README.md

---
language:
- en
base_model:
- google/gemma-2-9b-it
license: gemma
model-index:
- name: google/Gemma-Embeddings-v1.0
  results:
  - dataset:
      config: en
      name: MTEB AmazonCounterfactualClassification (en)
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
      split: test
      type: mteb/amazon_counterfactual
    metrics:
    - type: accuracy
      value: 94.6269
    - type: f1
      value: 91.9315
    - type: f1_weighted
      value: 94.77029999999999
    - type: ap
      value: 77.8258
    - type: ap_weighted
      value: 77.8258
    - type: main_score
      value: 94.6269
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB AmazonPolarityClassification (default)
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
      split: test
      type: mteb/amazon_polarity
    metrics:
    - type: accuracy
      value: 97.0382
    - type: f1
      value: 97.0377
    - type: f1_weighted
      value: 97.0377
    - type: ap
      value: 95.8721
    - type: ap_weighted
      value: 95.8721
    - type: main_score
      value: 97.0382
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB AmazonReviewsClassification (en)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
    metrics:
    - type: accuracy
      value: 65.30799999999999
    - type: f1
      value: 64.4521
    - type: f1_weighted
      value: 64.4521
    - type: main_score
      value: 65.30799999999999
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB ArguAna (default)
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
      split: test
      type: mteb/arguana
    metrics:
    - type: ndcg_at_1
      value: 69.844
    - type: ndcg_at_3
      value: 82.047
    - type: ndcg_at_5
      value: 83.734
    - type: ndcg_at_10
      value: 84.821
    - type: ndcg_at_20
      value: 85.051
    - type: ndcg_at_100
      value: 85.231
    - type: ndcg_at_1000
      value: 85.231
    - type: map_at_1
      value: 69.844
    - type: map_at_3
      value: 79.125
    - type: map_at_5
      value: 80.071
    - type: map_at_10
      value: 80.537
    - type: map_at_20
      value: 80.598
    - type: map_at_100
      value: 80.626
    - type: map_at_1000
      value: 80.626
    - type: recall_at_1
      value: 69.844
    - type: recall_at_3
      value: 90.469
    - type: recall_at_5
      value: 94.523
    - type: recall_at_10
      value: 97.795
    - type: recall_at_20
      value: 98.72
    - type: recall_at_100
      value: 99.644
    - type: recall_at_1000
      value: 99.644
    - type: precision_at_1
      value: 69.844
    - type: precision_at_3
      value: 30.156
    - type: precision_at_5
      value: 18.905
    - type: precision_at_10
      value: 9.78
    - type: precision_at_20
      value: 4.936
    - type: precision_at_100
      value: 0.996
    - type: precision_at_1000
      value: 0.1
    - type: mrr_at_1
      value: 70.0569
    - type: mrr_at_3
      value: 79.20819999999999
    - type: mrr_at_5
      value: 80.1541
    - type: mrr_at_10
      value: 80.6206
    - type: mrr_at_20
      value: 80.6819
    - type: mrr_at_100
      value: 80.7099
    - type: mrr_at_1000
      value: 80.7099
    - type: nauc_ndcg_at_1_max
      value: 4.4853
    - type: nauc_ndcg_at_1_std
      value: -32.4139
    - type: nauc_ndcg_at_1_diff1
      value: 54.961000000000006
    - type: nauc_ndcg_at_3_max
      value: 10.9114
    - type: nauc_ndcg_at_3_std
      value: -33.466499999999996
    - type: nauc_ndcg_at_3_diff1
      value: 50.809599999999996
    - type: nauc_ndcg_at_5_max
      value: 8.2551
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      value: -33.0891
    - type: nauc_ndcg_at_5_diff1
      value: 50.942600000000006
    - type: nauc_ndcg_at_10_max
      value: 8.9955
    - type: nauc_ndcg_at_10_std
      value: -33.372
    - type: nauc_ndcg_at_10_diff1
      value: 52.88420000000001
    - type: nauc_ndcg_at_20_max
      value: 8.0304
    - type: nauc_ndcg_at_20_std
      value: -33.2286
    - type: nauc_ndcg_at_20_diff1
      value: 52.56459999999999
    - type: nauc_ndcg_at_100_max
      value: 7.7877
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      value: -32.5506
    - type: nauc_ndcg_at_100_diff1
      value: 52.207800000000006
    - type: nauc_ndcg_at_1000_max
      value: 7.7877
    - type: nauc_ndcg_at_1000_std
      value: -32.5506
    - type: nauc_ndcg_at_1000_diff1
      value: 52.207800000000006
    - type: nauc_map_at_1_max
      value: 4.4853
    - type: nauc_map_at_1_std
      value: -32.4139
    - type: nauc_map_at_1_diff1
      value: 54.961000000000006
    - type: nauc_map_at_3_max
      value: 8.5875
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      value: -33.1539
    - type: nauc_map_at_3_diff1
      value: 51.7761
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      value: 7.2324
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      value: -32.9639
    - type: nauc_map_at_5_diff1
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      value: 7.4474
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    - type: nauc_map_at_10_diff1
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      value: -32.9841
    - type: nauc_map_at_1000_diff1
      value: 52.469100000000005
    - type: nauc_recall_at_1_max
      value: 4.4853
    - type: nauc_recall_at_1_std
      value: -32.4139
    - type: nauc_recall_at_1_diff1
      value: 54.961000000000006
    - type: nauc_recall_at_3_max
      value: 24.187
    - type: nauc_recall_at_3_std
      value: -35.2013
    - type: nauc_recall_at_3_diff1
      value: 45.690599999999996
    - type: nauc_recall_at_5_max
      value: 16.9677
    - type: nauc_recall_at_5_std
      value: -34.041700000000006
    - type: nauc_recall_at_5_diff1
      value: 42.5248
    - type: nauc_recall_at_10_max
      value: 43.9168
    - type: nauc_recall_at_10_std
      value: -39.8657
    - type: nauc_recall_at_10_diff1
      value: 66.1909
    - type: nauc_recall_at_20_max
      value: 29.317300000000003
    - type: nauc_recall_at_20_std
      value: -37.4268
    - type: nauc_recall_at_20_diff1
      value: 62.67660000000001
    - type: nauc_recall_at_100_max
      value: 37.0551
    - type: nauc_recall_at_100_std
      value: 85.8517
    - type: nauc_recall_at_100_diff1
      value: 21.2768
    - type: nauc_recall_at_1000_max
      value: 37.0551
    - type: nauc_recall_at_1000_std
      value: 85.8517
    - type: nauc_recall_at_1000_diff1
      value: 21.2768
    - type: nauc_precision_at_1_max
      value: 4.4853
    - type: nauc_precision_at_1_std
      value: -32.4139
    - type: nauc_precision_at_1_diff1
      value: 54.961000000000006
    - type: nauc_precision_at_3_max
      value: 24.187
    - type: nauc_precision_at_3_std
      value: -35.2013
    - type: nauc_precision_at_3_diff1
      value: 45.690599999999996
    - type: nauc_precision_at_5_max
      value: 16.9677
    - type: nauc_precision_at_5_std
      value: -34.041700000000006
    - type: nauc_precision_at_5_diff1
      value: 42.5248
    - type: nauc_precision_at_10_max
      value: 43.9168
    - type: nauc_precision_at_10_std
      value: -39.8657
    - type: nauc_precision_at_10_diff1
      value: 66.1909
    - type: nauc_precision_at_20_max
      value: 29.317300000000003
    - type: nauc_precision_at_20_std
      value: -37.4268
    - type: nauc_precision_at_20_diff1
      value: 62.67660000000001
    - type: nauc_precision_at_100_max
      value: 37.0551
    - type: nauc_precision_at_100_std
      value: 85.8517
    - type: nauc_precision_at_100_diff1
      value: 21.2768
    - type: nauc_precision_at_1000_max
      value: 37.0551
    - type: nauc_precision_at_1000_std
      value: 85.8517
    - type: nauc_precision_at_1000_diff1
      value: 21.2768
    - type: nauc_mrr_at_1_max
      value: 4.6327
    - type: nauc_mrr_at_1_std
      value: -32.4116
    - type: nauc_mrr_at_1_diff1
      value: 54.4129
    - type: nauc_mrr_at_3_max
      value: 8.6301
    - type: nauc_mrr_at_3_std
      value: -33.264700000000005
    - type: nauc_mrr_at_3_diff1
      value: 51.452
    - type: nauc_mrr_at_5_max
      value: 7.273899999999999
    - type: nauc_mrr_at_5_std
      value: -33.0802
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      value: 51.5652
    - type: nauc_mrr_at_10_max
      value: 7.4876
    - type: nauc_mrr_at_10_std
      value: -33.2021
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      value: 52.2296
    - type: nauc_mrr_at_20_max
      value: 7.277699999999999
    - type: nauc_mrr_at_20_std
      value: -33.1827
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      value: 52.15880000000001
    - type: nauc_mrr_at_100_max
      value: 7.249999999999999
    - type: nauc_mrr_at_100_std
      value: -33.110299999999995
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      value: 52.1158
    - type: nauc_mrr_at_1000_max
      value: 7.249999999999999
    - type: nauc_mrr_at_1000_std
      value: -33.110299999999995
    - type: nauc_mrr_at_1000_diff1
      value: 52.1158
    - type: main_score
      value: 84.821
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB ArxivClusteringP2P (default)
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
      split: test
      type: mteb/arxiv-clustering-p2p
    metrics:
    - type: v_measure
      value: 54.8264
    - type: v_measure_std
      value: 14.505199999999999
    - type: main_score
      value: 54.8264
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB ArxivClusteringS2S (default)
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
      split: test
      type: mteb/arxiv-clustering-s2s
    metrics:
    - type: v_measure
      value: 50.022299999999994
    - type: v_measure_std
      value: 14.4899
    - type: main_score
      value: 50.022299999999994
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB AskUbuntuDupQuestions (default)
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
      split: test
      type: mteb/askubuntudupquestions-reranking
    metrics:
    - type: map
      value: 65.6388
    - type: mrr
      value: 79.3677
    - type: nAUC_map_max
      value: 31.682900000000004
    - type: nAUC_map_std
      value: 20.0437
    - type: nAUC_map_diff1
      value: 8.7821
    - type: nAUC_mrr_max
      value: 44.033
    - type: nAUC_mrr_std
      value: 33.0875
    - type: nAUC_mrr_diff1
      value: 17.7949
    - type: main_score
      value: 65.6388
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB BIOSSES (default)
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
      split: test
      type: mteb/biosses-sts
    metrics:
    - type: pearson
      value: 89.9755
    - type: spearman
      value: 89.8099
    - type: cosine_pearson
      value: 89.9755
    - type: cosine_spearman
      value: 89.8099
    - type: manhattan_pearson
      value: 87.7735
    - type: manhattan_spearman
      value: 89.57310000000001
    - type: euclidean_pearson
      value: 87.708
    - type: euclidean_spearman
      value: 89.8099
    - type: main_score
      value: 89.8099
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB Banking77Classification (default)
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
      split: test
      type: mteb/banking77
    metrics:
    - type: accuracy
      value: 93.16879999999999
    - type: f1
      value: 93.1524
    - type: f1_weighted
      value: 93.1524
    - type: main_score
      value: 93.16879999999999
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB BiorxivClusteringP2P (default)
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
      split: test
      type: mteb/biorxiv-clustering-p2p
    metrics:
    - type: v_measure
      value: 54.024499999999996
    - type: v_measure_std
      value: 1.0512000000000001
    - type: main_score
      value: 54.024499999999996
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB BiorxivClusteringS2S (default)
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
      split: test
      type: mteb/biorxiv-clustering-s2s
    metrics:
    - type: v_measure
      value: 50.925799999999995
    - type: v_measure_std
      value: 1.024
    - type: main_score
      value: 50.925799999999995
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB CQADupstackAndroidRetrieval (default)
      revision: f46a197baaae43b4f621051089b82a364682dfeb
      split: test
      type: mteb/cqadupstack-android
    metrics:
    - type: ndcg_at_1
      value: 47.067
    - type: ndcg_at_3
      value: 53.561
    - type: ndcg_at_5
      value: 56.497
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    - type: map_at_1000
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      value: 56.269999999999996
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      value: 64.259
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    - type: recall_at_1000
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    - type: precision_at_1000
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      type: Retrieval
  - dataset:
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      name: MTEB ImdbClassification (default)
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
      split: test
      type: mteb/imdb
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    task:
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  - dataset:
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      name: MTEB MSMARCO (default)
      revision: c5a29a104738b98a9e76336939199e264163d4a0
      split: dev
      type: mteb/msmarco
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    task:
      type: Retrieval
  - dataset:
      config: en
      name: MTEB MTOPDomainClassification (en)
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      split: test
      type: mteb/mtop_domain
    metrics:
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    - type: f1
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    - type: f1_weighted
      value: 99.21640000000001
    - type: main_score
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    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MTOPIntentClassification (en)
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
      split: test
      type: mteb/mtop_intent
    metrics:
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    - type: f1_weighted
      value: 95.2685
    - type: main_score
      value: 94.5372
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MassiveIntentClassification (en)
      revision: 4672e20407010da34463acc759c162ca9734bca6
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 82.0646
    - type: f1
      value: 80.2035
    - type: f1_weighted
      value: 80.8017
    - type: main_score
      value: 82.0646
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MassiveScenarioClassification (en)
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
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      value: 87.5723
    - type: f1
      value: 86.2565
    - type: f1_weighted
      value: 86.92020000000001
    - type: main_score
      value: 87.5723
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB MedrxivClusteringP2P (default)
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
      split: test
      type: mteb/medrxiv-clustering-p2p
    metrics:
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      value: 47.488200000000006
    - type: v_measure_std
      value: 1.2606
    - type: main_score
      value: 47.488200000000006
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB MedrxivClusteringS2S (default)
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
      split: test
      type: mteb/medrxiv-clustering-s2s
    metrics:
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      value: 45.0597
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      value: 1.5357
    - type: main_score
      value: 45.0597
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB MindSmallReranking (default)
      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
      split: test
      type: mteb/mind_small
    metrics:
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      value: 32.1466
    - type: nAUC_map_max
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      value: -8.7712
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      value: 8.7311
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      value: -11.0311
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      value: -5.2932
    - type: nAUC_mrr_diff1
      value: 8.7991
    - type: main_score
      value: 30.8519
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB NFCorpus (default)
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
      split: test
      type: mteb/nfcorpus
    metrics:
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      value: 46.766000000000005
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      value: 44.401
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      value: 40.955000000000005
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      value: 38.436
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      value: 37.101
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      value: 45.458999999999996
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      value: 11.305
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      value: 13.355
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      value: 15.841
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      value: 17.724
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      value: 20.146
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      value: 21.664
    - type: recall_at_1
      value: 6.7860000000000005
    - type: recall_at_3
      value: 12.848
    - type: recall_at_5
      value: 16.059
    - type: recall_at_10
      value: 20.699
    - type: recall_at_20
      value: 25.349
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      value: 37.377
    - type: recall_at_1000
      value: 68.326
    - type: precision_at_1
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      value: 43.963
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      value: 38.7
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      value: 30.402
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      value: 22.415
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      value: 9.074
    - type: precision_at_1000
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    - type: mrr_at_1
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    - type: mrr_at_3
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      value: 61.6213
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      value: 61.9851
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    - type: nauc_map_at_1000_std
      value: -68.77210000000001
    - type: nauc_map_at_1000_diff1
      value: 79.8039
    - type: nauc_recall_at_1_max
      value: 21.4243
    - type: nauc_recall_at_1_std
      value: -57.04900000000001
    - type: nauc_recall_at_1_diff1
      value: 83.3378
    - type: nauc_recall_at_3_max
      value: 22.6679
    - type: nauc_recall_at_3_std
      value: -86.9046
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      value: 77.608
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      value: 24.4242
    - type: nauc_recall_at_5_std
      value: -100.1963
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      value: 77.5562
    - type: nauc_recall_at_10_max
      value: 26.995599999999996
    - type: nauc_recall_at_10_std
      value: -110.56330000000001
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    - type: nauc_recall_at_20_max
      value: 27.3385
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      value: -117.10199999999999
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      value: 77.7938
    - type: nauc_recall_at_100_max
      value: 33.0847
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      value: -110.4169
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      value: 76.4873
    - type: nauc_recall_at_1000_max
      value: -16.532
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      value: -24.5592
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      value: 72.233
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      value: 33.0127
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      value: -59.3688
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      value: 8.1134
    - type: nauc_precision_at_3_diff1
      value: -27.1918
    - type: nauc_precision_at_5_max
      value: 1.3161
    - type: nauc_precision_at_5_std
      value: 21.8406
    - type: nauc_precision_at_5_diff1
      value: -37.5509
    - type: nauc_precision_at_10_max
      value: -1.4878
    - type: nauc_precision_at_10_std
      value: 35.5171
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    - type: nauc_precision_at_20_std
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    - type: nauc_precision_at_100_max
      value: -4.3248
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      value: 51.5534
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      value: 53.2738
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      value: -46.8777
    - type: nauc_mrr_at_1_max
      value: 32.994099999999996
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      value: -59.4653
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      value: 81.0983
    - type: nauc_mrr_at_3_max
      value: 33.381699999999995
    - type: nauc_mrr_at_3_std
      value: -65.6011
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      value: 80.3293
    - type: nauc_mrr_at_5_max
      value: 33.5696
    - type: nauc_mrr_at_5_std
      value: -65.3317
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      value: 80.5711
    - type: nauc_mrr_at_10_max
      value: 33.453500000000005
    - type: nauc_mrr_at_10_std
      value: -64.90209999999999
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      value: 80.5965
    - type: nauc_mrr_at_20_max
      value: 33.414500000000004
    - type: nauc_mrr_at_20_std
      value: -64.7197
    - type: nauc_mrr_at_20_diff1
      value: 80.5804
    - type: nauc_mrr_at_100_max
      value: 33.4032
    - type: nauc_mrr_at_100_std
      value: -64.6315
    - type: nauc_mrr_at_100_diff1
      value: 80.5771
    - type: nauc_mrr_at_1000_max
      value: 33.4024
    - type: nauc_mrr_at_1000_std
      value: -64.6301
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      value: 80.5769
    - type: main_score
      value: 91.019
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB RedditClustering (default)
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
      split: test
      type: mteb/reddit-clustering
    metrics:
    - type: v_measure
      value: 72.7484
    - type: v_measure_std
      value: 2.9369
    - type: main_score
      value: 72.7484
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB RedditClusteringP2P (default)
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
      split: test
      type: mteb/reddit-clustering-p2p
    metrics:
    - type: v_measure
      value: 73.0078
    - type: v_measure_std
      value: 12.3013
    - type: main_score
      value: 73.0078
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB SCIDOCS (default)
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
      split: test
      type: mteb/scidocs
    metrics:
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      value: 31.3
    - type: ndcg_at_3
      value: 26.807
    - type: ndcg_at_5
      value: 24.29
    - type: ndcg_at_10
      value: 29.189999999999998
    - type: ndcg_at_20
      value: 33.212
    - type: ndcg_at_100
      value: 41.062
    - type: ndcg_at_1000
      value: 46.201
    - type: map_at_1
      value: 6.358
    - type: map_at_3
      value: 12.309000000000001
    - type: map_at_5
      value: 15.543000000000001
    - type: map_at_10
      value: 18.404999999999998
    - type: map_at_20
      value: 20.102
    - type: map_at_100
      value: 22.012
    - type: map_at_1000
      value: 22.391
    - type: recall_at_1
      value: 6.358
    - type: recall_at_3
      value: 15.482999999999999
    - type: recall_at_5
      value: 22.343
    - type: recall_at_10
      value: 31.378
    - type: recall_at_20
      value: 40.797
    - type: recall_at_100
      value: 66.122
    - type: recall_at_1000
      value: 90.878
    - type: precision_at_1
      value: 31.3
    - type: precision_at_3
      value: 25.467000000000002
    - type: precision_at_5
      value: 22.06
    - type: precision_at_10
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    - type: precision_at_20
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    - type: precision_at_100
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    - type: precision_at_1000
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    - type: mrr_at_1
      value: 31.3
    - type: mrr_at_3
      value: 41.5167
    - type: mrr_at_5
      value: 43.8317
    - type: mrr_at_10
      value: 45.236900000000006
    - type: mrr_at_20
      value: 45.894200000000005
    - type: mrr_at_100
      value: 46.2296
    - type: mrr_at_1000
      value: 46.247
    - type: nauc_ndcg_at_1_max
      value: 22.6455
    - type: nauc_ndcg_at_1_std
      value: -3.4214
    - type: nauc_ndcg_at_1_diff1
      value: 22.2194
    - type: nauc_ndcg_at_3_max
      value: 26.16
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      value: -4.1874
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      value: 15.6529
    - type: nauc_ndcg_at_5_max
      value: 29.849500000000003
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      value: -3.5488
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      value: 15.6251
    - type: nauc_ndcg_at_10_max
      value: 30.462600000000002
    - type: nauc_ndcg_at_10_std
      value: -2.4431000000000003
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    - type: nauc_ndcg_at_20_max
      value: 32.0054
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      value: -0.9074000000000001
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      value: 13.2326
    - type: nauc_ndcg_at_100_max
      value: 33.604099999999995
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      value: 3.8350000000000004
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      value: 12.7082
    - type: nauc_ndcg_at_1000_max
      value: 32.5997
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      value: 3.2862
    - type: nauc_ndcg_at_1000_diff1
      value: 13.7365
    - type: nauc_map_at_1_max
      value: 22.3207
    - type: nauc_map_at_1_std
      value: -3.543
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      value: 21.9335
    - type: nauc_map_at_3_max
      value: 24.9035
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      value: -5.9363
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      value: 15.101
    - type: nauc_map_at_5_max
      value: 28.5337
    - type: nauc_map_at_5_std
      value: -6.2807
    - type: nauc_map_at_5_diff1
      value: 14.9171
    - type: nauc_map_at_10_max
      value: 29.496899999999997
    - type: nauc_map_at_10_std
      value: -5.608
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      value: 12.7308
    - type: nauc_map_at_20_max
      value: 30.4348
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      value: -4.4265
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      value: 12.4533
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      value: -2.6229999999999998
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      value: 12.2408
    - type: nauc_map_at_1000_max
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      value: -2.5584
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      value: 12.295499999999999
    - type: nauc_recall_at_1_max
      value: 22.3207
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      value: -3.543
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      value: 21.9335
    - type: nauc_recall_at_3_max
      value: 26.617800000000003
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      value: -4.601
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      value: 12.969800000000001
    - type: nauc_recall_at_5_max
      value: 31.523
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      value: -2.8593
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      value: 13.077
    - type: nauc_recall_at_10_max
      value: 30.361
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      value: -0.7305
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      value: 8.5364
    - type: nauc_recall_at_20_max
      value: 31.821700000000003
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      value: 2.5871999999999997
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      value: 7.7219
    - type: nauc_recall_at_100_max
      value: 32.658500000000004
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      value: 17.088
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      value: 4.2962
    - type: nauc_recall_at_1000_max
      value: 28.8568
    - type: nauc_recall_at_1000_std
      value: 30.724400000000003
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      value: 5.7278
    - type: nauc_precision_at_1_max
      value: 22.6455
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      value: -3.4214
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      value: 22.2194
    - type: nauc_precision_at_3_max
      value: 27.0287
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      value: -4.2745999999999995
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      value: 13.2524
    - type: nauc_precision_at_5_max
      value: 31.798199999999998
    - type: nauc_precision_at_5_std
      value: -2.6458
    - type: nauc_precision_at_5_diff1
      value: 13.1913
    - type: nauc_precision_at_10_max
      value: 30.442700000000002
    - type: nauc_precision_at_10_std
      value: -0.7052
    - type: nauc_precision_at_10_diff1
      value: 8.698500000000001
    - type: nauc_precision_at_20_max
      value: 31.8098
    - type: nauc_precision_at_20_std
      value: 2.6527
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      value: 7.988199999999999
    - type: nauc_precision_at_100_max
      value: 31.9799
    - type: nauc_precision_at_100_std
      value: 16.4552
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      value: 4.6661
    - type: nauc_precision_at_1000_max
      value: 26.039099999999998
    - type: nauc_precision_at_1000_std
      value: 26.8761
    - type: nauc_precision_at_1000_diff1
      value: 5.564299999999999
    - type: nauc_mrr_at_1_max
      value: 22.6455
    - type: nauc_mrr_at_1_std
      value: -3.4214
    - type: nauc_mrr_at_1_diff1
      value: 22.2194
    - type: nauc_mrr_at_3_max
      value: 25.827699999999997
    - type: nauc_mrr_at_3_std
      value: -2.0878
    - type: nauc_mrr_at_3_diff1
      value: 19.0105
    - type: nauc_mrr_at_5_max
      value: 26.479799999999997
    - type: nauc_mrr_at_5_std
      value: -1.0343
    - type: nauc_mrr_at_5_diff1
      value: 19.4599
    - type: nauc_mrr_at_10_max
      value: 26.3345
    - type: nauc_mrr_at_10_std
      value: -1.0147
    - type: nauc_mrr_at_10_diff1
      value: 19.572
    - type: nauc_mrr_at_20_max
      value: 26.4581
    - type: nauc_mrr_at_20_std
      value: -1.0342
    - type: nauc_mrr_at_20_diff1
      value: 19.5204
    - type: nauc_mrr_at_100_max
      value: 26.334200000000003
    - type: nauc_mrr_at_100_std
      value: -1.0591
    - type: nauc_mrr_at_100_diff1
      value: 19.5134
    - type: nauc_mrr_at_1000_max
      value: 26.3192
    - type: nauc_mrr_at_1000_std
      value: -1.0868
    - type: nauc_mrr_at_1000_diff1
      value: 19.5308
    - type: main_score
      value: 29.189999999999998
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB SICK-R (default)
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
      split: test
      type: mteb/sickr-sts
    metrics:
    - type: pearson
      value: 82.9977
    - type: spearman
      value: 82.7264
    - type: cosine_pearson
      value: 82.9977
    - type: cosine_spearman
      value: 82.7264
    - type: manhattan_pearson
      value: 79.2844
    - type: manhattan_spearman
      value: 82.706
    - type: euclidean_pearson
      value: 79.30319999999999
    - type: euclidean_spearman
      value: 82.7264
    - type: main_score
      value: 82.7264
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS12 (default)
      revision: a0d554a64d88156834ff5ae9920b964011b16384
      split: test
      type: mteb/sts12-sts
    metrics:
    - type: pearson
      value: 86.691
    - type: spearman
      value: 79.9669
    - type: cosine_pearson
      value: 86.691
    - type: cosine_spearman
      value: 79.9669
    - type: manhattan_pearson
      value: 81.131
    - type: manhattan_spearman
      value: 79.9913
    - type: euclidean_pearson
      value: 81.13550000000001
    - type: euclidean_spearman
      value: 79.9667
    - type: main_score
      value: 79.9669
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS13 (default)
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
      split: test
      type: mteb/sts13-sts
    metrics:
    - type: pearson
      value: 85.1053
    - type: spearman
      value: 83.94890000000001
    - type: cosine_pearson
      value: 85.1053
    - type: cosine_spearman
      value: 83.94890000000001
    - type: manhattan_pearson
      value: 83.7957
    - type: manhattan_spearman
      value: 83.8831
    - type: euclidean_pearson
      value: 83.8318
    - type: euclidean_spearman
      value: 83.94890000000001
    - type: main_score
      value: 83.94890000000001
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS14 (default)
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
      split: test
      type: mteb/sts14-sts
    metrics:
    - type: pearson
      value: 84.23610000000001
    - type: spearman
      value: 84.2503
    - type: cosine_pearson
      value: 84.23610000000001
    - type: cosine_spearman
      value: 84.2503
    - type: manhattan_pearson
      value: 82.3061
    - type: manhattan_spearman
      value: 84.2598
    - type: euclidean_pearson
      value: 82.30330000000001
    - type: euclidean_spearman
      value: 84.2503
    - type: main_score
      value: 84.2503
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS15 (default)
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
      split: test
      type: mteb/sts15-sts
    metrics:
    - type: pearson
      value: 90.5569
    - type: spearman
      value: 90.4496
    - type: cosine_pearson
      value: 90.5569
    - type: cosine_spearman
      value: 90.4496
    - type: manhattan_pearson
      value: 88.5942
    - type: manhattan_spearman
      value: 90.4286
    - type: euclidean_pearson
      value: 88.6003
    - type: euclidean_spearman
      value: 90.4496
    - type: main_score
      value: 90.4496
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS16 (default)
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
      split: test
      type: mteb/sts16-sts
    metrics:
    - type: pearson
      value: 86.447
    - type: spearman
      value: 86.4776
    - type: cosine_pearson
      value: 86.447
    - type: cosine_spearman
      value: 86.4776
    - type: manhattan_pearson
      value: 85.3768
    - type: manhattan_spearman
      value: 86.48599999999999
    - type: euclidean_pearson
      value: 85.3792
    - type: euclidean_spearman
      value: 86.4776
    - type: main_score
      value: 86.4776
    task:
      type: STS
  - dataset:
      config: en-en
      name: MTEB STS17 (en-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: pearson
      value: 90.40820000000001
    - type: spearman
      value: 89.7495
    - type: cosine_pearson
      value: 90.40820000000001
    - type: cosine_spearman
      value: 89.7495
    - type: manhattan_pearson
      value: 88.20519999999999
    - type: manhattan_spearman
      value: 89.62689999999999
    - type: euclidean_pearson
      value: 88.268
    - type: euclidean_spearman
      value: 89.7495
    - type: main_score
      value: 89.7495
    task:
      type: STS
  - dataset:
      config: en
      name: MTEB STS22 (en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: pearson
      value: 69.5732
    - type: spearman
      value: 67.7261
    - type: cosine_pearson
      value: 69.5732
    - type: cosine_spearman
      value: 67.7261
    - type: manhattan_pearson
      value: 69.7793
    - type: manhattan_spearman
      value: 67.9213
    - type: euclidean_pearson
      value: 69.6908
    - type: euclidean_spearman
      value: 67.7261
    - type: main_score
      value: 67.7261
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STSBenchmark (default)
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
      split: test
      type: mteb/stsbenchmark-sts
    metrics:
    - type: pearson
      value: 86.6914
    - type: spearman
      value: 87.2151
    - type: cosine_pearson
      value: 86.6914
    - type: cosine_spearman
      value: 87.2151
    - type: manhattan_pearson
      value: 85.8277
    - type: manhattan_spearman
      value: 87.2492
    - type: euclidean_pearson
      value: 85.79719999999999
    - type: euclidean_spearman
      value: 87.2151
    - type: main_score
      value: 87.2151
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB SciDocsRR (default)
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
      split: test
      type: mteb/scidocs-reranking
    metrics:
    - type: map
      value: 89.137
    - type: mrr
      value: 96.7541
    - type: nAUC_map_max
      value: 52.1481
    - type: nAUC_map_std
      value: 72.15859999999999
    - type: nAUC_map_diff1
      value: -10.389
    - type: nAUC_mrr_max
      value: 85.25160000000001
    - type: nAUC_mrr_std
      value: 87.73570000000001
    - type: nAUC_mrr_diff1
      value: 30.605300000000003
    - type: main_score
      value: 89.137
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SciFact (default)
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
      split: test
      type: mteb/scifact
    metrics:
    - type: ndcg_at_1
      value: 71.667
    - type: ndcg_at_3
      value: 79.611
    - type: ndcg_at_5
      value: 81.394
    - type: ndcg_at_10
      value: 83.279
    - type: ndcg_at_20
      value: 83.8
    - type: ndcg_at_100
      value: 84.233
    - type: ndcg_at_1000
      value: 84.316
    - type: map_at_1
      value: 68.57799999999999
    - type: map_at_3
      value: 76.639
    - type: map_at_5
      value: 78.168
    - type: map_at_10
      value: 79.148
    - type: map_at_20
      value: 79.31
    - type: map_at_100
      value: 79.36800000000001
    - type: map_at_1000
      value: 79.37100000000001
    - type: recall_at_1
      value: 68.57799999999999
    - type: recall_at_3
      value: 85.47200000000001
    - type: recall_at_5
      value: 89.839
    - type: recall_at_10
      value: 95
    - type: recall_at_20
      value: 97
    - type: recall_at_100
      value: 99.333
    - type: recall_at_1000
      value: 100
    - type: precision_at_1
      value: 71.667
    - type: precision_at_3
      value: 31
    - type: precision_at_5
      value: 20.067
    - type: precision_at_10
      value: 10.767
    - type: precision_at_20
      value: 5.5
    - type: precision_at_100
      value: 1.123
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: mrr_at_1
      value: 71.6667
    - type: mrr_at_3
      value: 78.2222
    - type: mrr_at_5
      value: 79.0222
    - type: mrr_at_10
      value: 79.7295
    - type: mrr_at_20
      value: 79.83879999999999
    - type: mrr_at_100
      value: 79.89739999999999
    - type: mrr_at_1000
      value: 79.9004
    - type: nauc_ndcg_at_1_max
      value: 42.2431
    - type: nauc_ndcg_at_1_std
      value: -2.0832
    - type: nauc_ndcg_at_1_diff1
      value: 76.9413
    - type: nauc_ndcg_at_3_max
      value: 34.7709
    - type: nauc_ndcg_at_3_std
      value: -6.3732999999999995
    - type: nauc_ndcg_at_3_diff1
      value: 74.6789
    - type: nauc_ndcg_at_5_max
      value: 37.940400000000004
    - type: nauc_ndcg_at_5_std
      value: -3.9581999999999997
    - type: nauc_ndcg_at_5_diff1
      value: 75.22330000000001
    - type: nauc_ndcg_at_10_max
      value: 41.6103
    - type: nauc_ndcg_at_10_std
      value: -0.0314
    - type: nauc_ndcg_at_10_diff1
      value: 75.2945
    - type: nauc_ndcg_at_20_max
      value: 42.524
    - type: nauc_ndcg_at_20_std
      value: 0.2979
    - type: nauc_ndcg_at_20_diff1
      value: 75.4989
    - type: nauc_ndcg_at_100_max
      value: 41.727399999999996
    - type: nauc_ndcg_at_100_std
      value: -0.4197
    - type: nauc_ndcg_at_100_diff1
      value: 75.7163
    - type: nauc_ndcg_at_1000_max
      value: 41.3855
    - type: nauc_ndcg_at_1000_std
      value: -0.6131
    - type: nauc_ndcg_at_1000_diff1
      value: 75.618
    - type: nauc_map_at_1_max
      value: 32.7432
    - type: nauc_map_at_1_std
      value: -10.6948
    - type: nauc_map_at_1_diff1
      value: 77.2203
    - type: nauc_map_at_3_max
      value: 32.7526
    - type: nauc_map_at_3_std
      value: -7.8953
    - type: nauc_map_at_3_diff1
      value: 75.88380000000001
    - type: nauc_map_at_5_max
      value: 36.868
    - type: nauc_map_at_5_std
      value: -4.5381
    - type: nauc_map_at_5_diff1
      value: 75.5504
    - type: nauc_map_at_10_max
      value: 39.0762
    - type: nauc_map_at_10_std
      value: -2.1559
    - type: nauc_map_at_10_diff1
      value: 75.5037
    - type: nauc_map_at_20_max
      value: 39.3914
    - type: nauc_map_at_20_std
      value: -2.075
    - type: nauc_map_at_20_diff1
      value: 75.5527
    - type: nauc_map_at_100_max
      value: 39.2883
    - type: nauc_map_at_100_std
      value: -2.1987
    - type: nauc_map_at_100_diff1
      value: 75.57979999999999
    - type: nauc_map_at_1000_max
      value: 39.278200000000005
    - type: nauc_map_at_1000_std
      value: -2.1991
    - type: nauc_map_at_1000_diff1
      value: 75.5776
    - type: nauc_recall_at_1_max
      value: 32.7432
    - type: nauc_recall_at_1_std
      value: -10.6948
    - type: nauc_recall_at_1_diff1
      value: 77.2203
    - type: nauc_recall_at_3_max
      value: 23.718500000000002
    - type: nauc_recall_at_3_std
      value: -14.9527
    - type: nauc_recall_at_3_diff1
      value: 70.99849999999999
    - type: nauc_recall_at_5_max
      value: 34.1278
    - type: nauc_recall_at_5_std
      value: -8.9991
    - type: nauc_recall_at_5_diff1
      value: 72.9131
    - type: nauc_recall_at_10_max
      value: 53.4174
    - type: nauc_recall_at_10_std
      value: 10.591299999999999
    - type: nauc_recall_at_10_diff1
      value: 72.1148
    - type: nauc_recall_at_20_max
      value: 74.4061
    - type: nauc_recall_at_20_std
      value: 23.5605
    - type: nauc_recall_at_20_diff1
      value: 74.515
    - type: nauc_recall_at_100_max
      value: 100
    - type: nauc_recall_at_100_std
      value: 41.4332
    - type: nauc_recall_at_100_diff1
      value: 93.4641
    - type: nauc_recall_at_1000_max
      value: null
    - type: nauc_recall_at_1000_std
      value: null
    - type: nauc_recall_at_1000_diff1
      value: null
    - type: nauc_precision_at_1_max
      value: 42.2431
    - type: nauc_precision_at_1_std
      value: -2.0832
    - type: nauc_precision_at_1_diff1
      value: 76.9413
    - type: nauc_precision_at_3_max
      value: 31.2606
    - type: nauc_precision_at_3_std
      value: 19.564300000000003
    - type: nauc_precision_at_3_diff1
      value: 27.538899999999998
    - type: nauc_precision_at_5_max
      value: 36.896
    - type: nauc_precision_at_5_std
      value: 32.9313
    - type: nauc_precision_at_5_diff1
      value: 5.233899999999999
    - type: nauc_precision_at_10_max
      value: 40.0781
    - type: nauc_precision_at_10_std
      value: 48.0555
    - type: nauc_precision_at_10_diff1
      value: -14.6074
    - type: nauc_precision_at_20_max
      value: 39.3814
    - type: nauc_precision_at_20_std
      value: 49.9845
    - type: nauc_precision_at_20_diff1
      value: -21.171
    - type: nauc_precision_at_100_max
      value: 36.6046
    - type: nauc_precision_at_100_std
      value: 53.1439
    - type: nauc_precision_at_100_diff1
      value: -30.216500000000003
    - type: nauc_precision_at_1000_max
      value: 34.7361
    - type: nauc_precision_at_1000_std
      value: 53.4891
    - type: nauc_precision_at_1000_diff1
      value: -33.8617
    - type: nauc_mrr_at_1_max
      value: 42.2431
    - type: nauc_mrr_at_1_std
      value: -2.0832
    - type: nauc_mrr_at_1_diff1
      value: 76.9413
    - type: nauc_mrr_at_3_max
      value: 40.1861
    - type: nauc_mrr_at_3_std
      value: -2.1431
    - type: nauc_mrr_at_3_diff1
      value: 75.3883
    - type: nauc_mrr_at_5_max
      value: 40.9913
    - type: nauc_mrr_at_5_std
      value: -1.6580000000000001
    - type: nauc_mrr_at_5_diff1
      value: 75.8294
    - type: nauc_mrr_at_10_max
      value: 41.8035
    - type: nauc_mrr_at_10_std
      value: -1.1311
    - type: nauc_mrr_at_10_diff1
      value: 75.9254
    - type: nauc_mrr_at_20_max
      value: 41.9873
    - type: nauc_mrr_at_20_std
      value: -1.1159000000000001
    - type: nauc_mrr_at_20_diff1
      value: 75.9764
    - type: nauc_mrr_at_100_max
      value: 41.890699999999995
    - type: nauc_mrr_at_100_std
      value: -1.239
    - type: nauc_mrr_at_100_diff1
      value: 76.00529999999999
    - type: nauc_mrr_at_1000_max
      value: 41.8809
    - type: nauc_mrr_at_1000_std
      value: -1.2392
    - type: nauc_mrr_at_1000_diff1
      value: 76.0031
    - type: main_score
      value: 83.279
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB SprintDuplicateQuestions (default)
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
      split: test
      type: mteb/sprintduplicatequestions-pairclassification
    metrics:
    - type: similarity_accuracy
      value: 99.8644
    - type: similarity_accuracy_threshold
      value: 85.02
    - type: similarity_f1
      value: 93.1875
    - type: similarity_f1_threshold
      value: 85.02
    - type: similarity_precision
      value: 92.6805
    - type: similarity_recall
      value: 93.7
    - type: similarity_ap
      value: 96.7847
    - type: cosine_accuracy
      value: 99.8644
    - type: cosine_accuracy_threshold
      value: 85.02
    - type: cosine_f1
      value: 93.1875
    - type: cosine_f1_threshold
      value: 85.02
    - type: cosine_precision
      value: 92.6805
    - type: cosine_recall
      value: 93.7
    - type: cosine_ap
      value: 96.7847
    - type: manhattan_accuracy
      value: 99.8634
    - type: manhattan_accuracy_threshold
      value: 2593.8221
    - type: manhattan_f1
      value: 93.1275
    - type: manhattan_f1_threshold
      value: 2593.8221
    - type: manhattan_precision
      value: 92.7579
    - type: manhattan_recall
      value: 93.5
    - type: manhattan_ap
      value: 96.806
    - type: euclidean_accuracy
      value: 99.8644
    - type: euclidean_accuracy_threshold
      value: 54.7358
    - type: euclidean_f1
      value: 93.1875
    - type: euclidean_f1_threshold
      value: 54.7358
    - type: euclidean_precision
      value: 92.6805
    - type: euclidean_recall
      value: 93.7
    - type: euclidean_ap
      value: 96.7847
    - type: dot_accuracy
      value: 99.8644
    - type: dot_accuracy_threshold
      value: 85.02
    - type: dot_f1
      value: 93.1875
    - type: dot_f1_threshold
      value: 85.02
    - type: dot_precision
      value: 92.6805
    - type: dot_recall
      value: 93.7
    - type: dot_ap
      value: 96.7847
    - type: max_accuracy
      value: 99.8644
    - type: max_f1
      value: 93.1875
    - type: max_precision
      value: 92.7579
    - type: max_recall
      value: 93.7
    - type: max_ap
      value: 96.806
    - type: main_score
      value: 96.806
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB StackExchangeClustering (default)
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
      split: test
      type: mteb/stackexchange-clustering
    metrics:
    - type: v_measure
      value: 81.7075
    - type: v_measure_std
      value: 2.4228
    - type: main_score
      value: 81.7075
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB StackExchangeClusteringP2P (default)
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
      split: test
      type: mteb/stackexchange-clustering-p2p
    metrics:
    - type: v_measure
      value: 39.836
    - type: v_measure_std
      value: 1.5339
    - type: main_score
      value: 39.836
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB StackOverflowDupQuestions (default)
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
      split: test
      type: mteb/stackoverflowdupquestions-reranking
    metrics:
    - type: map
      value: 62.9227
    - type: mrr
      value: 64.1239
    - type: nAUC_map_max
      value: 9.3055
    - type: nAUC_map_std
      value: 3.2321000000000004
    - type: nAUC_map_diff1
      value: 45.2884
    - type: nAUC_mrr_max
      value: 10.8913
    - type: nAUC_mrr_std
      value: 4.1469
    - type: nAUC_mrr_diff1
      value: 45.280300000000004
    - type: main_score
      value: 62.9227
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SummEval (default)
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
      split: test
      type: mteb/summeval
    metrics:
    - type: pearson
      value: 45.5445
    - type: spearman
      value: 40.5224
    - type: cosine_spearman
      value: 40.5224
    - type: cosine_pearson
      value: 45.5445
    - type: dot_spearman
      value: 40.5224
    - type: dot_pearson
      value: 45.5446
    - type: main_score
      value: 40.5224
    task:
      type: Summarization
  - dataset:
      config: default
      name: MTEB TRECCOVID (default)
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
      split: test
      type: mteb/trec-covid
    metrics:
    - type: ndcg_at_1
      value: 86
    - type: ndcg_at_3
      value: 86.70400000000001
    - type: ndcg_at_5
      value: 84.654
    - type: ndcg_at_10
      value: 80.972
    - type: ndcg_at_20
      value: 76.783
    - type: ndcg_at_100
      value: 63.146
    - type: ndcg_at_1000
      value: 56.424
    - type: map_at_1
      value: 0.251
    - type: map_at_3
      value: 0.719
    - type: map_at_5
      value: 1.131
    - type: map_at_10
      value: 2.0820000000000003
    - type: map_at_20
      value: 3.746
    - type: map_at_100
      value: 13.020999999999999
    - type: map_at_1000
      value: 31.527
    - type: recall_at_1
      value: 0.251
    - type: recall_at_3
      value: 0.742
    - type: recall_at_5
      value: 1.179
    - type: recall_at_10
      value: 2.237
    - type: recall_at_20
      value: 4.144
    - type: recall_at_100
      value: 16.054
    - type: recall_at_1000
      value: 52.76
    - type: precision_at_1
      value: 92
    - type: precision_at_3
      value: 92
    - type: precision_at_5
      value: 88.8
    - type: precision_at_10
      value: 85
    - type: precision_at_20
      value: 79.7
    - type: precision_at_100
      value: 64.53999999999999
    - type: precision_at_1000
      value: 24.471999999999998
    - type: mrr_at_1
      value: 92
    - type: mrr_at_3
      value: 95.6667
    - type: mrr_at_5
      value: 95.6667
    - type: mrr_at_10
      value: 95.6667
    - type: mrr_at_20
      value: 95.6667
    - type: mrr_at_100
      value: 95.6667
    - type: mrr_at_1000
      value: 95.6667
    - type: nauc_ndcg_at_1_max
      value: 7.0274
    - type: nauc_ndcg_at_1_std
      value: 41.318
    - type: nauc_ndcg_at_1_diff1
      value: -46.5125
    - type: nauc_ndcg_at_3_max
      value: 2.0167
    - type: nauc_ndcg_at_3_std
      value: 36.144999999999996
    - type: nauc_ndcg_at_3_diff1
      value: -17.705199999999998
    - type: nauc_ndcg_at_5_max
      value: -6.812
    - type: nauc_ndcg_at_5_std
      value: 41.8996
    - type: nauc_ndcg_at_5_diff1
      value: -14.7154
    - type: nauc_ndcg_at_10_max
      value: 15.1784
    - type: nauc_ndcg_at_10_std
      value: 51.709799999999994
    - type: nauc_ndcg_at_10_diff1
      value: -5.0968
    - type: nauc_ndcg_at_20_max
      value: 28.403200000000002
    - type: nauc_ndcg_at_20_std
      value: 59.824299999999994
    - type: nauc_ndcg_at_20_diff1
      value: -14.036000000000001
    - type: nauc_ndcg_at_100_max
      value: 35.4195
    - type: nauc_ndcg_at_100_std
      value: 75.7747
    - type: nauc_ndcg_at_100_diff1
      value: -10.4627
    - type: nauc_ndcg_at_1000_max
      value: 31.450400000000002
    - type: nauc_ndcg_at_1000_std
      value: 78.85940000000001
    - type: nauc_ndcg_at_1000_diff1
      value: -1.3263
    - type: nauc_map_at_1_max
      value: -3.8297
    - type: nauc_map_at_1_std
      value: -10.6113
    - type: nauc_map_at_1_diff1
      value: 9.2146
    - type: nauc_map_at_3_max
      value: -3.1165000000000003
    - type: nauc_map_at_3_std
      value: -8.4396
    - type: nauc_map_at_3_diff1
      value: 14.183000000000002
    - type: nauc_map_at_5_max
      value: -4.4023
    - type: nauc_map_at_5_std
      value: -6.641500000000001
    - type: nauc_map_at_5_diff1
      value: 16.1186
    - type: nauc_map_at_10_max
      value: 1.802
    - type: nauc_map_at_10_std
      value: 0.9958
    - type: nauc_map_at_10_diff1
      value: 20.3485
    - type: nauc_map_at_20_max
      value: 10.9146
    - type: nauc_map_at_20_std
      value: 10.3413
    - type: nauc_map_at_20_diff1
      value: 14.7839
    - type: nauc_map_at_100_max
      value: 25.633
    - type: nauc_map_at_100_std
      value: 44.9724
    - type: nauc_map_at_100_diff1
      value: 6.572699999999999
    - type: nauc_map_at_1000_max
      value: 33.8688
    - type: nauc_map_at_1000_std
      value: 76.9255
    - type: nauc_map_at_1000_diff1
      value: -5.8205
    - type: nauc_recall_at_1_max
      value: -3.8297
    - type: nauc_recall_at_1_std
      value: -10.6113
    - type: nauc_recall_at_1_diff1
      value: 9.2146
    - type: nauc_recall_at_3_max
      value: -6.209
    - type: nauc_recall_at_3_std
      value: -11.3272
    - type: nauc_recall_at_3_diff1
      value: 16.497500000000002
    - type: nauc_recall_at_5_max
      value: -7.6928
    - type: nauc_recall_at_5_std
      value: -8.9985
    - type: nauc_recall_at_5_diff1
      value: 19.028100000000002
    - type: nauc_recall_at_10_max
      value: -1.3407
    - type: nauc_recall_at_10_std
      value: -2.5698
    - type: nauc_recall_at_10_diff1
      value: 21.570700000000002
    - type: nauc_recall_at_20_max
      value: 6.866700000000001
    - type: nauc_recall_at_20_std
      value: 5.7298
    - type: nauc_recall_at_20_diff1
      value: 16.050800000000002
    - type: nauc_recall_at_100_max
      value: 16.4856
    - type: nauc_recall_at_100_std
      value: 33.1774
    - type: nauc_recall_at_100_diff1
      value: 12.0273
    - type: nauc_recall_at_1000_max
      value: 25.3677
    - type: nauc_recall_at_1000_std
      value: 71.1541
    - type: nauc_recall_at_1000_diff1
      value: 0.796
    - type: nauc_precision_at_1_max
      value: 57.236200000000004
    - type: nauc_precision_at_1_std
      value: 47.7241
    - type: nauc_precision_at_1_diff1
      value: -57.8198
    - type: nauc_precision_at_3_max
      value: 35.6953
    - type: nauc_precision_at_3_std
      value: 31.414199999999997
    - type: nauc_precision_at_3_diff1
      value: -6.7696000000000005
    - type: nauc_precision_at_5_max
      value: 1.699
    - type: nauc_precision_at_5_std
      value: 37.6284
    - type: nauc_precision_at_5_diff1
      value: -4.9533000000000005
    - type: nauc_precision_at_10_max
      value: 31.645400000000002
    - type: nauc_precision_at_10_std
      value: 48.4684
    - type: nauc_precision_at_10_diff1
      value: 8.3324
    - type: nauc_precision_at_20_max
      value: 45.7958
    - type: nauc_precision_at_20_std
      value: 56.3558
    - type: nauc_precision_at_20_diff1
      value: -7.8348
    - type: nauc_precision_at_100_max
      value: 40.1005
    - type: nauc_precision_at_100_std
      value: 73.342
    - type: nauc_precision_at_100_diff1
      value: -7.284400000000001
    - type: nauc_precision_at_1000_max
      value: 27.9268
    - type: nauc_precision_at_1000_std
      value: 50.145799999999994
    - type: nauc_precision_at_1000_diff1
      value: -15.678700000000001
    - type: nauc_mrr_at_1_max
      value: 57.236200000000004
    - type: nauc_mrr_at_1_std
      value: 47.7241
    - type: nauc_mrr_at_1_diff1
      value: -57.8198
    - type: nauc_mrr_at_3_max
      value: 53.7779
    - type: nauc_mrr_at_3_std
      value: 51.74530000000001
    - type: nauc_mrr_at_3_diff1
      value: -49.1094
    - type: nauc_mrr_at_5_max
      value: 53.7779
    - type: nauc_mrr_at_5_std
      value: 51.74530000000001
    - type: nauc_mrr_at_5_diff1
      value: -49.1094
    - type: nauc_mrr_at_10_max
      value: 53.7779
    - type: nauc_mrr_at_10_std
      value: 51.74530000000001
    - type: nauc_mrr_at_10_diff1
      value: -49.1094
    - type: nauc_mrr_at_20_max
      value: 53.7779
    - type: nauc_mrr_at_20_std
      value: 51.74530000000001
    - type: nauc_mrr_at_20_diff1
      value: -49.1094
    - type: nauc_mrr_at_100_max
      value: 53.7779
    - type: nauc_mrr_at_100_std
      value: 51.74530000000001
    - type: nauc_mrr_at_100_diff1
      value: -49.1094
    - type: nauc_mrr_at_1000_max
      value: 53.7779
    - type: nauc_mrr_at_1000_std
      value: 51.74530000000001
    - type: nauc_mrr_at_1000_diff1
      value: -49.1094
    - type: main_score
      value: 80.972
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB Touche2020 (default)
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
      split: test
      type: mteb/touche2020
    metrics:
    - type: ndcg_at_1
      value: 45.918
    - type: ndcg_at_3
      value: 42.414
    - type: ndcg_at_5
      value: 36.911
    - type: ndcg_at_10
      value: 34.059
    - type: ndcg_at_20
      value: 33.789
    - type: ndcg_at_100
      value: 43.24
    - type: ndcg_at_1000
      value: 53.028
    - type: map_at_1
      value: 3.711
    - type: map_at_3
      value: 8.031
    - type: map_at_5
      value: 10.174999999999999
    - type: map_at_10
      value: 13.745
    - type: map_at_20
      value: 16.833000000000002
    - type: map_at_100
      value: 20.534
    - type: map_at_1000
      value: 21.929000000000002
    - type: recall_at_1
      value: 3.711
    - type: recall_at_3
      value: 9.289
    - type: recall_at_5
      value: 12.469
    - type: recall_at_10
      value: 20.31
    - type: recall_at_20
      value: 28.549999999999997
    - type: recall_at_100
      value: 50.132
    - type: recall_at_1000
      value: 78.636
    - type: precision_at_1
      value: 48.980000000000004
    - type: precision_at_3
      value: 43.537
    - type: precision_at_5
      value: 35.510000000000005
    - type: precision_at_10
      value: 29.592000000000002
    - type: precision_at_20
      value: 21.633
    - type: precision_at_100
      value: 8.265
    - type: precision_at_1000
      value: 1.478
    - type: mrr_at_1
      value: 48.9796
    - type: mrr_at_3
      value: 61.9048
    - type: mrr_at_5
      value: 62.8231
    - type: mrr_at_10
      value: 64.78620000000001
    - type: mrr_at_20
      value: 64.8882
    - type: mrr_at_100
      value: 64.9667
    - type: mrr_at_1000
      value: 64.9667
    - type: nauc_ndcg_at_1_max
      value: -14.377
    - type: nauc_ndcg_at_1_std
      value: -24.7998
    - type: nauc_ndcg_at_1_diff1
      value: -2.7112000000000003
    - type: nauc_ndcg_at_3_max
      value: -25.411
    - type: nauc_ndcg_at_3_std
      value: -21.4105
    - type: nauc_ndcg_at_3_diff1
      value: 11.6233
    - type: nauc_ndcg_at_5_max
      value: -18.7583
    - type: nauc_ndcg_at_5_std
      value: -12.3778
    - type: nauc_ndcg_at_5_diff1
      value: 2.0221
    - type: nauc_ndcg_at_10_max
      value: -20.5164
    - type: nauc_ndcg_at_10_std
      value: -15.9037
    - type: nauc_ndcg_at_10_diff1
      value: 4.8377
    - type: nauc_ndcg_at_20_max
      value: -24.3335
    - type: nauc_ndcg_at_20_std
      value: -15.4334
    - type: nauc_ndcg_at_20_diff1
      value: 5.2053
    - type: nauc_ndcg_at_100_max
      value: -27.9931
    - type: nauc_ndcg_at_100_std
      value: -0.267
    - type: nauc_ndcg_at_100_diff1
      value: 8.0295
    - type: nauc_ndcg_at_1000_max
      value: -22.2584
    - type: nauc_ndcg_at_1000_std
      value: 16.6679
    - type: nauc_ndcg_at_1000_diff1
      value: -0.8999999999999999
    - type: nauc_map_at_1_max
      value: -19.5845
    - type: nauc_map_at_1_std
      value: -33.0644
    - type: nauc_map_at_1_diff1
      value: -5.815300000000001
    - type: nauc_map_at_3_max
      value: -28.4895
    - type: nauc_map_at_3_std
      value: -32.191199999999995
    - type: nauc_map_at_3_diff1
      value: 9.8452
    - type: nauc_map_at_5_max
      value: -17.3979
    - type: nauc_map_at_5_std
      value: -21.3281
    - type: nauc_map_at_5_diff1
      value: -2.7651
    - type: nauc_map_at_10_max
      value: -16.5472
    - type: nauc_map_at_10_std
      value: -21.7069
    - type: nauc_map_at_10_diff1
      value: -1.7826000000000002
    - type: nauc_map_at_20_max
      value: -18.6049
    - type: nauc_map_at_20_std
      value: -17.8565
    - type: nauc_map_at_20_diff1
      value: -0.0181
    - type: nauc_map_at_100_max
      value: -20.030800000000003
    - type: nauc_map_at_100_std
      value: -8.6978
    - type: nauc_map_at_100_diff1
      value: 1.1159000000000001
    - type: nauc_map_at_1000_max
      value: -18.5756
    - type: nauc_map_at_1000_std
      value: -4.4186000000000005
    - type: nauc_map_at_1000_diff1
      value: -0.7358
    - type: nauc_recall_at_1_max
      value: -19.5845
    - type: nauc_recall_at_1_std
      value: -33.0644
    - type: nauc_recall_at_1_diff1
      value: -5.815300000000001
    - type: nauc_recall_at_3_max
      value: -33.051199999999994
    - type: nauc_recall_at_3_std
      value: -30.767099999999996
    - type: nauc_recall_at_3_diff1
      value: 11.7941
    - type: nauc_recall_at_5_max
      value: -18.8571
    - type: nauc_recall_at_5_std
      value: -17.8328
    - type: nauc_recall_at_5_diff1
      value: -5.9348
    - type: nauc_recall_at_10_max
      value: -20.657700000000002
    - type: nauc_recall_at_10_std
      value: -20.5083
    - type: nauc_recall_at_10_diff1
      value: 0.7172999999999999
    - type: nauc_recall_at_20_max
      value: -21.78
    - type: nauc_recall_at_20_std
      value: -12.2194
    - type: nauc_recall_at_20_diff1
      value: 2.4215
    - type: nauc_recall_at_100_max
      value: -28.1499
    - type: nauc_recall_at_100_std
      value: 12.5616
    - type: nauc_recall_at_100_diff1
      value: 6.282400000000001
    - type: nauc_recall_at_1000_max
      value: -3.4448
    - type: nauc_recall_at_1000_std
      value: 70.2153
    - type: nauc_recall_at_1000_diff1
      value: -20.1278
    - type: nauc_precision_at_1_max
      value: -16.253600000000002
    - type: nauc_precision_at_1_std
      value: -28.961100000000002
    - type: nauc_precision_at_1_diff1
      value: -4.5123999999999995
    - type: nauc_precision_at_3_max
      value: -31.231399999999997
    - type: nauc_precision_at_3_std
      value: -21.6787
    - type: nauc_precision_at_3_diff1
      value: 14.080799999999998
    - type: nauc_precision_at_5_max
      value: -18.4843
    - type: nauc_precision_at_5_std
      value: -4.0988
    - type: nauc_precision_at_5_diff1
      value: -2.3491
    - type: nauc_precision_at_10_max
      value: -21.7679
    - type: nauc_precision_at_10_std
      value: -2.7599
    - type: nauc_precision_at_10_diff1
      value: 10.6409
    - type: nauc_precision_at_20_max
      value: -17.049300000000002
    - type: nauc_precision_at_20_std
      value: 12.609200000000001
    - type: nauc_precision_at_20_diff1
      value: 11.3369
    - type: nauc_precision_at_100_max
      value: -9.675699999999999
    - type: nauc_precision_at_100_std
      value: 44.9955
    - type: nauc_precision_at_100_diff1
      value: 5.7501999999999995
    - type: nauc_precision_at_1000_max
      value: 29.789500000000004
    - type: nauc_precision_at_1000_std
      value: 58.205200000000005
    - type: nauc_precision_at_1000_diff1
      value: -22.6755
    - type: nauc_mrr_at_1_max
      value: -16.253600000000002
    - type: nauc_mrr_at_1_std
      value: -28.961100000000002
    - type: nauc_mrr_at_1_diff1
      value: -4.5123999999999995
    - type: nauc_mrr_at_3_max
      value: -30.4084
    - type: nauc_mrr_at_3_std
      value: -29.1267
    - type: nauc_mrr_at_3_diff1
      value: -2.9535
    - type: nauc_mrr_at_5_max
      value: -31.6427
    - type: nauc_mrr_at_5_std
      value: -27.5858
    - type: nauc_mrr_at_5_diff1
      value: -2.032
    - type: nauc_mrr_at_10_max
      value: -31.1008
    - type: nauc_mrr_at_10_std
      value: -27.338099999999997
    - type: nauc_mrr_at_10_diff1
      value: -0.1675
    - type: nauc_mrr_at_20_max
      value: -30.7834
    - type: nauc_mrr_at_20_std
      value: -27.6591
    - type: nauc_mrr_at_20_diff1
      value: -0.3828
    - type: nauc_mrr_at_100_max
      value: -30.3645
    - type: nauc_mrr_at_100_std
      value: -28.003
    - type: nauc_mrr_at_100_diff1
      value: -0.48979999999999996
    - type: nauc_mrr_at_1000_max
      value: -30.3645
    - type: nauc_mrr_at_1000_std
      value: -28.003
    - type: nauc_mrr_at_1000_diff1
      value: -0.48979999999999996
    - type: main_score
      value: 34.059
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB ToxicConversationsClassification (default)
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
      split: test
      type: mteb/toxic_conversations_50k
    metrics:
    - type: accuracy
      value: 95.1318
    - type: f1
      value: 84.8018
    - type: f1_weighted
      value: 95.3488
    - type: ap
      value: 54.4247
    - type: ap_weighted
      value: 54.4247
    - type: main_score
      value: 95.1318
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB TweetSentimentExtractionClassification (default)
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
      split: test
      type: mteb/tweet_sentiment_extraction
    metrics:
    - type: accuracy
      value: 81.4488
    - type: f1
      value: 81.77990000000001
    - type: f1_weighted
      value: 81.4677
    - type: main_score
      value: 81.4488
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB TwentyNewsgroupsClustering (default)
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
      split: test
      type: mteb/twentynewsgroups-clustering
    metrics:
    - type: v_measure
      value: 71.18560000000001
    - type: v_measure_std
      value: 1.1396
    - type: main_score
      value: 71.18560000000001
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB TwitterSemEval2015 (default)
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
      split: test
      type: mteb/twittersemeval2015-pairclassification
    metrics:
    - type: similarity_accuracy
      value: 88.3293
    - type: similarity_accuracy_threshold
      value: 89.5055
    - type: similarity_f1
      value: 72.9896
    - type: similarity_f1_threshold
      value: 87.6934
    - type: similarity_precision
      value: 69.5767
    - type: similarity_recall
      value: 76.7546
    - type: similarity_ap
      value: 80.33160000000001
    - type: cosine_accuracy
      value: 88.3293
    - type: cosine_accuracy_threshold
      value: 89.5055
    - type: cosine_f1
      value: 72.9896
    - type: cosine_f1_threshold
      value: 87.6934
    - type: cosine_precision
      value: 69.5767
    - type: cosine_recall
      value: 76.7546
    - type: cosine_ap
      value: 80.33160000000001
    - type: manhattan_accuracy
      value: 88.29350000000001
    - type: manhattan_accuracy_threshold
      value: 2182.2741
    - type: manhattan_f1
      value: 73.0484
    - type: manhattan_f1_threshold
      value: 2329.781
    - type: manhattan_precision
      value: 70.9245
    - type: manhattan_recall
      value: 75.3034
    - type: manhattan_ap
      value: 80.3871
    - type: euclidean_accuracy
      value: 88.3293
    - type: euclidean_accuracy_threshold
      value: 45.8136
    - type: euclidean_f1
      value: 72.9896
    - type: euclidean_f1_threshold
      value: 49.6117
    - type: euclidean_precision
      value: 69.5767
    - type: euclidean_recall
      value: 76.7546
    - type: euclidean_ap
      value: 80.33160000000001
    - type: dot_accuracy
      value: 88.3293
    - type: dot_accuracy_threshold
      value: 89.5055
    - type: dot_f1
      value: 72.9896
    - type: dot_f1_threshold
      value: 87.6934
    - type: dot_precision
      value: 69.5767
    - type: dot_recall
      value: 76.7546
    - type: dot_ap
      value: 80.33160000000001
    - type: max_accuracy
      value: 88.3293
    - type: max_f1
      value: 73.0484
    - type: max_precision
      value: 70.9245
    - type: max_recall
      value: 76.7546
    - type: max_ap
      value: 80.3871
    - type: main_score
      value: 80.3871
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB TwitterURLCorpus (default)
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
      split: test
      type: mteb/twitterurlcorpus-pairclassification
    metrics:
    - type: similarity_accuracy
      value: 89.5098
    - type: similarity_accuracy_threshold
      value: 86.3375
    - type: similarity_f1
      value: 79.5103
    - type: similarity_f1_threshold
      value: 85.09649999999999
    - type: similarity_precision
      value: 77.381
    - type: similarity_recall
      value: 81.76010000000001
    - type: similarity_ap
      value: 87.07770000000001
    - type: cosine_accuracy
      value: 89.5098
    - type: cosine_accuracy_threshold
      value: 86.3375
    - type: cosine_f1
      value: 79.5103
    - type: cosine_f1_threshold
      value: 85.09649999999999
    - type: cosine_precision
      value: 77.381
    - type: cosine_recall
      value: 81.76010000000001
    - type: cosine_ap
      value: 87.07770000000001
    - type: manhattan_accuracy
      value: 89.5195
    - type: manhattan_accuracy_threshold
      value: 2522.3334999999997
    - type: manhattan_f1
      value: 79.4922
    - type: manhattan_f1_threshold
      value: 2646.0447
    - type: manhattan_precision
      value: 75.5303
    - type: manhattan_recall
      value: 83.8928
    - type: manhattan_ap
      value: 87.0889
    - type: euclidean_accuracy
      value: 89.5098
    - type: euclidean_accuracy_threshold
      value: 52.2734
    - type: euclidean_f1
      value: 79.5103
    - type: euclidean_f1_threshold
      value: 54.595800000000004
    - type: euclidean_precision
      value: 77.381
    - type: euclidean_recall
      value: 81.76010000000001
    - type: euclidean_ap
      value: 87.07770000000001
    - type: dot_accuracy
      value: 89.5098
    - type: dot_accuracy_threshold
      value: 86.3375
    - type: dot_f1
      value: 79.5103
    - type: dot_f1_threshold
      value: 85.09649999999999
    - type: dot_precision
      value: 77.381
    - type: dot_recall
      value: 81.76010000000001
    - type: dot_ap
      value: 87.07770000000001
    - type: max_accuracy
      value: 89.5195
    - type: max_f1
      value: 79.5103
    - type: max_precision
      value: 77.381
    - type: max_recall
      value: 83.8928
    - type: max_ap
      value: 87.0889
    - type: main_score
      value: 87.0889
    task:
      type: PairClassification
tags:
- mteb
---


# Gemma Embeddings v1.0

GemmaEmbed is a dense-vector embedding model, trained especially for retrieval.  As of December 12, 2024, GemmaEmbed achieves the #1 position overall on the MTEB leaderboard, with a score of 72.72.  

# Important Notes
* This is not an official Google product.
* This is a research project.

# Results summary

Results comparing with BGE-EN-ICL and NV-Embed-v2 on each task in [MTEB](https://huggingface.co./spaces/mteb/leaderboard):

Model | Total (56) |Classification (12) | Classification Pair (3) | STS (10) |Clustering (11) | Reranking (4) | Retrieval (15) | Summary (1)
-- | -- | -- | -- | -- | -- | -- | -- | --
bge-en-icl | 0.7167 | 0.8895 | 0.8814 | 0.8425 | 0.5789 | 0.5986 | 0.6216 | 0.3077
NV-Embed-v2 | 0.7231 | 0.9037 | 0.8867 | 0.8431 | 0.5846 | 0.6065 | 0.6265 | 0.3070
Gemma-Embeddings-v1.0 | 0.7272 | 0.9000 | 0.8809 | 0.8423 | 0.5826 | 0.6214 | 0.6371 | 0.4052

# Model & Data

Our base encoder model is [Gemma2 9B](https://huggingface.co./google/gemma-2-9b). 

We use the [BGE-EN-ICL training data](https://huggingface.co./datasets/cfli/bge-full-data).

# Research Team

* Nicholas Monath
* Michael Boratko
* Seungyeon Kim
* Andrew McCallum
* Rob Fergus
* Manzil Zaheer