tags:

• mteb
• Sentence Transformers
• sentence-similarity
• sentence-transformers model-index:
• name: multilingual-e5-base results:
  • task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
    • type: accuracy value: 78.97014925373135
    • type: ap value: 43.69351129103008
    • type: f1 value: 73.38075030070492
  • task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (de) config: de split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
    • type: accuracy value: 71.7237687366167
    • type: ap value: 82.22089859962671
    • type: f1 value: 69.95532758884401
  • task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en-ext) config: en-ext split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
    • type: accuracy value: 79.65517241379312
    • type: ap value: 28.507918657094738
    • type: f1 value: 66.84516013726119
  • task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (ja) config: ja split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
    • type: accuracy value: 73.32976445396146
    • type: ap value: 20.720481637566014
    • type: f1 value: 59.78002763416003
  • task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics:
    • type: accuracy value: 90.63775
    • type: ap value: 87.22277903861716
    • type: f1 value: 90.60378636386807
  • task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
    • type: accuracy value: 44.546
    • type: f1 value: 44.05666638370923
  • task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (de) config: de split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
    • type: accuracy value: 41.828
    • type: f1 value: 41.2710255644252
  • task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (es) config: es split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
    • type: accuracy value: 40.534
    • type: f1 value: 39.820743174270326
  • task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (fr) config: fr split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
    • type: accuracy value: 39.684
    • type: f1 value: 39.11052682815307
  • task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (ja) config: ja split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
    • type: accuracy value: 37.436
    • type: f1 value: 37.07082931930871
  • task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (zh) config: zh split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
    • type: accuracy value: 37.226000000000006
    • type: f1 value: 36.65372077739185
  • task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics:
    • type: map_at_1 value: 22.831000000000003
    • type: map_at_10 value: 36.42
    • type: map_at_100 value: 37.699
    • type: map_at_1000 value: 37.724000000000004
    • type: map_at_3 value: 32.207
    • type: map_at_5 value: 34.312
    • type: mrr_at_1 value: 23.257
    • type: mrr_at_10 value: 36.574
    • type: mrr_at_100 value: 37.854
    • type: mrr_at_1000 value: 37.878
    • type: mrr_at_3 value: 32.385000000000005
    • type: mrr_at_5 value: 34.48
    • type: ndcg_at_1 value: 22.831000000000003
    • type: ndcg_at_10 value: 44.230000000000004
    • type: ndcg_at_100 value: 49.974000000000004
    • type: ndcg_at_1000 value: 50.522999999999996
    • type: ndcg_at_3 value: 35.363
    • type: ndcg_at_5 value: 39.164
    • type: precision_at_1 value: 22.831000000000003
    • type: precision_at_10 value: 6.935
    • type: precision_at_100 value: 0.9520000000000001
    • type: precision_at_1000 value: 0.099
    • type: precision_at_3 value: 14.841
    • type: precision_at_5 value: 10.754
    • type: recall_at_1 value: 22.831000000000003
    • type: recall_at_10 value: 69.346
    • type: recall_at_100 value: 95.235
    • type: recall_at_1000 value: 99.36
    • type: recall_at_3 value: 44.523
    • type: recall_at_5 value: 53.769999999999996
  • task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics:
    • type: v_measure value: 40.27789869854063
  • task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics:
    • type: v_measure value: 35.41979463347428
  • task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics:
    • type: map value: 58.22752045109304
    • type: mrr value: 71.51112430198303
  • task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics:
    • type: cos_sim_pearson value: 84.71147646622866
    • type: cos_sim_spearman value: 85.059167046486
    • type: euclidean_pearson value: 75.88421613600647
    • type: euclidean_spearman value: 75.12821787150585
    • type: manhattan_pearson value: 75.22005646957604
    • type: manhattan_spearman value: 74.42880434453272
  • task: type: BitextMining dataset: type: mteb/bucc-bitext-mining name: MTEB BUCC (de-en) config: de-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics:
    • type: accuracy value: 99.23799582463465
    • type: f1 value: 99.12665274878218
    • type: precision value: 99.07098121085595
    • type: recall value: 99.23799582463465
  • task: type: BitextMining dataset: type: mteb/bucc-bitext-mining name: MTEB BUCC (fr-en) config: fr-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics:
    • type: accuracy value: 97.88685890380806
    • type: f1 value: 97.59336708489249
    • type: precision value: 97.44662117543473
    • type: recall value: 97.88685890380806
  • task: type: BitextMining dataset: type: mteb/bucc-bitext-mining name: MTEB BUCC (ru-en) config: ru-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics:
    • type: accuracy value: 97.47142362313821
    • type: f1 value: 97.1989377670015
    • type: precision value: 97.06384944001847
    • type: recall value: 97.47142362313821
  • task: type: BitextMining dataset: type: mteb/bucc-bitext-mining name: MTEB BUCC (zh-en) config: zh-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics:
    • type: accuracy value: 98.4728804634018
    • type: f1 value: 98.2973494821836
    • type: precision value: 98.2095839915745
    • type: recall value: 98.4728804634018
  • task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics:
    • type: accuracy value: 82.74025974025975
    • type: f1 value: 82.67420447730439
  • task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics:
    • type: v_measure value: 35.0380848063507
  • task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics:
    • type: v_measure value: 29.45956405670166
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 32.122
    • type: map_at_10 value: 42.03
    • type: map_at_100 value: 43.364000000000004
    • type: map_at_1000 value: 43.474000000000004
    • type: map_at_3 value: 38.804
    • type: map_at_5 value: 40.585
    • type: mrr_at_1 value: 39.914
    • type: mrr_at_10 value: 48.227
    • type: mrr_at_100 value: 49.018
    • type: mrr_at_1000 value: 49.064
    • type: mrr_at_3 value: 45.994
    • type: mrr_at_5 value: 47.396
    • type: ndcg_at_1 value: 39.914
    • type: ndcg_at_10 value: 47.825
    • type: ndcg_at_100 value: 52.852
    • type: ndcg_at_1000 value: 54.891
    • type: ndcg_at_3 value: 43.517
    • type: ndcg_at_5 value: 45.493
    • type: precision_at_1 value: 39.914
    • type: precision_at_10 value: 8.956
    • type: precision_at_100 value: 1.388
    • type: precision_at_1000 value: 0.182
    • type: precision_at_3 value: 20.791999999999998
    • type: precision_at_5 value: 14.821000000000002
    • type: recall_at_1 value: 32.122
    • type: recall_at_10 value: 58.294999999999995
    • type: recall_at_100 value: 79.726
    • type: recall_at_1000 value: 93.099
    • type: recall_at_3 value: 45.017
    • type: recall_at_5 value: 51.002
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 29.677999999999997
    • type: map_at_10 value: 38.684000000000005
    • type: map_at_100 value: 39.812999999999995
    • type: map_at_1000 value: 39.945
    • type: map_at_3 value: 35.831
    • type: map_at_5 value: 37.446
    • type: mrr_at_1 value: 37.771
    • type: mrr_at_10 value: 44.936
    • type: mrr_at_100 value: 45.583
    • type: mrr_at_1000 value: 45.634
    • type: mrr_at_3 value: 42.771
    • type: mrr_at_5 value: 43.994
    • type: ndcg_at_1 value: 37.771
    • type: ndcg_at_10 value: 44.059
    • type: ndcg_at_100 value: 48.192
    • type: ndcg_at_1000 value: 50.375
    • type: ndcg_at_3 value: 40.172000000000004
    • type: ndcg_at_5 value: 41.899
    • type: precision_at_1 value: 37.771
    • type: precision_at_10 value: 8.286999999999999
    • type: precision_at_100 value: 1.322
    • type: precision_at_1000 value: 0.178
    • type: precision_at_3 value: 19.406000000000002
    • type: precision_at_5 value: 13.745
    • type: recall_at_1 value: 29.677999999999997
    • type: recall_at_10 value: 53.071
    • type: recall_at_100 value: 70.812
    • type: recall_at_1000 value: 84.841
    • type: recall_at_3 value: 41.016000000000005
    • type: recall_at_5 value: 46.22
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 42.675000000000004
    • type: map_at_10 value: 53.93599999999999
    • type: map_at_100 value: 54.806999999999995
    • type: map_at_1000 value: 54.867
    • type: map_at_3 value: 50.934000000000005
    • type: map_at_5 value: 52.583
    • type: mrr_at_1 value: 48.339
    • type: mrr_at_10 value: 57.265
    • type: mrr_at_100 value: 57.873
    • type: mrr_at_1000 value: 57.906
    • type: mrr_at_3 value: 55.193000000000005
    • type: mrr_at_5 value: 56.303000000000004
    • type: ndcg_at_1 value: 48.339
    • type: ndcg_at_10 value: 59.19799999999999
    • type: ndcg_at_100 value: 62.743
    • type: ndcg_at_1000 value: 63.99399999999999
    • type: ndcg_at_3 value: 54.367
    • type: ndcg_at_5 value: 56.548
    • type: precision_at_1 value: 48.339
    • type: precision_at_10 value: 9.216000000000001
    • type: precision_at_100 value: 1.1809999999999998
    • type: precision_at_1000 value: 0.134
    • type: precision_at_3 value: 23.72
    • type: precision_at_5 value: 16.025
    • type: recall_at_1 value: 42.675000000000004
    • type: recall_at_10 value: 71.437
    • type: recall_at_100 value: 86.803
    • type: recall_at_1000 value: 95.581
    • type: recall_at_3 value: 58.434
    • type: recall_at_5 value: 63.754
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 23.518
    • type: map_at_10 value: 30.648999999999997
    • type: map_at_100 value: 31.508999999999997
    • type: map_at_1000 value: 31.604
    • type: map_at_3 value: 28.247
    • type: map_at_5 value: 29.65
    • type: mrr_at_1 value: 25.650000000000002
    • type: mrr_at_10 value: 32.771
    • type: mrr_at_100 value: 33.554
    • type: mrr_at_1000 value: 33.629999999999995
    • type: mrr_at_3 value: 30.433
    • type: mrr_at_5 value: 31.812
    • type: ndcg_at_1 value: 25.650000000000002
    • type: ndcg_at_10 value: 34.929
    • type: ndcg_at_100 value: 39.382
    • type: ndcg_at_1000 value: 41.913
    • type: ndcg_at_3 value: 30.292
    • type: ndcg_at_5 value: 32.629999999999995
    • type: precision_at_1 value: 25.650000000000002
    • type: precision_at_10 value: 5.311
    • type: precision_at_100 value: 0.792
    • type: precision_at_1000 value: 0.105
    • type: precision_at_3 value: 12.58
    • type: precision_at_5 value: 8.994
    • type: recall_at_1 value: 23.518
    • type: recall_at_10 value: 46.19
    • type: recall_at_100 value: 67.123
    • type: recall_at_1000 value: 86.442
    • type: recall_at_3 value: 33.678000000000004
    • type: recall_at_5 value: 39.244
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 15.891
    • type: map_at_10 value: 22.464000000000002
    • type: map_at_100 value: 23.483
    • type: map_at_1000 value: 23.613
    • type: map_at_3 value: 20.080000000000002
    • type: map_at_5 value: 21.526
    • type: mrr_at_1 value: 20.025000000000002
    • type: mrr_at_10 value: 26.712999999999997
    • type: mrr_at_100 value: 27.650000000000002
    • type: mrr_at_1000 value: 27.737000000000002
    • type: mrr_at_3 value: 24.274
    • type: mrr_at_5 value: 25.711000000000002
    • type: ndcg_at_1 value: 20.025000000000002
    • type: ndcg_at_10 value: 27.028999999999996
    • type: ndcg_at_100 value: 32.064
    • type: ndcg_at_1000 value: 35.188
    • type: ndcg_at_3 value: 22.512999999999998
    • type: ndcg_at_5 value: 24.89
    • type: precision_at_1 value: 20.025000000000002
    • type: precision_at_10 value: 4.776
    • type: precision_at_100 value: 0.8500000000000001
    • type: precision_at_1000 value: 0.125
    • type: precision_at_3 value: 10.531
    • type: precision_at_5 value: 7.811
    • type: recall_at_1 value: 15.891
    • type: recall_at_10 value: 37.261
    • type: recall_at_100 value: 59.12
    • type: recall_at_1000 value: 81.356
    • type: recall_at_3 value: 24.741
    • type: recall_at_5 value: 30.753999999999998
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 27.544
    • type: map_at_10 value: 36.283
    • type: map_at_100 value: 37.467
    • type: map_at_1000 value: 37.574000000000005
    • type: map_at_3 value: 33.528999999999996
    • type: map_at_5 value: 35.028999999999996
    • type: mrr_at_1 value: 34.166999999999994
    • type: mrr_at_10 value: 41.866
    • type: mrr_at_100 value: 42.666
    • type: mrr_at_1000 value: 42.716
    • type: mrr_at_3 value: 39.541
    • type: mrr_at_5 value: 40.768
    • type: ndcg_at_1 value: 34.166999999999994
    • type: ndcg_at_10 value: 41.577
    • type: ndcg_at_100 value: 46.687
    • type: ndcg_at_1000 value: 48.967
    • type: ndcg_at_3 value: 37.177
    • type: ndcg_at_5 value: 39.097
    • type: precision_at_1 value: 34.166999999999994
    • type: precision_at_10 value: 7.420999999999999
    • type: precision_at_100 value: 1.165
    • type: precision_at_1000 value: 0.154
    • type: precision_at_3 value: 17.291999999999998
    • type: precision_at_5 value: 12.166
    • type: recall_at_1 value: 27.544
    • type: recall_at_10 value: 51.99399999999999
    • type: recall_at_100 value: 73.738
    • type: recall_at_1000 value: 89.33
    • type: recall_at_3 value: 39.179
    • type: recall_at_5 value: 44.385999999999996
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 26.661
    • type: map_at_10 value: 35.475
    • type: map_at_100 value: 36.626999999999995
    • type: map_at_1000 value: 36.741
    • type: map_at_3 value: 32.818000000000005
    • type: map_at_5 value: 34.397
    • type: mrr_at_1 value: 32.647999999999996
    • type: mrr_at_10 value: 40.784
    • type: mrr_at_100 value: 41.602
    • type: mrr_at_1000 value: 41.661
    • type: mrr_at_3 value: 38.68
    • type: mrr_at_5 value: 39.838
    • type: ndcg_at_1 value: 32.647999999999996
    • type: ndcg_at_10 value: 40.697
    • type: ndcg_at_100 value: 45.799
    • type: ndcg_at_1000 value: 48.235
    • type: ndcg_at_3 value: 36.516
    • type: ndcg_at_5 value: 38.515
    • type: precision_at_1 value: 32.647999999999996
    • type: precision_at_10 value: 7.202999999999999
    • type: precision_at_100 value: 1.1360000000000001
    • type: precision_at_1000 value: 0.151
    • type: precision_at_3 value: 17.314
    • type: precision_at_5 value: 12.145999999999999
    • type: recall_at_1 value: 26.661
    • type: recall_at_10 value: 50.995000000000005
    • type: recall_at_100 value: 73.065
    • type: recall_at_1000 value: 89.781
    • type: recall_at_3 value: 39.073
    • type: recall_at_5 value: 44.395
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 25.946583333333333
    • type: map_at_10 value: 33.79725
    • type: map_at_100 value: 34.86408333333333
    • type: map_at_1000 value: 34.9795
    • type: map_at_3 value: 31.259999999999998
    • type: map_at_5 value: 32.71541666666666
    • type: mrr_at_1 value: 30.863749999999996
    • type: mrr_at_10 value: 37.99183333333333
    • type: mrr_at_100 value: 38.790499999999994
    • type: mrr_at_1000 value: 38.85575000000001
    • type: mrr_at_3 value: 35.82083333333333
    • type: mrr_at_5 value: 37.07533333333333
    • type: ndcg_at_1 value: 30.863749999999996
    • type: ndcg_at_10 value: 38.52141666666667
    • type: ndcg_at_100 value: 43.17966666666667
    • type: ndcg_at_1000 value: 45.64608333333333
    • type: ndcg_at_3 value: 34.333000000000006
    • type: ndcg_at_5 value: 36.34975
    • type: precision_at_1 value: 30.863749999999996
    • type: precision_at_10 value: 6.598999999999999
    • type: precision_at_100 value: 1.0502500000000001
    • type: precision_at_1000 value: 0.14400000000000002
    • type: precision_at_3 value: 15.557583333333334
    • type: precision_at_5 value: 11.020000000000001
    • type: recall_at_1 value: 25.946583333333333
    • type: recall_at_10 value: 48.36991666666666
    • type: recall_at_100 value: 69.02408333333334
    • type: recall_at_1000 value: 86.43858333333331
    • type: recall_at_3 value: 36.4965
    • type: recall_at_5 value: 41.76258333333334
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 22.431
    • type: map_at_10 value: 28.889
    • type: map_at_100 value: 29.642000000000003
    • type: map_at_1000 value: 29.742
    • type: map_at_3 value: 26.998
    • type: map_at_5 value: 28.172000000000004
    • type: mrr_at_1 value: 25.307000000000002
    • type: mrr_at_10 value: 31.763
    • type: mrr_at_100 value: 32.443
    • type: mrr_at_1000 value: 32.531
    • type: mrr_at_3 value: 29.959000000000003
    • type: mrr_at_5 value: 31.063000000000002
    • type: ndcg_at_1 value: 25.307000000000002
    • type: ndcg_at_10 value: 32.586999999999996
    • type: ndcg_at_100 value: 36.5
    • type: ndcg_at_1000 value: 39.133
    • type: ndcg_at_3 value: 29.25
    • type: ndcg_at_5 value: 31.023
    • type: precision_at_1 value: 25.307000000000002
    • type: precision_at_10 value: 4.954
    • type: precision_at_100 value: 0.747
    • type: precision_at_1000 value: 0.104
    • type: precision_at_3 value: 12.577
    • type: precision_at_5 value: 8.741999999999999
    • type: recall_at_1 value: 22.431
    • type: recall_at_10 value: 41.134
    • type: recall_at_100 value: 59.28600000000001
    • type: recall_at_1000 value: 78.857
    • type: recall_at_3 value: 31.926
    • type: recall_at_5 value: 36.335
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 17.586
    • type: map_at_10 value: 23.304
    • type: map_at_100 value: 24.159
    • type: map_at_1000 value: 24.281
    • type: map_at_3 value: 21.316
    • type: map_at_5 value: 22.383
    • type: mrr_at_1 value: 21.645
    • type: mrr_at_10 value: 27.365000000000002
    • type: mrr_at_100 value: 28.108
    • type: mrr_at_1000 value: 28.192
    • type: mrr_at_3 value: 25.482
    • type: mrr_at_5 value: 26.479999999999997
    • type: ndcg_at_1 value: 21.645
    • type: ndcg_at_10 value: 27.306
    • type: ndcg_at_100 value: 31.496000000000002
    • type: ndcg_at_1000 value: 34.53
    • type: ndcg_at_3 value: 23.73
    • type: ndcg_at_5 value: 25.294
    • type: precision_at_1 value: 21.645
    • type: precision_at_10 value: 4.797
    • type: precision_at_100 value: 0.8059999999999999
    • type: precision_at_1000 value: 0.121
    • type: precision_at_3 value: 10.850999999999999
    • type: precision_at_5 value: 7.736
    • type: recall_at_1 value: 17.586
    • type: recall_at_10 value: 35.481
    • type: recall_at_100 value: 54.534000000000006
    • type: recall_at_1000 value: 76.456
    • type: recall_at_3 value: 25.335
    • type: recall_at_5 value: 29.473
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 25.095
    • type: map_at_10 value: 32.374
    • type: map_at_100 value: 33.537
    • type: map_at_1000 value: 33.634
    • type: map_at_3 value: 30.089
    • type: map_at_5 value: 31.433
    • type: mrr_at_1 value: 29.198
    • type: mrr_at_10 value: 36.01
    • type: mrr_at_100 value: 37.022
    • type: mrr_at_1000 value: 37.083
    • type: mrr_at_3 value: 33.94
    • type: mrr_at_5 value: 35.148
    • type: ndcg_at_1 value: 29.198
    • type: ndcg_at_10 value: 36.729
    • type: ndcg_at_100 value: 42.114000000000004
    • type: ndcg_at_1000 value: 44.592
    • type: ndcg_at_3 value: 32.644
    • type: ndcg_at_5 value: 34.652
    • type: precision_at_1 value: 29.198
    • type: precision_at_10 value: 5.970000000000001
    • type: precision_at_100 value: 0.967
    • type: precision_at_1000 value: 0.129
    • type: precision_at_3 value: 14.396999999999998
    • type: precision_at_5 value: 10.093
    • type: recall_at_1 value: 25.095
    • type: recall_at_10 value: 46.392
    • type: recall_at_100 value: 69.706
    • type: recall_at_1000 value: 87.738
    • type: recall_at_3 value: 35.303000000000004
    • type: recall_at_5 value: 40.441
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 26.857999999999997
    • type: map_at_10 value: 34.066
    • type: map_at_100 value: 35.671
    • type: map_at_1000 value: 35.881
    • type: map_at_3 value: 31.304
    • type: map_at_5 value: 32.885
    • type: mrr_at_1 value: 32.411
    • type: mrr_at_10 value: 38.987
    • type: mrr_at_100 value: 39.894
    • type: mrr_at_1000 value: 39.959
    • type: mrr_at_3 value: 36.626999999999995
    • type: mrr_at_5 value: 38.011
    • type: ndcg_at_1 value: 32.411
    • type: ndcg_at_10 value: 39.208
    • type: ndcg_at_100 value: 44.626
    • type: ndcg_at_1000 value: 47.43
    • type: ndcg_at_3 value: 35.091
    • type: ndcg_at_5 value: 37.119
    • type: precision_at_1 value: 32.411
    • type: precision_at_10 value: 7.51
    • type: precision_at_100 value: 1.486
    • type: precision_at_1000 value: 0.234
    • type: precision_at_3 value: 16.14
    • type: precision_at_5 value: 11.976
    • type: recall_at_1 value: 26.857999999999997
    • type: recall_at_10 value: 47.407
    • type: recall_at_100 value: 72.236
    • type: recall_at_1000 value: 90.77
    • type: recall_at_3 value: 35.125
    • type: recall_at_5 value: 40.522999999999996
  • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 21.3
    • type: map_at_10 value: 27.412999999999997
    • type: map_at_100 value: 28.29
    • type: map_at_1000 value: 28.398
    • type: map_at_3 value: 25.169999999999998
    • type: map_at_5 value: 26.496
    • type: mrr_at_1 value: 23.29
    • type: mrr_at_10 value: 29.215000000000003
    • type: mrr_at_100 value: 30.073
    • type: mrr_at_1000 value: 30.156
    • type: mrr_at_3 value: 26.956000000000003
    • type: mrr_at_5 value: 28.38
    • type: ndcg_at_1 value: 23.29
    • type: ndcg_at_10 value: 31.113000000000003
    • type: ndcg_at_100 value: 35.701
    • type: ndcg_at_1000 value: 38.505
    • type: ndcg_at_3 value: 26.727
    • type: ndcg_at_5 value: 29.037000000000003
    • type: precision_at_1 value: 23.29
    • type: precision_at_10 value: 4.787
    • type: precision_at_100 value: 0.763
    • type: precision_at_1000 value: 0.11100000000000002
    • type: precision_at_3 value: 11.091
    • type: precision_at_5 value: 7.985
    • type: recall_at_1 value: 21.3
    • type: recall_at_10 value: 40.782000000000004
    • type: recall_at_100 value: 62.13999999999999
    • type: recall_at_1000 value: 83.012
    • type: recall_at_3 value: 29.131
    • type: recall_at_5 value: 34.624
  • task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics:
    • type: map_at_1 value: 9.631
    • type: map_at_10 value: 16.634999999999998
    • type: map_at_100 value: 18.23
    • type: map_at_1000 value: 18.419
    • type: map_at_3 value: 13.66
    • type: map_at_5 value: 15.173
    • type: mrr_at_1 value: 21.368000000000002
    • type: mrr_at_10 value: 31.56
    • type: mrr_at_100 value: 32.58
    • type: mrr_at_1000 value: 32.633
    • type: mrr_at_3 value: 28.241
    • type: mrr_at_5 value: 30.225
    • type: ndcg_at_1 value: 21.368000000000002
    • type: ndcg_at_10 value: 23.855999999999998
    • type: ndcg_at_100 value: 30.686999999999998
    • type: ndcg_at_1000 value: 34.327000000000005
    • type: ndcg_at_3 value: 18.781
    • type: ndcg_at_5 value: 20.73
    • type: precision_at_1 value: 21.368000000000002
    • type: precision_at_10 value: 7.564
    • type: precision_at_100 value: 1.496
    • type: precision_at_1000 value: 0.217
    • type: precision_at_3 value: 13.876
    • type: precision_at_5 value: 11.062
    • type: recall_at_1 value: 9.631
    • type: recall_at_10 value: 29.517
    • type: recall_at_100 value: 53.452
    • type: recall_at_1000 value: 74.115
    • type: recall_at_3 value: 17.605999999999998
    • type: recall_at_5 value: 22.505
  • task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics:
    • type: map_at_1 value: 8.885
    • type: map_at_10 value: 18.798000000000002
    • type: map_at_100 value: 26.316
    • type: map_at_1000 value: 27.869
    • type: map_at_3 value: 13.719000000000001
    • type: map_at_5 value: 15.716
    • type: mrr_at_1 value: 66
    • type: mrr_at_10 value: 74.263
    • type: mrr_at_100 value: 74.519
    • type: mrr_at_1000 value: 74.531
    • type: mrr_at_3 value: 72.458
    • type: mrr_at_5 value: 73.321
    • type: ndcg_at_1 value: 53.87499999999999
    • type: ndcg_at_10 value: 40.355999999999995
    • type: ndcg_at_100 value: 44.366
    • type: ndcg_at_1000 value: 51.771
    • type: ndcg_at_3 value: 45.195
    • type: ndcg_at_5 value: 42.187000000000005
    • type: precision_at_1 value: 66
    • type: precision_at_10 value: 31.75
    • type: precision_at_100 value: 10.11
    • type: precision_at_1000 value: 1.9800000000000002
    • type: precision_at_3 value: 48.167
    • type: precision_at_5 value: 40.050000000000004
    • type: recall_at_1 value: 8.885
    • type: recall_at_10 value: 24.471999999999998
    • type: recall_at_100 value: 49.669000000000004
    • type: recall_at_1000 value: 73.383
    • type: recall_at_3 value: 14.872
    • type: recall_at_5 value: 18.262999999999998
  • task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics:
    • type: accuracy value: 45.18
    • type: f1 value: 40.26878691789978
  • task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics:
    • type: map_at_1 value: 62.751999999999995
    • type: map_at_10 value: 74.131
    • type: map_at_100 value: 74.407
    • type: map_at_1000 value: 74.423
    • type: map_at_3 value: 72.329
    • type: map_at_5 value: 73.555
    • type: mrr_at_1 value: 67.282
    • type: mrr_at_10 value: 78.292
    • type: mrr_at_100 value: 78.455
    • type: mrr_at_1000 value: 78.458
    • type: mrr_at_3 value: 76.755
    • type: mrr_at_5 value: 77.839
    • type: ndcg_at_1 value: 67.282
    • type: ndcg_at_10 value: 79.443
    • type: ndcg_at_100 value: 80.529
    • type: ndcg_at_1000 value: 80.812
    • type: ndcg_at_3 value: 76.281
    • type: ndcg_at_5 value: 78.235
    • type: precision_at_1 value: 67.282
    • type: precision_at_10 value: 10.078
    • type: precision_at_100 value: 1.082
    • type: precision_at_1000 value: 0.11199999999999999
    • type: precision_at_3 value: 30.178
    • type: precision_at_5 value: 19.232
    • type: recall_at_1 value: 62.751999999999995
    • type: recall_at_10 value: 91.521
    • type: recall_at_100 value: 95.997
    • type: recall_at_1000 value: 97.775
    • type: recall_at_3 value: 83.131
    • type: recall_at_5 value: 87.93299999999999
  • task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics:
    • type: map_at_1 value: 18.861
    • type: map_at_10 value: 30.252000000000002
    • type: map_at_100 value: 32.082
    • type: map_at_1000 value: 32.261
    • type: map_at_3 value: 25.909
    • type: map_at_5 value: 28.296
    • type: mrr_at_1 value: 37.346000000000004
    • type: mrr_at_10 value: 45.802
    • type: mrr_at_100 value: 46.611999999999995
    • type: mrr_at_1000 value: 46.659
    • type: mrr_at_3 value: 43.056
    • type: mrr_at_5 value: 44.637
    • type: ndcg_at_1 value: 37.346000000000004
    • type: ndcg_at_10 value: 38.169
    • type: ndcg_at_100 value: 44.864
    • type: ndcg_at_1000 value: 47.974
    • type: ndcg_at_3 value: 33.619
    • type: ndcg_at_5 value: 35.317
    • type: precision_at_1 value: 37.346000000000004
    • type: precision_at_10 value: 10.693999999999999
    • type: precision_at_100 value: 1.775
    • type: precision_at_1000 value: 0.231
    • type: precision_at_3 value: 22.325
    • type: precision_at_5 value: 16.852
    • type: recall_at_1 value: 18.861
    • type: recall_at_10 value: 45.672000000000004
    • type: recall_at_100 value: 70.60499999999999
    • type: recall_at_1000 value: 89.216
    • type: recall_at_3 value: 30.361
    • type: recall_at_5 value: 36.998999999999995
  • task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics:
    • type: map_at_1 value: 37.852999999999994
    • type: map_at_10 value: 59.961
    • type: map_at_100 value: 60.78
    • type: map_at_1000 value: 60.843
    • type: map_at_3 value: 56.39999999999999
    • type: map_at_5 value: 58.646
    • type: mrr_at_1 value: 75.70599999999999
    • type: mrr_at_10 value: 82.321
    • type: mrr_at_100 value: 82.516
    • type: mrr_at_1000 value: 82.525
    • type: mrr_at_3 value: 81.317
    • type: mrr_at_5 value: 81.922
    • type: ndcg_at_1 value: 75.70599999999999
    • type: ndcg_at_10 value: 68.557
    • type: ndcg_at_100 value: 71.485
    • type: ndcg_at_1000 value: 72.71600000000001
    • type: ndcg_at_3 value: 63.524
    • type: ndcg_at_5 value: 66.338
    • type: precision_at_1 value: 75.70599999999999
    • type: precision_at_10 value: 14.463000000000001
    • type: precision_at_100 value: 1.677
    • type: precision_at_1000 value: 0.184
    • type: precision_at_3 value: 40.806
    • type: precision_at_5 value: 26.709
    • type: recall_at_1 value: 37.852999999999994
    • type: recall_at_10 value: 72.316
    • type: recall_at_100 value: 83.842
    • type: recall_at_1000 value: 91.999
    • type: recall_at_3 value: 61.209
    • type: recall_at_5 value: 66.77199999999999
  • task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics:
    • type: accuracy value: 85.46039999999999
    • type: ap value: 79.9812521351881
    • type: f1 value: 85.31722909702084
  • task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics:
    • type: map_at_1 value: 22.704
    • type: map_at_10 value: 35.329
    • type: map_at_100 value: 36.494
    • type: map_at_1000 value: 36.541000000000004
    • type: map_at_3 value: 31.476
    • type: map_at_5 value: 33.731
    • type: mrr_at_1 value: 23.294999999999998
    • type: mrr_at_10 value: 35.859
    • type: mrr_at_100 value: 36.968
    • type: mrr_at_1000 value: 37.008
    • type: mrr_at_3 value: 32.085
    • type: mrr_at_5 value: 34.299
    • type: ndcg_at_1 value: 23.324
    • type: ndcg_at_10 value: 42.274
    • type: ndcg_at_100 value: 47.839999999999996
    • type: ndcg_at_1000 value: 48.971
    • type: ndcg_at_3 value: 34.454
    • type: ndcg_at_5 value: 38.464
    • type: precision_at_1 value: 23.324
    • type: precision_at_10 value: 6.648
    • type: precision_at_100 value: 0.9440000000000001
    • type: precision_at_1000 value: 0.104
    • type: precision_at_3 value: 14.674999999999999
    • type: precision_at_5 value: 10.850999999999999
    • type: recall_at_1 value: 22.704
    • type: recall_at_10 value: 63.660000000000004
    • type: recall_at_100 value: 89.29899999999999
    • type: recall_at_1000 value: 97.88900000000001
    • type: recall_at_3 value: 42.441
    • type: recall_at_5 value: 52.04
  • task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
    • type: accuracy value: 93.1326949384405
    • type: f1 value: 92.89743579612082
  • task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (de) config: de split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
    • type: accuracy value: 89.62524654832347
    • type: f1 value: 88.65106082263151
  • task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (es) config: es split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
    • type: accuracy value: 90.59039359573046
    • type: f1 value: 90.31532892105662
  • task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (fr) config: fr split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
    • type: accuracy value: 86.21046038208581
    • type: f1 value: 86.41459529813113
  • task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (hi) config: hi split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
    • type: accuracy value: 87.3180351380423
    • type: f1 value: 86.71383078226444
  • task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (th) config: th split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
    • type: accuracy value: 86.24231464737792
    • type: f1 value: 86.31845567592403
  • task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
    • type: accuracy value: 75.27131782945736
    • type: f1 value: 57.52079940417103
  • task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (de) config: de split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
    • type: accuracy value: 71.2341504649197
    • type: f1 value: 51.349951558039244
  • task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (es) config: es split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
    • type: accuracy value: 71.27418278852569
    • type: f1 value: 50.1714985749095
  • task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (fr) config: fr split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
    • type: accuracy value: 67.68243031631694
    • type: f1 value: 50.1066160836192
  • task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (hi) config: hi split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
    • type: accuracy value: 69.2362854069559
    • type: f1 value: 48.821279948766424
  • task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (th) config: th split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
    • type: accuracy value: 71.71428571428571
    • type: f1 value: 53.94611389496195
  • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (af) config: af split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
    • type: accuracy value: 59.97646267652992
    • type: f1 value: 57.26797883561521
  • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (am) config: am split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
    • type: accuracy value: 53.65501008742435
    • type: f1 value: 50.416258382177034
  • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (ar) config: ar split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
    • type: accuracy value: 57.45796906523201
    • type: f1 value: 53.306690547422185
  • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (az) config: az split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
    • type: accuracy value: 62.59246805648957
    • type: f1 value: 59.818381969051494
  • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (bn) config: bn split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
    • type: accuracy value: 61.126429051782104
    • type: f1 value: 58.25993593933026
  • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (cy) config: cy split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
    • type: accuracy value: 50.057162071284466
    • type: f1 value: 46.96095728790911
  • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (da) config: da split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
    • type: accuracy value: 66.64425016812375
    • type: f1 value: 62.858291698755764
  • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (de) config: de split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
    • type: accuracy value: 66.08944182918628
    • type: f1 value: 62.44639030604241
  • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (el) config: el split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
    • type: accuracy value: 64.68056489576328
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    • type: accuracy value: 72.10827168796234
    • type: f1 value: 71.71954219691159
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (pl) config: pl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 70.59515803631471
    • type: f1 value: 70.05040128099003
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (pt) config: pt split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 70.83389374579691
    • type: f1 value: 70.84877936562735
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ro) config: ro split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 69.18628110289173
    • type: f1 value: 68.97232927921841
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ru) config: ru split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 72.99260255548083
    • type: f1 value: 72.85139492157732
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (sl) config: sl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 65.26227303295225
    • type: f1 value: 65.08833655469431
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (sq) config: sq split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 66.48621385339611
    • type: f1 value: 64.43483199071298
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (sv) config: sv split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 73.14391392064559
    • type: f1 value: 72.2580822579741
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (sw) config: sw split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 59.88567585743107
    • type: f1 value: 58.3073765932569
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ta) config: ta split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 62.38399462004034
    • type: f1 value: 60.82139544252606
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (te) config: te split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 62.58574310692671
    • type: f1 value: 60.71443370385374
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (th) config: th split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 71.61398789509079
    • type: f1 value: 70.99761812049401
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (tl) config: tl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 62.73705447209146
    • type: f1 value: 61.680849331794796
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (tr) config: tr split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 71.66778749159381
    • type: f1 value: 71.17320646080115
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (ur) config: ur split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 64.640215198386
    • type: f1 value: 63.301805157015444
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (vi) config: vi split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 70.00672494956288
    • type: f1 value: 70.26005548582106
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (zh-CN) config: zh-CN split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 75.42030934767989
    • type: f1 value: 75.2074842882598
  • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (zh-TW) config: zh-TW split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
    • type: accuracy value: 70.69266980497646
    • type: f1 value: 70.94103167391192
  • task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics:
    • type: v_measure value: 28.91697191169135
  • task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics:
    • type: v_measure value: 28.434000079573313
  • task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics:
    • type: map value: 30.96683513343383
    • type: mrr value: 31.967364078714834
  • task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics:
    • type: map_at_1 value: 5.5280000000000005
    • type: map_at_10 value: 11.793
    • type: map_at_100 value: 14.496999999999998
    • type: map_at_1000 value: 15.783
    • type: map_at_3 value: 8.838
    • type: map_at_5 value: 10.07
    • type: mrr_at_1 value: 43.653
    • type: mrr_at_10 value: 51.531000000000006
    • type: mrr_at_100 value: 52.205
    • type: mrr_at_1000 value: 52.242999999999995
    • type: mrr_at_3 value: 49.431999999999995
    • type: mrr_at_5 value: 50.470000000000006
    • type: ndcg_at_1 value: 42.415000000000006
    • type: ndcg_at_10 value: 32.464999999999996
    • type: ndcg_at_100 value: 28.927999999999997
    • type: ndcg_at_1000 value: 37.629000000000005
    • type: ndcg_at_3 value: 37.845
    • type: ndcg_at_5 value: 35.147
    • type: precision_at_1 value: 43.653
    • type: precision_at_10 value: 23.932000000000002
    • type: precision_at_100 value: 7.17
    • type: precision_at_1000 value: 1.967
    • type: precision_at_3 value: 35.397
    • type: precision_at_5 value: 29.907
    • type: recall_at_1 value: 5.5280000000000005
    • type: recall_at_10 value: 15.568000000000001
    • type: recall_at_100 value: 28.54
    • type: recall_at_1000 value: 59.864
    • type: recall_at_3 value: 9.822000000000001
    • type: recall_at_5 value: 11.726
  • task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics:
    • type: map_at_1 value: 37.041000000000004
    • type: map_at_10 value: 52.664
    • type: map_at_100 value: 53.477
    • type: map_at_1000 value: 53.505
    • type: map_at_3 value: 48.510999999999996
    • type: map_at_5 value: 51.036
    • type: mrr_at_1 value: 41.338
    • type: mrr_at_10 value: 55.071000000000005
    • type: mrr_at_100 value: 55.672
    • type: mrr_at_1000 value: 55.689
    • type: mrr_at_3 value: 51.82
    • type: mrr_at_5 value: 53.852
    • type: ndcg_at_1 value: 41.338
    • type: ndcg_at_10 value: 60.01800000000001
    • type: ndcg_at_100 value: 63.409000000000006
    • type: ndcg_at_1000 value: 64.017
    • type: ndcg_at_3 value: 52.44799999999999
    • type: ndcg_at_5 value: 56.571000000000005
    • type: precision_at_1 value: 41.338
    • type: precision_at_10 value: 9.531
    • type: precision_at_100 value: 1.145
    • type: precision_at_1000 value: 0.12
    • type: precision_at_3 value: 23.416
    • type: precision_at_5 value: 16.46
    • type: recall_at_1 value: 37.041000000000004
    • type: recall_at_10 value: 79.76299999999999
    • type: recall_at_100 value: 94.39
    • type: recall_at_1000 value: 98.851
    • type: recall_at_3 value: 60.465
    • type: recall_at_5 value: 69.906
  • task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics:
    • type: map_at_1 value: 69.952
    • type: map_at_10 value: 83.758
    • type: map_at_100 value: 84.406
    • type: map_at_1000 value: 84.425
    • type: map_at_3 value: 80.839
    • type: map_at_5 value: 82.646
    • type: mrr_at_1 value: 80.62
    • type: mrr_at_10 value: 86.947
    • type: mrr_at_100 value: 87.063
    • type: mrr_at_1000 value: 87.064
    • type: mrr_at_3 value: 85.96000000000001
    • type: mrr_at_5 value: 86.619
    • type: ndcg_at_1 value: 80.63
    • type: ndcg_at_10 value: 87.64800000000001
    • type: ndcg_at_100 value: 88.929
    • type: ndcg_at_1000 value: 89.054
    • type: ndcg_at_3 value: 84.765
    • type: ndcg_at_5 value: 86.291
    • type: precision_at_1 value: 80.63
    • type: precision_at_10 value: 13.314
    • type: precision_at_100 value: 1.525
    • type: precision_at_1000 value: 0.157
    • type: precision_at_3 value: 37.1
    • type: precision_at_5 value: 24.372
    • type: recall_at_1 value: 69.952
    • type: recall_at_10 value: 94.955
    • type: recall_at_100 value: 99.38
    • type: recall_at_1000 value: 99.96000000000001
    • type: recall_at_3 value: 86.60600000000001
    • type: recall_at_5 value: 90.997
  • task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics:
    • type: v_measure value: 42.41329517878427
  • task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics:
    • type: v_measure value: 55.171278362748666
  • task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics:
    • type: map_at_1 value: 4.213
    • type: map_at_10 value: 9.895
    • type: map_at_100 value: 11.776
    • type: map_at_1000 value: 12.084
    • type: map_at_3 value: 7.2669999999999995
    • type: map_at_5 value: 8.620999999999999
    • type: mrr_at_1 value: 20.8
    • type: mrr_at_10 value: 31.112000000000002
    • type: mrr_at_100 value: 32.274
    • type: mrr_at_1000 value: 32.35
    • type: mrr_at_3 value: 28.133000000000003
    • type: mrr_at_5 value: 29.892999999999997
    • type: ndcg_at_1 value: 20.8
    • type: ndcg_at_10 value: 17.163999999999998
    • type: ndcg_at_100 value: 24.738
    • type: ndcg_at_1000 value: 30.316
    • type: ndcg_at_3 value: 16.665
    • type: ndcg_at_5 value: 14.478
    • type: precision_at_1 value: 20.8
    • type: precision_at_10 value: 8.74
    • type: precision_at_100 value: 1.963
    • type: precision_at_1000 value: 0.33
    • type: precision_at_3 value: 15.467
    • type: precision_at_5 value: 12.6
    • type: recall_at_1 value: 4.213
    • type: recall_at_10 value: 17.698
    • type: recall_at_100 value: 39.838
    • type: recall_at_1000 value: 66.893
    • type: recall_at_3 value: 9.418
    • type: recall_at_5 value: 12.773000000000001
  • task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics:
    • type: cos_sim_pearson value: 82.90453315738294
    • type: cos_sim_spearman value: 78.51197850080254
    • type: euclidean_pearson value: 80.09647123597748
    • type: euclidean_spearman value: 78.63548011514061
    • type: manhattan_pearson value: 80.10645285675231
    • type: manhattan_spearman value: 78.57861806068901
  • task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics:
    • type: cos_sim_pearson value: 84.2616156846401
    • type: cos_sim_spearman value: 76.69713867850156
    • type: euclidean_pearson value: 77.97948563800394
    • type: euclidean_spearman value: 74.2371211567807
    • type: manhattan_pearson value: 77.69697879669705
    • type: manhattan_spearman value: 73.86529778022278
  • task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics:
    • type: cos_sim_pearson value: 77.0293269315045
    • type: cos_sim_spearman value: 78.02555120584198
    • type: euclidean_pearson value: 78.25398100379078
    • type: euclidean_spearman value: 78.66963870599464
    • type: manhattan_pearson value: 78.14314682167348
    • type: manhattan_spearman value: 78.57692322969135
  • task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics:
    • type: cos_sim_pearson value: 79.16989925136942
    • type: cos_sim_spearman value: 76.5996225327091
    • type: euclidean_pearson value: 77.8319003279786
    • type: euclidean_spearman value: 76.42824009468998
    • type: manhattan_pearson value: 77.69118862737736
    • type: manhattan_spearman value: 76.25568104762812
  • task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics:
    • type: cos_sim_pearson value: 87.42012286935325
    • type: cos_sim_spearman value: 88.15654297884122
    • type: euclidean_pearson value: 87.34082819427852
    • type: euclidean_spearman value: 88.06333589547084
    • type: manhattan_pearson value: 87.25115596784842
    • type: manhattan_spearman value: 87.9559927695203
  • task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics:
    • type: cos_sim_pearson value: 82.88222044996712
    • type: cos_sim_spearman value: 84.28476589061077
    • type: euclidean_pearson value: 83.17399758058309
    • type: euclidean_spearman value: 83.85497357244542
    • type: manhattan_pearson value: 83.0308397703786
    • type: manhattan_spearman value: 83.71554539935046
  • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (ko-ko) config: ko-ko split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
    • type: cos_sim_pearson value: 80.20682986257339
    • type: cos_sim_spearman value: 79.94567120362092
    • type: euclidean_pearson value: 79.43122480368902
    • type: euclidean_spearman value: 79.94802077264987
    • type: manhattan_pearson value: 79.32653021527081
    • type: manhattan_spearman value: 79.80961146709178
  • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (ar-ar) config: ar-ar split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
    • type: cos_sim_pearson value: 74.46578144394383
    • type: cos_sim_spearman value: 74.52496637472179
    • type: euclidean_pearson value: 72.2903807076809
    • type: euclidean_spearman value: 73.55549359771645
    • type: manhattan_pearson value: 72.09324837709393
    • type: manhattan_spearman value: 73.36743103606581
  • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-ar) config: en-ar split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
    • type: cos_sim_pearson value: 71.37272335116
    • type: cos_sim_spearman value: 71.26702117766037
    • type: euclidean_pearson value: 67.114829954434
    • type: euclidean_spearman value: 66.37938893947761
    • type: manhattan_pearson value: 66.79688574095246
    • type: manhattan_spearman value: 66.17292828079667
  • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-de) config: en-de split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
    • type: cos_sim_pearson value: 80.61016770129092
    • type: cos_sim_spearman value: 82.08515426632214
    • type: euclidean_pearson value: 80.557340361131
    • type: euclidean_spearman value: 80.37585812266175
    • type: manhattan_pearson value: 80.6782873404285
    • type: manhattan_spearman value: 80.6678073032024
  • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-en) config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
    • type: cos_sim_pearson value: 87.00150745350108
    • type: cos_sim_spearman value: 87.83441972211425
    • type: euclidean_pearson value: 87.94826702308792
    • type: euclidean_spearman value: 87.46143974860725
    • type: manhattan_pearson value: 87.97560344306105
    • type: manhattan_spearman value: 87.5267102829796
  • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-tr) config: en-tr split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
    • type: cos_sim_pearson value: 64.76325252267235
    • type: cos_sim_spearman value: 63.32615095463905
    • type: euclidean_pearson value: 64.07920669155716
    • type: euclidean_spearman value: 61.21409893072176
    • type: manhattan_pearson value: 64.26308625680016
    • type: manhattan_spearman value: 61.2438185254079
  • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (es-en) config: es-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
    • type: cos_sim_pearson value: 75.82644463022595
    • type: cos_sim_spearman value: 76.50381269945073
    • type: euclidean_pearson value: 75.1328548315934
    • type: euclidean_spearman value: 75.63761139408453
    • type: manhattan_pearson value: 75.18610101241407
    • type: manhattan_spearman value: 75.30669266354164
  • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (es-es) config: es-es split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
    • type: cos_sim_pearson value: 87.49994164686832
    • type: cos_sim_spearman value: 86.73743986245549
    • type: euclidean_pearson value: 86.8272894387145
    • type: euclidean_spearman value: 85.97608491000507
    • type: manhattan_pearson value: 86.74960140396779
    • type: manhattan_spearman value: 85.79285984190273
  • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (fr-en) config: fr-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
    • type: cos_sim_pearson value: 79.58172210788469
    • type: cos_sim_spearman value: 80.17516468334607
    • type: euclidean_pearson value: 77.56537843470504
    • type: euclidean_spearman value: 77.57264627395521
    • type: manhattan_pearson value: 78.09703521695943
    • type: manhattan_spearman value: 78.15942760916954
  • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (it-en) config: it-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
    • type: cos_sim_pearson value: 79.7589932931751
    • type: cos_sim_spearman value: 80.15210089028162
    • type: euclidean_pearson value: 77.54135223516057
    • type: euclidean_spearman value: 77.52697996368764
    • type: manhattan_pearson value: 77.65734439572518
    • type: manhattan_spearman value: 77.77702992016121
  • task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (nl-en) config: nl-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics:
    • type: cos_sim_pearson value: 79.16682365511267
    • type: cos_sim_spearman value: 79.25311267628506
    • type: euclidean_pearson value: 77.54882036762244
    • type: euclidean_spearman value: 77.33212935194827
    • type: manhattan_pearson value: 77.98405516064015
    • type: manhattan_spearman value: 77.85075717865719
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (en) config: en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 59.10473294775917
    • type: cos_sim_spearman value: 61.82780474476838
    • type: euclidean_pearson value: 45.885111672377256
    • type: euclidean_spearman value: 56.88306351932454
    • type: manhattan_pearson value: 46.101218127323186
    • type: manhattan_spearman value: 56.80953694186333
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de) config: de split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 45.781923079584146
    • type: cos_sim_spearman value: 55.95098449691107
    • type: euclidean_pearson value: 25.4571031323205
    • type: euclidean_spearman value: 49.859978118078935
    • type: manhattan_pearson value: 25.624938455041384
    • type: manhattan_spearman value: 49.99546185049401
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es) config: es split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 60.00618133997907
    • type: cos_sim_spearman value: 66.57896677718321
    • type: euclidean_pearson value: 42.60118466388821
    • type: euclidean_spearman value: 62.8210759715209
    • type: manhattan_pearson value: 42.63446860604094
    • type: manhattan_spearman value: 62.73803068925271
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (pl) config: pl split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 28.460759121626943
    • type: cos_sim_spearman value: 34.13459007469131
    • type: euclidean_pearson value: 6.0917739325525195
    • type: euclidean_spearman value: 27.9947262664867
    • type: manhattan_pearson value: 6.16877864169911
    • type: manhattan_spearman value: 28.00664163971514
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (tr) config: tr split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 57.42546621771696
    • type: cos_sim_spearman value: 63.699663168970474
    • type: euclidean_pearson value: 38.12085278789738
    • type: euclidean_spearman value: 58.12329140741536
    • type: manhattan_pearson value: 37.97364549443335
    • type: manhattan_spearman value: 57.81545502318733
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (ar) config: ar split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 46.82241380954213
    • type: cos_sim_spearman value: 57.86569456006391
    • type: euclidean_pearson value: 31.80480070178813
    • type: euclidean_spearman value: 52.484000620130104
    • type: manhattan_pearson value: 31.952708554646097
    • type: manhattan_spearman value: 52.8560972356195
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (ru) config: ru split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 52.00447170498087
    • type: cos_sim_spearman value: 60.664116225735164
    • type: euclidean_pearson value: 33.87382555421702
    • type: euclidean_spearman value: 55.74649067458667
    • type: manhattan_pearson value: 33.99117246759437
    • type: manhattan_spearman value: 55.98749034923899
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (zh) config: zh split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 58.06497233105448
    • type: cos_sim_spearman value: 65.62968801135676
    • type: euclidean_pearson value: 47.482076613243905
    • type: euclidean_spearman value: 62.65137791498299
    • type: manhattan_pearson value: 47.57052626104093
    • type: manhattan_spearman value: 62.436916516613294
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (fr) config: fr split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 70.49397298562575
    • type: cos_sim_spearman value: 74.79604041187868
    • type: euclidean_pearson value: 49.661891561317795
    • type: euclidean_spearman value: 70.31535537621006
    • type: manhattan_pearson value: 49.553715741850006
    • type: manhattan_spearman value: 70.24779344636806
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-en) config: de-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 55.640574515348696
    • type: cos_sim_spearman value: 54.927959317689
    • type: euclidean_pearson value: 29.00139666967476
    • type: euclidean_spearman value: 41.86386566971605
    • type: manhattan_pearson value: 29.47411067730344
    • type: manhattan_spearman value: 42.337438424952786
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es-en) config: es-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 68.14095292259312
    • type: cos_sim_spearman value: 73.99017581234789
    • type: euclidean_pearson value: 46.46304297872084
    • type: euclidean_spearman value: 60.91834114800041
    • type: manhattan_pearson value: 47.07072666338692
    • type: manhattan_spearman value: 61.70415727977926
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (it) config: it split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 73.27184653359575
    • type: cos_sim_spearman value: 77.76070252418626
    • type: euclidean_pearson value: 62.30586577544778
    • type: euclidean_spearman value: 75.14246629110978
    • type: manhattan_pearson value: 62.328196884927046
    • type: manhattan_spearman value: 75.1282792981433
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (pl-en) config: pl-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 71.59448528829957
    • type: cos_sim_spearman value: 70.37277734222123
    • type: euclidean_pearson value: 57.63145565721123
    • type: euclidean_spearman value: 66.10113048304427
    • type: manhattan_pearson value: 57.18897811586808
    • type: manhattan_spearman value: 66.5595511215901
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (zh-en) config: zh-en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 66.37520607720838
    • type: cos_sim_spearman value: 69.92282148997948
    • type: euclidean_pearson value: 40.55768770125291
    • type: euclidean_spearman value: 55.189128944669605
    • type: manhattan_pearson value: 41.03566433468883
    • type: manhattan_spearman value: 55.61251893174558
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (es-it) config: es-it split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 57.791929533771835
    • type: cos_sim_spearman value: 66.45819707662093
    • type: euclidean_pearson value: 39.03686018511092
    • type: euclidean_spearman value: 56.01282695640428
    • type: manhattan_pearson value: 38.91586623619632
    • type: manhattan_spearman value: 56.69394943612747
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-fr) config: de-fr split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 47.82224468473866
    • type: cos_sim_spearman value: 59.467307194781164
    • type: euclidean_pearson value: 27.428459190256145
    • type: euclidean_spearman value: 60.83463107397519
    • type: manhattan_pearson value: 27.487391578496638
    • type: manhattan_spearman value: 61.281380460246496
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (de-pl) config: de-pl split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 16.306666792752644
    • type: cos_sim_spearman value: 39.35486427252405
    • type: euclidean_pearson value: -2.7887154897955435
    • type: euclidean_spearman value: 27.1296051831719
    • type: manhattan_pearson value: -3.202291270581297
    • type: manhattan_spearman value: 26.32895849218158
  • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (fr-pl) config: fr-pl split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
    • type: cos_sim_pearson value: 59.67006803805076
    • type: cos_sim_spearman value: 73.24670207647144
    • type: euclidean_pearson value: 46.91884681500483
    • type: euclidean_spearman value: 16.903085094570333
    • type: manhattan_pearson value: 46.88391675325812
    • type: manhattan_spearman value: 28.17180849095055
  • task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics:
    • type: cos_sim_pearson value: 83.79555591223837
    • type: cos_sim_spearman value: 85.63658602085185
    • type: euclidean_pearson value: 85.22080894037671
    • type: euclidean_spearman value: 85.54113580167038
    • type: manhattan_pearson value: 85.1639505960118
    • type: manhattan_spearman value: 85.43502665436196
  • task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics:
    • type: map value: 80.73900991689766
    • type: mrr value: 94.81624131133934
  • task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics:
    • type: map_at_1 value: 55.678000000000004
    • type: map_at_10 value: 65.135
    • type: map_at_100 value: 65.824
    • type: map_at_1000 value: 65.852
    • type: map_at_3 value: 62.736000000000004
    • type: map_at_5 value: 64.411
    • type: mrr_at_1 value: 58.333
    • type: mrr_at_10 value: 66.5
    • type: mrr_at_100 value: 67.053
    • type: mrr_at_1000 value: 67.08
    • type: mrr_at_3 value: 64.944
    • type: mrr_at_5 value: 65.89399999999999
    • type: ndcg_at_1 value: 58.333
    • type: ndcg_at_10 value: 69.34700000000001
    • type: ndcg_at_100 value: 72.32
    • type: ndcg_at_1000 value: 73.014
    • type: ndcg_at_3 value: 65.578
    • type: ndcg_at_5 value: 67.738
    • type: precision_at_1 value: 58.333
    • type: precision_at_10 value: 9.033
    • type: precision_at_100 value: 1.0670000000000002
    • type: precision_at_1000 value: 0.11199999999999999
    • type: precision_at_3 value: 25.444
    • type: precision_at_5 value: 16.933
    • type: recall_at_1 value: 55.678000000000004
    • type: recall_at_10 value: 80.72200000000001
    • type: recall_at_100 value: 93.93299999999999
    • type: recall_at_1000 value: 99.333
    • type: recall_at_3 value: 70.783
    • type: recall_at_5 value: 75.978
  • task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics:
    • type: cos_sim_accuracy value: 99.74653465346535
    • type: cos_sim_ap value: 93.01476369929063
    • type: cos_sim_f1 value: 86.93009118541033
    • type: cos_sim_precision value: 88.09034907597535
    • type: cos_sim_recall value: 85.8
    • type: dot_accuracy value: 99.22970297029703
    • type: dot_ap value: 51.58725659485144
    • type: dot_f1 value: 53.51351351351352
    • type: dot_precision value: 58.235294117647065
    • type: dot_recall value: 49.5
    • type: euclidean_accuracy value: 99.74356435643564
    • type: euclidean_ap value: 92.40332894384368
    • type: euclidean_f1 value: 86.97838109602817
    • type: euclidean_precision value: 87.46208291203236
    • type: euclidean_recall value: 86.5
    • type: manhattan_accuracy value: 99.73069306930694
    • type: manhattan_ap value: 92.01320815721121
    • type: manhattan_f1 value: 86.4135864135864
    • type: manhattan_precision value: 86.32734530938124
    • type: manhattan_recall value: 86.5
    • type: max_accuracy value: 99.74653465346535
    • type: max_ap value: 93.01476369929063
    • type: max_f1 value: 86.97838109602817
  • task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics:
    • type: v_measure value: 55.2660514302523
  • task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics:
    • type: v_measure value: 30.4637783572547
  • task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics:
    • type: map value: 49.41377758357637
    • type: mrr value: 50.138451213818854
  • task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics:
    • type: cos_sim_pearson value: 28.887846011166594
    • type: cos_sim_spearman value: 30.10823258355903
    • type: dot_pearson value: 12.888049550236385
    • type: dot_spearman value: 12.827495903098123
  • task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics:
    • type: map_at_1 value: 0.21
    • type: map_at_10 value: 1.667
    • type: map_at_100 value: 9.15
    • type: map_at_1000 value: 22.927
    • type: map_at_3 value: 0.573
    • type: map_at_5 value: 0.915
    • type: mrr_at_1 value: 80
    • type: mrr_at_10 value: 87.167
    • type: mrr_at_100 value: 87.167
    • type: mrr_at_1000 value: 87.167
    • type: mrr_at_3 value: 85.667
    • type: mrr_at_5 value: 87.167
    • type: ndcg_at_1 value: 76
    • type: ndcg_at_10 value: 69.757
    • type: ndcg_at_100 value: 52.402
    • type: ndcg_at_1000 value: 47.737
    • type: ndcg_at_3 value: 71.866
    • type: ndcg_at_5 value: 72.225
    • type: precision_at_1 value: 80
    • type: precision_at_10 value: 75
    • type: precision_at_100 value: 53.959999999999994
    • type: precision_at_1000 value: 21.568
    • type: precision_at_3 value: 76.667
    • type: precision_at_5 value: 78
    • type: recall_at_1 value: 0.21
    • type: recall_at_10 value: 1.9189999999999998
    • type: recall_at_100 value: 12.589
    • type: recall_at_1000 value: 45.312000000000005
    • type: recall_at_3 value: 0.61
    • type: recall_at_5 value: 1.019
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (sqi-eng) config: sqi-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 92.10000000000001
    • type: f1 value: 90.06
    • type: precision value: 89.17333333333333
    • type: recall value: 92.10000000000001
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (fry-eng) config: fry-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 56.06936416184971
    • type: f1 value: 50.87508028259473
    • type: precision value: 48.97398843930635
    • type: recall value: 56.06936416184971
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (kur-eng) config: kur-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 57.3170731707317
    • type: f1 value: 52.96080139372822
    • type: precision value: 51.67861124382864
    • type: recall value: 57.3170731707317
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (tur-eng) config: tur-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 94.3
    • type: f1 value: 92.67333333333333
    • type: precision value: 91.90833333333333
    • type: recall value: 94.3
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (deu-eng) config: deu-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 97.7
    • type: f1 value: 97.07333333333332
    • type: precision value: 96.79500000000002
    • type: recall value: 97.7
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (nld-eng) config: nld-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 94.69999999999999
    • type: f1 value: 93.2
    • type: precision value: 92.48333333333333
    • type: recall value: 94.69999999999999
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ron-eng) config: ron-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 92.9
    • type: f1 value: 91.26666666666667
    • type: precision value: 90.59444444444445
    • type: recall value: 92.9
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ang-eng) config: ang-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 34.32835820895522
    • type: f1 value: 29.074180380150533
    • type: precision value: 28.068207322920596
    • type: recall value: 34.32835820895522
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ido-eng) config: ido-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 78.5
    • type: f1 value: 74.3945115995116
    • type: precision value: 72.82967843459222
    • type: recall value: 78.5
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (jav-eng) config: jav-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 66.34146341463415
    • type: f1 value: 61.2469400518181
    • type: precision value: 59.63977756660683
    • type: recall value: 66.34146341463415
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (isl-eng) config: isl-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 80.9
    • type: f1 value: 76.90349206349207
    • type: precision value: 75.32921568627451
    • type: recall value: 80.9
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (slv-eng) config: slv-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 84.93317132442284
    • type: f1 value: 81.92519105034295
    • type: precision value: 80.71283920615635
    • type: recall value: 84.93317132442284
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (cym-eng) config: cym-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 71.1304347826087
    • type: f1 value: 65.22394755003451
    • type: precision value: 62.912422360248435
    • type: recall value: 71.1304347826087
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (kaz-eng) config: kaz-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 79.82608695652173
    • type: f1 value: 75.55693581780538
    • type: precision value: 73.79420289855072
    • type: recall value: 79.82608695652173
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (est-eng) config: est-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 74
    • type: f1 value: 70.51022222222223
    • type: precision value: 69.29673599347512
    • type: recall value: 74
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (heb-eng) config: heb-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 78.7
    • type: f1 value: 74.14238095238095
    • type: precision value: 72.27214285714285
    • type: recall value: 78.7
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (gla-eng) config: gla-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
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  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (max-eng) config: max-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
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  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (hin-eng) config: hin-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
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  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (dsb-eng) config: dsb-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
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  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ber-eng) config: ber-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
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  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (tam-eng) config: tam-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 88.27361563517914
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  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (slk-eng) config: slk-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
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    • type: recall value: 88.6
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (tgl-eng) config: tgl-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
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    • type: recall value: 86.5
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ast-eng) config: ast-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
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  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (mkd-eng) config: mkd-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
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    • type: recall value: 77.9
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (khm-eng) config: khm-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 53.8781163434903
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    • type: recall value: 53.8781163434903
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ces-eng) config: ces-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 91.10000000000001
    • type: f1 value: 88.88
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  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (tzl-eng) config: tzl-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 38.46153846153847
    • type: f1 value: 34.43978243978244
    • type: precision value: 33.429487179487175
    • type: recall value: 38.46153846153847
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (urd-eng) config: urd-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 88.9
    • type: f1 value: 86.19888888888887
    • type: precision value: 85.07440476190476
    • type: recall value: 88.9
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ara-eng) config: ara-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
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    • type: recall value: 85.9
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (kor-eng) config: kor-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 86.8
    • type: f1 value: 83.36999999999999
    • type: precision value: 81.86833333333333
    • type: recall value: 86.8
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (yid-eng) config: yid-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 68.51415094339622
    • type: f1 value: 63.195000099481234
    • type: precision value: 61.394033442972116
    • type: recall value: 68.51415094339622
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (fin-eng) config: fin-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 88.5
    • type: f1 value: 86.14603174603175
    • type: precision value: 85.1162037037037
    • type: recall value: 88.5
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (tha-eng) config: tha-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 95.62043795620438
    • type: f1 value: 94.40389294403892
    • type: precision value: 93.7956204379562
    • type: recall value: 95.62043795620438
  • task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (wuu-eng) config: wuu-eng split: test revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 metrics:
    • type: accuracy value: 81.8
    • type: f1 value: 78.6532178932179
    • type: precision value: 77.46348795840176
    • type: recall value: 81.8
  • task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics:
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    • type: map_at_10 value: 8.5
    • type: map_at_100 value: 12.985
    • type: map_at_1000 value: 14.466999999999999
    • type: map_at_3 value: 4.859999999999999
    • type: map_at_5 value: 5.817
    • type: mrr_at_1 value: 28.571
    • type: mrr_at_10 value: 42.331
    • type: mrr_at_100 value: 43.592999999999996
    • type: mrr_at_1000 value: 43.592999999999996
    • type: mrr_at_3 value: 38.435
    • type: mrr_at_5 value: 39.966
    • type: ndcg_at_1 value: 26.531
    • type: ndcg_at_10 value: 21.353
    • type: ndcg_at_100 value: 31.087999999999997
    • type: ndcg_at_1000 value: 43.163000000000004
    • type: ndcg_at_3 value: 22.999
    • type: ndcg_at_5 value: 21.451
    • type: precision_at_1 value: 28.571
    • type: precision_at_10 value: 19.387999999999998
    • type: precision_at_100 value: 6.265
    • type: precision_at_1000 value: 1.4160000000000001
    • type: precision_at_3 value: 24.490000000000002
    • type: precision_at_5 value: 21.224
    • type: recall_at_1 value: 2.603
    • type: recall_at_10 value: 14.474
    • type: recall_at_100 value: 40.287
    • type: recall_at_1000 value: 76.606
    • type: recall_at_3 value: 5.978
    • type: recall_at_5 value: 7.819
  • task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics:
    • type: accuracy value: 69.7848
    • type: ap value: 13.661023167088224
    • type: f1 value: 53.61686134460943
  • task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics:
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    • type: f1 value: 61.55481034919965
  • task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics:
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  • task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics:
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    • type: cos_sim_ap value: 72.20760361208136
    • type: cos_sim_f1 value: 66.4447731755424
    • type: cos_sim_precision value: 62.35539102267469
    • type: cos_sim_recall value: 71.10817941952506
    • type: dot_accuracy value: 78.98313166835548
    • type: dot_ap value: 44.492521645493795
    • type: dot_f1 value: 45.814889336016094
    • type: dot_precision value: 37.02439024390244
    • type: dot_recall value: 60.07915567282321
    • type: euclidean_accuracy value: 85.3907134767837
    • type: euclidean_ap value: 71.53847289080343
    • type: euclidean_f1 value: 65.95952206778834
    • type: euclidean_precision value: 61.31006346328196
    • type: euclidean_recall value: 71.37203166226914
    • type: manhattan_accuracy value: 85.40859510043511
    • type: manhattan_ap value: 71.49664104395515
    • type: manhattan_f1 value: 65.98569969356485
    • type: manhattan_precision value: 63.928748144482924
    • type: manhattan_recall value: 68.17941952506597
    • type: max_accuracy value: 85.59933241938367
    • type: max_ap value: 72.20760361208136
    • type: max_f1 value: 66.4447731755424
  • task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics:
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    • type: cos_sim_ap value: 85.48178133644264
    • type: cos_sim_f1 value: 77.87816307403935
    • type: cos_sim_precision value: 75.88953021114926
    • type: cos_sim_recall value: 79.97382198952879
    • type: dot_accuracy value: 79.76287499514883
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    • type: dot_f1 value: 56.34566667855996
    • type: dot_precision value: 52.50349092359864
    • type: dot_recall value: 60.794579611949494
    • type: euclidean_accuracy value: 88.76857996662397
    • type: euclidean_ap value: 85.22764834359887
    • type: euclidean_f1 value: 77.65379751543554
    • type: euclidean_precision value: 75.11152683839401
    • type: euclidean_recall value: 80.37419156144134
    • type: manhattan_accuracy value: 88.6987231730508
    • type: manhattan_ap value: 85.18907981724007
    • type: manhattan_f1 value: 77.51967028849757
    • type: manhattan_precision value: 75.49992701795358
    • type: manhattan_recall value: 79.65044656606098
    • type: max_accuracy value: 88.83261536073273
    • type: max_ap value: 85.48178133644264
    • type: max_f1 value: 77.87816307403935 language:
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