license: cc-by-nc-4.0 tags:

• feature-extraction
• sentence-similarity
• mteb
• sentence-transformers language:
  • multilingual
  • af
  • am
  • ar
  • as
  • az
  • be
  • bg
  • bn
  • br
  • bs
  • ca
  • cs
  • cy
  • da
  • de
  • el
  • en
  • eo
  • es
  • et
  • eu
  • fa
  • fi
  • fr
  • fy
  • ga
  • gd
  • gl
  • gu
  • ha
  • he
  • hi
  • hr
  • hu
  • hy
  • id
  • is
  • it
  • ja
  • jv
  • ka
  • kk
  • km
  • kn
  • ko
  • ku
  • ky
  • la
  • lo
  • lt
  • lv
  • mg
  • mk
  • ml
  • mn
  • mr
  • ms
  • my
  • ne
  • nl
  • no
  • om
  • or
  • pa
  • pl
  • ps
  • pt
  • ro
  • ru
  • sa
  • sd
  • si
  • sk
  • sl
  • so
  • sq
  • sr
  • su
  • sv
  • sw
  • ta
  • te
  • th
  • tl
  • tr
  • ug
  • uk
  • ur
  • uz
  • vi
  • xh
  • yi
  • zh inference: false library_name: transformers model-index:
• name: jina-embeddings-v3 results:

  • dataset: config: default name: MTEB AFQMC (default) revision: b44c3b011063adb25877c13823db83bb193913c4 split: validation type: C-MTEB/AFQMC metrics:

    • type: cosine_pearson value: 41.74237700998808
    • type: cosine_spearman value: 43.4726782647566
    • type: euclidean_pearson value: 42.244585459479964
    • type: euclidean_spearman value: 43.525070045169606
    • type: main_score value: 43.4726782647566
    • type: manhattan_pearson value: 42.04616728224863
    • type: manhattan_spearman value: 43.308828270754645
    • type: pearson value: 41.74237700998808
    • type: spearman value: 43.4726782647566 task: type: STS

  • dataset: config: default name: MTEB ArguAna-PL (default) revision: 63fc86750af76253e8c760fc9e534bbf24d260a2 split: test type: clarin-knext/arguana-pl metrics:

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    • type: recall_at_1 value: 24.253
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  • dataset: config: default name: MTEB DBPedia-PL (default) revision: 76afe41d9af165cc40999fcaa92312b8b012064a split: test type: clarin-knext/dbpedia-pl metrics:

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  • dataset: config: default name: MTEB FiQA-PL (default) revision: 2e535829717f8bf9dc829b7f911cc5bbd4e6608e split: test type: clarin-knext/fiqa-pl metrics:

    • type: main_score value: 38.828
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  • dataset: config: default name: MTEB HotpotQA-PL (default) revision: a0bd479ac97b4ccb5bd6ce320c415d0bb4beb907 split: test type: clarin-knext/hotpotqa-pl metrics:

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  • dataset: config: default name: MTEB MSMARCO-PL (default) revision: 8634c07806d5cce3a6138e260e59b81760a0a640 split: test type: clarin-knext/msmarco-pl metrics:

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  • dataset: config: default name: MTEB NFCorpus-PL (default) revision: 9a6f9567fda928260afed2de480d79c98bf0bec0 split: test type: clarin-knext/nfcorpus-pl metrics:

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  • dataset: config: default name: MTEB NQ-PL (default) revision: f171245712cf85dd4700b06bef18001578d0ca8d split: test type: clarin-knext/nq-pl metrics:

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  • dataset: config: default name: MTEB Quora-PL (default) revision: 0be27e93455051e531182b85e85e425aba12e9d4 split: test type: clarin-knext/quora-pl metrics:

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  • dataset: config: default name: MTEB SCIDOCS-PL (default) revision: 45452b03f05560207ef19149545f168e596c9337 split: test type: clarin-knext/scidocs-pl metrics:

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  • dataset: config: default name: MTEB SciFact-PL (default) revision: 47932a35f045ef8ed01ba82bf9ff67f6e109207e split: test type: clarin-knext/scifact-pl metrics:

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  • dataset: config: default name: MTEB TRECCOVID-PL (default) revision: 81bcb408f33366c2a20ac54adafad1ae7e877fdd split: test type: clarin-knext/trec-covid-pl metrics:

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  • dataset: config: default name: MTEB CEDRClassification (default) revision: c0ba03d058e3e1b2f3fd20518875a4563dd12db4 split: test type: ai-forever/cedr-classification metrics:

    • type: accuracy value: 47.30605738575983
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  • dataset: config: ru name: MTEB MIRACLReranking (ru) revision: 6d1962c527217f8927fca80f890f14f36b2802af split: dev type: miracl/mmteb-miracl-reranking metrics:

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    • type: NDCG@1(MIRACL) value: 32.799
    • type: NDCG@10(MIRACL) value: 42.065000000000005
    • type: NDCG@100(MIRACL) value: 49.730999999999995
    • type: NDCG@1000(MIRACL) value: 49.730999999999995
    • type: NDCG@20(MIRACL) value: 46.0
    • type: NDCG@3(MIRACL) value: 34.481
    • type: NDCG@5(MIRACL) value: 37.452999999999996
    • type: P@1(MIRACL) value: 32.799
    • type: P@10(MIRACL) value: 11.668000000000001
    • type: P@100(MIRACL) value: 1.9529999999999998
    • type: P@1000(MIRACL) value: 0.19499999999999998
    • type: P@20(MIRACL) value: 7.51
    • type: P@3(MIRACL) value: 20.823
    • type: P@5(MIRACL) value: 16.728
    • type: Recall@1(MIRACL) value: 20.721999999999998
    • type: Recall@10(MIRACL) value: 54.762
    • type: Recall@100(MIRACL) value: 79.952
    • type: Recall@1000(MIRACL) value: 79.952
    • type: Recall@20(MIRACL) value: 66.26100000000001
    • type: Recall@3(MIRACL) value: 34.410000000000004
    • type: Recall@5(MIRACL) value: 42.659000000000006
    • type: main_score value: 42.065000000000005
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    • type: nAUC_P@20_diff1(MIRACL) value: -22.947528755272426
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    • type: nAUC_Recall@1000_diff1(MIRACL) value: -38.69835271863148
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    • type: nAUC_Recall@10_diff1(MIRACL) value: -0.08109036309433801
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    • type: nAUC_Recall@10_std(MIRACL) value: 8.791982704261589
    • type: nAUC_Recall@1_diff1(MIRACL) value: 28.698973487482206
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    • type: nAUC_Recall@1_std(MIRACL) value: -1.1247408800976524
    • type: nAUC_Recall@20_diff1(MIRACL) value: -13.312171017942623
    • type: nAUC_Recall@20_max(MIRACL) value: 24.19847346821666
    • type: nAUC_Recall@20_std(MIRACL) value: 15.8157702609797
    • type: nAUC_Recall@3_diff1(MIRACL) value: 16.909128321353343
    • type: nAUC_Recall@3_max(MIRACL) value: 6.552122731902991
    • type: nAUC_Recall@3_std(MIRACL) value: 1.9963898223457228
    • type: nAUC_Recall@5_diff1(MIRACL) value: 9.990292655247721
    • type: nAUC_Recall@5_max(MIRACL) value: 9.361722273507574
    • type: nAUC_Recall@5_std(MIRACL) value: 3.270918827854495 task: type: Reranking

  • dataset: config: default name: MTEB SensitiveTopicsClassification (default) revision: 416b34a802308eac30e4192afc0ff99bb8dcc7f2 split: test type: ai-forever/sensitive-topics-classification metrics:

    • type: accuracy value: 30.634765625
    • type: f1 value: 32.647559808678665
    • type: lrap value: 45.94319661458259
    • type: main_score value: 30.634765625 task: type: MultilabelClassification

  • dataset: config: default name: MTEB ATEC (default) revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865 split: test type: C-MTEB/ATEC metrics:

    • type: cosine_pearson value: 47.541497334563296
    • type: cosine_spearman value: 49.06268944206629
    • type: euclidean_pearson value: 51.838926748581635
    • type: euclidean_spearman value: 48.930697157135356
    • type: main_score value: 49.06268944206629
    • type: manhattan_pearson value: 51.835306769406365
    • type: manhattan_spearman value: 48.86135493444834
    • type: pearson value: 47.541497334563296
    • type: spearman value: 49.06268944206629 task: type: STS

  • dataset: config: default name: MTEB AllegroReviews (default) revision: b89853e6de927b0e3bfa8ecc0e56fe4e02ceafc6 split: test type: PL-MTEB/allegro-reviews metrics:

    • type: accuracy value: 49.51292246520874
    • type: f1 value: 44.14350234332397
    • type: f1_weighted value: 51.65508998354552
    • type: main_score value: 49.51292246520874 task: type: Classification

  • dataset: config: default name: MTEB AlloProfClusteringP2P (default) revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b split: test type: lyon-nlp/alloprof metrics:

    • type: main_score value: 63.883383458621665
    • type: v_measure value: 63.883383458621665
    • type: v_measure_std value: 2.693666879958465 task: type: Clustering

  • dataset: config: default name: MTEB 8TagsClustering revision: None split: test type: PL-MTEB/8tags-clustering metrics:

    • type: v_measure value: 43.657212124525546 task: type: Clustering

  • dataset: config: default name: MTEB AlloProfClusteringS2S (default) revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b split: test type: lyon-nlp/alloprof metrics:

    • type: main_score value: 46.85924588755251
    • type: v_measure value: 46.85924588755251
    • type: v_measure_std value: 2.1918258880872377 task: type: Clustering

  • dataset: config: default name: MTEB AlloprofReranking (default) revision: e40c8a63ce02da43200eccb5b0846fcaa888f562 split: test type: lyon-nlp/mteb-fr-reranking-alloprof-s2p metrics:

    • type: map value: 66.39013753839347
    • type: mrr value: 67.68045617786551
    • type: main_score value: 66.39013753839347 task: type: Reranking

  • dataset: config: default name: MTEB AlloprofRetrieval (default) revision: fcf295ea64c750f41fadbaa37b9b861558e1bfbd split: test type: lyon-nlp/alloprof metrics:

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    • type: map_at_1000 value: 49.39
    • type: map_at_20 value: 49.064
    • type: map_at_3 value: 45.675
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    • type: ndcg_at_1 value: 37.047000000000004
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    • type: precision_at_1 value: 37.047000000000004
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    • type: precision_at_100 value: 0.914
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    • type: recall_at_1 value: 37.047000000000004
    • type: recall_at_10 value: 72.366
    • type: recall_at_100 value: 91.408
    • type: recall_at_1000 value: 99.136
    • type: recall_at_20 value: 80.095
    • type: recall_at_3 value: 56.693000000000005
    • type: recall_at_5 value: 64.42099999999999 task: type: Retrieval

  • dataset: config: en name: MTEB AmazonCounterfactualClassification (en) revision: e8379541af4e31359cca9fbcf4b00f2671dba205 split: test type: mteb/amazon_counterfactual metrics:

    • type: accuracy value: 89.49253731343283
    • type: ap value: 61.88098616359918
    • type: ap_weighted value: 61.88098616359918
    • type: f1 value: 84.76516623679144
    • type: f1_weighted value: 89.92745276292968
    • type: main_score value: 89.49253731343283 task: type: Classification

  • dataset: config: de name: MTEB AmazonCounterfactualClassification (de) revision: e8379541af4e31359cca9fbcf4b00f2671dba205 split: test type: mteb/amazon_counterfactual metrics:

    • type: accuracy value: 89.61456102783727
    • type: ap value: 93.11816566733742
    • type: ap_weighted value: 93.11816566733742
    • type: f1 value: 88.27635757733722
    • type: f1_weighted value: 89.82581568285453
    • type: main_score value: 89.61456102783727 task: type: Classification

  • dataset: config: default name: MTEB AmazonPolarityClassification (default) revision: e2d317d38cd51312af73b3d32a06d1a08b442046 split: test type: mteb/amazon_polarity metrics:

    • type: accuracy value: 95.3825
    • type: ap value: 93.393033869502
    • type: ap_weighted value: 93.393033869502
    • type: f1 value: 95.38109007966307
    • type: f1_weighted value: 95.38109007966305
    • type: main_score value: 95.3825 task: type: Classification

  • dataset: config: en name: MTEB AmazonReviewsClassification (en) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics:

    • type: accuracy value: 49.768
    • type: f1 value: 48.95084821944411
    • type: f1_weighted value: 48.9508482194441
    • type: main_score value: 49.768 task: type: Classification

  • dataset: config: de name: MTEB AmazonReviewsClassification (de) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics:

    • type: accuracy value: 48.071999999999996
    • type: f1 value: 47.24171107487612
    • type: f1_weighted value: 47.24171107487612
    • type: main_score value: 48.071999999999996 task: type: Classification

  • dataset: config: es name: MTEB AmazonReviewsClassification (es) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics:

    • type: accuracy value: 48.102000000000004
    • type: f1 value: 47.27193805278696
    • type: f1_weighted value: 47.27193805278696
    • type: main_score value: 48.102000000000004 task: type: Classification

  • dataset: config: fr name: MTEB AmazonReviewsClassification (fr) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics:

    • type: accuracy value: 47.30800000000001
    • type: f1 value: 46.41683358017851
    • type: f1_weighted value: 46.41683358017851
    • type: main_score value: 47.30800000000001 task: type: Classification

  • dataset: config: zh name: MTEB AmazonReviewsClassification (zh) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics:

    • type: accuracy value: 44.944
    • type: f1 value: 44.223824487744395
    • type: f1_weighted value: 44.22382448774439
    • type: main_score value: 44.944 task: type: Classification

  • dataset: config: default name: MTEB ArguAna (default) revision: c22ab2a51041ffd869aaddef7af8d8215647e41a split: test type: mteb/arguana metrics:

    • type: map_at_1 value: 29.232000000000003
    • type: map_at_10 value: 45.117000000000004
    • type: map_at_100 value: 45.977000000000004
    • type: map_at_1000 value: 45.98
    • type: map_at_20 value: 45.815
    • type: map_at_3 value: 39.912
    • type: map_at_5 value: 42.693
    • type: mrr_at_1 value: 29.659000000000002
    • type: mrr_at_10 value: 45.253
    • type: mrr_at_100 value: 46.125
    • type: mrr_at_1000 value: 46.129
    • type: mrr_at_20 value: 45.964
    • type: mrr_at_3 value: 40.043
    • type: mrr_at_5 value: 42.870000000000005
    • type: ndcg_at_1 value: 29.232000000000003
    • type: ndcg_at_10 value: 54.327999999999996
    • type: ndcg_at_100 value: 57.86
    • type: ndcg_at_1000 value: 57.935
    • type: ndcg_at_20 value: 56.794
    • type: ndcg_at_3 value: 43.516
    • type: ndcg_at_5 value: 48.512
    • type: precision_at_1 value: 29.232000000000003
    • type: precision_at_10 value: 8.393
    • type: precision_at_100 value: 0.991
    • type: precision_at_1000 value: 0.1
    • type: precision_at_20 value: 4.676
    • type: precision_at_3 value: 17.994
    • type: precision_at_5 value: 13.215
    • type: recall_at_1 value: 29.232000000000003
    • type: recall_at_10 value: 83.926
    • type: recall_at_100 value: 99.075
    • type: recall_at_1000 value: 99.644
    • type: recall_at_20 value: 93.528
    • type: recall_at_3 value: 53.983000000000004
    • type: recall_at_5 value: 66.074
    • type: main_score value: 54.327999999999996 task: type: Retrieval

  • dataset: config: default name: MTEB ArxivClusteringP2P (default) revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d split: test type: mteb/arxiv-clustering-p2p metrics:

    • type: main_score value: 46.6636824632419
    • type: v_measure value: 46.6636824632419
    • type: v_measure_std value: 13.817129140714963 task: type: Clustering

  • dataset: config: default name: MTEB ArxivClusteringS2S (default) revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 split: test type: mteb/arxiv-clustering-s2s metrics:

    • type: main_score value: 39.271141892800024
    • type: v_measure value: 39.271141892800024
    • type: v_measure_std value: 14.276782483454827 task: type: Clustering

  • dataset: config: default name: MTEB AskUbuntuDupQuestions (default) revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 split: test type: mteb/askubuntudupquestions-reranking metrics:

    • type: map value: 65.04363277324629
    • type: mrr value: 78.2372598162072
    • type: main_score value: 65.04363277324629 task: type: Reranking

  • dataset: config: default name: MTEB MindSmallReranking (default) revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 split: test type: mteb/mind_small metrics:

    • type: map value: 30.83
    • type: main_score value: 30.83 task: type: Reranking

  • dataset: config: default name: MTEB BIOSSES (default) revision: d3fb88f8f02e40887cd149695127462bbcf29b4a split: test type: mteb/biosses-sts metrics:

    • type: cosine_pearson value: 88.80382082011027
    • type: cosine_spearman value: 88.68876782169106
    • type: euclidean_pearson value: 87.00802890147176
    • type: euclidean_spearman value: 87.43211268192712
    • type: main_score value: 88.68876782169106
    • type: manhattan_pearson value: 87.14062537179474
    • type: manhattan_spearman value: 87.59115245033443
    • type: pearson value: 88.80382082011027
    • type: spearman value: 88.68876782169106 task: type: STS

  • dataset: config: default name: MTEB BQ (default) revision: e3dda5e115e487b39ec7e618c0c6a29137052a55 split: test type: C-MTEB/BQ metrics:

    • type: cosine_pearson value: 61.588006604878196
    • type: cosine_spearman value: 63.20615427154465
    • type: euclidean_pearson value: 61.818547092516496
    • type: euclidean_spearman value: 63.21558009151778
    • type: main_score value: 63.20615427154465
    • type: manhattan_pearson value: 61.665588158487616
    • type: manhattan_spearman value: 63.051544488238584
    • type: pearson value: 61.588006604878196
    • type: spearman value: 63.20615427154465 task: type: STS

  • dataset: config: default name: MTEB BSARDRetrieval (default) revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59 split: test type: maastrichtlawtech/bsard metrics:

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    • type: map_at_100 value: 22.762
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    • type: map_at_3 value: 20.119999999999997
    • type: map_at_5 value: 20.931
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    • type: mrr_at_3 value: 20.12012012012012
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    • type: precision_at_1 value: 14.865
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    • type: precision_at_3 value: 8.709
    • type: precision_at_5 value: 5.946
    • type: recall_at_1 value: 14.865
    • type: recall_at_10 value: 34.685
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    • type: recall_at_1000 value: 86.937
    • type: recall_at_20 value: 43.694
    • type: recall_at_3 value: 26.125999999999998
    • type: recall_at_5 value: 29.73 task: type: Retrieval

  • dataset: config: default name: MTEB Banking77Classification (default) revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 split: test type: mteb/banking77 metrics:

    • type: accuracy value: 84.08116883116882
    • type: f1 value: 84.05587055990273
    • type: f1_weighted value: 84.05587055990274
    • type: main_score value: 84.08116883116882 task: type: Classification

  • dataset: config: default name: MTEB BiorxivClusteringP2P (default) revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 split: test type: mteb/biorxiv-clustering-p2p metrics:

    • type: main_score value: 38.1941007822277
    • type: v_measure value: 38.1941007822277
    • type: v_measure_std value: 0.7502113547288178 task: type: Clustering

  • dataset: config: default name: MTEB BiorxivClusteringS2S (default) revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 split: test type: mteb/biorxiv-clustering-s2s metrics:

    • type: main_score value: 34.42075599178318
    • type: v_measure value: 34.42075599178318
    • type: v_measure_std value: 0.600256720497283 task: type: Clustering

  • dataset: config: default name: MTEB BlurbsClusteringP2P (default) revision: a2dd5b02a77de3466a3eaa98ae586b5610314496 split: test type: slvnwhrl/blurbs-clustering-p2p metrics:

    • type: main_score value: 41.634627363047265
    • type: v_measure value: 41.634627363047265
    • type: v_measure_std value: 9.726923191225307 task: type: Clustering

  • dataset: config: default name: MTEB BlurbsClusteringS2S (default) revision: 22793b6a6465bf00120ad525e38c51210858132c split: test type: slvnwhrl/blurbs-clustering-s2s metrics:

    • type: main_score value: 20.996468295584197
    • type: v_measure value: 20.996468295584197
    • type: v_measure_std value: 9.225766688272197 task: type: Clustering

  • dataset: config: default name: MTEB CBD (default) revision: 36ddb419bcffe6a5374c3891957912892916f28d split: test type: PL-MTEB/cbd metrics:

    • type: accuracy value: 69.99
    • type: ap value: 22.57826353116948
    • type: ap_weighted value: 22.57826353116948
    • type: f1 value: 59.04574955548393
    • type: f1_weighted value: 74.36235022309789
    • type: main_score value: 69.99 task: type: Classification

  • dataset: config: default name: MTEB CDSC-E (default) revision: 0a3d4aa409b22f80eb22cbf59b492637637b536d split: test type: PL-MTEB/cdsce-pairclassification metrics:

    • type: cosine_accuracy value: 88.7
    • type: cosine_accuracy_threshold value: 97.37848043441772
    • type: cosine_ap value: 73.0405088928302
    • type: cosine_f1 value: 63.52201257861635
    • type: cosine_f1_threshold value: 96.98888063430786
    • type: cosine_precision value: 78.90625
    • type: cosine_recall value: 53.1578947368421
    • type: dot_accuracy value: 84.89999999999999
    • type: dot_accuracy_threshold value: 43603.09753417969
    • type: dot_ap value: 56.98157569085279
    • type: dot_f1 value: 57.606490872210955
    • type: dot_f1_threshold value: 40406.23779296875
    • type: dot_precision value: 46.864686468646866
    • type: dot_recall value: 74.73684210526315
    • type: euclidean_accuracy value: 88.5
    • type: euclidean_accuracy_threshold value: 498.0483055114746
    • type: euclidean_ap value: 72.97328234816734
    • type: euclidean_f1 value: 63.722397476340696
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    • type: euclidean_precision value: 79.52755905511812
    • type: euclidean_recall value: 53.1578947368421
    • type: main_score value: 73.0405088928302
    • type: manhattan_accuracy value: 88.6
    • type: manhattan_accuracy_threshold value: 12233.079528808594
    • type: manhattan_ap value: 72.92148503992615
    • type: manhattan_f1 value: 63.69426751592356
    • type: manhattan_f1_threshold value: 12392.754364013672
    • type: manhattan_precision value: 80.64516129032258
    • type: manhattan_recall value: 52.63157894736842
    • type: max_accuracy value: 88.7
    • type: max_ap value: 73.0405088928302
    • type: max_f1 value: 63.722397476340696
    • type: max_precision value: 80.64516129032258
    • type: max_recall value: 74.73684210526315
    • type: similarity_accuracy value: 88.7
    • type: similarity_accuracy_threshold value: 97.37848043441772
    • type: similarity_ap value: 73.0405088928302
    • type: similarity_f1 value: 63.52201257861635
    • type: similarity_f1_threshold value: 96.98888063430786
    • type: similarity_precision value: 78.90625
    • type: similarity_recall value: 53.1578947368421 task: type: PairClassification

  • dataset: config: default name: MTEB CDSC-R (default) revision: 1cd6abbb00df7d14be3dbd76a7dcc64b3a79a7cd split: test type: PL-MTEB/cdscr-sts metrics:

    • type: cosine_pearson value: 92.97492495289738
    • type: cosine_spearman value: 92.63248098608472
    • type: euclidean_pearson value: 92.04712487782031
    • type: euclidean_spearman value: 92.19679486755008
    • type: main_score value: 92.63248098608472
    • type: manhattan_pearson value: 92.0101187740438
    • type: manhattan_spearman value: 92.20926859332754
    • type: pearson value: 92.97492495289738
    • type: spearman value: 92.63248098608472 task: type: STS

  • dataset: config: default name: MTEB CLSClusteringP2P (default) revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476 split: test type: C-MTEB/CLSClusteringP2P metrics:

    • type: main_score value: 39.96377851800628
    • type: v_measure value: 39.96377851800628
    • type: v_measure_std value: 0.9793033243093288 task: type: Clustering

  • dataset: config: default name: MTEB CLSClusteringS2S (default) revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f split: test type: C-MTEB/CLSClusteringS2S metrics:

    • type: main_score value: 38.788850224595784
    • type: v_measure value: 38.788850224595784
    • type: v_measure_std value: 1.0712604145916924 task: type: Clustering

  • dataset: config: default name: MTEB CMedQAv1 revision: 8d7f1e942507dac42dc58017c1a001c3717da7df split: test type: C-MTEB/CMedQAv1-reranking metrics:

    • type: map value: 77.95952507806115
    • type: mrr value: 80.8643253968254
    • type: main_score value: 77.95952507806115 task: type: Reranking

  • dataset: config: default name: MTEB CMedQAv2 revision: 23d186750531a14a0357ca22cd92d712fd512ea0 split: test type: C-MTEB/CMedQAv2-reranking metrics:

    • type: map value: 78.21522500165045
    • type: mrr value: 81.28194444444443
    • type: main_score value: 78.21522500165045 task: type: Reranking

  • dataset: config: default name: MTEB CQADupstackAndroidRetrieval (default) revision: f46a197baaae43b4f621051089b82a364682dfeb split: test type: mteb/cqadupstack-android metrics:

    • type: map_at_1 value: 33.377
    • type: map_at_10 value: 46.371
    • type: map_at_100 value: 47.829
    • type: map_at_1000 value: 47.94
    • type: map_at_20 value: 47.205000000000005
    • type: map_at_3 value: 42.782
    • type: map_at_5 value: 44.86
    • type: mrr_at_1 value: 41.345
    • type: mrr_at_10 value: 52.187
    • type: mrr_at_100 value: 52.893
    • type: mrr_at_1000 value: 52.929
    • type: mrr_at_20 value: 52.637
    • type: mrr_at_3 value: 49.714000000000006
    • type: mrr_at_5 value: 51.373000000000005
    • type: ndcg_at_1 value: 41.345
    • type: ndcg_at_10 value: 52.946000000000005
    • type: ndcg_at_100 value: 57.92699999999999
    • type: ndcg_at_1000 value: 59.609
    • type: ndcg_at_20 value: 54.900999999999996
    • type: ndcg_at_3 value: 48.357
    • type: ndcg_at_5 value: 50.739000000000004
    • type: precision_at_1 value: 41.345
    • type: precision_at_10 value: 10.186
    • type: precision_at_100 value: 1.554
    • type: precision_at_1000 value: 0.2
    • type: precision_at_20 value: 5.959
    • type: precision_at_3 value: 23.796
    • type: precision_at_5 value: 17.024
    • type: recall_at_1 value: 33.377
    • type: recall_at_10 value: 65.067
    • type: recall_at_100 value: 86.04899999999999
    • type: recall_at_1000 value: 96.54899999999999
    • type: recall_at_20 value: 72.071
    • type: recall_at_3 value: 51.349999999999994
    • type: recall_at_5 value: 58.41
    • type: main_score value: 52.946000000000005 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackEnglishRetrieval (default) revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 split: test type: mteb/cqadupstack-english metrics:

    • type: map_at_1 value: 31.097
    • type: map_at_10 value: 42.183
    • type: map_at_100 value: 43.580999999999996
    • type: map_at_1000 value: 43.718
    • type: map_at_20 value: 42.921
    • type: map_at_3 value: 38.963
    • type: map_at_5 value: 40.815
    • type: mrr_at_1 value: 39.745000000000005
    • type: mrr_at_10 value: 48.736000000000004
    • type: mrr_at_100 value: 49.405
    • type: mrr_at_1000 value: 49.452
    • type: mrr_at_20 value: 49.118
    • type: mrr_at_3 value: 46.497
    • type: mrr_at_5 value: 47.827999999999996
    • type: ndcg_at_1 value: 39.745000000000005
    • type: ndcg_at_10 value: 48.248000000000005
    • type: ndcg_at_100 value: 52.956
    • type: ndcg_at_1000 value: 54.99699999999999
    • type: ndcg_at_20 value: 50.01
    • type: ndcg_at_3 value: 43.946000000000005
    • type: ndcg_at_5 value: 46.038000000000004
    • type: precision_at_1 value: 39.745000000000005
    • type: precision_at_10 value: 9.229
    • type: precision_at_100 value: 1.5070000000000001
    • type: precision_at_1000 value: 0.199
    • type: precision_at_20 value: 5.489999999999999
    • type: precision_at_3 value: 21.38
    • type: precision_at_5 value: 15.274
    • type: recall_at_1 value: 31.097
    • type: recall_at_10 value: 58.617
    • type: recall_at_100 value: 78.55199999999999
    • type: recall_at_1000 value: 91.13900000000001
    • type: recall_at_20 value: 64.92
    • type: recall_at_3 value: 45.672000000000004
    • type: recall_at_5 value: 51.669
    • type: main_score value: 48.248000000000005 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackGamingRetrieval (default) revision: 4885aa143210c98657558c04aaf3dc47cfb54340 split: test type: mteb/cqadupstack-gaming metrics:

    • type: map_at_1 value: 39.745000000000005
    • type: map_at_10 value: 52.063
    • type: map_at_100 value: 53.077
    • type: map_at_1000 value: 53.13
    • type: map_at_20 value: 52.66
    • type: map_at_3 value: 48.662
    • type: map_at_5 value: 50.507000000000005
    • type: mrr_at_1 value: 45.391999999999996
    • type: mrr_at_10 value: 55.528
    • type: mrr_at_100 value: 56.16100000000001
    • type: mrr_at_1000 value: 56.192
    • type: mrr_at_20 value: 55.923
    • type: mrr_at_3 value: 52.93600000000001
    • type: mrr_at_5 value: 54.435
    • type: ndcg_at_1 value: 45.391999999999996
    • type: ndcg_at_10 value: 58.019
    • type: ndcg_at_100 value: 61.936
    • type: ndcg_at_1000 value: 63.015
    • type: ndcg_at_20 value: 59.691
    • type: ndcg_at_3 value: 52.294
    • type: ndcg_at_5 value: 55.017
    • type: precision_at_1 value: 45.391999999999996
    • type: precision_at_10 value: 9.386
    • type: precision_at_100 value: 1.232
    • type: precision_at_1000 value: 0.136
    • type: precision_at_20 value: 5.223
    • type: precision_at_3 value: 23.177
    • type: precision_at_5 value: 15.9
    • type: recall_at_1 value: 39.745000000000005
    • type: recall_at_10 value: 72.08099999999999
    • type: recall_at_100 value: 88.85300000000001
    • type: recall_at_1000 value: 96.569
    • type: recall_at_20 value: 78.203
    • type: recall_at_3 value: 56.957
    • type: recall_at_5 value: 63.63100000000001
    • type: main_score value: 58.019 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackGisRetrieval (default) revision: 5003b3064772da1887988e05400cf3806fe491f2 split: test type: mteb/cqadupstack-gis metrics:

    • type: map_at_1 value: 26.651999999999997
    • type: map_at_10 value: 35.799
    • type: map_at_100 value: 36.846000000000004
    • type: map_at_1000 value: 36.931000000000004
    • type: map_at_20 value: 36.341
    • type: map_at_3 value: 32.999
    • type: map_at_5 value: 34.597
    • type: mrr_at_1 value: 28.814
    • type: mrr_at_10 value: 37.869
    • type: mrr_at_100 value: 38.728
    • type: mrr_at_1000 value: 38.795
    • type: mrr_at_20 value: 38.317
    • type: mrr_at_3 value: 35.235
    • type: mrr_at_5 value: 36.738
    • type: ndcg_at_1 value: 28.814
    • type: ndcg_at_10 value: 41.028
    • type: ndcg_at_100 value: 46.162
    • type: ndcg_at_1000 value: 48.15
    • type: ndcg_at_20 value: 42.824
    • type: ndcg_at_3 value: 35.621
    • type: ndcg_at_5 value: 38.277
    • type: precision_at_1 value: 28.814
    • type: precision_at_10 value: 6.361999999999999
    • type: precision_at_100 value: 0.9450000000000001
    • type: precision_at_1000 value: 0.11399999999999999
    • type: precision_at_20 value: 3.6159999999999997
    • type: precision_at_3 value: 15.140999999999998
    • type: precision_at_5 value: 10.712000000000002
    • type: recall_at_1 value: 26.651999999999997
    • type: recall_at_10 value: 55.038
    • type: recall_at_100 value: 78.806
    • type: recall_at_1000 value: 93.485
    • type: recall_at_20 value: 61.742
    • type: recall_at_3 value: 40.682
    • type: recall_at_5 value: 46.855000000000004
    • type: main_score value: 41.028 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackMathematicaRetrieval (default) revision: 90fceea13679c63fe563ded68f3b6f06e50061de split: test type: mteb/cqadupstack-mathematica metrics:

    • type: map_at_1 value: 17.627000000000002
    • type: map_at_10 value: 26.436999999999998
    • type: map_at_100 value: 27.85
    • type: map_at_1000 value: 27.955999999999996
    • type: map_at_20 value: 27.233
    • type: map_at_3 value: 23.777
    • type: map_at_5 value: 25.122
    • type: mrr_at_1 value: 22.387999999999998
    • type: mrr_at_10 value: 31.589
    • type: mrr_at_100 value: 32.641999999999996
    • type: mrr_at_1000 value: 32.696999999999996
    • type: mrr_at_20 value: 32.201
    • type: mrr_at_3 value: 28.98
    • type: mrr_at_5 value: 30.342000000000002
    • type: ndcg_at_1 value: 22.387999999999998
    • type: ndcg_at_10 value: 32.129999999999995
    • type: ndcg_at_100 value: 38.562999999999995
    • type: ndcg_at_1000 value: 40.903
    • type: ndcg_at_20 value: 34.652
    • type: ndcg_at_3 value: 27.26
    • type: ndcg_at_5 value: 29.235
    • type: precision_at_1 value: 22.387999999999998
    • type: precision_at_10 value: 5.970000000000001
    • type: precision_at_100 value: 1.068
    • type: precision_at_1000 value: 0.13899999999999998
    • type: precision_at_20 value: 3.6999999999999997
    • type: precision_at_3 value: 13.267000000000001
    • type: precision_at_5 value: 9.403
    • type: recall_at_1 value: 17.627000000000002
    • type: recall_at_10 value: 44.71
    • type: recall_at_100 value: 72.426
    • type: recall_at_1000 value: 88.64699999999999
    • type: recall_at_20 value: 53.65
    • type: recall_at_3 value: 30.989
    • type: recall_at_5 value: 36.237
    • type: main_score value: 32.129999999999995 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackPhysicsRetrieval (default) revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 split: test type: mteb/cqadupstack-physics metrics:

    • type: map_at_1 value: 30.891000000000002
    • type: map_at_10 value: 41.519
    • type: map_at_100 value: 42.896
    • type: map_at_1000 value: 42.992999999999995
    • type: map_at_20 value: 42.287
    • type: map_at_3 value: 37.822
    • type: map_at_5 value: 39.976
    • type: mrr_at_1 value: 37.921
    • type: mrr_at_10 value: 47.260999999999996
    • type: mrr_at_100 value: 48.044
    • type: mrr_at_1000 value: 48.08
    • type: mrr_at_20 value: 47.699999999999996
    • type: mrr_at_3 value: 44.513999999999996
    • type: mrr_at_5 value: 46.064
    • type: ndcg_at_1 value: 37.921
    • type: ndcg_at_10 value: 47.806
    • type: ndcg_at_100 value: 53.274
    • type: ndcg_at_1000 value: 55.021
    • type: ndcg_at_20 value: 49.973
    • type: ndcg_at_3 value: 42.046
    • type: ndcg_at_5 value: 44.835
    • type: precision_at_1 value: 37.921
    • type: precision_at_10 value: 8.767999999999999
    • type: precision_at_100 value: 1.353
    • type: precision_at_1000 value: 0.168
    • type: precision_at_20 value: 5.135
    • type: precision_at_3 value: 20.051
    • type: precision_at_5 value: 14.398
    • type: recall_at_1 value: 30.891000000000002
    • type: recall_at_10 value: 60.897999999999996
    • type: recall_at_100 value: 83.541
    • type: recall_at_1000 value: 94.825
    • type: recall_at_20 value: 68.356
    • type: recall_at_3 value: 44.65
    • type: recall_at_5 value: 51.919000000000004
    • type: main_score value: 47.806 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackProgrammersRetrieval (default) revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 split: test type: mteb/cqadupstack-programmers metrics:

    • type: map_at_1 value: 27.654
    • type: map_at_10 value: 38.025999999999996
    • type: map_at_100 value: 39.425
    • type: map_at_1000 value: 39.528
    • type: map_at_20 value: 38.838
    • type: map_at_3 value: 34.745
    • type: map_at_5 value: 36.537
    • type: mrr_at_1 value: 34.018
    • type: mrr_at_10 value: 43.314
    • type: mrr_at_100 value: 44.283
    • type: mrr_at_1000 value: 44.327
    • type: mrr_at_20 value: 43.929
    • type: mrr_at_3 value: 40.868
    • type: mrr_at_5 value: 42.317
    • type: ndcg_at_1 value: 34.018
    • type: ndcg_at_10 value: 43.887
    • type: ndcg_at_100 value: 49.791000000000004
    • type: ndcg_at_1000 value: 51.834
    • type: ndcg_at_20 value: 46.376
    • type: ndcg_at_3 value: 38.769999999999996
    • type: ndcg_at_5 value: 41.144
    • type: precision_at_1 value: 34.018
    • type: precision_at_10 value: 8.001999999999999
    • type: precision_at_100 value: 1.2630000000000001
    • type: precision_at_1000 value: 0.16
    • type: precision_at_20 value: 4.737
    • type: precision_at_3 value: 18.417
    • type: precision_at_5 value: 13.150999999999998
    • type: recall_at_1 value: 27.654
    • type: recall_at_10 value: 56.111
    • type: recall_at_100 value: 81.136
    • type: recall_at_1000 value: 94.788
    • type: recall_at_20 value: 65.068
    • type: recall_at_3 value: 41.713
    • type: recall_at_5 value: 48.106
    • type: main_score value: 43.887 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackRetrieval (default) revision: CQADupstackRetrieval_is_a_combined_dataset split: test type: CQADupstackRetrieval_is_a_combined_dataset metrics:

    • type: main_score value: 42.58858333333333
    • type: ndcg_at_10 value: 42.58858333333333 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackStatsRetrieval (default) revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a split: test type: mteb/cqadupstack-stats metrics:

    • type: map_at_1 value: 24.501
    • type: map_at_10 value: 32.814
    • type: map_at_100 value: 33.754
    • type: map_at_1000 value: 33.859
    • type: map_at_20 value: 33.324
    • type: map_at_3 value: 30.758000000000003
    • type: map_at_5 value: 31.936999999999998
    • type: mrr_at_1 value: 27.761000000000003
    • type: mrr_at_10 value: 35.662
    • type: mrr_at_100 value: 36.443999999999996
    • type: mrr_at_1000 value: 36.516999999999996
    • type: mrr_at_20 value: 36.085
    • type: mrr_at_3 value: 33.742
    • type: mrr_at_5 value: 34.931
    • type: ndcg_at_1 value: 27.761000000000003
    • type: ndcg_at_10 value: 37.208000000000006
    • type: ndcg_at_100 value: 41.839
    • type: ndcg_at_1000 value: 44.421
    • type: ndcg_at_20 value: 38.917
    • type: ndcg_at_3 value: 33.544000000000004
    • type: ndcg_at_5 value: 35.374
    • type: precision_at_1 value: 27.761000000000003
    • type: precision_at_10 value: 5.92
    • type: precision_at_100 value: 0.899
    • type: precision_at_1000 value: 0.12
    • type: precision_at_20 value: 3.4130000000000003
    • type: precision_at_3 value: 15.031
    • type: precision_at_5 value: 10.306999999999999
    • type: recall_at_1 value: 24.501
    • type: recall_at_10 value: 47.579
    • type: recall_at_100 value: 69.045
    • type: recall_at_1000 value: 88.032
    • type: recall_at_20 value: 54.125
    • type: recall_at_3 value: 37.202
    • type: recall_at_5 value: 41.927
    • type: main_score value: 37.208000000000006 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackTexRetrieval (default) revision: 46989137a86843e03a6195de44b09deda022eec7 split: test type: mteb/cqadupstack-tex metrics:

    • type: map_at_1 value: 18.29
    • type: map_at_10 value: 26.183
    • type: map_at_100 value: 27.351999999999997
    • type: map_at_1000 value: 27.483999999999998
    • type: map_at_20 value: 26.798
    • type: map_at_3 value: 23.629
    • type: map_at_5 value: 24.937
    • type: mrr_at_1 value: 22.299
    • type: mrr_at_10 value: 30.189
    • type: mrr_at_100 value: 31.098
    • type: mrr_at_1000 value: 31.177
    • type: mrr_at_20 value: 30.697000000000003
    • type: mrr_at_3 value: 27.862
    • type: mrr_at_5 value: 29.066
    • type: ndcg_at_1 value: 22.299
    • type: ndcg_at_10 value: 31.202
    • type: ndcg_at_100 value: 36.617
    • type: ndcg_at_1000 value: 39.544000000000004
    • type: ndcg_at_20 value: 33.177
    • type: ndcg_at_3 value: 26.639000000000003
    • type: ndcg_at_5 value: 28.526
    • type: precision_at_1 value: 22.299
    • type: precision_at_10 value: 5.8020000000000005
    • type: precision_at_100 value: 1.0070000000000001
    • type: precision_at_1000 value: 0.14400000000000002
    • type: precision_at_20 value: 3.505
    • type: precision_at_3 value: 12.698
    • type: precision_at_5 value: 9.174
    • type: recall_at_1 value: 18.29
    • type: recall_at_10 value: 42.254999999999995
    • type: recall_at_100 value: 66.60000000000001
    • type: recall_at_1000 value: 87.31400000000001
    • type: recall_at_20 value: 49.572
    • type: recall_at_3 value: 29.342000000000002
    • type: recall_at_5 value: 34.221000000000004
    • type: main_score value: 31.202 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackUnixRetrieval (default) revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 split: test type: mteb/cqadupstack-unix metrics:

    • type: map_at_1 value: 27.722
    • type: map_at_10 value: 37.698
    • type: map_at_100 value: 38.899
    • type: map_at_1000 value: 38.998
    • type: map_at_20 value: 38.381
    • type: map_at_3 value: 34.244
    • type: map_at_5 value: 36.295
    • type: mrr_at_1 value: 32.183
    • type: mrr_at_10 value: 41.429
    • type: mrr_at_100 value: 42.308
    • type: mrr_at_1000 value: 42.358000000000004
    • type: mrr_at_20 value: 41.957
    • type: mrr_at_3 value: 38.401999999999994
    • type: mrr_at_5 value: 40.294999999999995
    • type: ndcg_at_1 value: 32.183
    • type: ndcg_at_10 value: 43.519000000000005
    • type: ndcg_at_100 value: 48.786
    • type: ndcg_at_1000 value: 50.861999999999995
    • type: ndcg_at_20 value: 45.654
    • type: ndcg_at_3 value: 37.521
    • type: ndcg_at_5 value: 40.615
    • type: precision_at_1 value: 32.183
    • type: precision_at_10 value: 7.603
    • type: precision_at_100 value: 1.135
    • type: precision_at_1000 value: 0.14200000000000002
    • type: precision_at_20 value: 4.408
    • type: precision_at_3 value: 17.071
    • type: precision_at_5 value: 12.668
    • type: recall_at_1 value: 27.722
    • type: recall_at_10 value: 57.230000000000004
    • type: recall_at_100 value: 79.97999999999999
    • type: recall_at_1000 value: 94.217
    • type: recall_at_20 value: 64.864
    • type: recall_at_3 value: 41.215
    • type: recall_at_5 value: 48.774
    • type: main_score value: 43.519000000000005 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackWebmastersRetrieval (default) revision: 160c094312a0e1facb97e55eeddb698c0abe3571 split: test type: mteb/cqadupstack-webmasters metrics:

    • type: map_at_1 value: 25.852999999999998
    • type: map_at_10 value: 35.394999999999996
    • type: map_at_100 value: 37.291999999999994
    • type: map_at_1000 value: 37.495
    • type: map_at_20 value: 36.372
    • type: map_at_3 value: 32.336
    • type: map_at_5 value: 34.159
    • type: mrr_at_1 value: 31.818
    • type: mrr_at_10 value: 40.677
    • type: mrr_at_100 value: 41.728
    • type: mrr_at_1000 value: 41.778
    • type: mrr_at_20 value: 41.301
    • type: mrr_at_3 value: 38.208
    • type: mrr_at_5 value: 39.592
    • type: ndcg_at_1 value: 31.818
    • type: ndcg_at_10 value: 41.559000000000005
    • type: ndcg_at_100 value: 48.012
    • type: ndcg_at_1000 value: 50.234
    • type: ndcg_at_20 value: 44.15
    • type: ndcg_at_3 value: 36.918
    • type: ndcg_at_5 value: 39.227000000000004
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    • type: precision_at_100 value: 1.625
    • type: precision_at_1000 value: 0.245
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    • type: precision_at_3 value: 17.655
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    • type: recall_at_1 value: 25.852999999999998
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    • type: recall_at_1000 value: 94.657
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    • type: recall_at_3 value: 39.300000000000004
    • type: recall_at_5 value: 45.754
    • type: main_score value: 41.559000000000005 task: type: Retrieval

  • dataset: config: default name: MTEB CQADupstackWordpressRetrieval (default) revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 split: test type: mteb/cqadupstack-wordpress metrics:

    • type: map_at_1 value: 19.23
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    • type: mrr_at_100 value: 31.195
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    • type: precision_at_100 value: 0.893
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    • type: precision_at_20 value: 3.29
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    • type: recall_at_1 value: 19.23
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    • type: recall_at_20 value: 55.533
    • type: recall_at_3 value: 32.865
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    • type: main_score value: 33.511 task: type: Retrieval

  • dataset: config: default name: MTEB ClimateFEVER (default) revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 split: test type: mteb/climate-fever metrics:

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    • type: recall_at_1 value: 19.594
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    • type: recall_at_20 value: 52.611
    • type: recall_at_3 value: 32.528
    • type: recall_at_5 value: 38.933
    • type: main_score value: 42.363 task: type: Retrieval

  • dataset: config: default name: MTEB CmedqaRetrieval (default) revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301 split: dev type: C-MTEB/CmedqaRetrieval metrics:

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  • dataset: config: default name: MTEB Cmnli (default) revision: None split: validation type: C-MTEB/CMNLI metrics:

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  • dataset: config: default name: MTEB CovidRetrieval (default) revision: 1271c7809071a13532e05f25fb53511ffce77117 split: dev type: C-MTEB/CovidRetrieval metrics:

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  • dataset: config: default name: MTEB EmotionClassification (default) revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 split: test type: mteb/emotion metrics:

    • type: accuracy value: 73.29999999999998
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  • dataset: config: default name: MTEB FEVER (default) revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 split: test type: mteb/fever metrics:

    • type: map_at_1 value: 78.371
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    • type: ndcg_at_1 value: 84.443
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    • type: precision_at_1 value: 84.443
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    • type: recall_at_1 value: 78.371
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    • type: recall_at_20 value: 95.707
    • type: recall_at_3 value: 90.853
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  • dataset: config: default name: MTEB FiQA2018 (default) revision: 27a168819829fe9bcd655c2df245fb19452e8e06 split: test type: mteb/fiqa metrics:

    • type: map_at_1 value: 23.810000000000002
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    • type: recall_at_1 value: 23.810000000000002
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    • type: recall_at_3 value: 38.098
    • type: recall_at_5 value: 44.414
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  • dataset: config: default name: MTEB GeoreviewClassification (default) revision: 3765c0d1de6b7d264bc459433c45e5a75513839c split: test type: ai-forever/georeview-classification metrics:

    • type: accuracy value: 48.0126953125
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  • dataset: config: default name: MTEB GeoreviewClusteringP2P (default) revision: 97a313c8fc85b47f13f33e7e9a95c1ad888c7fec split: test type: ai-forever/georeview-clustering-p2p metrics:

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  • dataset: config: default name: MTEB GerDaLIR (default) revision: 0bb47f1d73827e96964edb84dfe552f62f4fd5eb split: test type: jinaai/ger_da_lir metrics:

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  • dataset: config: default name: MTEB GermanSTSBenchmark (default) revision: e36907544d44c3a247898ed81540310442329e20 split: test type: jinaai/german-STSbenchmark metrics:

    • type: cosine_pearson value: 86.55319003300265
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  • dataset: config: default name: MTEB HALClusteringS2S (default) revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915 split: test type: lyon-nlp/clustering-hal-s2s metrics:

    • type: main_score value: 27.477557517301303
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  • dataset: config: default name: MTEB HeadlineClassification (default) revision: 2fe05ee6b5832cda29f2ef7aaad7b7fe6a3609eb split: test type: ai-forever/headline-classification metrics:

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  • dataset: config: default name: MTEB HotpotQA (default) revision: ab518f4d6fcca38d87c25209f94beba119d02014 split: test type: mteb/hotpotqa metrics:

    • type: map_at_1 value: 38.143
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    • type: recall_at_1 value: 38.143
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    • type: recall_at_1000 value: 86.077
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    • type: recall_at_3 value: 56.989000000000004
    • type: recall_at_5 value: 61.35
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  • dataset: config: default name: MTEB IFlyTek (default) revision: 421605374b29664c5fc098418fe20ada9bd55f8a split: validation type: C-MTEB/IFlyTek-classification metrics:

    • type: accuracy value: 41.67756829549827
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  • dataset: config: default name: MTEB ImdbClassification (default) revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 split: test type: mteb/imdb metrics:

    • type: accuracy value: 91.90440000000001
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    • type: f1 value: 91.89564361975891
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  • dataset: config: default name: MTEB InappropriatenessClassification (default) revision: 601651fdc45ef243751676e62dd7a19f491c0285 split: test type: ai-forever/inappropriateness-classification metrics:

    • type: accuracy value: 61.0498046875
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    • type: f1 value: 60.867630038606954
    • type: f1_weighted value: 60.867630038606954
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  • dataset: config: default name: MTEB JDReview (default) revision: b7c64bd89eb87f8ded463478346f76731f07bf8b split: test type: C-MTEB/JDReview-classification metrics:

    • type: accuracy value: 83.50844277673546
    • type: ap value: 48.46732380712268
    • type: ap_weighted value: 48.46732380712268
    • type: f1 value: 77.43967451387445
    • type: f1_weighted value: 84.78462929014114
    • type: main_score value: 83.50844277673546 task: type: Classification

  • dataset: config: default name: MTEB KinopoiskClassification (default) revision: 5911f26666ac11af46cb9c6849d0dc80a378af24 split: test type: ai-forever/kinopoisk-sentiment-classification metrics:

    • type: accuracy value: 62.393333333333324
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    • type: f1_weighted value: 61.35940129568015
    • type: main_score value: 62.393333333333324 task: type: Classification

  • dataset: config: default name: MTEB LCQMC (default) revision: 17f9b096f80380fce5ed12a9be8be7784b337daf split: test type: C-MTEB/LCQMC metrics:

    • type: cosine_pearson value: 67.74375505907872
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    • type: manhattan_spearman value: 75.83288262176175
    • type: pearson value: 67.74375505907872
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  • dataset: config: default name: MTEB LEMBNarrativeQARetrieval (default) revision: 6e346642246bfb4928c560ee08640dc84d074e8c split: test type: dwzhu/LongEmbed metrics:

    • type: map_at_1 value: 23.093
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    • type: map_at_100 value: 31.423000000000002
    • type: map_at_1000 value: 31.533
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    • type: map_at_5 value: 29.253
    • type: mrr_at_1 value: 23.093
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    • type: mrr_at_20 value: 30.835
    • type: mrr_at_3 value: 27.983999999999998
    • type: mrr_at_5 value: 29.253
    • type: ndcg_at_1 value: 23.093
    • type: ndcg_at_10 value: 34.297
    • type: ndcg_at_100 value: 41.049
    • type: ndcg_at_1000 value: 43.566
    • type: ndcg_at_20 value: 36.52
    • type: ndcg_at_3 value: 29.629
    • type: ndcg_at_5 value: 31.926
    • type: precision_at_1 value: 23.093
    • type: precision_at_10 value: 4.735
    • type: precision_at_100 value: 0.8109999999999999
    • type: precision_at_1000 value: 0.1
    • type: precision_at_20 value: 2.8080000000000003
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    • type: recall_at_1 value: 23.093
    • type: recall_at_10 value: 47.354
    • type: recall_at_100 value: 81.147
    • type: recall_at_1000 value: 100.0
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    • type: recall_at_5 value: 40.004
    • type: main_score value: 34.297 task: type: Retrieval

  • dataset: config: default name: MTEB LEMBNeedleRetrieval (default) revision: 6e346642246bfb4928c560ee08640dc84d074e8c split: test_256 type: dwzhu/LongEmbed metrics:

    • type: map_at_1 value: 64.0
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    • type: map_at_100 value: 77.265
    • type: map_at_1000 value: 77.265
    • type: map_at_20 value: 77.265
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    • type: mrr_at_1 value: 64.0
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    • type: mrr_at_1000 value: 77.265
    • type: mrr_at_20 value: 77.265
    • type: mrr_at_3 value: 76.333
    • type: mrr_at_5 value: 76.833
    • type: ndcg_at_1 value: 64.0
    • type: ndcg_at_10 value: 82.325
    • type: ndcg_at_100 value: 82.883
    • type: ndcg_at_1000 value: 82.883
    • type: ndcg_at_20 value: 82.883
    • type: ndcg_at_3 value: 80.833
    • type: ndcg_at_5 value: 81.694
    • type: precision_at_1 value: 64.0
    • type: precision_at_10 value: 9.8
    • type: precision_at_100 value: 1.0
    • type: precision_at_1000 value: 0.1
    • type: precision_at_20 value: 5.0
    • type: precision_at_3 value: 31.333
    • type: precision_at_5 value: 19.2
    • type: recall_at_1 value: 64.0
    • type: recall_at_10 value: 98.0
    • type: recall_at_100 value: 100.0
    • type: recall_at_1000 value: 100.0
    • type: recall_at_20 value: 100.0
    • type: recall_at_3 value: 94.0
    • type: recall_at_5 value: 96.0
    • type: main_score value: 64.0 task: type: Retrieval

  • dataset: config: default name: MTEB LEMBPasskeyRetrieval (default) revision: 6e346642246bfb4928c560ee08640dc84d074e8c split: test_256 type: dwzhu/LongEmbed metrics:

    • type: map_at_1 value: 100.0
    • type: map_at_10 value: 100.0
    • type: map_at_100 value: 100.0
    • type: map_at_1000 value: 100.0
    • type: map_at_20 value: 100.0
    • type: map_at_3 value: 100.0
    • type: map_at_5 value: 100.0
    • type: mrr_at_1 value: 100.0
    • type: mrr_at_10 value: 100.0
    • type: mrr_at_100 value: 100.0
    • type: mrr_at_1000 value: 100.0
    • type: mrr_at_20 value: 100.0
    • type: mrr_at_3 value: 100.0
    • type: mrr_at_5 value: 100.0
    • type: ndcg_at_1 value: 100.0
    • type: ndcg_at_10 value: 100.0
    • type: ndcg_at_100 value: 100.0
    • type: ndcg_at_1000 value: 100.0
    • type: ndcg_at_20 value: 100.0
    • type: ndcg_at_3 value: 100.0
    • type: ndcg_at_5 value: 100.0
    • type: precision_at_1 value: 100.0
    • type: precision_at_10 value: 10.0
    • type: precision_at_100 value: 1.0
    • type: precision_at_1000 value: 0.1
    • type: precision_at_20 value: 5.0
    • type: precision_at_3 value: 33.333
    • type: precision_at_5 value: 20.0
    • type: recall_at_1 value: 100.0
    • type: recall_at_10 value: 100.0
    • type: recall_at_100 value: 100.0
    • type: recall_at_1000 value: 100.0
    • type: recall_at_20 value: 100.0
    • type: recall_at_3 value: 100.0
    • type: recall_at_5 value: 100.0
    • type: main_score value: 100.0 task: type: Retrieval

  • dataset: config: default name: MTEB LEMBQMSumRetrieval (default) revision: 6e346642246bfb4928c560ee08640dc84d074e8c split: test type: dwzhu/LongEmbed metrics:

    • type: map_at_1 value: 24.361
    • type: map_at_10 value: 33.641
    • type: map_at_100 value: 35.104
    • type: map_at_1000 value: 35.127
    • type: map_at_20 value: 34.388999999999996
    • type: map_at_3 value: 30.255
    • type: map_at_5 value: 32.079
    • type: mrr_at_1 value: 24.361
    • type: mrr_at_10 value: 33.641
    • type: mrr_at_100 value: 35.104
    • type: mrr_at_1000 value: 35.127
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    • type: mrr_at_3 value: 30.255
    • type: mrr_at_5 value: 32.079
    • type: ndcg_at_1 value: 24.361
    • type: ndcg_at_10 value: 39.337
    • type: ndcg_at_100 value: 47.384
    • type: ndcg_at_1000 value: 47.75
    • type: ndcg_at_20 value: 42.077999999999996
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    • type: precision_at_1 value: 24.361
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    • type: precision_at_100 value: 0.975
    • type: precision_at_1000 value: 0.1
    • type: precision_at_20 value: 3.435
    • type: precision_at_3 value: 12.661
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    • type: recall_at_1 value: 24.361
    • type: recall_at_10 value: 57.826
    • type: recall_at_100 value: 97.51100000000001
    • type: recall_at_1000 value: 100.0
    • type: recall_at_20 value: 68.697
    • type: recall_at_3 value: 37.983
    • type: recall_at_5 value: 45.972
    • type: main_score value: 39.337 task: type: Retrieval

  • dataset: config: default name: MTEB LEMBSummScreenFDRetrieval (default) revision: 6e346642246bfb4928c560ee08640dc84d074e8c split: validation type: dwzhu/LongEmbed metrics:

    • type: map_at_1 value: 84.821
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    • type: map_at_1000 value: 90.158
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    • type: mrr_at_1 value: 84.821
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    • type: mrr_at_1000 value: 90.158
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    • type: ndcg_at_1 value: 84.821
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    • type: ndcg_at_1000 value: 92.535
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    • type: precision_at_1 value: 84.821
    • type: precision_at_10 value: 9.911
    • type: precision_at_100 value: 1.0
    • type: precision_at_1000 value: 0.1
    • type: precision_at_20 value: 4.97
    • type: precision_at_3 value: 31.746000000000002
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    • type: recall_at_1 value: 84.821
    • type: recall_at_10 value: 99.107
    • type: recall_at_100 value: 100.0
    • type: recall_at_1000 value: 100.0
    • type: recall_at_20 value: 99.405
    • type: recall_at_3 value: 95.238
    • type: recall_at_5 value: 97.321
    • type: main_score value: 92.334 task: type: Retrieval

  • dataset: config: default name: MTEB LEMBWikimQARetrieval (default) revision: 6e346642246bfb4928c560ee08640dc84d074e8c split: test type: dwzhu/LongEmbed metrics:

    • type: map_at_1 value: 53.667
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    • type: mrr_at_10 value: 61.719
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    • type: ndcg_at_1 value: 53.667
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    • type: ndcg_at_100 value: 69.726
    • type: ndcg_at_1000 value: 70.143
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    • type: precision_at_1 value: 53.667
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    • type: precision_at_100 value: 0.97
    • type: precision_at_1000 value: 0.1
    • type: precision_at_20 value: 4.3
    • type: precision_at_3 value: 22.0
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    • type: recall_at_1 value: 53.667
    • type: recall_at_10 value: 79.667
    • type: recall_at_100 value: 97.0
    • type: recall_at_1000 value: 100.0
    • type: recall_at_20 value: 86.0
    • type: recall_at_3 value: 66.0
    • type: recall_at_5 value: 73.667
    • type: main_score value: 66.018 task: type: Retrieval

  • dataset: config: deu-deu name: MTEB MLQARetrieval (deu-deu) revision: 397ed406c1a7902140303e7faf60fff35b58d285 split: test type: facebook/mlqa metrics:

    • type: main_score value: 67.548
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  • dataset: config: deu-spa name: MTEB MLQARetrieval (deu-spa) revision: 397ed406c1a7902140303e7faf60fff35b58d285 split: test type: facebook/mlqa metrics:

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  • dataset: config: deu-eng name: MTEB MLQARetrieval (deu-eng) revision: 397ed406c1a7902140303e7faf60fff35b58d285 split: test type: facebook/mlqa metrics:

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  • dataset: config: spa-deu name: MTEB MLQARetrieval (spa-deu) revision: 397ed406c1a7902140303e7faf60fff35b58d285 split: test type: facebook/mlqa metrics:

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  • dataset: config: spa-spa name: MTEB MLQARetrieval (spa-spa) revision: 397ed406c1a7902140303e7faf60fff35b58d285 split: test type: facebook/mlqa metrics:

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  • dataset: config: spa-eng name: MTEB MLQARetrieval (spa-eng) revision: 397ed406c1a7902140303e7faf60fff35b58d285 split: test type: facebook/mlqa metrics:

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  • dataset: config: eng-deu name: MTEB MLQARetrieval (eng-deu) revision: 397ed406c1a7902140303e7faf60fff35b58d285 split: test type: facebook/mlqa metrics:

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  • dataset: config: eng-spa name: MTEB MLQARetrieval (eng-spa) revision: 397ed406c1a7902140303e7faf60fff35b58d285 split: test type: facebook/mlqa metrics:

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  • dataset: config: eng-eng name: MTEB MLQARetrieval (eng-eng) revision: 397ed406c1a7902140303e7faf60fff35b58d285 split: test type: facebook/mlqa metrics:

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  • dataset: config: de name: MTEB MLSUMClusteringP2P (de) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:

    • type: main_score value: 41.267647761702854
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  • dataset: config: fr name: MTEB MLSUMClusteringP2P (fr) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:

    • type: main_score value: 44.68714862333979
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  • dataset: config: ru name: MTEB MLSUMClusteringP2P (ru) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:

    • type: main_score value: 41.92518785753813
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  • dataset: config: es name: MTEB MLSUMClusteringP2P (es) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:

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  • dataset: config: de name: MTEB MLSUMClusteringS2S (de) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:

    • type: main_score value: 40.07927325071353
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  • dataset: config: fr name: MTEB MLSUMClusteringS2S (fr) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:

    • type: main_score value: 44.88484854069901
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  • dataset: config: ru name: MTEB MLSUMClusteringS2S (ru) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:

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  • dataset: config: es name: MTEB MLSUMClusteringS2S (es) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:

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  • dataset: config: default name: MTEB MMarcoReranking (default) revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6 split: dev type: C-MTEB/Mmarco-reranking metrics:

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  • dataset: config: default name: MTEB MMarcoRetrieval (default) revision: 539bbde593d947e2a124ba72651aafc09eb33fc2 split: dev type: C-MTEB/MMarcoRetrieval metrics:

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    • type: precision_at_100 value: 1.0330000000000001
    • type: precision_at_1000 value: 0.105
    • type: precision_at_20 value: 4.958
    • type: precision_at_3 value: 28.515
    • type: precision_at_5 value: 18.201
    • type: recall_at_1 value: 66.872
    • type: recall_at_10 value: 90.688
    • type: recall_at_100 value: 96.99
    • type: recall_at_1000 value: 98.958
    • type: recall_at_20 value: 93.21199999999999
    • type: recall_at_3 value: 80.84599999999999
    • type: recall_at_5 value: 85.732 task: type: Retrieval

  • dataset: config: default name: MTEB MSMARCO (default) revision: c5a29a104738b98a9e76336939199e264163d4a0 split: dev type: mteb/msmarco metrics:

    • type: map_at_1 value: 21.861
    • type: map_at_10 value: 34.008
    • type: map_at_100 value: 35.174
    • type: map_at_1000 value: 35.224
    • type: map_at_20 value: 34.705999999999996
    • type: map_at_3 value: 30.209000000000003
    • type: map_at_5 value: 32.351
    • type: mrr_at_1 value: 22.493
    • type: mrr_at_10 value: 34.583999999999996
    • type: mrr_at_100 value: 35.691
    • type: mrr_at_1000 value: 35.736000000000004
    • type: mrr_at_20 value: 35.257
    • type: mrr_at_3 value: 30.85
    • type: mrr_at_5 value: 32.962
    • type: ndcg_at_1 value: 22.493
    • type: ndcg_at_10 value: 40.815
    • type: ndcg_at_100 value: 46.483999999999995
    • type: ndcg_at_1000 value: 47.73
    • type: ndcg_at_20 value: 43.302
    • type: ndcg_at_3 value: 33.056000000000004
    • type: ndcg_at_5 value: 36.879
    • type: precision_at_1 value: 22.493
    • type: precision_at_10 value: 6.465999999999999
    • type: precision_at_100 value: 0.932
    • type: precision_at_1000 value: 0.104
    • type: precision_at_20 value: 3.752
    • type: precision_at_3 value: 14.069
    • type: precision_at_5 value: 10.384
    • type: recall_at_1 value: 21.861
    • type: recall_at_10 value: 61.781
    • type: recall_at_100 value: 88.095
    • type: recall_at_1000 value: 97.625
    • type: recall_at_20 value: 71.44500000000001
    • type: recall_at_3 value: 40.653
    • type: recall_at_5 value: 49.841
    • type: main_score value: 40.815 task: type: Retrieval

  • dataset: config: en name: MTEB MTOPDomainClassification (en) revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf split: test type: mteb/mtop_domain metrics:

    • type: accuracy value: 97.4874601003192
    • type: f1 value: 97.19067544931094
    • type: f1_weighted value: 97.49331776181019
    • type: main_score value: 97.4874601003192 task: type: Classification

  • dataset: config: de name: MTEB MTOPDomainClassification (de) revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf split: test type: mteb/mtop_domain metrics:

    • type: accuracy value: 96.89489997182305
    • type: f1 value: 96.51138586512977
    • type: f1_weighted value: 96.89723065967186
    • type: main_score value: 96.89489997182305 task: type: Classification

  • dataset: config: es name: MTEB MTOPDomainClassification (es) revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf split: test type: mteb/mtop_domain metrics:

    • type: accuracy value: 97.17144763175452
    • type: f1 value: 96.81785681878274
    • type: f1_weighted value: 97.1778974586874
    • type: main_score value: 97.17144763175452 task: type: Classification

  • dataset: config: fr name: MTEB MTOPDomainClassification (fr) revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf split: test type: mteb/mtop_domain metrics:

    • type: accuracy value: 96.30128405887879
    • type: f1 value: 95.94555923088487
    • type: f1_weighted value: 96.30399416794926
    • type: main_score value: 96.30128405887879 task: type: Classification

  • dataset: config: en name: MTEB MTOPIntentClassification (en) revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba split: test type: mteb/mtop_intent metrics:

    • type: accuracy value: 84.53488372093022
    • type: f1 value: 61.77995074251401
    • type: f1_weighted value: 86.8005170485101
    • type: main_score value: 84.53488372093022 task: type: Classification

  • dataset: config: de name: MTEB MTOPIntentClassification (de) revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba split: test type: mteb/mtop_intent metrics:

    • type: accuracy value: 80.79459002535924
    • type: f1 value: 56.08938302001448
    • type: f1_weighted value: 83.66582131948252
    • type: main_score value: 80.79459002535924 task: type: Classification

  • dataset: config: es name: MTEB MTOPIntentClassification (es) revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba split: test type: mteb/mtop_intent metrics:

    • type: accuracy value: 84.7765176784523
    • type: f1 value: 61.39860057885528
    • type: f1_weighted value: 86.94881745670745
    • type: main_score value: 84.7765176784523 task: type: Classification

  • dataset: config: fr name: MTEB MTOPIntentClassification (fr) revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba split: test type: mteb/mtop_intent metrics:

    • type: accuracy value: 82.2079549013467
    • type: f1 value: 59.90260478749016
    • type: f1_weighted value: 84.36861708593257
    • type: main_score value: 82.2079549013467 task: type: Classification

  • dataset: config: eng name: MTEB MasakhaNEWSClassification (eng) revision: 18193f187b92da67168c655c9973a165ed9593dd split: test type: mteb/masakhanews metrics:

    • type: accuracy value: 74.98945147679325
    • type: f1 value: 74.3157483560261
    • type: f1_weighted value: 75.01179008904884
    • type: main_score value: 74.98945147679325 task: type: Classification

  • dataset: config: fra name: MTEB MasakhaNEWSClassification (fra) revision: 18193f187b92da67168c655c9973a165ed9593dd split: test type: mteb/masakhanews metrics:

    • type: accuracy value: 74.02843601895735
    • type: f1 value: 70.40326349620732
    • type: f1_weighted value: 74.6596277063484
    • type: main_score value: 74.02843601895735 task: type: Classification

  • dataset: config: amh name: MTEB MasakhaNEWSClusteringP2P (amh) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 69.45780291725053
    • type: v_measure value: 69.45780291725053
    • type: v_measure_std value: 36.54340055904091 task: type: Clustering

  • dataset: config: eng name: MTEB MasakhaNEWSClusteringP2P (eng) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 64.88996119332239
    • type: v_measure value: 64.88996119332239
    • type: v_measure_std value: 30.017223408197268 task: type: Clustering

  • dataset: config: fra name: MTEB MasakhaNEWSClusteringP2P (fra) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 42.362383958691666
    • type: v_measure value: 42.362383958691666
    • type: v_measure_std value: 37.61076788039063 task: type: Clustering

  • dataset: config: hau name: MTEB MasakhaNEWSClusteringP2P (hau) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 43.29201252405562
    • type: v_measure value: 43.29201252405562
    • type: v_measure_std value: 34.31987945146255 task: type: Clustering

  • dataset: config: ibo name: MTEB MasakhaNEWSClusteringP2P (ibo) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 33.59926542995238
    • type: v_measure value: 33.59926542995238
    • type: v_measure_std value: 35.70048601084112 task: type: Clustering

  • dataset: config: lin name: MTEB MasakhaNEWSClusteringP2P (lin) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 67.58487601893106
    • type: v_measure value: 67.58487601893106
    • type: v_measure_std value: 35.16784970777931 task: type: Clustering

  • dataset: config: lug name: MTEB MasakhaNEWSClusteringP2P (lug) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 50.01220872023533
    • type: v_measure value: 50.01220872023533
    • type: v_measure_std value: 41.87411574676182 task: type: Clustering

  • dataset: config: orm name: MTEB MasakhaNEWSClusteringP2P (orm) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 29.007847502598317
    • type: v_measure value: 29.007847502598317
    • type: v_measure_std value: 38.374997395079994 task: type: Clustering

  • dataset: config: pcm name: MTEB MasakhaNEWSClusteringP2P (pcm) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 79.13520228554611
    • type: v_measure value: 79.13520228554611
    • type: v_measure_std value: 18.501843848275183 task: type: Clustering

  • dataset: config: run name: MTEB MasakhaNEWSClusteringP2P (run) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 60.317213909746656
    • type: v_measure value: 60.317213909746656
    • type: v_measure_std value: 36.500281823747386 task: type: Clustering

  • dataset: config: sna name: MTEB MasakhaNEWSClusteringP2P (sna) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 59.395277358240946
    • type: v_measure value: 59.395277358240946
    • type: v_measure_std value: 37.500916816164654 task: type: Clustering

  • dataset: config: som name: MTEB MasakhaNEWSClusteringP2P (som) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 38.18638688704302
    • type: v_measure value: 38.18638688704302
    • type: v_measure_std value: 35.453681137564466 task: type: Clustering

  • dataset: config: swa name: MTEB MasakhaNEWSClusteringP2P (swa) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 29.49230755729658
    • type: v_measure value: 29.49230755729658
    • type: v_measure_std value: 28.284313285264645 task: type: Clustering

  • dataset: config: tir name: MTEB MasakhaNEWSClusteringP2P (tir) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 60.632258622750115
    • type: v_measure value: 60.632258622750115
    • type: v_measure_std value: 34.429711214740564 task: type: Clustering

  • dataset: config: xho name: MTEB MasakhaNEWSClusteringP2P (xho) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 41.76322918806381
    • type: v_measure value: 41.76322918806381
    • type: v_measure_std value: 36.43245296200775 task: type: Clustering

  • dataset: config: yor name: MTEB MasakhaNEWSClusteringP2P (yor) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 33.17083910808645
    • type: v_measure value: 33.17083910808645
    • type: v_measure_std value: 34.87547994284835 task: type: Clustering

  • dataset: config: amh name: MTEB MasakhaNEWSClusteringS2S (amh) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 60.95132147787602
    • type: v_measure value: 60.95132147787602
    • type: v_measure_std value: 37.330148394033365 task: type: Clustering

  • dataset: config: eng name: MTEB MasakhaNEWSClusteringS2S (eng) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 60.974810831426595
    • type: v_measure value: 60.974810831426595
    • type: v_measure_std value: 24.934675467507827 task: type: Clustering

  • dataset: config: fra name: MTEB MasakhaNEWSClusteringS2S (fra) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 44.479206673553335
    • type: v_measure value: 44.479206673553335
    • type: v_measure_std value: 32.58254804499339 task: type: Clustering

  • dataset: config: hau name: MTEB MasakhaNEWSClusteringS2S (hau) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 26.4742082741682
    • type: v_measure value: 26.4742082741682
    • type: v_measure_std value: 22.344929192323097 task: type: Clustering

  • dataset: config: ibo name: MTEB MasakhaNEWSClusteringS2S (ibo) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 38.906129911741985
    • type: v_measure value: 38.906129911741985
    • type: v_measure_std value: 34.785601792668444 task: type: Clustering

  • dataset: config: lin name: MTEB MasakhaNEWSClusteringS2S (lin) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 62.60982020876592
    • type: v_measure value: 62.60982020876592
    • type: v_measure_std value: 40.7368955715045 task: type: Clustering

  • dataset: config: lug name: MTEB MasakhaNEWSClusteringS2S (lug) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 42.70424106365967
    • type: v_measure value: 42.70424106365967
    • type: v_measure_std value: 46.80946241135087 task: type: Clustering

  • dataset: config: orm name: MTEB MasakhaNEWSClusteringS2S (orm) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 28.609942199922322
    • type: v_measure value: 28.609942199922322
    • type: v_measure_std value: 38.46685040191088 task: type: Clustering

  • dataset: config: pcm name: MTEB MasakhaNEWSClusteringS2S (pcm) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 76.83901348810822
    • type: v_measure value: 76.83901348810822
    • type: v_measure_std value: 17.57617141269189 task: type: Clustering

  • dataset: config: run name: MTEB MasakhaNEWSClusteringS2S (run) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 46.89757547846193
    • type: v_measure value: 46.89757547846193
    • type: v_measure_std value: 44.58903590203438 task: type: Clustering

  • dataset: config: sna name: MTEB MasakhaNEWSClusteringS2S (sna) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 55.37185207068829
    • type: v_measure value: 55.37185207068829
    • type: v_measure_std value: 36.944574863543004 task: type: Clustering

  • dataset: config: som name: MTEB MasakhaNEWSClusteringS2S (som) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 37.44211021681754
    • type: v_measure value: 37.44211021681754
    • type: v_measure_std value: 33.41469994463241 task: type: Clustering

  • dataset: config: swa name: MTEB MasakhaNEWSClusteringS2S (swa) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 26.020680621216062
    • type: v_measure value: 26.020680621216062
    • type: v_measure_std value: 25.480037522570413 task: type: Clustering

  • dataset: config: tir name: MTEB MasakhaNEWSClusteringS2S (tir) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 63.74306846771303
    • type: v_measure value: 63.74306846771303
    • type: v_measure_std value: 32.19119631078685 task: type: Clustering

  • dataset: config: xho name: MTEB MasakhaNEWSClusteringS2S (xho) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 24.580890519243777
    • type: v_measure value: 24.580890519243777
    • type: v_measure_std value: 37.941836363967106 task: type: Clustering

  • dataset: config: yor name: MTEB MasakhaNEWSClusteringS2S (yor) revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 split: test type: masakhane/masakhanews metrics:

    • type: main_score value: 43.63458888828314
    • type: v_measure value: 43.63458888828314
    • type: v_measure_std value: 31.28169350649098 task: type: Clustering

  • dataset: config: pl name: MTEB MassiveIntentClassification (pl) revision: 4672e20407010da34463acc759c162ca9734bca6 split: test type: mteb/amazon_massive_intent metrics:

    • type: accuracy value: 75.37323470073974
    • type: f1 value: 71.1836877753734
    • type: f1_weighted value: 75.72073213955457
    • type: main_score value: 75.37323470073974 task: type: Classification

  • dataset: config: de name: MTEB MassiveIntentClassification (de) revision: 4672e20407010da34463acc759c162ca9734bca6 split: test type: mteb/amazon_massive_intent metrics:

    • type: accuracy value: 74.83523873570948
    • type: f1 value: 70.72375821116886
    • type: f1_weighted value: 75.20800490010755
    • type: main_score value: 74.83523873570948 task: type: Classification

  • dataset: config: es name: MTEB MassiveIntentClassification (es) revision: 4672e20407010da34463acc759c162ca9734bca6 split: test type: mteb/amazon_massive_intent metrics:

    • type: accuracy value: 75.31607262945528
    • type: f1 value: 72.06063554897662
    • type: f1_weighted value: 75.72438161355252
    • type: main_score value: 75.31607262945528 task: type: Classification

  • dataset: config: ru name: MTEB MassiveIntentClassification (ru) revision: 4672e20407010da34463acc759c162ca9734bca6 split: test type: mteb/amazon_massive_intent metrics:

    • type: accuracy value: 76.7955615332885
    • type: f1 value: 73.08099648499756
    • type: f1_weighted value: 77.18482068239668
    • type: main_score value: 76.7955615332885 task: type: Classification

  • dataset: config: en name: MTEB MassiveIntentClassification (en) revision: 4672e20407010da34463acc759c162ca9734bca6 split: test type: mteb/amazon_massive_intent metrics:

    • type: accuracy value: 77.60591795561534
    • type: f1 value: 74.46676705370395
    • type: f1_weighted value: 77.69888062336614
    • type: main_score value: 77.60591795561534 task: type: Classification

  • dataset: config: fr name: MTEB MassiveIntentClassification (fr) revision: 4672e20407010da34463acc759c162ca9734bca6 split: test type: mteb/amazon_massive_intent metrics:

    • type: accuracy value: 76.32145258910558
    • type: f1 value: 72.89824154178328
    • type: f1_weighted value: 76.6539327979472
    • type: main_score value: 76.32145258910558 task: type: Classification

  • dataset: config: zh-CN name: MTEB MassiveIntentClassification (zh-CN) revision: 4672e20407010da34463acc759c162ca9734bca6 split: test type: mteb/amazon_massive_intent metrics:

    • type: accuracy value: 73.21788836583724
    • type: f1 value: 70.45594512246377
    • type: f1_weighted value: 73.67862536499393
    • type: main_score value: 73.21788836583724 task: type: Classification

  • dataset: config: zh-CN name: MTEB MassiveScenarioClassification (zh-CN) revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8 split: test type: mteb/amazon_massive_scenario metrics:

    • type: accuracy value: 80.82044384667114
    • type: f1 value: 80.53217664465089
    • type: f1_weighted value: 80.94535087010512
    • type: main_score value: 80.82044384667114 task: type: Classification

  • dataset: config: pl name: MTEB MassiveScenarioClassification (pl) revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8 split: test type: mteb/amazon_massive_scenario metrics:

    • type: accuracy value: 82.1049092131809
    • type: f1 value: 81.55343463694733
    • type: f1_weighted value: 82.33509098770782
    • type: main_score value: 82.1049092131809 task: type: Classification

  • dataset: config: es name: MTEB MassiveScenarioClassification (es) revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8 split: test type: mteb/amazon_massive_scenario metrics:

    • type: accuracy value: 82.58238063214526
    • type: f1 value: 82.27974449333072
    • type: f1_weighted value: 82.81337569618209
    • type: main_score value: 82.58238063214526 task: type: Classification

  • dataset: config: de name: MTEB MassiveScenarioClassification (de) revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8 split: test type: mteb/amazon_massive_scenario metrics:

    • type: accuracy value: 83.97108271687962
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  • dataset: config: en name: MTEB MassiveScenarioClassification (en) revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8 split: test type: mteb/amazon_massive_scenario metrics:

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  • dataset: config: fr name: MTEB MassiveScenarioClassification (fr) revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8 split: test type: mteb/amazon_massive_scenario metrics:

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  • dataset: config: ru name: MTEB MassiveScenarioClassification (ru) revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8 split: test type: mteb/amazon_massive_scenario metrics:

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  • dataset: config: default name: MTEB MedicalRetrieval (default) revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6 split: dev type: C-MTEB/MedicalRetrieval metrics:

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  • dataset: config: default name: MTEB MedrxivClusteringP2P (default) revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 split: test type: mteb/medrxiv-clustering-p2p metrics:

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  • dataset: config: default name: MTEB MedrxivClusteringS2S (default) revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 split: test type: mteb/medrxiv-clustering-s2s metrics:

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  • dataset: config: de name: MTEB MintakaRetrieval (de) revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e split: test type: jinaai/mintakaqa metrics:

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  • dataset: config: es name: MTEB MintakaRetrieval (es) revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e split: test type: jinaai/mintakaqa metrics:

    • type: main_score value: 26.912000000000003
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  • dataset: config: fr name: MTEB MintakaRetrieval (fr) revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e split: test type: jinaai/mintakaqa metrics:

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  • dataset: config: default name: MTEB MultilingualSentiment (default) revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a split: test type: C-MTEB/MultilingualSentiment-classification metrics:

    • type: accuracy value: 73.20999999999998
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  • dataset: config: default name: MTEB NFCorpus (default) revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 split: test type: mteb/nfcorpus metrics:

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    • type: recall_at_1 value: 4.822
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    • type: recall_at_3 value: 10.259
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    • type: main_score value: 36.623 task: type: Retrieval

  • dataset: config: default name: MTEB NQ (default) revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 split: test type: mteb/nq metrics:

    • type: map_at_1 value: 41.411
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    • type: mrr_at_5 value: 58.74
    • type: ndcg_at_1 value: 46.205
    • type: ndcg_at_10 value: 64.23100000000001
    • type: ndcg_at_100 value: 67.242
    • type: ndcg_at_1000 value: 67.72500000000001
    • type: ndcg_at_20 value: 65.77300000000001
    • type: ndcg_at_3 value: 57.516
    • type: ndcg_at_5 value: 61.11600000000001
    • type: precision_at_1 value: 46.205
    • type: precision_at_10 value: 9.873
    • type: precision_at_100 value: 1.158
    • type: precision_at_1000 value: 0.12
    • type: precision_at_20 value: 5.319
    • type: precision_at_3 value: 25.424999999999997
    • type: precision_at_5 value: 17.375
    • type: recall_at_1 value: 41.411
    • type: recall_at_10 value: 82.761
    • type: recall_at_100 value: 95.52199999999999
    • type: recall_at_1000 value: 99.02499999999999
    • type: recall_at_20 value: 88.34
    • type: recall_at_3 value: 65.73
    • type: recall_at_5 value: 73.894
    • type: main_score value: 64.23100000000001 task: type: Retrieval

  • dataset: config: default name: MTEB Ocnli (default) revision: 66e76a618a34d6d565d5538088562851e6daa7ec split: validation type: C-MTEB/OCNLI metrics:

    • type: cosine_accuracy value: 62.3714131023281
    • type: cosine_accuracy_threshold value: 79.70921993255615
    • type: cosine_ap value: 66.41380155495659
    • type: cosine_f1 value: 68.89547185780786
    • type: cosine_f1_threshold value: 72.91591167449951
    • type: cosine_precision value: 57.485875706214685
    • type: cosine_recall value: 85.95564941921859
    • type: dot_accuracy value: 60.47644829453167
    • type: dot_accuracy_threshold value: 36627.362060546875
    • type: dot_ap value: 63.696303449293204
    • type: dot_f1 value: 68.3986041101202
    • type: dot_f1_threshold value: 30452.72216796875
    • type: dot_precision value: 54.04411764705882
    • type: dot_recall value: 93.13621964097149
    • type: euclidean_accuracy value: 63.02111532214402
    • type: euclidean_accuracy_threshold value: 1392.76762008667
    • type: euclidean_ap value: 66.65907089443218
    • type: euclidean_f1 value: 69.05036524413688
    • type: euclidean_f1_threshold value: 1711.5310668945312
    • type: euclidean_precision value: 54.29262394195889
    • type: euclidean_recall value: 94.82576557550159
    • type: main_score value: 63.02111532214402
    • type: manhattan_accuracy value: 62.75040606388739
    • type: manhattan_accuracy_threshold value: 32475.347900390625
    • type: manhattan_ap value: 66.50943585125434
    • type: manhattan_f1 value: 69.08382066276802
    • type: manhattan_f1_threshold value: 41238.470458984375
    • type: manhattan_precision value: 54.75896168108776
    • type: manhattan_recall value: 93.55860612460401
    • type: max_accuracy value: 63.02111532214402
    • type: max_ap value: 66.65907089443218
    • type: max_f1 value: 69.08382066276802
    • type: max_precision value: 57.485875706214685
    • type: max_recall value: 94.82576557550159
    • type: similarity_accuracy value: 62.3714131023281
    • type: similarity_accuracy_threshold value: 79.70921993255615
    • type: similarity_ap value: 66.41380155495659
    • type: similarity_f1 value: 68.89547185780786
    • type: similarity_f1_threshold value: 72.91591167449951
    • type: similarity_precision value: 57.485875706214685
    • type: similarity_recall value: 85.95564941921859 task: type: PairClassification

  • dataset: config: default name: MTEB OnlineShopping (default) revision: e610f2ebd179a8fda30ae534c3878750a96db120 split: test type: C-MTEB/OnlineShopping-classification metrics:

    • type: accuracy value: 91.88000000000001
    • type: ap value: 89.52463684448476
    • type: ap_weighted value: 89.52463684448476
    • type: f1 value: 91.86313022306673
    • type: f1_weighted value: 91.87806318146912
    • type: main_score value: 91.88000000000001 task: type: Classification

  • dataset: config: en name: MTEB OpusparcusPC (en) revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a split: test.full type: GEM/opusparcus metrics:

    • type: cosine_accuracy value: 92.65578635014838
    • type: cosine_accuracy_threshold value: 74.02530312538147
    • type: cosine_ap value: 98.3834226153613
    • type: cosine_f1 value: 94.92567913890312
    • type: cosine_f1_threshold value: 74.02530312538147
    • type: cosine_precision value: 95.562435500516
    • type: cosine_recall value: 94.29735234215886
    • type: dot_accuracy value: 91.54302670623146
    • type: dot_accuracy_threshold value: 34452.29187011719
    • type: dot_ap value: 98.1237257754439
    • type: dot_f1 value: 94.22400803616273
    • type: dot_f1_threshold value: 33670.41931152344
    • type: dot_precision value: 92.9633300297324
    • type: dot_recall value: 95.5193482688391
    • type: euclidean_accuracy value: 92.28486646884274
    • type: euclidean_accuracy_threshold value: 1602.8022766113281
    • type: euclidean_ap value: 98.3099021504706
    • type: euclidean_f1 value: 94.75277497477296
    • type: euclidean_f1_threshold value: 1604.7462463378906
    • type: euclidean_precision value: 93.89999999999999
    • type: euclidean_recall value: 95.62118126272912
    • type: main_score value: 98.3834226153613
    • type: manhattan_accuracy value: 92.2106824925816
    • type: manhattan_accuracy_threshold value: 38872.90954589844
    • type: manhattan_ap value: 98.28694101230218
    • type: manhattan_f1 value: 94.67815509376584
    • type: manhattan_f1_threshold value: 38872.90954589844
    • type: manhattan_precision value: 94.24823410696267
    • type: manhattan_recall value: 95.11201629327903
    • type: max_accuracy value: 92.65578635014838
    • type: max_ap value: 98.3834226153613
    • type: max_f1 value: 94.92567913890312
    • type: max_precision value: 95.562435500516
    • type: max_recall value: 95.62118126272912
    • type: similarity_accuracy value: 92.65578635014838
    • type: similarity_accuracy_threshold value: 74.02530312538147
    • type: similarity_ap value: 98.3834226153613
    • type: similarity_f1 value: 94.92567913890312
    • type: similarity_f1_threshold value: 74.02530312538147
    • type: similarity_precision value: 95.562435500516
    • type: similarity_recall value: 94.29735234215886 task: type: PairClassification

  • dataset: config: de name: MTEB OpusparcusPC (de) revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a split: test.full type: GEM/opusparcus metrics:

    • type: cosine_accuracy value: 87.72178850248403
    • type: cosine_accuracy_threshold value: 73.33863377571106
    • type: cosine_ap value: 96.98901408834976
    • type: cosine_f1 value: 91.89944134078212
    • type: cosine_f1_threshold value: 71.45810127258301
    • type: cosine_precision value: 89.64577656675749
    • type: cosine_recall value: 94.26934097421203
    • type: dot_accuracy value: 86.30234208658624
    • type: dot_accuracy_threshold value: 32027.130126953125
    • type: dot_ap value: 96.12260574893256
    • type: dot_f1 value: 91.31602506714414
    • type: dot_f1_threshold value: 30804.376220703125
    • type: dot_precision value: 85.93091828138164
    • type: dot_recall value: 97.42120343839542
    • type: euclidean_accuracy value: 87.9347054648687
    • type: euclidean_accuracy_threshold value: 1609.6670150756836
    • type: euclidean_ap value: 97.00238860358252
    • type: euclidean_f1 value: 92.1089063221043
    • type: euclidean_f1_threshold value: 1641.8487548828125
    • type: euclidean_precision value: 89.10714285714286
    • type: euclidean_recall value: 95.31996179560649
    • type: main_score value: 97.00238860358252
    • type: manhattan_accuracy value: 87.72178850248403
    • type: manhattan_accuracy_threshold value: 40137.060546875
    • type: manhattan_ap value: 96.98653728159941
    • type: manhattan_f1 value: 92.03865623561896
    • type: manhattan_f1_threshold value: 40137.060546875
    • type: manhattan_precision value: 88.80994671403198
    • type: manhattan_recall value: 95.51098376313276
    • type: max_accuracy value: 87.9347054648687
    • type: max_ap value: 97.00238860358252
    • type: max_f1 value: 92.1089063221043
    • type: max_precision value: 89.64577656675749
    • type: max_recall value: 97.42120343839542
    • type: similarity_accuracy value: 87.72178850248403
    • type: similarity_accuracy_threshold value: 73.33863377571106
    • type: similarity_ap value: 96.98901408834976
    • type: similarity_f1 value: 91.89944134078212
    • type: similarity_f1_threshold value: 71.45810127258301
    • type: similarity_precision value: 89.64577656675749
    • type: similarity_recall value: 94.26934097421203 task: type: PairClassification

  • dataset: config: fr name: MTEB OpusparcusPC (fr) revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a split: test.full type: GEM/opusparcus metrics:

    • type: cosine_accuracy value: 80.92643051771117
    • type: cosine_accuracy_threshold value: 76.68856382369995
    • type: cosine_ap value: 93.74622381534307
    • type: cosine_f1 value: 87.12328767123287
    • type: cosine_f1_threshold value: 71.64022922515869
    • type: cosine_precision value: 80.64243448858834
    • type: cosine_recall value: 94.73684210526315
    • type: dot_accuracy value: 80.858310626703
    • type: dot_accuracy_threshold value: 34028.3935546875
    • type: dot_ap value: 91.18448457633308
    • type: dot_f1 value: 86.82606657290202
    • type: dot_f1_threshold value: 34028.3935546875
    • type: dot_precision value: 82.2380106571936
    • type: dot_recall value: 91.9563058589871
    • type: euclidean_accuracy value: 80.858310626703
    • type: euclidean_accuracy_threshold value: 1595.7651138305664
    • type: euclidean_ap value: 93.8182717829648
    • type: euclidean_f1 value: 87.04044117647058
    • type: euclidean_f1_threshold value: 1609.2475891113281
    • type: euclidean_precision value: 81.00940975192472
    • type: euclidean_recall value: 94.04170804369414
    • type: main_score value: 93.8182717829648
    • type: manhattan_accuracy value: 80.99455040871935
    • type: manhattan_accuracy_threshold value: 38092.132568359375
    • type: manhattan_ap value: 93.77563401151711
    • type: manhattan_f1 value: 86.91983122362869
    • type: manhattan_f1_threshold value: 38092.132568359375
    • type: manhattan_precision value: 82.32682060390763
    • type: manhattan_recall value: 92.05561072492551
    • type: max_accuracy value: 80.99455040871935
    • type: max_ap value: 93.8182717829648
    • type: max_f1 value: 87.12328767123287
    • type: max_precision value: 82.32682060390763
    • type: max_recall value: 94.73684210526315
    • type: similarity_accuracy value: 80.92643051771117
    • type: similarity_accuracy_threshold value: 76.68856382369995
    • type: similarity_ap value: 93.74622381534307
    • type: similarity_f1 value: 87.12328767123287
    • type: similarity_f1_threshold value: 71.64022922515869
    • type: similarity_precision value: 80.64243448858834
    • type: similarity_recall value: 94.73684210526315 task: type: PairClassification

  • dataset: config: ru name: MTEB OpusparcusPC (ru) revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a split: test.full type: GEM/opusparcus metrics:

    • type: cosine_accuracy value: 76.83823529411765
    • type: cosine_accuracy_threshold value: 72.70769476890564
    • type: cosine_ap value: 89.56692049908222
    • type: cosine_f1 value: 83.99832003359934
    • type: cosine_f1_threshold value: 70.9052324295044
    • type: cosine_precision value: 76.16146230007617
    • type: cosine_recall value: 93.63295880149812
    • type: dot_accuracy value: 76.28676470588235
    • type: dot_accuracy_threshold value: 33740.68908691406
    • type: dot_ap value: 87.77185177141567
    • type: dot_f1 value: 83.62251375370292
    • type: dot_f1_threshold value: 32726.611328125
    • type: dot_precision value: 76.29343629343629
    • type: dot_recall value: 92.50936329588015
    • type: euclidean_accuracy value: 77.32843137254902
    • type: euclidean_accuracy_threshold value: 1566.510009765625
    • type: euclidean_ap value: 89.60605626791111
    • type: euclidean_f1 value: 84.06546080964686
    • type: euclidean_f1_threshold value: 1576.4202117919922
    • type: euclidean_precision value: 77.83094098883574
    • type: euclidean_recall value: 91.38576779026218
    • type: main_score value: 89.60605626791111
    • type: manhattan_accuracy value: 76.89950980392157
    • type: manhattan_accuracy_threshold value: 38202.215576171875
    • type: manhattan_ap value: 89.55766894104868
    • type: manhattan_f1 value: 83.80462724935732
    • type: manhattan_f1_threshold value: 38934.375
    • type: manhattan_precision value: 77.25118483412322
    • type: manhattan_recall value: 91.57303370786516
    • type: max_accuracy value: 77.32843137254902
    • type: max_ap value: 89.60605626791111
    • type: max_f1 value: 84.06546080964686
    • type: max_precision value: 77.83094098883574
    • type: max_recall value: 93.63295880149812
    • type: similarity_accuracy value: 76.83823529411765
    • type: similarity_accuracy_threshold value: 72.70769476890564
    • type: similarity_ap value: 89.56692049908222
    • type: similarity_f1 value: 83.99832003359934
    • type: similarity_f1_threshold value: 70.9052324295044
    • type: similarity_precision value: 76.16146230007617
    • type: similarity_recall value: 93.63295880149812 task: type: PairClassification

  • dataset: config: default name: MTEB PAC (default) revision: fc69d1c153a8ccdcf1eef52f4e2a27f88782f543 split: test type: laugustyniak/abusive-clauses-pl metrics:

    • type: accuracy value: 68.39559803069794
    • type: ap value: 77.68074206719457
    • type: ap_weighted value: 77.68074206719457
    • type: f1 value: 66.23485605467732
    • type: f1_weighted value: 69.03201442129347
    • type: main_score value: 68.39559803069794 task: type: Classification

  • dataset: config: default name: MTEB PAWSX (default) revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1 split: test type: C-MTEB/PAWSX metrics:

    • type: cosine_pearson value: 13.161523266433587
    • type: cosine_spearman value: 15.557333873773386
    • type: euclidean_pearson value: 17.147508431907525
    • type: euclidean_spearman value: 15.664112857732146
    • type: main_score value: 15.557333873773386
    • type: manhattan_pearson value: 17.130875906264386
    • type: manhattan_spearman value: 15.624397342229637
    • type: pearson value: 13.161523266433587
    • type: spearman value: 15.557333873773386 task: type: STS

  • dataset: config: default name: MTEB PSC (default) revision: d05a294af9e1d3ff2bfb6b714e08a24a6cabc669 split: test type: PL-MTEB/psc-pairclassification metrics:

    • type: cosine_accuracy value: 97.86641929499072
    • type: cosine_accuracy_threshold value: 79.0391206741333
    • type: cosine_ap value: 99.19403807771533
    • type: cosine_f1 value: 96.45608628659475
    • type: cosine_f1_threshold value: 79.0391206741333
    • type: cosine_precision value: 97.50778816199377
    • type: cosine_recall value: 95.42682926829268
    • type: dot_accuracy value: 98.14471243042672
    • type: dot_accuracy_threshold value: 29808.1787109375
    • type: dot_ap value: 99.331999859971
    • type: dot_f1 value: 97.01492537313433
    • type: dot_f1_threshold value: 29808.1787109375
    • type: dot_precision value: 95.02923976608187
    • type: dot_recall value: 99.08536585365853
    • type: euclidean_accuracy value: 97.49536178107606
    • type: euclidean_accuracy_threshold value: 1276.227855682373
    • type: euclidean_ap value: 98.91056467717377
    • type: euclidean_f1 value: 95.83975346687212
    • type: euclidean_f1_threshold value: 1276.227855682373
    • type: euclidean_precision value: 96.88473520249221
    • type: euclidean_recall value: 94.8170731707317
    • type: main_score value: 99.331999859971
    • type: manhattan_accuracy value: 97.49536178107606
    • type: manhattan_accuracy_threshold value: 31097.674560546875
    • type: manhattan_ap value: 98.95694691792707
    • type: manhattan_f1 value: 95.83975346687212
    • type: manhattan_f1_threshold value: 31097.674560546875
    • type: manhattan_precision value: 96.88473520249221
    • type: manhattan_recall value: 94.8170731707317
    • type: max_accuracy value: 98.14471243042672
    • type: max_ap value: 99.331999859971
    • type: max_f1 value: 97.01492537313433
    • type: max_precision value: 97.50778816199377
    • type: max_recall value: 99.08536585365853
    • type: similarity_accuracy value: 97.86641929499072
    • type: similarity_accuracy_threshold value: 79.0391206741333
    • type: similarity_ap value: 99.19403807771533
    • type: similarity_f1 value: 96.45608628659475
    • type: similarity_f1_threshold value: 79.0391206741333
    • type: similarity_precision value: 97.50778816199377
    • type: similarity_recall value: 95.42682926829268 task: type: PairClassification

  • dataset: config: en name: MTEB PawsXPairClassification (en) revision: 8a04d940a42cd40658986fdd8e3da561533a3646 split: test type: google-research-datasets/paws-x metrics:

    • type: cosine_accuracy value: 61.8
    • type: cosine_accuracy_threshold value: 99.5664119720459
    • type: cosine_ap value: 60.679317786040585
    • type: cosine_f1 value: 63.17354143441101
    • type: cosine_f1_threshold value: 97.22164869308472
    • type: cosine_precision value: 47.6457399103139
    • type: cosine_recall value: 93.71554575523705
    • type: dot_accuracy value: 55.7
    • type: dot_accuracy_threshold value: 48353.62548828125
    • type: dot_ap value: 48.53805970536875
    • type: dot_f1 value: 62.42214532871972
    • type: dot_f1_threshold value: 38215.53955078125
    • type: dot_precision value: 45.48663640948058
    • type: dot_recall value: 99.44873208379272
    • type: euclidean_accuracy value: 61.75000000000001
    • type: euclidean_accuracy_threshold value: 189.0761137008667
    • type: euclidean_ap value: 60.55517418691518
    • type: euclidean_f1 value: 63.07977736549165
    • type: euclidean_f1_threshold value: 504.3168067932129
    • type: euclidean_precision value: 47.53914988814318
    • type: euclidean_recall value: 93.71554575523705
    • type: main_score value: 60.679317786040585
    • type: manhattan_accuracy value: 61.9
    • type: manhattan_accuracy_threshold value: 4695.778274536133
    • type: manhattan_ap value: 60.48686620413608
    • type: manhattan_f1 value: 62.92880855772778
    • type: manhattan_f1_threshold value: 12542.36831665039
    • type: manhattan_precision value: 47.28381374722838
    • type: manhattan_recall value: 94.04630650496141
    • type: max_accuracy value: 61.9
    • type: max_ap value: 60.679317786040585
    • type: max_f1 value: 63.17354143441101
    • type: max_precision value: 47.6457399103139
    • type: max_recall value: 99.44873208379272
    • type: similarity_accuracy value: 61.8
    • type: similarity_accuracy_threshold value: 99.5664119720459
    • type: similarity_ap value: 60.679317786040585
    • type: similarity_f1 value: 63.17354143441101
    • type: similarity_f1_threshold value: 97.22164869308472
    • type: similarity_precision value: 47.6457399103139
    • type: similarity_recall value: 93.71554575523705 task: type: PairClassification

  • dataset: config: de name: MTEB PawsXPairClassification (de) revision: 8a04d940a42cd40658986fdd8e3da561533a3646 split: test type: google-research-datasets/paws-x metrics:

    • type: cosine_accuracy value: 60.25
    • type: cosine_accuracy_threshold value: 99.54338073730469
    • type: cosine_ap value: 56.7863613689054
    • type: cosine_f1 value: 62.23499820337766
    • type: cosine_f1_threshold value: 89.95014429092407
    • type: cosine_precision value: 45.86864406779661
    • type: cosine_recall value: 96.75977653631284
    • type: dot_accuracy value: 56.8
    • type: dot_accuracy_threshold value: 47349.78332519531
    • type: dot_ap value: 49.7857806061729
    • type: dot_f1 value: 62.31225986727209
    • type: dot_f1_threshold value: 30143.206787109375
    • type: dot_precision value: 45.32520325203252
    • type: dot_recall value: 99.66480446927373
    • type: euclidean_accuracy value: 60.3
    • type: euclidean_accuracy_threshold value: 219.78106498718262
    • type: euclidean_ap value: 56.731544327179606
    • type: euclidean_f1 value: 62.19895287958115
    • type: euclidean_f1_threshold value: 1792.1623229980469
    • type: euclidean_precision value: 45.22842639593909
    • type: euclidean_recall value: 99.55307262569832
    • type: main_score value: 56.7863613689054
    • type: manhattan_accuracy value: 60.150000000000006
    • type: manhattan_accuracy_threshold value: 5104.503631591797
    • type: manhattan_ap value: 56.70304479768734
    • type: manhattan_f1 value: 62.22067039106145
    • type: manhattan_f1_threshold value: 42839.471435546875
    • type: manhattan_precision value: 45.2513966480447
    • type: manhattan_recall value: 99.55307262569832
    • type: max_accuracy value: 60.3
    • type: max_ap value: 56.7863613689054
    • type: max_f1 value: 62.31225986727209
    • type: max_precision value: 45.86864406779661
    • type: max_recall value: 99.66480446927373
    • type: similarity_accuracy value: 60.25
    • type: similarity_accuracy_threshold value: 99.54338073730469
    • type: similarity_ap value: 56.7863613689054
    • type: similarity_f1 value: 62.23499820337766
    • type: similarity_f1_threshold value: 89.95014429092407
    • type: similarity_precision value: 45.86864406779661
    • type: similarity_recall value: 96.75977653631284 task: type: PairClassification

  • dataset: config: es name: MTEB PawsXPairClassification (es) revision: 8a04d940a42cd40658986fdd8e3da561533a3646 split: test type: google-research-datasets/paws-x metrics:

    • type: cosine_accuracy value: 59.699999999999996
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    • type: cosine_ap value: 57.31662248806265
    • type: cosine_f1 value: 62.444061962134256
    • type: cosine_f1_threshold value: 74.75898265838623
    • type: cosine_precision value: 45.3953953953954
    • type: cosine_recall value: 100.0
    • type: dot_accuracy value: 55.900000000000006
    • type: dot_accuracy_threshold value: 47512.90283203125
    • type: dot_ap value: 49.39339147787568
    • type: dot_f1 value: 62.487082328625554
    • type: dot_f1_threshold value: 34989.03503417969
    • type: dot_precision value: 45.44088176352705
    • type: dot_recall value: 100.0
    • type: euclidean_accuracy value: 59.599999999999994
    • type: euclidean_accuracy_threshold value: 200.82547664642334
    • type: euclidean_ap value: 57.19737488445163
    • type: euclidean_f1 value: 62.444061962134256
    • type: euclidean_f1_threshold value: 1538.8837814331055
    • type: euclidean_precision value: 45.3953953953954
    • type: euclidean_recall value: 100.0
    • type: main_score value: 57.31662248806265
    • type: manhattan_accuracy value: 59.550000000000004
    • type: manhattan_accuracy_threshold value: 5016.501617431641
    • type: manhattan_ap value: 57.089959907945065
    • type: manhattan_f1 value: 62.444061962134256
    • type: manhattan_f1_threshold value: 37523.53515625
    • type: manhattan_precision value: 45.3953953953954
    • type: manhattan_recall value: 100.0
    • type: max_accuracy value: 59.699999999999996
    • type: max_ap value: 57.31662248806265
    • type: max_f1 value: 62.487082328625554
    • type: max_precision value: 45.44088176352705
    • type: max_recall value: 100.0
    • type: similarity_accuracy value: 59.699999999999996
    • type: similarity_accuracy_threshold value: 99.55930709838867
    • type: similarity_ap value: 57.31662248806265
    • type: similarity_f1 value: 62.444061962134256
    • type: similarity_f1_threshold value: 74.75898265838623
    • type: similarity_precision value: 45.3953953953954
    • type: similarity_recall value: 100.0 task: type: PairClassification

  • dataset: config: fr name: MTEB PawsXPairClassification (fr) revision: 8a04d940a42cd40658986fdd8e3da561533a3646 split: test type: google-research-datasets/paws-x metrics:

    • type: cosine_accuracy value: 61.150000000000006
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    • type: cosine_ap value: 59.43845317938599
    • type: cosine_f1 value: 62.51298026998961
    • type: cosine_f1_threshold value: 76.77866220474243
    • type: cosine_precision value: 45.468277945619334
    • type: cosine_recall value: 100.0
    • type: dot_accuracy value: 55.75
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    • type: dot_ap value: 50.15949290538757
    • type: dot_f1 value: 62.53462603878117
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    • type: dot_precision value: 45.4911838790932
    • type: dot_recall value: 100.0
    • type: euclidean_accuracy value: 61.050000000000004
    • type: euclidean_accuracy_threshold value: 240.8097267150879
    • type: euclidean_ap value: 59.367971294226216
    • type: euclidean_f1 value: 62.51298026998961
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    • type: euclidean_precision value: 45.468277945619334
    • type: euclidean_recall value: 100.0
    • type: main_score value: 59.43845317938599
    • type: manhattan_accuracy value: 60.95
    • type: manhattan_accuracy_threshold value: 5701.206207275391
    • type: manhattan_ap value: 59.30094096378774
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    • type: manhattan_f1_threshold value: 33445.672607421875
    • type: manhattan_precision value: 45.4911838790932
    • type: manhattan_recall value: 100.0
    • type: max_accuracy value: 61.150000000000006
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    • type: max_recall value: 100.0
    • type: similarity_accuracy value: 61.150000000000006
    • type: similarity_accuracy_threshold value: 99.36153888702393
    • type: similarity_ap value: 59.43845317938599
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    • type: similarity_f1_threshold value: 76.77866220474243
    • type: similarity_precision value: 45.468277945619334
    • type: similarity_recall value: 100.0 task: type: PairClassification

  • dataset: config: zh name: MTEB PawsXPairClassification (zh) revision: 8a04d940a42cd40658986fdd8e3da561533a3646 split: test type: google-research-datasets/paws-x metrics:

    • type: cosine_accuracy value: 58.85
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    • type: cosine_ap value: 54.66913160570546
    • type: cosine_f1 value: 62.32136632973162
    • type: cosine_f1_threshold value: 76.4499306678772
    • type: cosine_precision value: 45.265822784810126
    • type: cosine_recall value: 100.0
    • type: dot_accuracy value: 56.25
    • type: dot_accuracy_threshold value: 47351.9287109375
    • type: dot_ap value: 48.5266232989438
    • type: dot_f1 value: 62.277951933124356
    • type: dot_f1_threshold value: 31325.28076171875
    • type: dot_precision value: 45.220030349013655
    • type: dot_recall value: 100.0
    • type: euclidean_accuracy value: 58.9
    • type: euclidean_accuracy_threshold value: 144.24468278884888
    • type: euclidean_ap value: 54.66981490353506
    • type: euclidean_f1 value: 62.32136632973162
    • type: euclidean_f1_threshold value: 1484.908676147461
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    • type: euclidean_recall value: 100.0
    • type: main_score value: 54.66981490353506
    • type: manhattan_accuracy value: 58.9
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    • type: max_accuracy value: 58.9
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    • type: similarity_accuracy value: 58.85
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    • type: similarity_recall value: 100.0 task: type: PairClassification

  • dataset: config: default name: MTEB PolEmo2.0-IN (default) revision: d90724373c70959f17d2331ad51fb60c71176b03 split: test type: PL-MTEB/polemo2_in metrics:

    • type: accuracy value: 83.75346260387812
    • type: f1 value: 81.98304891214909
    • type: f1_weighted value: 84.29623200830078
    • type: main_score value: 83.75346260387812 task: type: Classification

  • dataset: config: default name: MTEB PolEmo2.0-OUT (default) revision: 6a21ab8716e255ab1867265f8b396105e8aa63d4 split: test type: PL-MTEB/polemo2_out metrics:

    • type: accuracy value: 66.53846153846153
    • type: f1 value: 52.71826064368638
    • type: f1_weighted value: 69.10010124630334
    • type: main_score value: 66.53846153846153 task: type: Classification

  • dataset: config: default name: MTEB PPC revision: None split: test type: PL-MTEB/ppc-pairclassification metrics:

    • type: cosine_accuracy value: 81.8
    • type: cosine_accuracy_threshold value: 90.47793745994568
    • type: cosine_ap value: 91.42490266080884
    • type: cosine_f1 value: 85.4632587859425
    • type: cosine_f1_threshold value: 90.47793745994568
    • type: cosine_precision value: 82.56172839506173
    • type: cosine_recall value: 88.57615894039735
    • type: dot_accuracy value: 74.6
    • type: dot_accuracy_threshold value: 42102.23693847656
    • type: dot_ap value: 86.20060009096979
    • type: dot_f1 value: 80.02842928216063
    • type: dot_f1_threshold value: 38970.16906738281
    • type: dot_precision value: 70.1120797011208
    • type: dot_recall value: 93.21192052980133
    • type: euclidean_accuracy value: 81.5
    • type: euclidean_accuracy_threshold value: 880.433464050293
    • type: euclidean_ap value: 91.33143477982087
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    • type: main_score value: 91.42490266080884
    • type: manhattan_accuracy value: 81.3
    • type: manhattan_accuracy_threshold value: 22100.830078125
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    • type: manhattan_f1_threshold value: 24043.515014648438
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    • type: manhattan_recall value: 90.89403973509934
    • type: max_accuracy value: 81.8
    • type: max_ap value: 91.42490266080884
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    • type: max_precision value: 82.56172839506173
    • type: max_recall value: 93.21192052980133
    • type: similarity_accuracy value: 81.8
    • type: similarity_accuracy_threshold value: 90.47793745994568
    • type: similarity_ap value: 91.42490266080884
    • type: similarity_f1 value: 85.4632587859425
    • type: similarity_f1_threshold value: 90.47793745994568
    • type: similarity_precision value: 82.56172839506173
    • type: similarity_recall value: 88.57615894039735 task: type: PairClassification

  • dataset: config: default name: MTEB QuoraRetrieval (default) revision: e4e08e0b7dbe3c8700f0daef558ff32256715259 split: test type: mteb/quora metrics:

    • type: map_at_1 value: 71.419
    • type: map_at_10 value: 85.542
    • type: map_at_100 value: 86.161
    • type: map_at_1000 value: 86.175
    • type: map_at_20 value: 85.949
    • type: map_at_3 value: 82.623
    • type: map_at_5 value: 84.5
    • type: mrr_at_1 value: 82.27
    • type: mrr_at_10 value: 88.21900000000001
    • type: mrr_at_100 value: 88.313
    • type: mrr_at_1000 value: 88.31400000000001
    • type: mrr_at_20 value: 88.286
    • type: mrr_at_3 value: 87.325
    • type: mrr_at_5 value: 87.97500000000001
    • type: ndcg_at_1 value: 82.3
    • type: ndcg_at_10 value: 89.088
    • type: ndcg_at_100 value: 90.217
    • type: ndcg_at_1000 value: 90.29700000000001
    • type: ndcg_at_20 value: 89.697
    • type: ndcg_at_3 value: 86.435
    • type: ndcg_at_5 value: 87.966
    • type: precision_at_1 value: 82.3
    • type: precision_at_10 value: 13.527000000000001
    • type: precision_at_100 value: 1.537
    • type: precision_at_1000 value: 0.157
    • type: precision_at_20 value: 7.165000000000001
    • type: precision_at_3 value: 37.92
    • type: precision_at_5 value: 24.914
    • type: recall_at_1 value: 71.419
    • type: recall_at_10 value: 95.831
    • type: recall_at_100 value: 99.64
    • type: recall_at_1000 value: 99.988
    • type: recall_at_20 value: 97.76599999999999
    • type: recall_at_3 value: 88.081
    • type: recall_at_5 value: 92.50500000000001
    • type: main_score value: 89.088 task: type: Retrieval

  • dataset: config: default name: MTEB RUParaPhraserSTS (default) revision: 43265056790b8f7c59e0139acb4be0a8dad2c8f4 split: test type: merionum/ru_paraphraser metrics:

    • type: cosine_pearson value: 67.91177744712421
    • type: cosine_spearman value: 76.77113726753656
    • type: euclidean_pearson value: 73.81454206068638
    • type: euclidean_spearman value: 76.92529493599028
    • type: main_score value: 76.77113726753656
    • type: manhattan_pearson value: 73.81690454439168
    • type: manhattan_spearman value: 76.87333776705002
    • type: pearson value: 67.91177744712421
    • type: spearman value: 76.77113726753656 task: type: STS

  • dataset: config: default name: MTEB RedditClustering (default) revision: 24640382cdbf8abc73003fb0fa6d111a705499eb split: test type: mteb/reddit-clustering metrics:

    • type: main_score value: 55.39924225216962
    • type: v_measure value: 55.39924225216962
    • type: v_measure_std value: 4.723802279292467 task: type: Clustering

  • dataset: config: default name: MTEB RedditClusteringP2P (default) revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 split: test type: mteb/reddit-clustering-p2p metrics:

    • type: main_score value: 62.87465161304012
    • type: v_measure value: 62.87465161304012
    • type: v_measure_std value: 12.082670914488473 task: type: Clustering

  • dataset: config: default name: MTEB RiaNewsRetrieval (default) revision: 82374b0bbacda6114f39ff9c5b925fa1512ca5d7 split: test type: ai-forever/ria-news-retrieval metrics:

    • type: main_score value: 79.209
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  • dataset: config: default name: MTEB RuBQReranking (default) revision: 2e96b8f098fa4b0950fc58eacadeb31c0d0c7fa2 split: test type: ai-forever/rubq-reranking metrics:

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  • dataset: config: default name: MTEB RuBQRetrieval (default) revision: e19b6ffa60b3bc248e0b41f4cc37c26a55c2a67b split: test type: ai-forever/rubq-retrieval metrics:

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    • type: recall_at_1 value: 44.187
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  • dataset: config: default name: MTEB RuReviewsClassification (default) revision: f6d2c31f4dc6b88f468552750bfec05b4b41b05a split: test type: ai-forever/ru-reviews-classification metrics:

    • type: accuracy value: 67.5830078125
    • type: f1 value: 67.56931936632446
    • type: f1_weighted value: 67.57137733752779
    • type: main_score value: 67.5830078125 task: type: Classification

  • dataset: config: default name: MTEB RuSTSBenchmarkSTS (default) revision: 7cf24f325c6da6195df55bef3d86b5e0616f3018 split: test type: ai-forever/ru-stsbenchmark-sts metrics:

    • type: cosine_pearson value: 85.90493484626788
    • type: cosine_spearman value: 86.21965691667411
    • type: euclidean_pearson value: 86.07499842984909
    • type: euclidean_spearman value: 86.55506818735688
    • type: main_score value: 86.21965691667411
    • type: manhattan_pearson value: 85.95976420231729
    • type: manhattan_spearman value: 86.48604243661234
    • type: pearson value: 85.90493484626788
    • type: spearman value: 86.21965691667411 task: type: STS

  • dataset: config: default name: MTEB RuSciBenchGRNTIClassification (default) revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1 split: test type: ai-forever/ru-scibench-grnti-classification metrics:

    • type: accuracy value: 59.1943359375
    • type: f1 value: 58.894480861440414
    • type: f1_weighted value: 58.903615560240866
    • type: main_score value: 59.1943359375 task: type: Classification

  • dataset: config: default name: MTEB RuSciBenchGRNTIClusteringP2P (default) revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1 split: test type: ai-forever/ru-scibench-grnti-classification metrics:

    • type: main_score value: 57.99209448663228
    • type: v_measure value: 57.99209448663228
    • type: v_measure_std value: 1.0381163861993816 task: type: Clustering

  • dataset: config: default name: MTEB RuSciBenchOECDClassification (default) revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471 split: test type: ai-forever/ru-scibench-oecd-classification metrics:

    • type: accuracy value: 45.556640625
    • type: f1 value: 45.159163104085906
    • type: f1_weighted value: 45.16098316398626
    • type: main_score value: 45.556640625 task: type: Classification

  • dataset: config: default name: MTEB RuSciBenchOECDClusteringP2P (default) revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471 split: test type: ai-forever/ru-scibench-oecd-classification metrics:

    • type: main_score value: 50.787548070488974
    • type: v_measure value: 50.787548070488974
    • type: v_measure_std value: 0.8569958168946827 task: type: Clustering

  • dataset: config: default name: MTEB SCIDOCS (default) revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88 split: test type: mteb/scidocs metrics:

    • type: map_at_1 value: 4.843
    • type: map_at_10 value: 11.752
    • type: map_at_100 value: 13.919
    • type: map_at_1000 value: 14.198
    • type: map_at_20 value: 12.898000000000001
    • type: map_at_3 value: 8.603
    • type: map_at_5 value: 10.069
    • type: mrr_at_1 value: 23.799999999999997
    • type: mrr_at_10 value: 34.449999999999996
    • type: mrr_at_100 value: 35.64
    • type: mrr_at_1000 value: 35.691
    • type: mrr_at_20 value: 35.213
    • type: mrr_at_3 value: 31.383
    • type: mrr_at_5 value: 33.062999999999995
    • type: ndcg_at_1 value: 23.799999999999997
    • type: ndcg_at_10 value: 19.811
    • type: ndcg_at_100 value: 28.108
    • type: ndcg_at_1000 value: 33.1
    • type: ndcg_at_20 value: 22.980999999999998
    • type: ndcg_at_3 value: 19.153000000000002
    • type: ndcg_at_5 value: 16.408
    • type: precision_at_1 value: 23.799999999999997
    • type: precision_at_10 value: 10.16
    • type: precision_at_100 value: 2.1999999999999997
    • type: precision_at_1000 value: 0.34099999999999997
    • type: precision_at_20 value: 6.915
    • type: precision_at_3 value: 17.8
    • type: precision_at_5 value: 14.14
    • type: recall_at_1 value: 4.843
    • type: recall_at_10 value: 20.595
    • type: recall_at_100 value: 44.66
    • type: recall_at_1000 value: 69.152
    • type: recall_at_20 value: 28.04
    • type: recall_at_3 value: 10.833
    • type: recall_at_5 value: 14.346999999999998
    • type: main_score value: 19.811 task: type: Retrieval

  • dataset: config: default name: MTEB SICK-E-PL (default) revision: 71bba34b0ece6c56dfcf46d9758a27f7a90f17e9 split: test type: PL-MTEB/sicke-pl-pairclassification metrics:

    • type: cosine_accuracy value: 80.90093762739502
    • type: cosine_accuracy_threshold value: 94.40930485725403
    • type: cosine_ap value: 71.15400909912427
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    • type: cosine_f1_threshold value: 91.53673648834229
    • type: cosine_precision value: 62.4922504649721
    • type: cosine_recall value: 71.7948717948718
    • type: dot_accuracy value: 78.41418671015083
    • type: dot_accuracy_threshold value: 42924.45068359375
    • type: dot_ap value: 63.34003025365763
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    • type: dot_recall value: 76.21082621082621
    • type: euclidean_accuracy value: 80.67672238075826
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    • type: manhattan_recall value: 72.15099715099716
    • type: max_accuracy value: 80.90093762739502
    • type: max_ap value: 71.15400909912427
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    • type: max_recall value: 76.21082621082621
    • type: similarity_accuracy value: 80.90093762739502
    • type: similarity_accuracy_threshold value: 94.40930485725403
    • type: similarity_ap value: 71.15400909912427
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    • type: similarity_f1_threshold value: 91.53673648834229
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    • type: similarity_recall value: 71.7948717948718 task: type: PairClassification

  • dataset: config: default name: MTEB SICK-R (default) revision: 20a6d6f312dd54037fe07a32d58e5e168867909d split: test type: mteb/sickr-sts metrics:

    • type: cosine_pearson value: 92.3339946866199
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    • type: pearson value: 92.3339946866199
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  • dataset: config: default name: MTEB SICK-R-PL (default) revision: fd5c2441b7eeff8676768036142af4cfa42c1339 split: test type: PL-MTEB/sickr-pl-sts metrics:

    • type: cosine_pearson value: 85.27883048457821
    • type: cosine_spearman value: 80.53204892678619
    • type: euclidean_pearson value: 82.78520705216168
    • type: euclidean_spearman value: 80.27848359873212
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    • type: manhattan_spearman value: 80.21507977473146
    • type: pearson value: 85.27883048457821
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  • dataset: config: default name: MTEB SICKFr (default) revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a split: test type: Lajavaness/SICK-fr metrics:

    • type: cosine_pearson value: 88.77029361817212
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    • type: euclidean_pearson value: 85.85331086208573
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    • type: manhattan_spearman value: 83.60833111525962
    • type: pearson value: 88.77029361817212
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  • dataset: config: default name: MTEB STS12 (default) revision: a0d554a64d88156834ff5ae9920b964011b16384 split: test type: mteb/sts12-sts metrics:

    • type: cosine_pearson value: 88.76435859522375
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    • type: euclidean_pearson value: 87.43566183874832
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    • type: manhattan_spearman value: 82.89253043430163
    • type: pearson value: 88.76435859522375
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  • dataset: config: default name: MTEB STS13 (default) revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca split: test type: mteb/sts13-sts metrics:

    • type: cosine_pearson value: 88.86627241652141
    • type: cosine_spearman value: 89.49011599120688
    • type: euclidean_pearson value: 89.3314120073772
    • type: euclidean_spearman value: 89.8226502776963
    • type: main_score value: 89.49011599120688
    • type: manhattan_pearson value: 89.2252179076963
    • type: manhattan_spearman value: 89.74573844021225
    • type: pearson value: 88.86627241652141
    • type: spearman value: 89.49011599120688 task: type: STS

  • dataset: config: default name: MTEB STS14 (default) revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 split: test type: mteb/sts14-sts metrics:

    • type: cosine_pearson value: 87.22891405215968
    • type: cosine_spearman value: 84.9467188157614
    • type: euclidean_pearson value: 87.20330004726237
    • type: euclidean_spearman value: 85.34806059461808
    • type: main_score value: 84.9467188157614
    • type: manhattan_pearson value: 87.15224666107623
    • type: manhattan_spearman value: 85.34596898699708
    • type: pearson value: 87.22891405215968
    • type: spearman value: 84.9467188157614 task: type: STS

  • dataset: config: default name: MTEB STS15 (default) revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 split: test type: mteb/sts15-sts metrics:

    • type: cosine_pearson value: 88.14066430111033
    • type: cosine_spearman value: 89.31337445552545
    • type: euclidean_pearson value: 89.08039335366983
    • type: euclidean_spearman value: 89.6658762856415
    • type: main_score value: 89.31337445552545
    • type: manhattan_pearson value: 89.08057438154486
    • type: manhattan_spearman value: 89.68673984203022
    • type: pearson value: 88.14066430111033
    • type: spearman value: 89.31337445552545 task: type: STS

  • dataset: config: default name: MTEB STS16 (default) revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 split: test type: mteb/sts16-sts metrics:

    • type: cosine_pearson value: 85.14908856657084
    • type: cosine_spearman value: 86.84648320786727
    • type: euclidean_pearson value: 86.11454713131947
    • type: euclidean_spearman value: 86.77738862047961
    • type: main_score value: 86.84648320786727
    • type: manhattan_pearson value: 86.07804821916372
    • type: manhattan_spearman value: 86.78676064310474
    • type: pearson value: 85.14908856657084
    • type: spearman value: 86.84648320786727 task: type: STS

  • dataset: config: en-en name: MTEB STS17 (en-en) revision: faeb762787bd10488a50c8b5be4a3b82e411949c split: test type: mteb/sts17-crosslingual-sts metrics:

    • type: cosine_pearson value: 89.61633502468356
    • type: cosine_spearman value: 89.99772663224805
    • type: euclidean_pearson value: 90.14056501501044
    • type: euclidean_spearman value: 90.04496896837503
    • type: main_score value: 89.99772663224805
    • type: manhattan_pearson value: 90.08964860311801
    • type: manhattan_spearman value: 90.00091712362196
    • type: pearson value: 89.61633502468356
    • type: spearman value: 89.99772663224805 task: type: STS

  • dataset: config: es-en name: MTEB STS17 (es-en) revision: faeb762787bd10488a50c8b5be4a3b82e411949c split: test type: mteb/sts17-crosslingual-sts metrics:

    • type: cosine_pearson value: 86.44548026840202
    • type: cosine_spearman value: 87.26263108768539
    • type: euclidean_pearson value: 86.42844593583838
    • type: euclidean_spearman value: 86.89388428664364
    • type: main_score value: 87.26263108768539
    • type: manhattan_pearson value: 86.47186940800881
    • type: manhattan_spearman value: 87.02163091089946
    • type: pearson value: 86.44548026840202
    • type: spearman value: 87.26263108768539 task: type: STS

  • dataset: config: en-de name: MTEB STS17 (en-de) revision: faeb762787bd10488a50c8b5be4a3b82e411949c split: test type: mteb/sts17-crosslingual-sts metrics:

    • type: cosine_pearson value: 87.89345132532758
    • type: cosine_spearman value: 87.96246221327699
    • type: euclidean_pearson value: 88.49013032701419
    • type: euclidean_spearman value: 87.81981265317344
    • type: main_score value: 87.96246221327699
    • type: manhattan_pearson value: 88.31360914178538
    • type: manhattan_spearman value: 87.62734530005075
    • type: pearson value: 87.89345132532758
    • type: spearman value: 87.96246221327699 task: type: STS

  • dataset: config: es-es name: MTEB STS17 (es-es) revision: faeb762787bd10488a50c8b5be4a3b82e411949c split: test type: mteb/sts17-crosslingual-sts metrics:

    • type: cosine_pearson value: 88.4084678497171
    • type: cosine_spearman value: 88.77640638748285
    • type: euclidean_pearson value: 89.60124312475843
    • type: euclidean_spearman value: 88.4321442688528
    • type: main_score value: 88.77640638748285
    • type: manhattan_pearson value: 89.62375118021299
    • type: manhattan_spearman value: 88.46998118661577
    • type: pearson value: 88.4084678497171
    • type: spearman value: 88.77640638748285 task: type: STS

  • dataset: config: fr-en name: MTEB STS17 (fr-en) revision: faeb762787bd10488a50c8b5be4a3b82e411949c split: test type: mteb/sts17-crosslingual-sts metrics:

    • type: cosine_pearson value: 87.30688801326498
    • type: cosine_spearman value: 87.55684697258378
    • type: euclidean_pearson value: 87.89672951056794
    • type: euclidean_spearman value: 87.28050429201674
    • type: main_score value: 87.55684697258378
    • type: manhattan_pearson value: 87.74292745320572
    • type: manhattan_spearman value: 87.16383993876582
    • type: pearson value: 87.30688801326498
    • type: spearman value: 87.55684697258378 task: type: STS

  • dataset: config: zh-en name: MTEB STS22 (zh-en) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 73.46180375170147
    • type: cosine_spearman value: 73.39559590127081
    • type: euclidean_pearson value: 73.72613901293681
    • type: euclidean_spearman value: 71.85465165176795
    • type: main_score value: 73.39559590127081
    • type: manhattan_pearson value: 73.07859140869076
    • type: manhattan_spearman value: 71.22047343718893
    • type: pearson value: 73.46180375170147
    • type: spearman value: 73.39559590127081 task: type: STS

  • dataset: config: zh name: MTEB STS22 (zh) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 62.47531620842637
    • type: cosine_spearman value: 66.22504667157702
    • type: euclidean_pearson value: 66.76201254783692
    • type: euclidean_spearman value: 66.86115760269463
    • type: main_score value: 66.22504667157702
    • type: manhattan_pearson value: 66.73847836793489
    • type: manhattan_spearman value: 66.7677116377695
    • type: pearson value: 62.47531620842637
    • type: spearman value: 66.22504667157702 task: type: STS

  • dataset: config: es name: MTEB STS22 (es) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 69.89707002436481
    • type: cosine_spearman value: 72.2054865735116
    • type: euclidean_pearson value: 71.81856615570756
    • type: euclidean_spearman value: 72.72593304629407
    • type: main_score value: 72.2054865735116
    • type: manhattan_pearson value: 72.00362684700072
    • type: manhattan_spearman value: 72.62783534769964
    • type: pearson value: 69.89707002436481
    • type: spearman value: 72.2054865735116 task: type: STS

  • dataset: config: fr name: MTEB STS22 (fr) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 81.59623734395916
    • type: cosine_spearman value: 83.28946105111358
    • type: euclidean_pearson value: 79.377330171466
    • type: euclidean_spearman value: 81.81029781662205
    • type: main_score value: 83.28946105111358
    • type: manhattan_pearson value: 78.96970881689698
    • type: manhattan_spearman value: 81.91773236079703
    • type: pearson value: 81.59623734395916
    • type: spearman value: 83.28946105111358 task: type: STS

  • dataset: config: de-fr name: MTEB STS22 (de-fr) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 55.03825643126142
    • type: cosine_spearman value: 58.25792501780429
    • type: euclidean_pearson value: 50.38007603973409
    • type: euclidean_spearman value: 59.39961789383097
    • type: main_score value: 58.25792501780429
    • type: manhattan_pearson value: 50.518568927999155
    • type: manhattan_spearman value: 59.84185466003894
    • type: pearson value: 55.03825643126142
    • type: spearman value: 58.25792501780429 task: type: STS

  • dataset: config: pl-en name: MTEB STS22 (pl-en) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 77.77233721490776
    • type: cosine_spearman value: 76.17596588017625
    • type: euclidean_pearson value: 74.47600468156611
    • type: euclidean_spearman value: 72.61278728057012
    • type: main_score value: 76.17596588017625
    • type: manhattan_pearson value: 74.48118910099699
    • type: manhattan_spearman value: 73.33167419101696
    • type: pearson value: 77.77233721490776
    • type: spearman value: 76.17596588017625 task: type: STS

  • dataset: config: pl name: MTEB STS22 (pl) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 42.87453608131507
    • type: cosine_spearman value: 45.137849894401185
    • type: euclidean_pearson value: 31.66964197694796
    • type: euclidean_spearman value: 44.1014900837869
    • type: main_score value: 45.137849894401185
    • type: manhattan_pearson value: 31.007199259384745
    • type: manhattan_spearman value: 43.48181523288926
    • type: pearson value: 42.87453608131507
    • type: spearman value: 45.137849894401185 task: type: STS

  • dataset: config: en name: MTEB STS22 (en) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 66.87400150638176
    • type: cosine_spearman value: 67.27861354834066
    • type: euclidean_pearson value: 66.81789582140216
    • type: euclidean_spearman value: 66.44220479858708
    • type: main_score value: 67.27861354834066
    • type: manhattan_pearson value: 66.92509859033235
    • type: manhattan_spearman value: 66.46841124185076
    • type: pearson value: 66.87400150638176
    • type: spearman value: 67.27861354834066 task: type: STS

  • dataset: config: ru name: MTEB STS22 (ru) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 61.819804551576084
    • type: cosine_spearman value: 65.0864146772135
    • type: euclidean_pearson value: 62.518151090361876
    • type: euclidean_spearman value: 65.13608138548017
    • type: main_score value: 65.0864146772135
    • type: manhattan_pearson value: 62.51413246915267
    • type: manhattan_spearman value: 65.19077543064323
    • type: pearson value: 61.819804551576084
    • type: spearman value: 65.0864146772135 task: type: STS

  • dataset: config: de name: MTEB STS22 (de) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 54.85728696035389
    • type: cosine_spearman value: 61.60906359227576
    • type: euclidean_pearson value: 52.57582587901851
    • type: euclidean_spearman value: 61.41823097598308
    • type: main_score value: 61.60906359227576
    • type: manhattan_pearson value: 52.500978361080506
    • type: manhattan_spearman value: 61.30365596659758
    • type: pearson value: 54.85728696035389
    • type: spearman value: 61.60906359227576 task: type: STS

  • dataset: config: fr-pl name: MTEB STS22 (fr-pl) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 67.68016005631422
    • type: cosine_spearman value: 84.51542547285167
    • type: euclidean_pearson value: 66.19871164667245
    • type: euclidean_spearman value: 73.24670207647144
    • type: main_score value: 84.51542547285167
    • type: manhattan_pearson value: 67.0443525268974
    • type: manhattan_spearman value: 73.24670207647144
    • type: pearson value: 67.68016005631422
    • type: spearman value: 84.51542547285167 task: type: STS

  • dataset: config: de-pl name: MTEB STS22 (de-pl) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 47.49467414030747
    • type: cosine_spearman value: 56.81512095681289
    • type: euclidean_pearson value: 48.42860221765214
    • type: euclidean_spearman value: 58.63197306329092
    • type: main_score value: 56.81512095681289
    • type: manhattan_pearson value: 48.39594959260441
    • type: manhattan_spearman value: 58.63197306329092
    • type: pearson value: 47.49467414030747
    • type: spearman value: 56.81512095681289 task: type: STS

  • dataset: config: es-en name: MTEB STS22 (es-en) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 76.8364678896155
    • type: cosine_spearman value: 78.45516413087114
    • type: euclidean_pearson value: 78.62779318576634
    • type: euclidean_spearman value: 78.88760695649488
    • type: main_score value: 78.45516413087114
    • type: manhattan_pearson value: 78.62131335760031
    • type: manhattan_spearman value: 78.81861844200388
    • type: pearson value: 76.8364678896155
    • type: spearman value: 78.45516413087114 task: type: STS

  • dataset: config: de-en name: MTEB STS22 (de-en) revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 split: test type: mteb/sts22-crosslingual-sts metrics:

    • type: cosine_pearson value: 65.16640313911604
    • type: cosine_spearman value: 60.887608967403914
    • type: euclidean_pearson value: 67.49902244990913
    • type: euclidean_spearman value: 59.2458787136538
    • type: main_score value: 60.887608967403914
    • type: manhattan_pearson value: 67.34313506388378
    • type: manhattan_spearman value: 59.05283429200166
    • type: pearson value: 65.16640313911604
    • type: spearman value: 60.887608967403914 task: type: STS

  • dataset: config: default name: MTEB STSB (default) revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0 split: test type: C-MTEB/STSB metrics:

    • type: cosine_pearson value: 81.5092853013241
    • type: cosine_spearman value: 83.54005474244292
    • type: euclidean_pearson value: 83.7246578378554
    • type: euclidean_spearman value: 84.46767551087716
    • type: main_score value: 83.54005474244292
    • type: manhattan_pearson value: 83.65922665594636
    • type: manhattan_spearman value: 84.42431449101848
    • type: pearson value: 81.5092853013241
    • type: spearman value: 83.54005474244292 task: type: STS

  • dataset: config: default name: MTEB STSBenchmark (default) revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 split: test type: mteb/stsbenchmark-sts metrics:

    • type: cosine_pearson value: 87.70246866744966
    • type: cosine_spearman value: 89.44070045346106
    • type: euclidean_pearson value: 89.56956519641007
    • type: euclidean_spearman value: 89.95830112784283
    • type: main_score value: 89.44070045346106
    • type: manhattan_pearson value: 89.48264471425145
    • type: manhattan_spearman value: 89.87900732483114
    • type: pearson value: 87.70246866744966
    • type: spearman value: 89.44070045346106 task: type: STS

  • dataset: config: de name: MTEB STSBenchmarkMultilingualSTS (de) revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c split: test type: mteb/stsb_multi_mt metrics:

    • type: cosine_pearson value: 86.83701990805217
    • type: cosine_spearman value: 87.80280785492258
    • type: euclidean_pearson value: 87.77325330043514
    • type: euclidean_spearman value: 88.3564607283144
    • type: main_score value: 87.80280785492258
    • type: manhattan_pearson value: 87.6745449945946
    • type: manhattan_spearman value: 88.30660465978795
    • type: pearson value: 86.83701990805217
    • type: spearman value: 87.80280785492258 task: type: STS

  • dataset: config: zh name: MTEB STSBenchmarkMultilingualSTS (zh) revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c split: test type: mteb/stsb_multi_mt metrics:

    • type: cosine_pearson value: 84.27751020600267
    • type: cosine_spearman value: 85.63500407412486
    • type: euclidean_pearson value: 85.21829891649696
    • type: euclidean_spearman value: 85.9384575715382
    • type: main_score value: 85.63500407412486
    • type: manhattan_pearson value: 85.10797194089801
    • type: manhattan_spearman value: 85.8770162042784
    • type: pearson value: 84.27751020600267
    • type: spearman value: 85.63500407412486 task: type: STS

  • dataset: config: fr name: MTEB STSBenchmarkMultilingualSTS (fr) revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c split: test type: mteb/stsb_multi_mt metrics:

    • type: cosine_pearson value: 86.56833656723254
    • type: cosine_spearman value: 87.4393978501382
    • type: euclidean_pearson value: 87.45171512751267
    • type: euclidean_spearman value: 88.13106516566947
    • type: main_score value: 87.4393978501382
    • type: manhattan_pearson value: 87.33010961793333
    • type: manhattan_spearman value: 88.06707425102182
    • type: pearson value: 86.56833656723254
    • type: spearman value: 87.4393978501382 task: type: STS

  • dataset: config: pl name: MTEB STSBenchmarkMultilingualSTS (pl) revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c split: test type: mteb/stsb_multi_mt metrics:

    • type: cosine_pearson value: 85.45065540325523
    • type: cosine_spearman value: 85.47881076789359
    • type: euclidean_pearson value: 85.1999493863155
    • type: euclidean_spearman value: 85.7874947669187
    • type: main_score value: 85.47881076789359
    • type: manhattan_pearson value: 85.06075305990376
    • type: manhattan_spearman value: 85.71563015639558
    • type: pearson value: 85.45065540325523
    • type: spearman value: 85.47881076789359 task: type: STS

  • dataset: config: es name: MTEB STSBenchmarkMultilingualSTS (es) revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c split: test type: mteb/stsb_multi_mt metrics:

    • type: cosine_pearson value: 87.11952824079832
    • type: cosine_spearman value: 87.9643473573153
    • type: euclidean_pearson value: 88.11750364639971
    • type: euclidean_spearman value: 88.63695109016498
    • type: main_score value: 87.9643473573153
    • type: manhattan_pearson value: 88.00294453126699
    • type: manhattan_spearman value: 88.53750241758391
    • type: pearson value: 87.11952824079832
    • type: spearman value: 87.9643473573153 task: type: STS

  • dataset: config: ru name: MTEB STSBenchmarkMultilingualSTS (ru) revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c split: test type: mteb/stsb_multi_mt metrics:

    • type: cosine_pearson value: 85.99804354414991
    • type: cosine_spearman value: 86.30252111551002
    • type: euclidean_pearson value: 86.1880652037762
    • type: euclidean_spearman value: 86.69556223944502
    • type: main_score value: 86.30252111551002
    • type: manhattan_pearson value: 86.0736400320898
    • type: manhattan_spearman value: 86.61747927593393
    • type: pearson value: 85.99804354414991
    • type: spearman value: 86.30252111551002 task: type: STS

  • dataset: config: en name: MTEB STSBenchmarkMultilingualSTS (en) revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c split: test type: mteb/stsb_multi_mt metrics:

    • type: cosine_pearson value: 87.70246861738103
    • type: cosine_spearman value: 89.44070045346106
    • type: euclidean_pearson value: 89.56956518833663
    • type: euclidean_spearman value: 89.95830112784283
    • type: main_score value: 89.44070045346106
    • type: manhattan_pearson value: 89.48264470792915
    • type: manhattan_spearman value: 89.87900732483114
    • type: pearson value: 87.70246861738103
    • type: spearman value: 89.44070045346106 task: type: STS

  • dataset: config: default name: MTEB SciDocsRR (default) revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab split: test type: mteb/scidocs-reranking metrics:

    • type: map value: 84.88064122814694
    • type: mrr value: 95.84832651009123
    • type: main_score value: 84.88064122814694 task: type: Reranking

  • dataset: config: default name: MTEB SciFact (default) revision: 0228b52cf27578f30900b9e5271d331663a030d7 split: test type: mteb/scifact metrics:

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    • type: recall_at_1 value: 57.289
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    • type: recall_at_3 value: 73.22800000000001
    • type: recall_at_5 value: 79.444
    • type: main_score value: 72.309 task: type: Retrieval

  • dataset: config: default name: MTEB SpanishNewsClusteringP2P (default) revision: bf8ca8ddc5b7da4f7004720ddf99bbe0483480e6 split: test type: jinaai/spanish_news_clustering metrics:

    • type: main_score value: 45.04477709795154
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  • dataset: config: default name: MTEB SpanishPassageRetrievalS2S (default) revision: 9cddf2ce5209ade52c2115ccfa00eb22c6d3a837 split: test type: jinaai/spanish_passage_retrieval metrics:

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    • type: recall_at_1 value: 15.736
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  • dataset: config: default name: MTEB SprintDuplicateQuestions (default) revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 split: test type: mteb/sprintduplicatequestions-pairclassification metrics:

    • type: cosine_accuracy value: 99.87326732673267
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    • type: dot_recall value: 92.5
    • type: euclidean_accuracy value: 99.87128712871286
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    • type: euclidean_recall value: 92.7
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    • type: manhattan_accuracy value: 99.86930693069307
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    • type: manhattan_recall value: 92.4
    • type: max_accuracy value: 99.87326732673267
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    • type: similarity_accuracy value: 99.87326732673267
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  • dataset: config: default name: MTEB StackExchangeClustering (default) revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 split: test type: mteb/stackexchange-clustering metrics:

    • type: main_score value: 65.6560129719848
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    • type: v_measure_std value: 4.781229811487539 task: type: Clustering

  • dataset: config: default name: MTEB StackExchangeClusteringP2P (default) revision: 815ca46b2622cec33ccafc3735d572c266efdb44 split: test type: mteb/stackexchange-clustering-p2p metrics:

    • type: main_score value: 35.07546243853692
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  • dataset: config: default name: MTEB StackOverflowDupQuestions (default) revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 split: test type: mteb/stackoverflowdupquestions-reranking metrics:

    • type: map value: 51.771005199508835
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  • dataset: config: default name: MTEB SummEval (default) revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c split: test type: mteb/summeval metrics:

    • type: cosine_pearson value: 29.48686238342228
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  • dataset: config: default name: MTEB SummEvalFr (default) revision: b385812de6a9577b6f4d0f88c6a6e35395a94054 split: test type: lyon-nlp/summarization-summeval-fr-p2p metrics:

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  • dataset: config: default name: MTEB SyntecReranking (default) revision: b205c5084a0934ce8af14338bf03feb19499c84d split: test type: lyon-nlp/mteb-fr-reranking-syntec-s2p metrics:

    • type: map value: 73.31666666666666
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  • dataset: config: default name: MTEB SyntecRetrieval (default) revision: 19661ccdca4dfc2d15122d776b61685f48c68ca9 split: test type: lyon-nlp/mteb-fr-retrieval-syntec-s2p metrics:

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  • dataset: config: default name: MTEB T2Reranking (default) revision: 76631901a18387f85eaa53e5450019b87ad58ef9 split: dev type: C-MTEB/T2Reranking metrics:

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  • dataset: config: default name: MTEB T2Retrieval (default) revision: 8731a845f1bf500a4f111cf1070785c793d10e64 split: dev type: C-MTEB/T2Retrieval metrics:

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  • dataset: config: default name: MTEB TERRa (default) revision: 7b58f24536063837d644aab9a023c62199b2a612 split: dev type: ai-forever/terra-pairclassification metrics:

    • type: cosine_accuracy value: 60.586319218241044
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  • dataset: config: default name: MTEB TNews (default) revision: 317f262bf1e6126357bbe89e875451e4b0938fe4 split: validation type: C-MTEB/TNews-classification metrics:

    • type: accuracy value: 45.967999999999996
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  • dataset: config: default name: MTEB TRECCOVID (default) revision: bb9466bac8153a0349341eb1b22e06409e78ef4e split: test type: mteb/trec-covid metrics:

    • type: map_at_1 value: 0.251
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    • type: precision_at_20 value: 75.2
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    • type: precision_at_5 value: 84.8
    • type: recall_at_1 value: 0.251
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    • type: recall_at_1000 value: 50.09
    • type: recall_at_20 value: 3.8309999999999995
    • type: recall_at_3 value: 0.696
    • type: recall_at_5 value: 1.1400000000000001
    • type: main_score value: 77.71900000000001 task: type: Retrieval

  • dataset: config: default name: MTEB TenKGnadClusteringP2P (default) revision: 5c59e41555244b7e45c9a6be2d720ab4bafae558 split: test type: slvnwhrl/tenkgnad-clustering-p2p metrics:

    • type: main_score value: 43.763609722295215
    • type: v_measure value: 43.763609722295215
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  • dataset: config: default name: MTEB TenKGnadClusteringS2S (default) revision: 6cddbe003f12b9b140aec477b583ac4191f01786 split: test type: slvnwhrl/tenkgnad-clustering-s2s metrics:

    • type: main_score value: 39.762424448504355
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  • dataset: config: default name: MTEB ThuNewsClusteringP2P (default) revision: 5798586b105c0434e4f0fe5e767abe619442cf93 split: test type: C-MTEB/ThuNewsClusteringP2P metrics:

    • type: main_score value: 63.133819258289456
    • type: v_measure value: 63.133819258289456
    • type: v_measure_std value: 1.8854253356479695 task: type: Clustering

  • dataset: config: default name: MTEB ThuNewsClusteringS2S (default) revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d split: test type: C-MTEB/ThuNewsClusteringS2S metrics:

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    • type: v_measure value: 58.98195851785808
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  • dataset: config: default name: MTEB Touche2020 (default) revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f split: test type: mteb/touche2020 metrics:

    • type: map_at_1 value: 3.3550000000000004
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    • type: recall_at_1 value: 3.3550000000000004
    • type: recall_at_10 value: 16.41
    • type: recall_at_100 value: 47.272
    • type: recall_at_1000 value: 83.584
    • type: recall_at_20 value: 24.091
    • type: recall_at_3 value: 6.8180000000000005
    • type: recall_at_5 value: 9.677
    • type: main_score value: 26.298 task: type: Retrieval

  • dataset: config: default name: MTEB ToxicConversationsClassification (default) revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de split: test type: mteb/toxic_conversations_50k metrics:

    • type: accuracy value: 91.2890625
    • type: ap value: 33.95547153875715
    • type: ap_weighted value: 33.95547153875715
    • type: f1 value: 75.10768597556462
    • type: f1_weighted value: 92.00161208992606
    • type: main_score value: 91.2890625 task: type: Classification

  • dataset: config: default name: MTEB TweetSentimentExtractionClassification (default) revision: d604517c81ca91fe16a244d1248fc021f9ecee7a split: test type: mteb/tweet_sentiment_extraction metrics:

    • type: accuracy value: 71.3978494623656
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    • type: f1_weighted value: 71.13860187349744
    • type: main_score value: 71.3978494623656 task: type: Classification

  • dataset: config: default name: MTEB TwentyNewsgroupsClustering (default) revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 split: test type: mteb/twentynewsgroups-clustering metrics:

    • type: main_score value: 52.4921688720602
    • type: v_measure value: 52.4921688720602
    • type: v_measure_std value: 0.992768152658908 task: type: Clustering

  • dataset: config: default name: MTEB TwitterSemEval2015 (default) revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 split: test type: mteb/twittersemeval2015-pairclassification metrics:

    • type: cosine_accuracy value: 85.11652858079513
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  • dataset: config: default name: MTEB TwitterURLCorpus (default) revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf split: test type: mteb/twitterurlcorpus-pairclassification metrics:

    • type: cosine_accuracy value: 88.10299996119068
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  • dataset: config: default name: MTEB VideoRetrieval (default) revision: 58c2597a5943a2ba48f4668c3b90d796283c5639 split: dev type: C-MTEB/VideoRetrieval metrics:

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  • dataset: config: default name: MTEB Waimai (default) revision: 339287def212450dcaa9df8c22bf93e9980c7023 split: test type: C-MTEB/waimai-classification metrics:

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  • dataset: config: en name: MTEB XMarket (en) revision: dfe57acff5b62c23732a7b7d3e3fb84ff501708b split: test type: jinaai/xmarket_ml metrics:

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  • dataset: config: de name: MTEB XMarket (de) revision: dfe57acff5b62c23732a7b7d3e3fb84ff501708b split: test type: jinaai/xmarket_ml metrics:

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  • dataset: config: es name: MTEB XMarket (es) revision: dfe57acff5b62c23732a7b7d3e3fb84ff501708b split: test type: jinaai/xmarket_ml metrics:

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  • dataset: config: deu-deu name: MTEB XPQARetrieval (deu-deu) revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f split: test type: jinaai/xpqa metrics:

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  • dataset: config: deu-eng name: MTEB XPQARetrieval (deu-eng) revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f split: test type: jinaai/xpqa metrics:

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  • dataset: config: eng-deu name: MTEB XPQARetrieval (eng-deu) revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f split: test type: jinaai/xpqa metrics:

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  • dataset: config: pol-eng name: MTEB XPQARetrieval (pol-eng) revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f split: test type: jinaai/xpqa metrics:

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  • dataset: config: spa-eng name: MTEB XPQARetrieval (spa-eng) revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f split: test type: jinaai/xpqa metrics:

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  • dataset: config: fra-eng name: MTEB XPQARetrieval (fra-eng) revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f split: test type: jinaai/xpqa metrics:

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