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jina-embeddings-v2-small-en

Feature Extraction
sentence-transformers
PyTorch
Core ML
ONNX
Safetensors
English
bert
sentence-similarity
mteb
custom_code
Eval Results
text-embeddings-inference
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pipeline_tag: sentence-similarity tags:

  • finetuner
  • sentence-transformers
  • feature-extraction
  • sentence-similarity
  • mteb datasets:
  • jinaai/negation-dataset language: en license: apache-2.0 model-index:
  • name: jina-embedding-s-en-v2 results:
    • task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics:
      • type: accuracy value: 69.70149253731343
      • type: ap value: 32.22528779918184
      • type: f1 value: 63.66857824618267
    • task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics:
      • type: accuracy value: 79.55879999999999
      • type: ap value: 73.97885664972738
      • type: f1 value: 79.4849322624122
    • task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics:
      • type: accuracy value: 38.69
      • type: f1 value: 37.17512734389121
    • task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics:
      • type: map_at_1 value: 23.684
      • type: map_at_10 value: 39.086999999999996
      • type: map_at_100 value: 40.222
      • type: map_at_1000 value: 40.231
      • type: map_at_3 value: 34.282000000000004
      • type: map_at_5 value: 36.689
      • type: mrr_at_1 value: 23.826
      • type: mrr_at_10 value: 39.147
      • type: mrr_at_100 value: 40.282000000000004
      • type: mrr_at_1000 value: 40.291
      • type: mrr_at_3 value: 34.353
      • type: mrr_at_5 value: 36.739
      • type: ndcg_at_1 value: 23.684
      • type: ndcg_at_10 value: 48.081
      • type: ndcg_at_100 value: 52.902
      • type: ndcg_at_1000 value: 53.111
      • type: ndcg_at_3 value: 37.937
      • type: ndcg_at_5 value: 42.32
      • type: precision_at_1 value: 23.684
      • type: precision_at_10 value: 7.703
      • type: precision_at_100 value: 0.98
      • type: precision_at_1000 value: 0.1
      • type: precision_at_3 value: 16.192999999999998
      • type: precision_at_5 value: 11.863
      • type: recall_at_1 value: 23.684
      • type: recall_at_10 value: 77.027
      • type: recall_at_100 value: 98.009
      • type: recall_at_1000 value: 99.57300000000001
      • type: recall_at_3 value: 48.577999999999996
      • type: recall_at_5 value: 59.317
    • task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics:
      • type: v_measure value: 44.249612940073035
    • task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics:
      • type: v_measure value: 35.39423011105325
    • task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics:
      • type: map value: 59.89078304869791
      • type: mrr value: 73.5045948203843
    • task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics:
      • type: cos_sim_pearson value: 82.49373811125967
      • type: cos_sim_spearman value: 81.0446177409314
      • type: euclidean_pearson value: 82.1327844624042
      • type: euclidean_spearman value: 81.0446177409314
      • type: manhattan_pearson value: 81.88575541723692
      • type: manhattan_spearman value: 81.0705219456341
    • task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics:
      • type: accuracy value: 78.27272727272728
      • type: f1 value: 77.36583416688741
    • task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics:
      • type: v_measure value: 36.12447585258704
    • task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics:
      • type: v_measure value: 29.305990951348743
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 31.458000000000002
      • type: map_at_10 value: 42.132
      • type: map_at_100 value: 43.47
      • type: map_at_1000 value: 43.612
      • type: map_at_3 value: 38.718
      • type: map_at_5 value: 40.556
      • type: mrr_at_1 value: 38.627
      • type: mrr_at_10 value: 47.998000000000005
      • type: mrr_at_100 value: 48.726
      • type: mrr_at_1000 value: 48.778
      • type: mrr_at_3 value: 45.255
      • type: mrr_at_5 value: 46.893
      • type: ndcg_at_1 value: 38.627
      • type: ndcg_at_10 value: 48.229
      • type: ndcg_at_100 value: 53.108999999999995
      • type: ndcg_at_1000 value: 55.385
      • type: ndcg_at_3 value: 43.191
      • type: ndcg_at_5 value: 45.385999999999996
      • type: precision_at_1 value: 38.627
      • type: precision_at_10 value: 9.142
      • type: precision_at_100 value: 1.462
      • type: precision_at_1000 value: 0.19499999999999998
      • type: precision_at_3 value: 20.552999999999997
      • type: precision_at_5 value: 14.677999999999999
      • type: recall_at_1 value: 31.458000000000002
      • type: recall_at_10 value: 59.619
      • type: recall_at_100 value: 79.953
      • type: recall_at_1000 value: 94.921
      • type: recall_at_3 value: 44.744
      • type: recall_at_5 value: 51.010999999999996
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 26.762000000000004
      • type: map_at_10 value: 35.366
      • type: map_at_100 value: 36.481
      • type: map_at_1000 value: 36.614999999999995
      • type: map_at_3 value: 33.071
      • type: map_at_5 value: 34.495
      • type: mrr_at_1 value: 33.312000000000005
      • type: mrr_at_10 value: 40.841
      • type: mrr_at_100 value: 41.54
      • type: mrr_at_1000 value: 41.592
      • type: mrr_at_3 value: 38.928000000000004
      • type: mrr_at_5 value: 40.119
      • type: ndcg_at_1 value: 33.312000000000005
      • type: ndcg_at_10 value: 40.238
      • type: ndcg_at_100 value: 44.647
      • type: ndcg_at_1000 value: 47.010999999999996
      • type: ndcg_at_3 value: 36.991
      • type: ndcg_at_5 value: 38.721
      • type: precision_at_1 value: 33.312000000000005
      • type: precision_at_10 value: 7.4079999999999995
      • type: precision_at_100 value: 1.253
      • type: precision_at_1000 value: 0.17500000000000002
      • type: precision_at_3 value: 17.898
      • type: precision_at_5 value: 12.687999999999999
      • type: recall_at_1 value: 26.762000000000004
      • type: recall_at_10 value: 48.41
      • type: recall_at_100 value: 67.523
      • type: recall_at_1000 value: 82.91199999999999
      • type: recall_at_3 value: 38.6
      • type: recall_at_5 value: 43.477
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 37.578
      • type: map_at_10 value: 49.415
      • type: map_at_100 value: 50.339
      • type: map_at_1000 value: 50.402
      • type: map_at_3 value: 46.412
      • type: map_at_5 value: 48.183
      • type: mrr_at_1 value: 43.072
      • type: mrr_at_10 value: 52.82599999999999
      • type: mrr_at_100 value: 53.456
      • type: mrr_at_1000 value: 53.493
      • type: mrr_at_3 value: 50.407999999999994
      • type: mrr_at_5 value: 51.922000000000004
      • type: ndcg_at_1 value: 43.072
      • type: ndcg_at_10 value: 54.949000000000005
      • type: ndcg_at_100 value: 58.744
      • type: ndcg_at_1000 value: 60.150000000000006
      • type: ndcg_at_3 value: 49.864000000000004
      • type: ndcg_at_5 value: 52.503
      • type: precision_at_1 value: 43.072
      • type: precision_at_10 value: 8.734
      • type: precision_at_100 value: 1.1520000000000001
      • type: precision_at_1000 value: 0.132
      • type: precision_at_3 value: 22.131999999999998
      • type: precision_at_5 value: 15.21
      • type: recall_at_1 value: 37.578
      • type: recall_at_10 value: 67.918
      • type: recall_at_100 value: 84.373
      • type: recall_at_1000 value: 94.529
      • type: recall_at_3 value: 54.457
      • type: recall_at_5 value: 60.941
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 23.394000000000002
      • type: map_at_10 value: 31.791000000000004
      • type: map_at_100 value: 32.64
      • type: map_at_1000 value: 32.727000000000004
      • type: map_at_3 value: 29.557
      • type: map_at_5 value: 30.858999999999998
      • type: mrr_at_1 value: 25.085
      • type: mrr_at_10 value: 33.721000000000004
      • type: mrr_at_100 value: 34.492
      • type: mrr_at_1000 value: 34.564
      • type: mrr_at_3 value: 31.619999999999997
      • type: mrr_at_5 value: 32.896
      • type: ndcg_at_1 value: 25.085
      • type: ndcg_at_10 value: 36.370000000000005
      • type: ndcg_at_100 value: 40.96
      • type: ndcg_at_1000 value: 43.171
      • type: ndcg_at_3 value: 32.104
      • type: ndcg_at_5 value: 34.300000000000004
      • type: precision_at_1 value: 25.085
      • type: precision_at_10 value: 5.537
      • type: precision_at_100 value: 0.8340000000000001
      • type: precision_at_1000 value: 0.105
      • type: precision_at_3 value: 13.71
      • type: precision_at_5 value: 9.514
      • type: recall_at_1 value: 23.394000000000002
      • type: recall_at_10 value: 48.549
      • type: recall_at_100 value: 70.341
      • type: recall_at_1000 value: 87.01299999999999
      • type: recall_at_3 value: 36.947
      • type: recall_at_5 value: 42.365
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 14.818000000000001
      • type: map_at_10 value: 21.773999999999997
      • type: map_at_100 value: 22.787
      • type: map_at_1000 value: 22.915
      • type: map_at_3 value: 19.414
      • type: map_at_5 value: 20.651
      • type: mrr_at_1 value: 18.657
      • type: mrr_at_10 value: 25.794
      • type: mrr_at_100 value: 26.695999999999998
      • type: mrr_at_1000 value: 26.776
      • type: mrr_at_3 value: 23.279
      • type: mrr_at_5 value: 24.598
      • type: ndcg_at_1 value: 18.657
      • type: ndcg_at_10 value: 26.511000000000003
      • type: ndcg_at_100 value: 31.447999999999997
      • type: ndcg_at_1000 value: 34.71
      • type: ndcg_at_3 value: 21.92
      • type: ndcg_at_5 value: 23.938000000000002
      • type: precision_at_1 value: 18.657
      • type: precision_at_10 value: 4.9
      • type: precision_at_100 value: 0.851
      • type: precision_at_1000 value: 0.127
      • type: precision_at_3 value: 10.488999999999999
      • type: precision_at_5 value: 7.710999999999999
      • type: recall_at_1 value: 14.818000000000001
      • type: recall_at_10 value: 37.408
      • type: recall_at_100 value: 58.81999999999999
      • type: recall_at_1000 value: 82.612
      • type: recall_at_3 value: 24.561
      • type: recall_at_5 value: 29.685
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 26.332
      • type: map_at_10 value: 35.366
      • type: map_at_100 value: 36.569
      • type: map_at_1000 value: 36.689
      • type: map_at_3 value: 32.582
      • type: map_at_5 value: 34.184
      • type: mrr_at_1 value: 32.05
      • type: mrr_at_10 value: 40.902
      • type: mrr_at_100 value: 41.754000000000005
      • type: mrr_at_1000 value: 41.811
      • type: mrr_at_3 value: 38.547
      • type: mrr_at_5 value: 40.019
      • type: ndcg_at_1 value: 32.05
      • type: ndcg_at_10 value: 40.999
      • type: ndcg_at_100 value: 46.284
      • type: ndcg_at_1000 value: 48.698
      • type: ndcg_at_3 value: 36.39
      • type: ndcg_at_5 value: 38.699
      • type: precision_at_1 value: 32.05
      • type: precision_at_10 value: 7.315
      • type: precision_at_100 value: 1.172
      • type: precision_at_1000 value: 0.156
      • type: precision_at_3 value: 17.036
      • type: precision_at_5 value: 12.089
      • type: recall_at_1 value: 26.332
      • type: recall_at_10 value: 52.410000000000004
      • type: recall_at_100 value: 74.763
      • type: recall_at_1000 value: 91.03
      • type: recall_at_3 value: 39.527
      • type: recall_at_5 value: 45.517
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 22.849
      • type: map_at_10 value: 31.502000000000002
      • type: map_at_100 value: 32.854
      • type: map_at_1000 value: 32.975
      • type: map_at_3 value: 28.997
      • type: map_at_5 value: 30.508999999999997
      • type: mrr_at_1 value: 28.195999999999998
      • type: mrr_at_10 value: 36.719
      • type: mrr_at_100 value: 37.674
      • type: mrr_at_1000 value: 37.743
      • type: mrr_at_3 value: 34.532000000000004
      • type: mrr_at_5 value: 35.845
      • type: ndcg_at_1 value: 28.195999999999998
      • type: ndcg_at_10 value: 36.605
      • type: ndcg_at_100 value: 42.524
      • type: ndcg_at_1000 value: 45.171
      • type: ndcg_at_3 value: 32.574
      • type: ndcg_at_5 value: 34.617
      • type: precision_at_1 value: 28.195999999999998
      • type: precision_at_10 value: 6.598
      • type: precision_at_100 value: 1.121
      • type: precision_at_1000 value: 0.153
      • type: precision_at_3 value: 15.601
      • type: precision_at_5 value: 11.073
      • type: recall_at_1 value: 22.849
      • type: recall_at_10 value: 46.528000000000006
      • type: recall_at_100 value: 72.09
      • type: recall_at_1000 value: 90.398
      • type: recall_at_3 value: 35.116
      • type: recall_at_5 value: 40.778
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 24.319500000000005
      • type: map_at_10 value: 32.530166666666666
      • type: map_at_100 value: 33.61566666666667
      • type: map_at_1000 value: 33.73808333333333
      • type: map_at_3 value: 30.074583333333326
      • type: map_at_5 value: 31.429666666666662
      • type: mrr_at_1 value: 28.675916666666666
      • type: mrr_at_10 value: 36.49308333333334
      • type: mrr_at_100 value: 37.310583333333334
      • type: mrr_at_1000 value: 37.37616666666666
      • type: mrr_at_3 value: 34.283166666666666
      • type: mrr_at_5 value: 35.54333333333334
      • type: ndcg_at_1 value: 28.675916666666666
      • type: ndcg_at_10 value: 37.403416666666665
      • type: ndcg_at_100 value: 42.25783333333333
      • type: ndcg_at_1000 value: 44.778333333333336
      • type: ndcg_at_3 value: 33.17099999999999
      • type: ndcg_at_5 value: 35.12666666666667
      • type: precision_at_1 value: 28.675916666666666
      • type: precision_at_10 value: 6.463083333333334
      • type: precision_at_100 value: 1.0585
      • type: precision_at_1000 value: 0.14633333333333332
      • type: precision_at_3 value: 15.158999999999997
      • type: precision_at_5 value: 10.673916666666667
      • type: recall_at_1 value: 24.319500000000005
      • type: recall_at_10 value: 47.9135
      • type: recall_at_100 value: 69.40266666666666
      • type: recall_at_1000 value: 87.12566666666666
      • type: recall_at_3 value: 36.03149999999999
      • type: recall_at_5 value: 41.12791666666668
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 22.997
      • type: map_at_10 value: 28.754999999999995
      • type: map_at_100 value: 29.555999999999997
      • type: map_at_1000 value: 29.653000000000002
      • type: map_at_3 value: 27.069
      • type: map_at_5 value: 27.884999999999998
      • type: mrr_at_1 value: 25.767
      • type: mrr_at_10 value: 31.195
      • type: mrr_at_100 value: 31.964
      • type: mrr_at_1000 value: 32.039
      • type: mrr_at_3 value: 29.601
      • type: mrr_at_5 value: 30.345
      • type: ndcg_at_1 value: 25.767
      • type: ndcg_at_10 value: 32.234
      • type: ndcg_at_100 value: 36.461
      • type: ndcg_at_1000 value: 39.005
      • type: ndcg_at_3 value: 29.052
      • type: ndcg_at_5 value: 30.248
      • type: precision_at_1 value: 25.767
      • type: precision_at_10 value: 4.893
      • type: precision_at_100 value: 0.761
      • type: precision_at_1000 value: 0.105
      • type: precision_at_3 value: 12.219
      • type: precision_at_5 value: 8.19
      • type: recall_at_1 value: 22.997
      • type: recall_at_10 value: 40.652
      • type: recall_at_100 value: 60.302
      • type: recall_at_1000 value: 79.17999999999999
      • type: recall_at_3 value: 31.680999999999997
      • type: recall_at_5 value: 34.698
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 16.3
      • type: map_at_10 value: 22.581
      • type: map_at_100 value: 23.517
      • type: map_at_1000 value: 23.638
      • type: map_at_3 value: 20.567
      • type: map_at_5 value: 21.688
      • type: mrr_at_1 value: 19.683
      • type: mrr_at_10 value: 26.185000000000002
      • type: mrr_at_100 value: 27.014
      • type: mrr_at_1000 value: 27.092
      • type: mrr_at_3 value: 24.145
      • type: mrr_at_5 value: 25.308999999999997
      • type: ndcg_at_1 value: 19.683
      • type: ndcg_at_10 value: 26.699
      • type: ndcg_at_100 value: 31.35
      • type: ndcg_at_1000 value: 34.348
      • type: ndcg_at_3 value: 23.026
      • type: ndcg_at_5 value: 24.731
      • type: precision_at_1 value: 19.683
      • type: precision_at_10 value: 4.814
      • type: precision_at_100 value: 0.836
      • type: precision_at_1000 value: 0.126
      • type: precision_at_3 value: 10.782
      • type: precision_at_5 value: 7.825
      • type: recall_at_1 value: 16.3
      • type: recall_at_10 value: 35.521
      • type: recall_at_100 value: 56.665
      • type: recall_at_1000 value: 78.361
      • type: recall_at_3 value: 25.223000000000003
      • type: recall_at_5 value: 29.626
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 24.596999999999998
      • type: map_at_10 value: 32.54
      • type: map_at_100 value: 33.548
      • type: map_at_1000 value: 33.661
      • type: map_at_3 value: 30.134
      • type: map_at_5 value: 31.468
      • type: mrr_at_1 value: 28.825
      • type: mrr_at_10 value: 36.495
      • type: mrr_at_100 value: 37.329
      • type: mrr_at_1000 value: 37.397999999999996
      • type: mrr_at_3 value: 34.359
      • type: mrr_at_5 value: 35.53
      • type: ndcg_at_1 value: 28.825
      • type: ndcg_at_10 value: 37.341
      • type: ndcg_at_100 value: 42.221
      • type: ndcg_at_1000 value: 44.799
      • type: ndcg_at_3 value: 33.058
      • type: ndcg_at_5 value: 34.961999999999996
      • type: precision_at_1 value: 28.825
      • type: precision_at_10 value: 6.175
      • type: precision_at_100 value: 0.97
      • type: precision_at_1000 value: 0.13
      • type: precision_at_3 value: 14.924999999999999
      • type: precision_at_5 value: 10.392
      • type: recall_at_1 value: 24.596999999999998
      • type: recall_at_10 value: 48.067
      • type: recall_at_100 value: 69.736
      • type: recall_at_1000 value: 87.855
      • type: recall_at_3 value: 36.248999999999995
      • type: recall_at_5 value: 41.086
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 24.224999999999998
      • type: map_at_10 value: 31.826
      • type: map_at_100 value: 33.366
      • type: map_at_1000 value: 33.6
      • type: map_at_3 value: 29.353
      • type: map_at_5 value: 30.736
      • type: mrr_at_1 value: 28.656
      • type: mrr_at_10 value: 36.092
      • type: mrr_at_100 value: 37.076
      • type: mrr_at_1000 value: 37.141999999999996
      • type: mrr_at_3 value: 33.86
      • type: mrr_at_5 value: 35.144999999999996
      • type: ndcg_at_1 value: 28.656
      • type: ndcg_at_10 value: 37.025999999999996
      • type: ndcg_at_100 value: 42.844
      • type: ndcg_at_1000 value: 45.716
      • type: ndcg_at_3 value: 32.98
      • type: ndcg_at_5 value: 34.922
      • type: precision_at_1 value: 28.656
      • type: precision_at_10 value: 6.976
      • type: precision_at_100 value: 1.48
      • type: precision_at_1000 value: 0.23700000000000002
      • type: precision_at_3 value: 15.348999999999998
      • type: precision_at_5 value: 11.028
      • type: recall_at_1 value: 24.224999999999998
      • type: recall_at_10 value: 46.589999999999996
      • type: recall_at_100 value: 72.331
      • type: recall_at_1000 value: 90.891
      • type: recall_at_3 value: 34.996
      • type: recall_at_5 value: 40.294000000000004
    • task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 20.524
      • type: map_at_10 value: 27.314
      • type: map_at_100 value: 28.260999999999996
      • type: map_at_1000 value: 28.37
      • type: map_at_3 value: 25.020999999999997
      • type: map_at_5 value: 25.942
      • type: mrr_at_1 value: 22.181
      • type: mrr_at_10 value: 29.149
      • type: mrr_at_100 value: 30.006
      • type: mrr_at_1000 value: 30.086000000000002
      • type: mrr_at_3 value: 26.863999999999997
      • type: mrr_at_5 value: 27.899
      • type: ndcg_at_1 value: 22.181
      • type: ndcg_at_10 value: 31.64
      • type: ndcg_at_100 value: 36.502
      • type: ndcg_at_1000 value: 39.176
      • type: ndcg_at_3 value: 26.901999999999997
      • type: ndcg_at_5 value: 28.493000000000002
      • type: precision_at_1 value: 22.181
      • type: precision_at_10 value: 5.065
      • type: precision_at_100 value: 0.8099999999999999
      • type: precision_at_1000 value: 0.11499999999999999
      • type: precision_at_3 value: 11.214
      • type: precision_at_5 value: 7.689
      • type: recall_at_1 value: 20.524
      • type: recall_at_10 value: 43.29
      • type: recall_at_100 value: 65.935
      • type: recall_at_1000 value: 85.80600000000001
      • type: recall_at_3 value: 30.276999999999997
      • type: recall_at_5 value: 34.056999999999995
    • task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics:
      • type: map_at_1 value: 10.488999999999999
      • type: map_at_10 value: 17.98
      • type: map_at_100 value: 19.581
      • type: map_at_1000 value: 19.739
      • type: map_at_3 value: 15.054
      • type: map_at_5 value: 16.439999999999998
      • type: mrr_at_1 value: 23.192
      • type: mrr_at_10 value: 33.831
      • type: mrr_at_100 value: 34.833
      • type: mrr_at_1000 value: 34.881
      • type: mrr_at_3 value: 30.793
      • type: mrr_at_5 value: 32.535
      • type: ndcg_at_1 value: 23.192
      • type: ndcg_at_10 value: 25.446
      • type: ndcg_at_100 value: 31.948
      • type: ndcg_at_1000 value: 35.028
      • type: ndcg_at_3 value: 20.744
      • type: ndcg_at_5 value: 22.233
      • type: precision_at_1 value: 23.192
      • type: precision_at_10 value: 8.026
      • type: precision_at_100 value: 1.482
      • type: precision_at_1000 value: 0.20500000000000002
      • type: precision_at_3 value: 15.548
      • type: precision_at_5 value: 11.87
      • type: recall_at_1 value: 10.488999999999999
      • type: recall_at_10 value: 30.865
      • type: recall_at_100 value: 53.428
      • type: recall_at_1000 value: 70.89
      • type: recall_at_3 value: 19.245
      • type: recall_at_5 value: 23.657
    • task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics:
      • type: map_at_1 value: 7.123
      • type: map_at_10 value: 14.448
      • type: map_at_100 value: 19.798
      • type: map_at_1000 value: 21.082
      • type: map_at_3 value: 10.815
      • type: map_at_5 value: 12.422
      • type: mrr_at_1 value: 53.5
      • type: mrr_at_10 value: 63.117999999999995
      • type: mrr_at_100 value: 63.617999999999995
      • type: mrr_at_1000 value: 63.63799999999999
      • type: mrr_at_3 value: 60.708
      • type: mrr_at_5 value: 62.171
      • type: ndcg_at_1 value: 42.125
      • type: ndcg_at_10 value: 31.703
      • type: ndcg_at_100 value: 35.935
      • type: ndcg_at_1000 value: 43.173
      • type: ndcg_at_3 value: 35.498000000000005
      • type: ndcg_at_5 value: 33.645
      • type: precision_at_1 value: 53.5
      • type: precision_at_10 value: 25.025
      • type: precision_at_100 value: 8.19
      • type: precision_at_1000 value: 1.806
      • type: precision_at_3 value: 39.083
      • type: precision_at_5 value: 33.050000000000004
      • type: recall_at_1 value: 7.123
      • type: recall_at_10 value: 19.581
      • type: recall_at_100 value: 42.061
      • type: recall_at_1000 value: 65.879
      • type: recall_at_3 value: 12.026
      • type: recall_at_5 value: 14.846
    • task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics:
      • type: accuracy value: 41.24
      • type: f1 value: 36.76174115773002
    • task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics:
      • type: map_at_1 value: 47.821999999999996
      • type: map_at_10 value: 59.794000000000004
      • type: map_at_100 value: 60.316
      • type: map_at_1000 value: 60.34
      • type: map_at_3 value: 57.202
      • type: map_at_5 value: 58.823
      • type: mrr_at_1 value: 51.485
      • type: mrr_at_10 value: 63.709
      • type: mrr_at_100 value: 64.144
      • type: mrr_at_1000 value: 64.158
      • type: mrr_at_3 value: 61.251
      • type: mrr_at_5 value: 62.818
      • type: ndcg_at_1 value: 51.485
      • type: ndcg_at_10 value: 66.097
      • type: ndcg_at_100 value: 68.37
      • type: ndcg_at_1000 value: 68.916
      • type: ndcg_at_3 value: 61.12800000000001
      • type: ndcg_at_5 value: 63.885000000000005
      • type: precision_at_1 value: 51.485
      • type: precision_at_10 value: 8.956999999999999
      • type: precision_at_100 value: 1.02
      • type: precision_at_1000 value: 0.108
      • type: precision_at_3 value: 24.807000000000002
      • type: precision_at_5 value: 16.387999999999998
      • type: recall_at_1 value: 47.821999999999996
      • type: recall_at_10 value: 81.773
      • type: recall_at_100 value: 91.731
      • type: recall_at_1000 value: 95.649
      • type: recall_at_3 value: 68.349
      • type: recall_at_5 value: 75.093
    • task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics:
      • type: map_at_1 value: 15.662999999999998
      • type: map_at_10 value: 25.726
      • type: map_at_100 value: 27.581
      • type: map_at_1000 value: 27.772000000000002
      • type: map_at_3 value: 21.859
      • type: map_at_5 value: 24.058
      • type: mrr_at_1 value: 30.247
      • type: mrr_at_10 value: 39.581
      • type: mrr_at_100 value: 40.594
      • type: mrr_at_1000 value: 40.647
      • type: mrr_at_3 value: 37.166
      • type: mrr_at_5 value: 38.585
      • type: ndcg_at_1 value: 30.247
      • type: ndcg_at_10 value: 32.934999999999995
      • type: ndcg_at_100 value: 40.062999999999995
      • type: ndcg_at_1000 value: 43.492
      • type: ndcg_at_3 value: 28.871000000000002
      • type: ndcg_at_5 value: 30.492
      • type: precision_at_1 value: 30.247
      • type: precision_at_10 value: 9.522
      • type: precision_at_100 value: 1.645
      • type: precision_at_1000 value: 0.22499999999999998
      • type: precision_at_3 value: 19.136
      • type: precision_at_5 value: 14.753
      • type: recall_at_1 value: 15.662999999999998
      • type: recall_at_10 value: 39.595
      • type: recall_at_100 value: 66.49199999999999
      • type: recall_at_1000 value: 87.19
      • type: recall_at_3 value: 26.346999999999998
      • type: recall_at_5 value: 32.423
    • task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics:
      • type: map_at_1 value: 30.176
      • type: map_at_10 value: 42.684
      • type: map_at_100 value: 43.582
      • type: map_at_1000 value: 43.668
      • type: map_at_3 value: 39.964
      • type: map_at_5 value: 41.589
      • type: mrr_at_1 value: 60.351
      • type: mrr_at_10 value: 67.669
      • type: mrr_at_100 value: 68.089
      • type: mrr_at_1000 value: 68.111
      • type: mrr_at_3 value: 66.144
      • type: mrr_at_5 value: 67.125
      • type: ndcg_at_1 value: 60.351
      • type: ndcg_at_10 value: 51.602000000000004
      • type: ndcg_at_100 value: 55.186
      • type: ndcg_at_1000 value: 56.96
      • type: ndcg_at_3 value: 47.251
      • type: ndcg_at_5 value: 49.584
      • type: precision_at_1 value: 60.351
      • type: precision_at_10 value: 10.804
      • type: precision_at_100 value: 1.3639999999999999
      • type: precision_at_1000 value: 0.16
      • type: precision_at_3 value: 29.561
      • type: precision_at_5 value: 19.581
      • type: recall_at_1 value: 30.176
      • type: recall_at_10 value: 54.018
      • type: recall_at_100 value: 68.22399999999999
      • type: recall_at_1000 value: 79.97999999999999
      • type: recall_at_3 value: 44.342
      • type: recall_at_5 value: 48.953
    • task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics:
      • type: accuracy value: 71.28320000000001
      • type: ap value: 65.20730065157146
      • type: f1 value: 71.19193683354304
    • task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics:
      • type: map_at_1 value: 19.686
      • type: map_at_10 value: 31.189
      • type: map_at_100 value: 32.368
      • type: map_at_1000 value: 32.43
      • type: map_at_3 value: 27.577
      • type: map_at_5 value: 29.603
      • type: mrr_at_1 value: 20.201
      • type: mrr_at_10 value: 31.762
      • type: mrr_at_100 value: 32.882
      • type: mrr_at_1000 value: 32.937
      • type: mrr_at_3 value: 28.177999999999997
      • type: mrr_at_5 value: 30.212
      • type: ndcg_at_1 value: 20.215
      • type: ndcg_at_10 value: 37.730999999999995
      • type: ndcg_at_100 value: 43.501
      • type: ndcg_at_1000 value: 45.031
      • type: ndcg_at_3 value: 30.336000000000002
      • type: ndcg_at_5 value: 33.961000000000006
      • type: precision_at_1 value: 20.215
      • type: precision_at_10 value: 6.036
      • type: precision_at_100 value: 0.895
      • type: precision_at_1000 value: 0.10300000000000001
      • type: precision_at_3 value: 13.028
      • type: precision_at_5 value: 9.633
      • type: recall_at_1 value: 19.686
      • type: recall_at_10 value: 57.867999999999995
      • type: recall_at_100 value: 84.758
      • type: recall_at_1000 value: 96.44500000000001
      • type: recall_at_3 value: 37.726
      • type: recall_at_5 value: 46.415
    • task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics:
      • type: accuracy value: 89.76972184222525
      • type: f1 value: 89.11949030406099
    • task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics:
      • type: accuracy value: 55.57455540355677
      • type: f1 value: 39.344920096224506
    • task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics:
      • type: accuracy value: 63.772696704774724
      • type: f1 value: 60.70041499812703
    • task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics:
      • type: accuracy value: 69.16274377942166
      • type: f1 value: 68.06744012208019
    • task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics:
      • type: v_measure value: 31.822626760555522
    • task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics:
      • type: v_measure value: 27.98469036402807
    • task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics:
      • type: map value: 30.911144124209166
      • type: mrr value: 31.950116175672292
    • task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics:
      • type: map_at_1 value: 5.157
      • type: map_at_10 value: 11.086
      • type: map_at_100 value: 13.927
      • type: map_at_1000 value: 15.226999999999999
      • type: map_at_3 value: 8.525
      • type: map_at_5 value: 9.767000000000001
      • type: mrr_at_1 value: 43.344
      • type: mrr_at_10 value: 51.646
      • type: mrr_at_100 value: 52.212
      • type: mrr_at_1000 value: 52.263999999999996
      • type: mrr_at_3 value: 50.052
      • type: mrr_at_5 value: 51.166
      • type: ndcg_at_1 value: 41.949999999999996
      • type: ndcg_at_10 value: 30.552
      • type: ndcg_at_100 value: 28.409000000000002
      • type: ndcg_at_1000 value: 37.328
      • type: ndcg_at_3 value: 37.114000000000004
      • type: ndcg_at_5 value: 34.117999999999995
      • type: precision_at_1 value: 43.344
      • type: precision_at_10 value: 22.198
      • type: precision_at_100 value: 7.234999999999999
      • type: precision_at_1000 value: 2.013
      • type: precision_at_3 value: 34.675
      • type: precision_at_5 value: 29.04
      • type: recall_at_1 value: 5.157
      • type: recall_at_10 value: 13.999
      • type: recall_at_100 value: 28.796
      • type: recall_at_1000 value: 60.84
      • type: recall_at_3 value: 9.603
      • type: recall_at_5 value: 11.638
    • task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics:
      • type: map_at_1 value: 33.024
      • type: map_at_10 value: 47.229
      • type: map_at_100 value: 48.195
      • type: map_at_1000 value: 48.229
      • type: map_at_3 value: 43.356
      • type: map_at_5 value: 45.857
      • type: mrr_at_1 value: 36.848
      • type: mrr_at_10 value: 49.801
      • type: mrr_at_100 value: 50.532999999999994
      • type: mrr_at_1000 value: 50.556
      • type: mrr_at_3 value: 46.605999999999995
      • type: mrr_at_5 value: 48.735
      • type: ndcg_at_1 value: 36.848
      • type: ndcg_at_10 value: 54.202
      • type: ndcg_at_100 value: 58.436
      • type: ndcg_at_1000 value: 59.252
      • type: ndcg_at_3 value: 47.082
      • type: ndcg_at_5 value: 51.254
      • type: precision_at_1 value: 36.848
      • type: precision_at_10 value: 8.636000000000001
      • type: precision_at_100 value: 1.105
      • type: precision_at_1000 value: 0.11800000000000001
      • type: precision_at_3 value: 21.08
      • type: precision_at_5 value: 15.07
      • type: recall_at_1 value: 33.024
      • type: recall_at_10 value: 72.699
      • type: recall_at_100 value: 91.387
      • type: recall_at_1000 value: 97.482
      • type: recall_at_3 value: 54.604
      • type: recall_at_5 value: 64.224
    • task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics:
      • type: map_at_1 value: 69.742
      • type: map_at_10 value: 83.43
      • type: map_at_100 value: 84.09400000000001
      • type: map_at_1000 value: 84.113
      • type: map_at_3 value: 80.464
      • type: map_at_5 value: 82.356
      • type: mrr_at_1 value: 80.31
      • type: mrr_at_10 value: 86.629
      • type: mrr_at_100 value: 86.753
      • type: mrr_at_1000 value: 86.75399999999999
      • type: mrr_at_3 value: 85.59
      • type: mrr_at_5 value: 86.346
      • type: ndcg_at_1 value: 80.28999999999999
      • type: ndcg_at_10 value: 87.323
      • type: ndcg_at_100 value: 88.682
      • type: ndcg_at_1000 value: 88.812
      • type: ndcg_at_3 value: 84.373
      • type: ndcg_at_5 value: 86.065
      • type: precision_at_1 value: 80.28999999999999
      • type: precision_at_10 value: 13.239999999999998
      • type: precision_at_100 value: 1.521
      • type: precision_at_1000 value: 0.156
      • type: precision_at_3 value: 36.827
      • type: precision_at_5 value: 24.272
      • type: recall_at_1 value: 69.742
      • type: recall_at_10 value: 94.645
      • type: recall_at_100 value: 99.375
      • type: recall_at_1000 value: 99.97200000000001
      • type: recall_at_3 value: 86.18400000000001
      • type: recall_at_5 value: 90.958
    • task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics:
      • type: v_measure value: 50.52987829115787
    • task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics:
      • type: v_measure value: 56.73289360025561
    • task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics:
      • type: map_at_1 value: 4.473
      • type: map_at_10 value: 10.953
      • type: map_at_100 value: 12.842
      • type: map_at_1000 value: 13.122
      • type: map_at_3 value: 7.863
      • type: map_at_5 value: 9.376
      • type: mrr_at_1 value: 22.0
      • type: mrr_at_10 value: 32.639
      • type: mrr_at_100 value: 33.658
      • type: mrr_at_1000 value: 33.727000000000004
      • type: mrr_at_3 value: 29.232999999999997
      • type: mrr_at_5 value: 31.373
      • type: ndcg_at_1 value: 22.0
      • type: ndcg_at_10 value: 18.736
      • type: ndcg_at_100 value: 26.209
      • type: ndcg_at_1000 value: 31.427
      • type: ndcg_at_3 value: 17.740000000000002
      • type: ndcg_at_5 value: 15.625
      • type: precision_at_1 value: 22.0
      • type: precision_at_10 value: 9.700000000000001
      • type: precision_at_100 value: 2.052
      • type: precision_at_1000 value: 0.331
      • type: precision_at_3 value: 16.533
      • type: precision_at_5 value: 13.74
      • type: recall_at_1 value: 4.473
      • type: recall_at_10 value: 19.627
      • type: recall_at_100 value: 41.63
      • type: recall_at_1000 value: 67.173
      • type: recall_at_3 value: 10.067
      • type: recall_at_5 value: 13.927
    • task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics:
      • type: cos_sim_pearson value: 83.27314719076216
      • type: cos_sim_spearman value: 76.39295628838427
      • type: euclidean_pearson value: 80.38849931283136
      • type: euclidean_spearman value: 76.39295685543406
      • type: manhattan_pearson value: 80.28382869912794
      • type: manhattan_spearman value: 76.28362123227473
    • task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics:
      • type: cos_sim_pearson value: 82.36858074786585
      • type: cos_sim_spearman value: 72.81528838052759
      • type: euclidean_pearson value: 78.83576324502302
      • type: euclidean_spearman value: 72.8152880167174
      • type: manhattan_pearson value: 78.81284819385367
      • type: manhattan_spearman value: 72.76091465928633
    • task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics:
      • type: cos_sim_pearson value: 81.08132718998489
      • type: cos_sim_spearman value: 82.00988939015869
      • type: euclidean_pearson value: 81.02243847451692
      • type: euclidean_spearman value: 82.00992010206836
      • type: manhattan_pearson value: 80.97749306075134
      • type: manhattan_spearman value: 81.97800195109437
    • task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics:
      • type: cos_sim_pearson value: 80.83442047735284
      • type: cos_sim_spearman value: 77.50930325127395
      • type: euclidean_pearson value: 79.34941050260747
      • type: euclidean_spearman value: 77.50930324686452
      • type: manhattan_pearson value: 79.28081079289419
      • type: manhattan_spearman value: 77.42311420628891
    • task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics:
      • type: cos_sim_pearson value: 85.70132781546333
      • type: cos_sim_spearman value: 86.58415907086527
      • type: euclidean_pearson value: 85.63892869817083
      • type: euclidean_spearman value: 86.58415907086527
      • type: manhattan_pearson value: 85.56054168116064
      • type: manhattan_spearman value: 86.50292824173809
    • task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics:
      • type: cos_sim_pearson value: 81.48780971731246
      • type: cos_sim_spearman value: 82.79818891852887
      • type: euclidean_pearson value: 81.93990926192305
      • type: euclidean_spearman value: 82.79818891852887
      • type: manhattan_pearson value: 81.97538189750966
      • type: manhattan_spearman value: 82.88761825524075
    • 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: 88.4989925729811
      • type: cos_sim_spearman value: 88.47370962620529
      • type: euclidean_pearson value: 88.2312980339956
      • type: euclidean_spearman value: 88.47370962620529
      • type: manhattan_pearson value: 88.15570940509707
      • type: manhattan_spearman value: 88.36900000569275
    • task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (en) config: en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics:
      • type: cos_sim_pearson value: 63.90740805015967
      • type: cos_sim_spearman value: 63.968359064784444
      • type: euclidean_pearson value: 64.67928113832794
      • type: euclidean_spearman value: 63.968359064784444
      • type: manhattan_pearson value: 63.92597430517486
      • type: manhattan_spearman value: 63.31372007361158
    • task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics:
      • type: cos_sim_pearson value: 82.56902991447632
      • type: cos_sim_spearman value: 83.16262853325924
      • type: euclidean_pearson value: 83.47693312869555
      • type: euclidean_spearman value: 83.16266829656969
      • type: manhattan_pearson value: 83.51067558632968
      • type: manhattan_spearman value: 83.25136388306153
    • task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics:
      • type: map value: 80.1518040851234
      • type: mrr value: 94.49083052024228
    • task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics:
      • type: map_at_1 value: 50.661
      • type: map_at_10 value: 59.816
      • type: map_at_100 value: 60.412
      • type: map_at_1000 value: 60.446999999999996
      • type: map_at_3 value: 56.567
      • type: map_at_5 value: 58.45
      • type: mrr_at_1 value: 53.667
      • type: mrr_at_10 value: 61.342
      • type: mrr_at_100 value: 61.8
      • type: mrr_at_1000 value: 61.836
      • type: mrr_at_3 value: 59.111000000000004
      • type: mrr_at_5 value: 60.411
      • type: ndcg_at_1 value: 53.667
      • type: ndcg_at_10 value: 64.488
      • type: ndcg_at_100 value: 67.291
      • type: ndcg_at_1000 value: 68.338
      • type: ndcg_at_3 value: 59.101000000000006
      • type: ndcg_at_5 value: 61.812999999999995
      • type: precision_at_1 value: 53.667
      • type: precision_at_10 value: 8.799999999999999
      • type: precision_at_100 value: 1.0330000000000001
      • type: precision_at_1000 value: 0.11199999999999999
      • type: precision_at_3 value: 23.0
      • type: precision_at_5 value: 15.6
      • type: recall_at_1 value: 50.661
      • type: recall_at_10 value: 77.422
      • type: recall_at_100 value: 90.667
      • type: recall_at_1000 value: 99.0
      • type: recall_at_3 value: 63.144
      • type: recall_at_5 value: 69.817
    • task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics:
      • type: cos_sim_accuracy value: 99.81287128712871
      • type: cos_sim_ap value: 94.91998708151321
      • type: cos_sim_f1 value: 90.36206017338093
      • type: cos_sim_precision value: 92.19562955254943
      • type: cos_sim_recall value: 88.6
      • type: dot_accuracy value: 99.81287128712871
      • type: dot_ap value: 94.91998708151321
      • type: dot_f1 value: 90.36206017338093
      • type: dot_precision value: 92.19562955254943
      • type: dot_recall value: 88.6
      • type: euclidean_accuracy value: 99.81287128712871
      • type: euclidean_ap value: 94.9199944407842
      • type: euclidean_f1 value: 90.36206017338093
      • type: euclidean_precision value: 92.19562955254943
      • type: euclidean_recall value: 88.6
      • type: manhattan_accuracy value: 99.8108910891089
      • type: manhattan_ap value: 94.83783896670839
      • type: manhattan_f1 value: 90.27989821882952
      • type: manhattan_precision value: 91.91709844559585
      • type: manhattan_recall value: 88.7
      • type: max_accuracy value: 99.81287128712871
      • type: max_ap value: 94.9199944407842
      • type: max_f1 value: 90.36206017338093
    • task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics:
      • type: v_measure value: 56.165546412944714
    • task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics:
      • type: v_measure value: 34.19894321136813
    • task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics:
      • type: map value: 50.02944308369115
      • type: mrr value: 50.63055714710127
    • task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics:
      • type: cos_sim_pearson value: 31.3377433394579
      • type: cos_sim_spearman value: 30.877807383527983
      • type: dot_pearson value: 31.337752376327405
      • type: dot_spearman value: 30.877807383527983
    • task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics:
      • type: map_at_1 value: 0.20500000000000002
      • type: map_at_10 value: 1.6099999999999999
      • type: map_at_100 value: 8.635
      • type: map_at_1000 value: 20.419999999999998
      • type: map_at_3 value: 0.59
      • type: map_at_5 value: 0.9249999999999999
      • type: mrr_at_1 value: 80.0
      • type: mrr_at_10 value: 88.452
      • type: mrr_at_100 value: 88.452
      • type: mrr_at_1000 value: 88.452
      • type: mrr_at_3 value: 87.667
      • type: mrr_at_5 value: 88.167
      • type: ndcg_at_1 value: 77.0
      • type: ndcg_at_10 value: 67.079
      • type: ndcg_at_100 value: 49.937
      • type: ndcg_at_1000 value: 44.031
      • type: ndcg_at_3 value: 73.123
      • type: ndcg_at_5 value: 70.435
      • type: precision_at_1 value: 80.0
      • type: precision_at_10 value: 70.39999999999999
      • type: precision_at_100 value: 51.25999999999999
      • type: precision_at_1000 value: 19.698
      • type: precision_at_3 value: 78.0
      • type: precision_at_5 value: 75.2
      • type: recall_at_1 value: 0.20500000000000002
      • type: recall_at_10 value: 1.8399999999999999
      • type: recall_at_100 value: 11.971
      • type: recall_at_1000 value: 41.042
      • type: recall_at_3 value: 0.632
      • type: recall_at_5 value: 1.008
    • task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics:
      • type: map_at_1 value: 1.183
      • type: map_at_10 value: 9.58
      • type: map_at_100 value: 16.27
      • type: map_at_1000 value: 17.977999999999998
      • type: map_at_3 value: 4.521
      • type: map_at_5 value: 6.567
      • type: mrr_at_1 value: 12.245000000000001
      • type: mrr_at_10 value: 33.486
      • type: mrr_at_100 value: 34.989
      • type: mrr_at_1000 value: 34.989
      • type: mrr_at_3 value: 28.231
      • type: mrr_at_5 value: 31.701
      • type: ndcg_at_1 value: 9.184000000000001
      • type: ndcg_at_10 value: 22.133
      • type: ndcg_at_100 value: 36.882
      • type: ndcg_at_1000 value: 48.487
      • type: ndcg_at_3 value: 18.971
      • type: ndcg_at_5 value: 20.107
      • type: precision_at_1 value: 12.245000000000001
      • type: precision_at_10 value: 21.837
      • type: precision_at_100 value: 8.265
      • type: precision_at_1000 value: 1.606
      • type: precision_at_3 value: 22.448999999999998
      • type: precision_at_5 value: 23.265
      • type: recall_at_1 value: 1.183
      • type: recall_at_10 value: 17.01
      • type: recall_at_100 value: 51.666000000000004
      • type: recall_at_1000 value: 87.56
      • type: recall_at_3 value: 6.0280000000000005
      • type: recall_at_5 value: 9.937999999999999
    • task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics:
      • type: accuracy value: 70.6812
      • type: ap value: 13.776718216594006
      • type: f1 value: 54.14269849375851
    • task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics:
      • type: accuracy value: 57.3372948500283
      • type: f1 value: 57.39381291375
    • task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics:
      • type: v_measure value: 41.49681931876514
    • task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics:
      • type: cos_sim_accuracy value: 84.65756690707516
      • type: cos_sim_ap value: 70.06190309300052
      • type: cos_sim_f1 value: 65.49254432311848
      • type: cos_sim_precision value: 59.00148085466469
      • type: cos_sim_recall value: 73.58839050131925
      • type: dot_accuracy value: 84.65756690707516
      • type: dot_ap value: 70.06187157356817
      • type: dot_f1 value: 65.49254432311848
      • type: dot_precision value: 59.00148085466469
      • type: dot_recall value: 73.58839050131925
      • type: euclidean_accuracy value: 84.65756690707516
      • type: euclidean_ap value: 70.06190439203068
      • type: euclidean_f1 value: 65.49254432311848
      • type: euclidean_precision value: 59.00148085466469
      • type: euclidean_recall value: 73.58839050131925
      • type: manhattan_accuracy value: 84.58604041246946
      • type: manhattan_ap value: 69.93103436414437
      • type: manhattan_f1 value: 65.48780487804878
      • type: manhattan_precision value: 60.8843537414966
      • type: manhattan_recall value: 70.84432717678101
      • type: max_accuracy value: 84.65756690707516
      • type: max_ap value: 70.06190439203068
      • type: max_f1 value: 65.49254432311848
    • task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics:
      • type: cos_sim_accuracy value: 88.78410369852912
      • type: cos_sim_ap value: 85.45825760499459
      • type: cos_sim_f1 value: 77.73455035163849
      • type: cos_sim_precision value: 75.5966239813737
      • type: cos_sim_recall value: 79.9969202340622
      • type: dot_accuracy value: 88.78410369852912
      • type: dot_ap value: 85.45825790635979
      • type: dot_f1 value: 77.73455035163849
      • type: dot_precision value: 75.5966239813737
      • type: dot_recall value: 79.9969202340622
      • type: euclidean_accuracy value: 88.78410369852912
      • type: euclidean_ap value: 85.45826341243391
      • type: euclidean_f1 value: 77.73455035163849
      • type: euclidean_precision value: 75.5966239813737
      • type: euclidean_recall value: 79.9969202340622
      • type: manhattan_accuracy value: 88.7026041060271
      • type: manhattan_ap value: 85.43182830781821
      • type: manhattan_f1 value: 77.61487303506651
      • type: manhattan_precision value: 76.20955773226477
      • type: manhattan_recall value: 79.07299045272559
      • type: max_accuracy value: 88.78410369852912
      • type: max_ap value: 85.45826341243391
      • type: max_f1 value: 77.73455035163849