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说明文档

library_name: sentence-transformers pipeline_tag: sentence-similarity tags:

  • feature-extraction
  • sentence-similarity
  • mteb
  • transformers
  • transformers.js model-index:
  • name: epoch_0_model results:
    • task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
      • type: accuracy value: 75.20895522388058
      • type: ap value: 38.57605549557802
      • type: f1 value: 69.35586565857854
    • task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics:
      • type: accuracy value: 91.8144
      • type: ap value: 88.65222882032363
      • type: f1 value: 91.80426301643274
    • task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
      • type: accuracy value: 47.162000000000006
      • type: f1 value: 46.59329642263158
    • task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics:
      • type: map_at_1 value: 24.253
      • type: map_at_10 value: 38.962
      • type: map_at_100 value: 40.081
      • type: map_at_1000 value: 40.089000000000006
      • type: map_at_3 value: 33.499
      • type: map_at_5 value: 36.351
      • type: mrr_at_1 value: 24.609
      • type: mrr_at_10 value: 39.099000000000004
      • type: mrr_at_100 value: 40.211000000000006
      • type: mrr_at_1000 value: 40.219
      • type: mrr_at_3 value: 33.677
      • type: mrr_at_5 value: 36.469
      • type: ndcg_at_1 value: 24.253
      • type: ndcg_at_10 value: 48.010999999999996
      • type: ndcg_at_100 value: 52.756
      • type: ndcg_at_1000 value: 52.964999999999996
      • type: ndcg_at_3 value: 36.564
      • type: ndcg_at_5 value: 41.711999999999996
      • type: precision_at_1 value: 24.253
      • type: precision_at_10 value: 7.738
      • type: precision_at_100 value: 0.98
      • type: precision_at_1000 value: 0.1
      • type: precision_at_3 value: 15.149000000000001
      • type: precision_at_5 value: 11.593
      • type: recall_at_1 value: 24.253
      • type: recall_at_10 value: 77.383
      • type: recall_at_100 value: 98.009
      • type: recall_at_1000 value: 99.644
      • type: recall_at_3 value: 45.448
      • type: recall_at_5 value: 57.965999999999994
    • task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics:
      • type: v_measure value: 45.69069567851087
    • task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics:
      • type: v_measure value: 36.35185490976283
    • task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics:
      • type: map value: 61.71274951450321
      • type: mrr value: 76.06032625423207
    • task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics:
      • type: cos_sim_pearson value: 86.73980520022269
      • type: cos_sim_spearman value: 84.24649792685918
      • type: euclidean_pearson value: 85.85197641158186
      • type: euclidean_spearman value: 84.24649792685918
      • type: manhattan_pearson value: 86.26809552711346
      • type: manhattan_spearman value: 84.56397504030865
    • task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics:
      • type: accuracy value: 84.25324675324674
      • type: f1 value: 84.17872280892557
    • task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics:
      • type: v_measure value: 38.770253446400886
    • task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics:
      • type: v_measure value: 32.94307095497281
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 32.164
      • type: map_at_10 value: 42.641
      • type: map_at_100 value: 43.947
      • type: map_at_1000 value: 44.074999999999996
      • type: map_at_3 value: 39.592
      • type: map_at_5 value: 41.204
      • type: mrr_at_1 value: 39.628
      • type: mrr_at_10 value: 48.625
      • type: mrr_at_100 value: 49.368
      • type: mrr_at_1000 value: 49.413000000000004
      • type: mrr_at_3 value: 46.400000000000006
      • type: mrr_at_5 value: 47.68
      • type: ndcg_at_1 value: 39.628
      • type: ndcg_at_10 value: 48.564
      • type: ndcg_at_100 value: 53.507000000000005
      • type: ndcg_at_1000 value: 55.635999999999996
      • type: ndcg_at_3 value: 44.471
      • type: ndcg_at_5 value: 46.137
      • type: precision_at_1 value: 39.628
      • type: precision_at_10 value: 8.856
      • type: precision_at_100 value: 1.429
      • type: precision_at_1000 value: 0.191
      • type: precision_at_3 value: 21.268
      • type: precision_at_5 value: 14.649000000000001
      • type: recall_at_1 value: 32.164
      • type: recall_at_10 value: 59.609
      • type: recall_at_100 value: 80.521
      • type: recall_at_1000 value: 94.245
      • type: recall_at_3 value: 46.521
      • type: recall_at_5 value: 52.083999999999996
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 31.526
      • type: map_at_10 value: 41.581
      • type: map_at_100 value: 42.815999999999995
      • type: map_at_1000 value: 42.936
      • type: map_at_3 value: 38.605000000000004
      • type: map_at_5 value: 40.351
      • type: mrr_at_1 value: 39.489999999999995
      • type: mrr_at_10 value: 47.829
      • type: mrr_at_100 value: 48.512
      • type: mrr_at_1000 value: 48.552
      • type: mrr_at_3 value: 45.754
      • type: mrr_at_5 value: 46.986
      • type: ndcg_at_1 value: 39.489999999999995
      • type: ndcg_at_10 value: 47.269
      • type: ndcg_at_100 value: 51.564
      • type: ndcg_at_1000 value: 53.53099999999999
      • type: ndcg_at_3 value: 43.301
      • type: ndcg_at_5 value: 45.239000000000004
      • type: precision_at_1 value: 39.489999999999995
      • type: precision_at_10 value: 8.93
      • type: precision_at_100 value: 1.415
      • type: precision_at_1000 value: 0.188
      • type: precision_at_3 value: 20.892
      • type: precision_at_5 value: 14.865999999999998
      • type: recall_at_1 value: 31.526
      • type: recall_at_10 value: 56.76
      • type: recall_at_100 value: 75.029
      • type: recall_at_1000 value: 87.491
      • type: recall_at_3 value: 44.786
      • type: recall_at_5 value: 50.254
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 40.987
      • type: map_at_10 value: 52.827
      • type: map_at_100 value: 53.751000000000005
      • type: map_at_1000 value: 53.81
      • type: map_at_3 value: 49.844
      • type: map_at_5 value: 51.473
      • type: mrr_at_1 value: 46.833999999999996
      • type: mrr_at_10 value: 56.389
      • type: mrr_at_100 value: 57.003
      • type: mrr_at_1000 value: 57.034
      • type: mrr_at_3 value: 54.17999999999999
      • type: mrr_at_5 value: 55.486999999999995
      • type: ndcg_at_1 value: 46.833999999999996
      • type: ndcg_at_10 value: 58.372
      • type: ndcg_at_100 value: 62.068
      • type: ndcg_at_1000 value: 63.288
      • type: ndcg_at_3 value: 53.400000000000006
      • type: ndcg_at_5 value: 55.766000000000005
      • type: precision_at_1 value: 46.833999999999996
      • type: precision_at_10 value: 9.191
      • type: precision_at_100 value: 1.192
      • type: precision_at_1000 value: 0.134
      • type: precision_at_3 value: 23.448
      • type: precision_at_5 value: 15.862000000000002
      • type: recall_at_1 value: 40.987
      • type: recall_at_10 value: 71.146
      • type: recall_at_100 value: 87.035
      • type: recall_at_1000 value: 95.633
      • type: recall_at_3 value: 58.025999999999996
      • type: recall_at_5 value: 63.815999999999995
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 24.587
      • type: map_at_10 value: 33.114
      • type: map_at_100 value: 34.043
      • type: map_at_1000 value: 34.123999999999995
      • type: map_at_3 value: 30.45
      • type: map_at_5 value: 31.813999999999997
      • type: mrr_at_1 value: 26.554
      • type: mrr_at_10 value: 35.148
      • type: mrr_at_100 value: 35.926
      • type: mrr_at_1000 value: 35.991
      • type: mrr_at_3 value: 32.599000000000004
      • type: mrr_at_5 value: 33.893
      • type: ndcg_at_1 value: 26.554
      • type: ndcg_at_10 value: 38.132
      • type: ndcg_at_100 value: 42.78
      • type: ndcg_at_1000 value: 44.919
      • type: ndcg_at_3 value: 32.833
      • type: ndcg_at_5 value: 35.168
      • type: precision_at_1 value: 26.554
      • type: precision_at_10 value: 5.921
      • type: precision_at_100 value: 0.8659999999999999
      • type: precision_at_1000 value: 0.109
      • type: precision_at_3 value: 13.861
      • type: precision_at_5 value: 9.605
      • type: recall_at_1 value: 24.587
      • type: recall_at_10 value: 51.690000000000005
      • type: recall_at_100 value: 73.428
      • type: recall_at_1000 value: 89.551
      • type: recall_at_3 value: 37.336999999999996
      • type: recall_at_5 value: 43.047000000000004
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 16.715
      • type: map_at_10 value: 24.251
      • type: map_at_100 value: 25.326999999999998
      • type: map_at_1000 value: 25.455
      • type: map_at_3 value: 21.912000000000003
      • type: map_at_5 value: 23.257
      • type: mrr_at_1 value: 20.274
      • type: mrr_at_10 value: 28.552
      • type: mrr_at_100 value: 29.42
      • type: mrr_at_1000 value: 29.497
      • type: mrr_at_3 value: 26.14
      • type: mrr_at_5 value: 27.502
      • type: ndcg_at_1 value: 20.274
      • type: ndcg_at_10 value: 29.088
      • type: ndcg_at_100 value: 34.293
      • type: ndcg_at_1000 value: 37.271
      • type: ndcg_at_3 value: 24.708
      • type: ndcg_at_5 value: 26.809
      • type: precision_at_1 value: 20.274
      • type: precision_at_10 value: 5.361
      • type: precision_at_100 value: 0.915
      • type: precision_at_1000 value: 0.13
      • type: precision_at_3 value: 11.733
      • type: precision_at_5 value: 8.556999999999999
      • type: recall_at_1 value: 16.715
      • type: recall_at_10 value: 39.587
      • type: recall_at_100 value: 62.336000000000006
      • type: recall_at_1000 value: 83.453
      • type: recall_at_3 value: 27.839999999999996
      • type: recall_at_5 value: 32.952999999999996
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 28.793000000000003
      • type: map_at_10 value: 38.582
      • type: map_at_100 value: 39.881
      • type: map_at_1000 value: 39.987
      • type: map_at_3 value: 35.851
      • type: map_at_5 value: 37.289
      • type: mrr_at_1 value: 34.455999999999996
      • type: mrr_at_10 value: 43.909
      • type: mrr_at_100 value: 44.74
      • type: mrr_at_1000 value: 44.786
      • type: mrr_at_3 value: 41.659
      • type: mrr_at_5 value: 43.010999999999996
      • type: ndcg_at_1 value: 34.455999999999996
      • type: ndcg_at_10 value: 44.266
      • type: ndcg_at_100 value: 49.639
      • type: ndcg_at_1000 value: 51.644
      • type: ndcg_at_3 value: 39.865
      • type: ndcg_at_5 value: 41.887
      • type: precision_at_1 value: 34.455999999999996
      • type: precision_at_10 value: 7.843999999999999
      • type: precision_at_100 value: 1.243
      • type: precision_at_1000 value: 0.158
      • type: precision_at_3 value: 18.831999999999997
      • type: precision_at_5 value: 13.147
      • type: recall_at_1 value: 28.793000000000003
      • type: recall_at_10 value: 55.68300000000001
      • type: recall_at_100 value: 77.99000000000001
      • type: recall_at_1000 value: 91.183
      • type: recall_at_3 value: 43.293
      • type: recall_at_5 value: 48.618
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 25.907000000000004
      • type: map_at_10 value: 35.519
      • type: map_at_100 value: 36.806
      • type: map_at_1000 value: 36.912
      • type: map_at_3 value: 32.748
      • type: map_at_5 value: 34.232
      • type: mrr_at_1 value: 31.621
      • type: mrr_at_10 value: 40.687
      • type: mrr_at_100 value: 41.583
      • type: mrr_at_1000 value: 41.638999999999996
      • type: mrr_at_3 value: 38.527
      • type: mrr_at_5 value: 39.612
      • type: ndcg_at_1 value: 31.621
      • type: ndcg_at_10 value: 41.003
      • type: ndcg_at_100 value: 46.617999999999995
      • type: ndcg_at_1000 value: 48.82
      • type: ndcg_at_3 value: 36.542
      • type: ndcg_at_5 value: 38.368
      • type: precision_at_1 value: 31.621
      • type: precision_at_10 value: 7.396999999999999
      • type: precision_at_100 value: 1.191
      • type: precision_at_1000 value: 0.153
      • type: precision_at_3 value: 17.39
      • type: precision_at_5 value: 12.1
      • type: recall_at_1 value: 25.907000000000004
      • type: recall_at_10 value: 52.115
      • type: recall_at_100 value: 76.238
      • type: recall_at_1000 value: 91.218
      • type: recall_at_3 value: 39.417
      • type: recall_at_5 value: 44.435
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 25.732166666666668
      • type: map_at_10 value: 34.51616666666667
      • type: map_at_100 value: 35.67241666666666
      • type: map_at_1000 value: 35.78675
      • type: map_at_3 value: 31.953416666666662
      • type: map_at_5 value: 33.333
      • type: mrr_at_1 value: 30.300166666666673
      • type: mrr_at_10 value: 38.6255
      • type: mrr_at_100 value: 39.46183333333334
      • type: mrr_at_1000 value: 39.519999999999996
      • type: mrr_at_3 value: 36.41299999999999
      • type: mrr_at_5 value: 37.6365
      • type: ndcg_at_1 value: 30.300166666666673
      • type: ndcg_at_10 value: 39.61466666666667
      • type: ndcg_at_100 value: 44.60808333333334
      • type: ndcg_at_1000 value: 46.91708333333334
      • type: ndcg_at_3 value: 35.26558333333333
      • type: ndcg_at_5 value: 37.220000000000006
      • type: precision_at_1 value: 30.300166666666673
      • type: precision_at_10 value: 6.837416666666667
      • type: precision_at_100 value: 1.10425
      • type: precision_at_1000 value: 0.14875
      • type: precision_at_3 value: 16.13716666666667
      • type: precision_at_5 value: 11.2815
      • type: recall_at_1 value: 25.732166666666668
      • type: recall_at_10 value: 50.578916666666665
      • type: recall_at_100 value: 72.42183333333334
      • type: recall_at_1000 value: 88.48766666666667
      • type: recall_at_3 value: 38.41325
      • type: recall_at_5 value: 43.515750000000004
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 23.951
      • type: map_at_10 value: 30.974
      • type: map_at_100 value: 31.804
      • type: map_at_1000 value: 31.900000000000002
      • type: map_at_3 value: 28.762
      • type: map_at_5 value: 29.94
      • type: mrr_at_1 value: 26.534000000000002
      • type: mrr_at_10 value: 33.553
      • type: mrr_at_100 value: 34.297
      • type: mrr_at_1000 value: 34.36
      • type: mrr_at_3 value: 31.391000000000002
      • type: mrr_at_5 value: 32.525999999999996
      • type: ndcg_at_1 value: 26.534000000000002
      • type: ndcg_at_10 value: 35.112
      • type: ndcg_at_100 value: 39.28
      • type: ndcg_at_1000 value: 41.723
      • type: ndcg_at_3 value: 30.902
      • type: ndcg_at_5 value: 32.759
      • type: precision_at_1 value: 26.534000000000002
      • type: precision_at_10 value: 5.445
      • type: precision_at_100 value: 0.819
      • type: precision_at_1000 value: 0.11
      • type: precision_at_3 value: 12.986
      • type: precision_at_5 value: 9.049
      • type: recall_at_1 value: 23.951
      • type: recall_at_10 value: 45.24
      • type: recall_at_100 value: 64.12299999999999
      • type: recall_at_1000 value: 82.28999999999999
      • type: recall_at_3 value: 33.806000000000004
      • type: recall_at_5 value: 38.277
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 16.829
      • type: map_at_10 value: 23.684
      • type: map_at_100 value: 24.683
      • type: map_at_1000 value: 24.81
      • type: map_at_3 value: 21.554000000000002
      • type: map_at_5 value: 22.768
      • type: mrr_at_1 value: 20.096
      • type: mrr_at_10 value: 27.230999999999998
      • type: mrr_at_100 value: 28.083999999999996
      • type: mrr_at_1000 value: 28.166000000000004
      • type: mrr_at_3 value: 25.212
      • type: mrr_at_5 value: 26.32
      • type: ndcg_at_1 value: 20.096
      • type: ndcg_at_10 value: 27.989000000000004
      • type: ndcg_at_100 value: 32.847
      • type: ndcg_at_1000 value: 35.896
      • type: ndcg_at_3 value: 24.116
      • type: ndcg_at_5 value: 25.964
      • type: precision_at_1 value: 20.096
      • type: precision_at_10 value: 5
      • type: precision_at_100 value: 0.8750000000000001
      • type: precision_at_1000 value: 0.131
      • type: precision_at_3 value: 11.207
      • type: precision_at_5 value: 8.08
      • type: recall_at_1 value: 16.829
      • type: recall_at_10 value: 37.407000000000004
      • type: recall_at_100 value: 59.101000000000006
      • type: recall_at_1000 value: 81.024
      • type: recall_at_3 value: 26.739
      • type: recall_at_5 value: 31.524
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 24.138
      • type: map_at_10 value: 32.275999999999996
      • type: map_at_100 value: 33.416000000000004
      • type: map_at_1000 value: 33.527
      • type: map_at_3 value: 29.854000000000003
      • type: map_at_5 value: 31.096
      • type: mrr_at_1 value: 28.450999999999997
      • type: mrr_at_10 value: 36.214
      • type: mrr_at_100 value: 37.134
      • type: mrr_at_1000 value: 37.198
      • type: mrr_at_3 value: 34.001999999999995
      • type: mrr_at_5 value: 35.187000000000005
      • type: ndcg_at_1 value: 28.450999999999997
      • type: ndcg_at_10 value: 37.166
      • type: ndcg_at_100 value: 42.454
      • type: ndcg_at_1000 value: 44.976
      • type: ndcg_at_3 value: 32.796
      • type: ndcg_at_5 value: 34.631
      • type: precision_at_1 value: 28.450999999999997
      • type: precision_at_10 value: 6.241
      • type: precision_at_100 value: 0.9950000000000001
      • type: precision_at_1000 value: 0.133
      • type: precision_at_3 value: 14.801
      • type: precision_at_5 value: 10.280000000000001
      • type: recall_at_1 value: 24.138
      • type: recall_at_10 value: 48.111
      • type: recall_at_100 value: 71.245
      • type: recall_at_1000 value: 88.986
      • type: recall_at_3 value: 36.119
      • type: recall_at_5 value: 40.846
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 23.244
      • type: map_at_10 value: 31.227
      • type: map_at_100 value: 33.007
      • type: map_at_1000 value: 33.223
      • type: map_at_3 value: 28.924
      • type: map_at_5 value: 30.017
      • type: mrr_at_1 value: 27.668
      • type: mrr_at_10 value: 35.524
      • type: mrr_at_100 value: 36.699
      • type: mrr_at_1000 value: 36.759
      • type: mrr_at_3 value: 33.366
      • type: mrr_at_5 value: 34.552
      • type: ndcg_at_1 value: 27.668
      • type: ndcg_at_10 value: 36.381
      • type: ndcg_at_100 value: 43.062
      • type: ndcg_at_1000 value: 45.656
      • type: ndcg_at_3 value: 32.501999999999995
      • type: ndcg_at_5 value: 34.105999999999995
      • type: precision_at_1 value: 27.668
      • type: precision_at_10 value: 6.798
      • type: precision_at_100 value: 1.492
      • type: precision_at_1000 value: 0.234
      • type: precision_at_3 value: 15.152
      • type: precision_at_5 value: 10.791
      • type: recall_at_1 value: 23.244
      • type: recall_at_10 value: 45.979
      • type: recall_at_100 value: 74.822
      • type: recall_at_1000 value: 91.078
      • type: recall_at_3 value: 34.925
      • type: recall_at_5 value: 39.126
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 19.945
      • type: map_at_10 value: 27.517999999999997
      • type: map_at_100 value: 28.588
      • type: map_at_1000 value: 28.682000000000002
      • type: map_at_3 value: 25.345000000000002
      • type: map_at_5 value: 26.555
      • type: mrr_at_1 value: 21.996
      • type: mrr_at_10 value: 29.845
      • type: mrr_at_100 value: 30.775999999999996
      • type: mrr_at_1000 value: 30.845
      • type: mrr_at_3 value: 27.726
      • type: mrr_at_5 value: 28.882
      • type: ndcg_at_1 value: 21.996
      • type: ndcg_at_10 value: 32.034
      • type: ndcg_at_100 value: 37.185
      • type: ndcg_at_1000 value: 39.645
      • type: ndcg_at_3 value: 27.750999999999998
      • type: ndcg_at_5 value: 29.805999999999997
      • type: precision_at_1 value: 21.996
      • type: precision_at_10 value: 5.065
      • type: precision_at_100 value: 0.819
      • type: precision_at_1000 value: 0.11399999999999999
      • type: precision_at_3 value: 12.076
      • type: precision_at_5 value: 8.392
      • type: recall_at_1 value: 19.945
      • type: recall_at_10 value: 43.62
      • type: recall_at_100 value: 67.194
      • type: recall_at_1000 value: 85.7
      • type: recall_at_3 value: 32.15
      • type: recall_at_5 value: 37.208999999999996
    • task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics:
      • type: map_at_1 value: 18.279
      • type: map_at_10 value: 31.052999999999997
      • type: map_at_100 value: 33.125
      • type: map_at_1000 value: 33.306000000000004
      • type: map_at_3 value: 26.208
      • type: map_at_5 value: 28.857
      • type: mrr_at_1 value: 42.671
      • type: mrr_at_10 value: 54.557
      • type: mrr_at_100 value: 55.142
      • type: mrr_at_1000 value: 55.169000000000004
      • type: mrr_at_3 value: 51.488
      • type: mrr_at_5 value: 53.439
      • type: ndcg_at_1 value: 42.671
      • type: ndcg_at_10 value: 41.276
      • type: ndcg_at_100 value: 48.376000000000005
      • type: ndcg_at_1000 value: 51.318
      • type: ndcg_at_3 value: 35.068
      • type: ndcg_at_5 value: 37.242
      • type: precision_at_1 value: 42.671
      • type: precision_at_10 value: 12.638
      • type: precision_at_100 value: 2.045
      • type: precision_at_1000 value: 0.26
      • type: precision_at_3 value: 26.08
      • type: precision_at_5 value: 19.805
      • type: recall_at_1 value: 18.279
      • type: recall_at_10 value: 46.946
      • type: recall_at_100 value: 70.97200000000001
      • type: recall_at_1000 value: 87.107
      • type: recall_at_3 value: 31.147999999999996
      • type: recall_at_5 value: 38.099
    • task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics:
      • type: map_at_1 value: 8.573
      • type: map_at_10 value: 19.747
      • type: map_at_100 value: 28.205000000000002
      • type: map_at_1000 value: 29.831000000000003
      • type: map_at_3 value: 14.109
      • type: map_at_5 value: 16.448999999999998
      • type: mrr_at_1 value: 71
      • type: mrr_at_10 value: 77.68599999999999
      • type: mrr_at_100 value: 77.995
      • type: mrr_at_1000 value: 78.00200000000001
      • type: mrr_at_3 value: 76.292
      • type: mrr_at_5 value: 77.029
      • type: ndcg_at_1 value: 59.12500000000001
      • type: ndcg_at_10 value: 43.9
      • type: ndcg_at_100 value: 47.863
      • type: ndcg_at_1000 value: 54.848
      • type: ndcg_at_3 value: 49.803999999999995
      • type: ndcg_at_5 value: 46.317
      • type: precision_at_1 value: 71
      • type: precision_at_10 value: 34.4
      • type: precision_at_100 value: 11.063
      • type: precision_at_1000 value: 1.989
      • type: precision_at_3 value: 52.333
      • type: precision_at_5 value: 43.7
      • type: recall_at_1 value: 8.573
      • type: recall_at_10 value: 25.615
      • type: recall_at_100 value: 53.385000000000005
      • type: recall_at_1000 value: 75.46000000000001
      • type: recall_at_3 value: 15.429
      • type: recall_at_5 value: 19.357
    • task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics:
      • type: accuracy value: 47.989999999999995
      • type: f1 value: 42.776314451497555
    • task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics:
      • type: map_at_1 value: 74.13499999999999
      • type: map_at_10 value: 82.825
      • type: map_at_100 value: 83.096
      • type: map_at_1000 value: 83.111
      • type: map_at_3 value: 81.748
      • type: map_at_5 value: 82.446
      • type: mrr_at_1 value: 79.553
      • type: mrr_at_10 value: 86.654
      • type: mrr_at_100 value: 86.774
      • type: mrr_at_1000 value: 86.778
      • type: mrr_at_3 value: 85.981
      • type: mrr_at_5 value: 86.462
      • type: ndcg_at_1 value: 79.553
      • type: ndcg_at_10 value: 86.345
      • type: ndcg_at_100 value: 87.32
      • type: ndcg_at_1000 value: 87.58200000000001
      • type: ndcg_at_3 value: 84.719
      • type: ndcg_at_5 value: 85.677
      • type: precision_at_1 value: 79.553
      • type: precision_at_10 value: 10.402000000000001
      • type: precision_at_100 value: 1.1119999999999999
      • type: precision_at_1000 value: 0.11499999999999999
      • type: precision_at_3 value: 32.413
      • type: precision_at_5 value: 20.138
      • type: recall_at_1 value: 74.13499999999999
      • type: recall_at_10 value: 93.215
      • type: recall_at_100 value: 97.083
      • type: recall_at_1000 value: 98.732
      • type: recall_at_3 value: 88.79
      • type: recall_at_5 value: 91.259
    • task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics:
      • type: map_at_1 value: 18.298000000000002
      • type: map_at_10 value: 29.901
      • type: map_at_100 value: 31.528
      • type: map_at_1000 value: 31.713
      • type: map_at_3 value: 25.740000000000002
      • type: map_at_5 value: 28.227999999999998
      • type: mrr_at_1 value: 36.728
      • type: mrr_at_10 value: 45.401
      • type: mrr_at_100 value: 46.27
      • type: mrr_at_1000 value: 46.315
      • type: mrr_at_3 value: 42.978
      • type: mrr_at_5 value: 44.29
      • type: ndcg_at_1 value: 36.728
      • type: ndcg_at_10 value: 37.456
      • type: ndcg_at_100 value: 43.832
      • type: ndcg_at_1000 value: 47
      • type: ndcg_at_3 value: 33.694
      • type: ndcg_at_5 value: 35.085
      • type: precision_at_1 value: 36.728
      • type: precision_at_10 value: 10.386
      • type: precision_at_100 value: 1.701
      • type: precision_at_1000 value: 0.22599999999999998
      • type: precision_at_3 value: 22.479
      • type: precision_at_5 value: 16.605
      • type: recall_at_1 value: 18.298000000000002
      • type: recall_at_10 value: 44.369
      • type: recall_at_100 value: 68.098
      • type: recall_at_1000 value: 87.21900000000001
      • type: recall_at_3 value: 30.215999999999998
      • type: recall_at_5 value: 36.861
    • task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics:
      • type: map_at_1 value: 39.568
      • type: map_at_10 value: 65.061
      • type: map_at_100 value: 65.896
      • type: map_at_1000 value: 65.95100000000001
      • type: map_at_3 value: 61.831
      • type: map_at_5 value: 63.849000000000004
      • type: mrr_at_1 value: 79.136
      • type: mrr_at_10 value: 84.58200000000001
      • type: mrr_at_100 value: 84.765
      • type: mrr_at_1000 value: 84.772
      • type: mrr_at_3 value: 83.684
      • type: mrr_at_5 value: 84.223
      • type: ndcg_at_1 value: 79.136
      • type: ndcg_at_10 value: 72.622
      • type: ndcg_at_100 value: 75.539
      • type: ndcg_at_1000 value: 76.613
      • type: ndcg_at_3 value: 68.065
      • type: ndcg_at_5 value: 70.58
      • type: precision_at_1 value: 79.136
      • type: precision_at_10 value: 15.215
      • type: precision_at_100 value: 1.7500000000000002
      • type: precision_at_1000 value: 0.189
      • type: precision_at_3 value: 44.011
      • type: precision_at_5 value: 28.388999999999996
      • type: recall_at_1 value: 39.568
      • type: recall_at_10 value: 76.077
      • type: recall_at_100 value: 87.481
      • type: recall_at_1000 value: 94.56400000000001
      • type: recall_at_3 value: 66.01599999999999
      • type: recall_at_5 value: 70.97200000000001
    • task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics:
      • type: accuracy value: 85.312
      • type: ap value: 80.36296867333715
      • type: f1 value: 85.26613311552218
    • task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics:
      • type: map_at_1 value: 23.363999999999997
      • type: map_at_10 value: 35.711999999999996
      • type: map_at_100 value: 36.876999999999995
      • type: map_at_1000 value: 36.923
      • type: map_at_3 value: 32.034
      • type: map_at_5 value: 34.159
      • type: mrr_at_1 value: 24.04
      • type: mrr_at_10 value: 36.345
      • type: mrr_at_100 value: 37.441
      • type: mrr_at_1000 value: 37.480000000000004
      • type: mrr_at_3 value: 32.713
      • type: mrr_at_5 value: 34.824
      • type: ndcg_at_1 value: 24.026
      • type: ndcg_at_10 value: 42.531
      • type: ndcg_at_100 value: 48.081
      • type: ndcg_at_1000 value: 49.213
      • type: ndcg_at_3 value: 35.044
      • type: ndcg_at_5 value: 38.834
      • type: precision_at_1 value: 24.026
      • type: precision_at_10 value: 6.622999999999999
      • type: precision_at_100 value: 0.941
      • type: precision_at_1000 value: 0.104
      • type: precision_at_3 value: 14.909
      • type: precision_at_5 value: 10.871
      • type: recall_at_1 value: 23.363999999999997
      • type: recall_at_10 value: 63.426
      • type: recall_at_100 value: 88.96300000000001
      • type: recall_at_1000 value: 97.637
      • type: recall_at_3 value: 43.095
      • type: recall_at_5 value: 52.178000000000004
    • task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
      • type: accuracy value: 93.0095759233926
      • type: f1 value: 92.78387794667408
    • task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
      • type: accuracy value: 75.0296397628819
      • type: f1 value: 58.45699589820874
    • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
      • type: accuracy value: 73.45662407531944
      • type: f1 value: 71.42364781421813
    • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
      • type: accuracy value: 77.07800941492937
      • type: f1 value: 77.22799045640845
    • task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics:
      • type: v_measure value: 34.531234379250606
    • task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics:
      • type: v_measure value: 30.941490381193802
    • task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics:
      • type: map value: 30.3115090856725
      • type: mrr value: 31.290667638675757
    • task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics:
      • type: map_at_1 value: 5.465
      • type: map_at_10 value: 13.03
      • type: map_at_100 value: 16.057
      • type: map_at_1000 value: 17.49
      • type: map_at_3 value: 9.553
      • type: map_at_5 value: 11.204
      • type: mrr_at_1 value: 43.653
      • type: mrr_at_10 value: 53.269
      • type: mrr_at_100 value: 53.72
      • type: mrr_at_1000 value: 53.761
      • type: mrr_at_3 value: 50.929
      • type: mrr_at_5 value: 52.461
      • type: ndcg_at_1 value: 42.26
      • type: ndcg_at_10 value: 34.673
      • type: ndcg_at_100 value: 30.759999999999998
      • type: ndcg_at_1000 value: 39.728
      • type: ndcg_at_3 value: 40.349000000000004
      • type: ndcg_at_5 value: 37.915
      • type: precision_at_1 value: 43.653
      • type: precision_at_10 value: 25.789
      • type: precision_at_100 value: 7.754999999999999
      • type: precision_at_1000 value: 2.07
      • type: precision_at_3 value: 38.596000000000004
      • type: precision_at_5 value: 33.251
      • type: recall_at_1 value: 5.465
      • type: recall_at_10 value: 17.148
      • type: recall_at_100 value: 29.768
      • type: recall_at_1000 value: 62.239
      • type: recall_at_3 value: 10.577
      • type: recall_at_5 value: 13.315
    • task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics:
      • type: map_at_1 value: 37.008
      • type: map_at_10 value: 52.467
      • type: map_at_100 value: 53.342999999999996
      • type: map_at_1000 value: 53.366
      • type: map_at_3 value: 48.412
      • type: map_at_5 value: 50.875
      • type: mrr_at_1 value: 41.541
      • type: mrr_at_10 value: 54.967
      • type: mrr_at_100 value: 55.611
      • type: mrr_at_1000 value: 55.627
      • type: mrr_at_3 value: 51.824999999999996
      • type: mrr_at_5 value: 53.763000000000005
      • type: ndcg_at_1 value: 41.541
      • type: ndcg_at_10 value: 59.724999999999994
      • type: ndcg_at_100 value: 63.38700000000001
      • type: ndcg_at_1000 value: 63.883
      • type: ndcg_at_3 value: 52.331
      • type: ndcg_at_5 value: 56.327000000000005
      • type: precision_at_1 value: 41.541
      • type: precision_at_10 value: 9.447
      • type: precision_at_100 value: 1.1520000000000001
      • type: precision_at_1000 value: 0.12
      • type: precision_at_3 value: 23.262
      • type: precision_at_5 value: 16.314999999999998
      • type: recall_at_1 value: 37.008
      • type: recall_at_10 value: 79.145
      • type: recall_at_100 value: 94.986
      • type: recall_at_1000 value: 98.607
      • type: recall_at_3 value: 60.277
      • type: recall_at_5 value: 69.407
    • task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 70.402
      • type: map_at_10 value: 84.181
      • type: map_at_100 value: 84.796
      • type: map_at_1000 value: 84.81400000000001
      • type: map_at_3 value: 81.209
      • type: map_at_5 value: 83.085
      • type: mrr_at_1 value: 81.02000000000001
      • type: mrr_at_10 value: 87.263
      • type: mrr_at_100 value: 87.36
      • type: mrr_at_1000 value: 87.36
      • type: mrr_at_3 value: 86.235
      • type: mrr_at_5 value: 86.945
      • type: ndcg_at_1 value: 81.01
      • type: ndcg_at_10 value: 87.99900000000001
      • type: ndcg_at_100 value: 89.217
      • type: ndcg_at_1000 value: 89.33
      • type: ndcg_at_3 value: 85.053
      • type: ndcg_at_5 value: 86.703
      • type: precision_at_1 value: 81.01
      • type: precision_at_10 value: 13.336
      • type: precision_at_100 value: 1.52
      • type: precision_at_1000 value: 0.156
      • type: precision_at_3 value: 37.14
      • type: precision_at_5 value: 24.44
      • type: recall_at_1 value: 70.402
      • type: recall_at_10 value: 95.214
      • type: recall_at_100 value: 99.438
      • type: recall_at_1000 value: 99.928
      • type: recall_at_3 value: 86.75699999999999
      • type: recall_at_5 value: 91.44099999999999
    • task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics:
      • type: v_measure value: 56.51721502758904
    • task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics:
      • type: v_measure value: 61.054808572333016
    • task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics:
      • type: map_at_1 value: 4.578
      • type: map_at_10 value: 11.036999999999999
      • type: map_at_100 value: 12.879999999999999
      • type: map_at_1000 value: 13.150999999999998
      • type: map_at_3 value: 8.133
      • type: map_at_5 value: 9.559
      • type: mrr_at_1 value: 22.6
      • type: mrr_at_10 value: 32.68
      • type: mrr_at_100 value: 33.789
      • type: mrr_at_1000 value: 33.854
      • type: mrr_at_3 value: 29.7
      • type: mrr_at_5 value: 31.480000000000004
      • type: ndcg_at_1 value: 22.6
      • type: ndcg_at_10 value: 18.616
      • type: ndcg_at_100 value: 25.883
      • type: ndcg_at_1000 value: 30.944
      • type: ndcg_at_3 value: 18.136
      • type: ndcg_at_5 value: 15.625
      • type: precision_at_1 value: 22.6
      • type: precision_at_10 value: 9.48
      • type: precision_at_100 value: 1.991
      • type: precision_at_1000 value: 0.321
      • type: precision_at_3 value: 16.8
      • type: precision_at_5 value: 13.54
      • type: recall_at_1 value: 4.578
      • type: recall_at_10 value: 19.213
      • type: recall_at_100 value: 40.397
      • type: recall_at_1000 value: 65.2
      • type: recall_at_3 value: 10.208
      • type: recall_at_5 value: 13.718
    • task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics:
      • type: cos_sim_pearson value: 83.44288351714071
      • type: cos_sim_spearman value: 79.37995604564952
      • type: euclidean_pearson value: 81.1078874670718
      • type: euclidean_spearman value: 79.37995905980499
      • type: manhattan_pearson value: 81.03697527288986
      • type: manhattan_spearman value: 79.33490235296236
    • task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics:
      • type: cos_sim_pearson value: 84.95557650436523
      • type: cos_sim_spearman value: 78.5190672399868
      • type: euclidean_pearson value: 81.58064025904707
      • type: euclidean_spearman value: 78.5190672399868
      • type: manhattan_pearson value: 81.52857930619889
      • type: manhattan_spearman value: 78.50421361308034
    • task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics:
      • type: cos_sim_pearson value: 84.79128416228737
      • type: cos_sim_spearman value: 86.05402451477147
      • type: euclidean_pearson value: 85.46280267054289
      • type: euclidean_spearman value: 86.05402451477147
      • type: manhattan_pearson value: 85.46278563858236
      • type: manhattan_spearman value: 86.08079590861004
    • task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics:
      • type: cos_sim_pearson value: 83.20623089568763
      • type: cos_sim_spearman value: 81.53786907061009
      • type: euclidean_pearson value: 82.82272250091494
      • type: euclidean_spearman value: 81.53786907061009
      • type: manhattan_pearson value: 82.78850494027013
      • type: manhattan_spearman value: 81.5135618083407
    • task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics:
      • type: cos_sim_pearson value: 85.46366618397936
      • type: cos_sim_spearman value: 86.96566013336908
      • type: euclidean_pearson value: 86.62651697548931
      • type: euclidean_spearman value: 86.96565526364454
      • type: manhattan_pearson value: 86.58812160258009
      • type: manhattan_spearman value: 86.9336484321288
    • task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics:
      • type: cos_sim_pearson value: 82.51858358641559
      • type: cos_sim_spearman value: 84.7652527954999
      • type: euclidean_pearson value: 84.23914783766861
      • type: euclidean_spearman value: 84.7652527954999
      • type: manhattan_pearson value: 84.22749648503171
      • type: manhattan_spearman value: 84.74527996746386
    • 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: 87.28026563313065
      • type: cos_sim_spearman value: 87.46928143824915
      • type: euclidean_pearson value: 88.30558762000372
      • type: euclidean_spearman value: 87.46928143824915
      • type: manhattan_pearson value: 88.10513330809331
      • type: manhattan_spearman value: 87.21069787834173
    • 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: 62.376497134587375
      • type: cos_sim_spearman value: 65.0159550112516
      • type: euclidean_pearson value: 65.64572120879598
      • type: euclidean_spearman value: 65.0159550112516
      • type: manhattan_pearson value: 65.88143604989976
      • type: manhattan_spearman value: 65.17547297222434
    • task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics:
      • type: cos_sim_pearson value: 84.22876368947644
      • type: cos_sim_spearman value: 85.46935577445318
      • type: euclidean_pearson value: 85.32830231392005
      • type: euclidean_spearman value: 85.46935577445318
      • type: manhattan_pearson value: 85.30353211758495
      • type: manhattan_spearman value: 85.42821085956945
    • task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics:
      • type: map value: 80.60986667767133
      • type: mrr value: 94.29432314236236
    • task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics:
      • type: map_at_1 value: 54.528
      • type: map_at_10 value: 65.187
      • type: map_at_100 value: 65.62599999999999
      • type: map_at_1000 value: 65.657
      • type: map_at_3 value: 62.352
      • type: map_at_5 value: 64.025
      • type: mrr_at_1 value: 57.333
      • type: mrr_at_10 value: 66.577
      • type: mrr_at_100 value: 66.88
      • type: mrr_at_1000 value: 66.908
      • type: mrr_at_3 value: 64.556
      • type: mrr_at_5 value: 65.739
      • type: ndcg_at_1 value: 57.333
      • type: ndcg_at_10 value: 70.275
      • type: ndcg_at_100 value: 72.136
      • type: ndcg_at_1000 value: 72.963
      • type: ndcg_at_3 value: 65.414
      • type: ndcg_at_5 value: 67.831
      • type: precision_at_1 value: 57.333
      • type: precision_at_10 value: 9.5
      • type: precision_at_100 value: 1.057
      • type: precision_at_1000 value: 0.11199999999999999
      • type: precision_at_3 value: 25.778000000000002
      • type: precision_at_5 value: 17.2
      • type: recall_at_1 value: 54.528
      • type: recall_at_10 value: 84.356
      • type: recall_at_100 value: 92.833
      • type: recall_at_1000 value: 99.333
      • type: recall_at_3 value: 71.283
      • type: recall_at_5 value: 77.14999999999999
    • task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics:
      • type: cos_sim_accuracy value: 99.74158415841585
      • type: cos_sim_ap value: 92.90048959850317
      • type: cos_sim_f1 value: 86.35650810245687
      • type: cos_sim_precision value: 90.4709748083242
      • type: cos_sim_recall value: 82.6
      • type: dot_accuracy value: 99.74158415841585
      • type: dot_ap value: 92.90048959850317
      • type: dot_f1 value: 86.35650810245687
      • type: dot_precision value: 90.4709748083242
      • type: dot_recall value: 82.6
      • type: euclidean_accuracy value: 99.74158415841585
      • type: euclidean_ap value: 92.90048959850317
      • type: euclidean_f1 value: 86.35650810245687
      • type: euclidean_precision value: 90.4709748083242
      • type: euclidean_recall value: 82.6
      • type: manhattan_accuracy value: 99.74158415841585
      • type: manhattan_ap value: 92.87344692947894
      • type: manhattan_f1 value: 86.38497652582159
      • type: manhattan_precision value: 90.29443838604145
      • type: manhattan_recall value: 82.8
      • type: max_accuracy value: 99.74158415841585
      • type: max_ap value: 92.90048959850317
      • type: max_f1 value: 86.38497652582159
    • task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics:
      • type: v_measure value: 63.191648770424216
    • task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics:
      • type: v_measure value: 34.02944668730218
    • task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics:
      • type: map value: 50.466386167525265
      • type: mrr value: 51.19071492233257
    • task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics:
      • type: cos_sim_pearson value: 30.198022505886435
      • type: cos_sim_spearman value: 30.40170257939193
      • type: dot_pearson value: 30.198015316402614
      • type: dot_spearman value: 30.40170257939193
    • task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics:
      • type: map_at_1 value: 0.242
      • type: map_at_10 value: 2.17
      • type: map_at_100 value: 12.221
      • type: map_at_1000 value: 28.63
      • type: map_at_3 value: 0.728
      • type: map_at_5 value: 1.185
      • type: mrr_at_1 value: 94
      • type: mrr_at_10 value: 97
      • type: mrr_at_100 value: 97
      • type: mrr_at_1000 value: 97
      • type: mrr_at_3 value: 97
      • type: mrr_at_5 value: 97
      • type: ndcg_at_1 value: 89
      • type: ndcg_at_10 value: 82.30499999999999
      • type: ndcg_at_100 value: 61.839999999999996
      • type: ndcg_at_1000 value: 53.381
      • type: ndcg_at_3 value: 88.877
      • type: ndcg_at_5 value: 86.05199999999999
      • type: precision_at_1 value: 94
      • type: precision_at_10 value: 87
      • type: precision_at_100 value: 63.38
      • type: precision_at_1000 value: 23.498
      • type: precision_at_3 value: 94
      • type: precision_at_5 value: 92
      • type: recall_at_1 value: 0.242
      • type: recall_at_10 value: 2.302
      • type: recall_at_100 value: 14.979000000000001
      • type: recall_at_1000 value: 49.638
      • type: recall_at_3 value: 0.753
      • type: recall_at_5 value: 1.226
    • task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics:
      • type: map_at_1 value: 3.006
      • type: map_at_10 value: 11.805
      • type: map_at_100 value: 18.146
      • type: map_at_1000 value: 19.788
      • type: map_at_3 value: 5.914
      • type: map_at_5 value: 8.801
      • type: mrr_at_1 value: 40.816
      • type: mrr_at_10 value: 56.36600000000001
      • type: mrr_at_100 value: 56.721999999999994
      • type: mrr_at_1000 value: 56.721999999999994
      • type: mrr_at_3 value: 52.041000000000004
      • type: mrr_at_5 value: 54.796
      • type: ndcg_at_1 value: 37.755
      • type: ndcg_at_10 value: 29.863
      • type: ndcg_at_100 value: 39.571
      • type: ndcg_at_1000 value: 51.385999999999996
      • type: ndcg_at_3 value: 32.578
      • type: ndcg_at_5 value: 32.351
      • type: precision_at_1 value: 40.816
      • type: precision_at_10 value: 26.531
      • type: precision_at_100 value: 7.796
      • type: precision_at_1000 value: 1.555
      • type: precision_at_3 value: 32.653
      • type: precision_at_5 value: 33.061
      • type: recall_at_1 value: 3.006
      • type: recall_at_10 value: 18.738
      • type: recall_at_100 value: 48.058
      • type: recall_at_1000 value: 83.41300000000001
      • type: recall_at_3 value: 7.166
      • type: recall_at_5 value: 12.102
    • task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics:
      • type: accuracy value: 71.4178
      • type: ap value: 14.648781342150446
      • type: f1 value: 55.07299194946378
    • task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics:
      • type: accuracy value: 60.919637804187886
      • type: f1 value: 61.24122013967399
    • task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics:
      • type: v_measure value: 49.207896583685695
    • task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics:
      • type: cos_sim_accuracy value: 86.23114978840078
      • type: cos_sim_ap value: 74.26624727825818
      • type: cos_sim_f1 value: 68.72377190817083
      • type: cos_sim_precision value: 64.56400742115028
      • type: cos_sim_recall value: 73.45646437994723
      • type: dot_accuracy value: 86.23114978840078
      • type: dot_ap value: 74.26624032659652
      • type: dot_f1 value: 68.72377190817083
      • type: dot_precision value: 64.56400742115028
      • type: dot_recall value: 73.45646437994723
      • type: euclidean_accuracy value: 86.23114978840078
      • type: euclidean_ap value: 74.26624714480556
      • type: euclidean_f1 value: 68.72377190817083
      • type: euclidean_precision value: 64.56400742115028
      • type: euclidean_recall value: 73.45646437994723
      • type: manhattan_accuracy value: 86.16558383501221
      • type: manhattan_ap value: 74.2091943976357
      • type: manhattan_f1 value: 68.64221520524654
      • type: manhattan_precision value: 63.59135913591359
      • type: manhattan_recall value: 74.5646437994723
      • type: max_accuracy value: 86.23114978840078
      • type: max_ap value: 74.26624727825818
      • type: max_f1 value: 68.72377190817083
    • task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics:
      • type: cos_sim_accuracy value: 89.3681841114604
      • type: cos_sim_ap value: 86.65166387498546
      • type: cos_sim_f1 value: 79.02581944698774
      • type: cos_sim_precision value: 75.35796605434099
      • type: cos_sim_recall value: 83.06898675700647
      • type: dot_accuracy value: 89.3681841114604
      • type: dot_ap value: 86.65166019802056
      • type: dot_f1 value: 79.02581944698774
      • type: dot_precision value: 75.35796605434099
      • type: dot_recall value: 83.06898675700647
      • type: euclidean_accuracy value: 89.3681841114604
      • type: euclidean_ap value: 86.65166462876266
      • type: euclidean_f1 value: 79.02581944698774
      • type: euclidean_precision value: 75.35796605434099
      • type: euclidean_recall value: 83.06898675700647
      • type: manhattan_accuracy value: 89.36624364497226
      • type: manhattan_ap value: 86.65076471274106
      • type: manhattan_f1 value: 79.07408783532733
      • type: manhattan_precision value: 76.41102972856527
      • type: manhattan_recall value: 81.92947336002464
      • type: max_accuracy value: 89.3681841114604
      • type: max_ap value: 86.65166462876266
      • type: max_f1 value: 79.07408783532733 license: apache-2.0 language:
  • en

BASF-AI/nomic-embed-text-v1.5

作者 BASF-AI

sentence-similarity sentence-transformers
↓ 118 ♥ 0

创建时间: 2025-01-10 00:04:58+00:00

更新时间: 2025-01-10 04:53:06+00:00

在 Hugging Face 上查看

文件 (14)

.gitattributes
1_Pooling/config.json
README.md
config.json
config_sentence_transformers.json
model.safetensors
modules.json
onnx/model.onnx ONNX
onnx/model_quantized.onnx ONNX
sentence_bert_config.json
special_tokens_map.json
tokenizer.json
tokenizer_config.json
vocab.txt