.299 - type: mrr_at_5 value: 41.182 - type: ndcg_at_1 value: 31.424000000000003 - type: ndcg_at_10 value: 24.758 - type: ndcg_at_100 value: 23.677999999999997 - type: ndcg_at_1000 value: 33.377 - type: ndcg_at_3 value: 28.302 - type: ndcg_at_5 value: 26.342 - type: precision_at_1 value: 33.437 - type: precision_at_10 value: 19.256999999999998 - type: precision_at_100 value: 6.662999999999999 - type: precision_at_1000 value: 1.9900000000000002 - type: precision_at_3 value: 27.761000000000003 - type: precision_at_5 value: 23.715 - type: recall_at_1 value: 3.3910000000000005 - type: recall_at_10 value: 11.068 - type: recall_at_100 value: 25.878 - type: recall_at_1000 value: 60.19 - type: recall_at_3 value: 6.1690000000000005 - type: recall_at_5 value: 7.767 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 15.168000000000001 - type: map_at_10 value: 26.177 - type: map_at_100 value: 27.564 - type: map_at_1000 value: 27.628999999999998 - type: map_at_3 value: 22.03 - type: map_at_5 value: 24.276 - type: mrr_at_1 value: 17.439 - type: mrr_at_10 value: 28.205000000000002 - type: mrr_at_100 value: 29.357 - type: mrr_at_1000 value: 29.408 - type: mrr_at_3 value: 24.377 - type: mrr_at_5 value: 26.540000000000003 - type: ndcg_at_1 value: 17.41 - type: ndcg_at_10 value: 32.936 - type: ndcg_at_100 value: 39.196999999999996 - type: ndcg_at_1000 value: 40.892 - type: ndcg_at_3 value: 24.721 - type: ndcg_at_5 value: 28.615000000000002 - type: precision_at_1 value: 17.41 - type: precision_at_10 value: 6.199000000000001 - type: precision_at_100 value: 0.9690000000000001 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 11.790000000000001 - type: precision_at_5 value: 9.264 - type: recall_at_1 value: 15.168000000000001 - type: recall_at_10 value: 51.914 - type: recall_at_100 value: 79.804 - type: recall_at_1000 value: 92.75999999999999 - type: recall_at_3 value: 30.212 - type: recall_at_5 value: 39.204 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 67.306 - type: map_at_10 value: 80.634 - type: map_at_100 value: 81.349 - type: map_at_1000 value: 81.37299999999999 - type: map_at_3 value: 77.691 - type: map_at_5 value: 79.512 - type: mrr_at_1 value: 77.56 - type: mrr_at_10 value: 84.177 - type: mrr_at_100 value: 84.35000000000001 - type: mrr_at_1000 value: 84.353 - type: mrr_at_3 value: 83.003 - type: mrr_at_5 value: 83.799 - type: ndcg_at_1 value: 77.58 - type: ndcg_at_10 value: 84.782 - type: ndcg_at_100 value: 86.443 - type: ndcg_at_1000 value: 86.654 - type: ndcg_at_3 value: 81.67 - type: ndcg_at_5 value: 83.356 - type: precision_at_1 value: 77.58 - type: precision_at_10 value: 12.875 - type: precision_at_100 value: 1.503 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 35.63 - type: precision_at_5 value: 23.483999999999998 - type: recall_at_1 value: 67.306 - type: recall_at_10 value: 92.64 - type: recall_at_100 value: 98.681 - type: recall_at_1000 value: 99.79 - type: recall_at_3 value: 83.682 - type: recall_at_5 value: 88.424 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 50.76319866126382 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 55.024711941648995 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 3.9379999999999997 - type: map_at_10 value: 8.817 - type: map_at_100 value: 10.546999999999999 - type: map_at_1000 value: 10.852 - type: map_at_3 value: 6.351999999999999 - type: map_at_5 value: 7.453 - type: mrr_at_1 value: 19.400000000000002 - type: mrr_at_10 value: 27.371000000000002 - type: mrr_at_100 value: 28.671999999999997 - type: mrr_at_1000 value: 28.747 - type: mrr_at_3 value: 24.583 - type: mrr_at_5 value: 26.143 - type: ndcg_at_1 value: 19.400000000000002 - type: ndcg_at_10 value: 15.264 - type: ndcg_at_100 value: 22.63 - type: ndcg_at_1000 value: 28.559 - type: ndcg_at_3 value: 14.424999999999999 - type: ndcg_at_5 value: 12.520000000000001 - type: precision_at_1 value: 19.400000000000002 - type: precision_at_10 value: 7.8100000000000005 - type: precision_at_100 value: 1.854 - type: precision_at_1000 value: 0.329 - type: precision_at_3 value: 13.100000000000001 - type: precision_at_5 value: 10.68 - type: recall_at_1 value: 3.9379999999999997 - type: recall_at_10 value: 15.903 - type: recall_at_100 value: 37.645 - type: recall_at_1000 value: 66.86 - type: recall_at_3 value: 7.993 - type: recall_at_5 value: 10.885 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 80.12689060151425 - type: cos_sim_spearman value: 70.46515535094771 - type: euclidean_pearson value: 77.17160003557223 - type: euclidean_spearman value: 70.4651757047438 - type: manhattan_pearson value: 77.18129609281937 - type: manhattan_spearman value: 70.46610403752913 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 70.451157033355 - type: cos_sim_spearman value: 63.99899601697852 - type: euclidean_pearson value: 67.46985359967678 - type: euclidean_spearman value: 64.00001637764805 - type: manhattan_pearson value: 67.56534741780037 - type: manhattan_spearman value: 64.06533893575366 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 77.65086614464292 - type: cos_sim_spearman value: 78.20169706921848 - type: euclidean_pearson value: 77.77758172155283 - type: euclidean_spearman value: 78.20169706921848 - type: manhattan_pearson value: 77.75077884860052 - type: manhattan_spearman value: 78.16875216484164 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 76.26381598259717 - type: cos_sim_spearman value: 70.78377709313477 - type: euclidean_pearson value: 74.82646556532096 - type: euclidean_spearman value: 70.78377658155212 - type: manhattan_pearson value: 74.81784766108225 - type: manhattan_spearman value: 70.79351454692176 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 79.00532026789739 - type: cos_sim_spearman value: 80.02708383244838 - type: euclidean_pearson value: 79.48345422610525 - type: euclidean_spearman value: 80.02708383244838 - type: manhattan_pearson value: 79.44519739854803 - type: manhattan_spearman value: 79.98344094559687 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 77.32783048164805 - type: cos_sim_spearman value: 78.79729961288045 - type: euclidean_pearson value: 78.72111945793154 - type: euclidean_spearman value: 78.79729904606872 - type: manhattan_pearson value: 78.72464311117116 - type: manhattan_spearman value: 78.822591248334 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-en) config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 82.04318630630854 - type: cos_sim_spearman value: 83.87886389259836 - type: euclidean_pearson value: 83.40385877895086 - type: euclidean_spearman value: 83.87886389259836 - type: manhattan_pearson value: 83.46337128901547 - type: manhattan_spearman value: 83.9723106941644 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (en) config: en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 63.003511169944595 - type: cos_sim_spearman value: 64.39318805580227 - type: euclidean_pearson value: 65.4797990735967 - type: euclidean_spearman value: 64.39318805580227 - type: manhattan_pearson value: 65.44604544280844 - type: manhattan_spearman value: 64.38742899984233 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 76.63101237585029 - type: cos_sim_spearman value: 75.57446967644269 - type: euclidean_pearson value: 76.93491768734478 - type: euclidean_spearman value: 75.57446967644269 - type: manhattan_pearson value: 76.92187567800636 - type: manhattan_spearman value: 75.57239337194585 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 78.5376604868993 - type: mrr value: 92.94422897364073 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 38.872 - type: map_at_10 value: 50.417 - type: map_at_100 value: 51.202000000000005 - type: map_at_1000 value: 51.25999999999999 - type: map_at_3 value: 47.02 - type: map_at_5 value: 49.326 - type: mrr_at_1 value: 41.0 - type: mrr_at_10 value: 51.674 - type: mrr_at_100 value: 52.32599999999999 - type: mrr_at_1000 value: 52.376999999999995 - type: mrr_at_3 value: 48.778 - type: mrr_at_5 value: 50.744 - type: ndcg_at_1 value: 41.0 - type: ndcg_at_10 value: 56.027 - type: ndcg_at_100 value: 59.362 - type: ndcg_at_1000 value: 60.839 - type: ndcg_at_3 value: 50.019999999999996 - type: ndcg_at_5 value: 53.644999999999996 - type: precision_at_1 value: 41.0 - type: precision_at_10 value: 8.1 - type: precision_at_100 value: 0.987 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 20.444000000000003 - type: precision_at_5 value: 14.466999999999999 - type: recall_at_1 value: 38.872 - type: recall_at_10 value: 71.906 - type: recall_at_100 value: 86.367 - type: recall_at_1000 value: 98.0 - type: recall_at_3 value: 56.206 - type: recall_at_5 value: 65.05 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.7039603960396 - type: cos_sim_ap value: 90.40809844250262 - type: cos_sim_f1 value: 84.53181583031557 - type: cos_sim_precision value: 87.56698821007502 - type: cos_sim_recall value: 81.69999999999999 - type: dot_accuracy value: 99.7039603960396 - type: dot_ap value: 90.40809844250262 - type: dot_f1 value: 84.53181583031557 - type: dot_precision value: 87.56698821007502 - type: dot_recall value: 81.69999999999999 - type: euclidean_accuracy value: 99.7039603960396 - type: euclidean_ap value: 90.4080982863383 - type: euclidean_f1 value: 84.53181583031557 - type: euclidean_precision value: 87.56698821007502 - type: euclidean_recall value: 81.69999999999999 - type: manhattan_accuracy value: 99.7 - type: manhattan_ap value: 90.39771161966652 - type: manhattan_f1 value: 84.32989690721648 - type: manhattan_precision value: 87.02127659574468 - type: manhattan_recall value: 81.8 - type: max_accuracy value: 99.7039603960396 - type: max_ap value: 90.40809844250262 - type: max_f1 value: 84.53181583031557 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 59.663210666678715 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 32.107791216468776 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 46.440691925067604 - type: mrr value: 47.03390257618199 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 31.067177519784074 - type: cos_sim_spearman value: 31.234728424648967 - type: dot_pearson value: 31.06717083018107 - type: dot_spearman value: 31.234728424648967 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.136 - type: map_at_10 value: 0.767 - type: map_at_100 value: 3.3689999999999998 - type: map_at_1000 value: 8.613999999999999 - type: map_at_3 value: 0.369 - type: map_at_5 value: 0.514 - type: mrr_at_1 value: 48.0 - type: mrr_at_10 value: 63.908 - type: mrr_at_100 value: 64.615 - type: mrr_at_1000 value: 64.615 - type: mrr_at_3 value: 62.0 - type: mrr_at_5 value: 63.4 - type: ndcg_at_1 value: 44.0 - type: ndcg_at_10 value: 38.579 - type: ndcg_at_100 value: 26.409 - type: ndcg_at_1000 value: 26.858999999999998 - type: ndcg_at_3 value: 47.134 - type: ndcg_at_5 value: 43.287 - type: precision_at_1 value: 48.0 - type: precision_at_10 value: 40.400000000000006 - type: precision_at_100 value: 26.640000000000004 - type: precision_at_1000 value: 12.04 - type: precision_at_3 value: 52.666999999999994 - type: precision_at_5 value: 46.800000000000004 - type: recall_at_1 value: 0.136 - type: recall_at_10 value: 1.0070000000000001 - type: recall_at_100 value: 6.318 - type: recall_at_1000 value: 26.522000000000002 - type: recall_at_3 value: 0.41700000000000004 - type: recall_at_5 value: 0.606 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.9949999999999999 - type: map_at_10 value: 8.304 - type: map_at_100 value: 13.644 - type: map_at_1000 value: 15.43 - type: map_at_3 value: 4.788 - type: map_at_5 value: 6.22 - type: mrr_at_1 value: 22.448999999999998 - type: mrr_at_10 value: 37.658 - type: mrr_at_100 value: 38.491 - type: mrr_at_1000 value: 38.503 - type: mrr_at_3 value: 32.312999999999995 - type: mrr_at_5 value: 35.68 - type: ndcg_at_1 value: 21.429000000000002 - type: ndcg_at_10 value: 18.995 - type: ndcg_at_100 value: 32.029999999999994 - type: ndcg_at_1000 value: 44.852 - type: ndcg_at_3 value: 19.464000000000002 - type: ndcg_at_5 value: 19.172 - type: precision_at_1 value: 22.448999999999998 - type: precision_at_10 value: 17.143 - type: precision_at_100 value: 6.877999999999999 - type: precision_at_1000 value: 1.524 - type: precision_at_3 value: 21.769 - type: precision_at_5 value: 20.0 - type: recall_at_1 value: 1.9949999999999999 - type: recall_at_10 value: 13.395999999999999 - type: recall_at_100 value: 44.348 - type: recall_at_1000 value: 82.622 - type: recall_at_3 value: 5.896 - type: recall_at_5 value: 8.554 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 67.9394 - type: ap value: 12.943337263423334 - type: f1 value: 52.28243093094156 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 56.414827391058296 - type: f1 value: 56.666412409573105 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 47.009746255495465 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 84.02574953805807 - type: cos_sim_ap value: 67.66599910763128 - type: cos_sim_f1 value: 63.491277990844985 - type: cos_sim_precision value: 59.77172140694154 - type: cos_sim_recall value: 67.70448548812665 - type: dot_accuracy value: 84.02574953805807 - type: dot_ap value: 67.66600090945406 - type: dot_f1 value: 63.491277990844985 - type: dot_precision value: 59.77172140694154 - type: dot_recall value: 67.70448548812665 - type: euclidean_accuracy value: 84.02574953805807 - type: euclidean_ap value: 67.6659842364448 - type: euclidean_f1 value: 63.491277990844985 - type: euclidean_precision value: 59.77172140694154 - type: euclidean_recall value: 67.70448548812665 - type: manhattan_accuracy value: 84.0317100792752 - type: manhattan_ap value: 67.66351692448987 - type: manhattan_f1 value: 63.48610948306178 - type: manhattan_precision value: 57.11875131828729 - type: manhattan_recall value: 71.45118733509234 - type: max_accuracy value: 84.0317100792752 - type: max_ap value: 67.66600090945406 - type: max_f1 value: 63.491277990844985 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 87.53832421314084 - type: cos_sim_ap value: 83.11416594316626 - type: cos_sim_f1 value: 75.41118114347518 - type: cos_sim_precision value: 73.12839059674504 - type: cos_sim_recall value: 77.8410840776101 - type: dot_accuracy value: 87.53832421314084 - type: dot_ap value: 83.11416226342155 - type: dot_f1 value: 75.41118114347518 - type: dot_precision value: 73.12839059674504 - type: dot_recall value: 77.8410840776101 - type: euclidean_accuracy value: 87.53832421314084 - type: euclidean_ap value: 83.11416284455395 - type: euclidean_f1 value: 75.41118114347518 - type: euclidean_precision value: 73.12839059674504 - type: euclidean_recall value: 77.8410840776101 - type: manhattan_accuracy value: 87.49369348391353 - type: manhattan_ap value: 83.08066812574694 - type: manhattan_f1 value: 75.36561228603892 - type: manhattan_precision value: 71.9202518363064 - type: manhattan_recall value: 79.15768401601478 - type: max_accuracy value: 87.53832421314084 - type: max_ap value: 83.11416594316626 - type: max_f1 value: 75.41118114347518 ---