README.md

---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
- arctic
- snowflake-arctic-embed
- transformers.js
- mlx
license: apache-2.0
language:
- af
- ar
- az
- be
- bg
- bn
- ca
- ceb
- cs
- cy
- da
- de
- el
- en
- es
- et
- eu
- fa
- fi
- fr
- gl
- gu
- he
- hi
- hr
- ht
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ky
- lo
- lt
- lv
- mk
- ml
- mn
- mr
- ms
- my
- ne
- nl
- pa
- pl
- pt
- qu
- ro
- ru
- si
- sk
- sl
- so
- sq
- sr
- sv
- sw
- ta
- te
- th
- tl
- tr
- uk
- ur
- vi
- yo
- zh
model-index:
- name: snowflake-arctic-embed-l-v2.0
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en-ext)
      type: mteb/amazon_counterfactual
      config: en-ext
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 67.039
    - type: f1
      value: 55.1806
    - type: f1_weighted
      value: 73.41149999999999
    - type: ap
      value: 17.9914
    - type: ap_weighted
      value: 17.9914
    - type: main_score
      value: 67.039
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 65.59700000000001
    - type: f1
      value: 60.244299999999996
    - type: f1_weighted
      value: 68.9975
    - type: ap
      value: 29.762100000000004
    - type: ap_weighted
      value: 29.762100000000004
    - type: main_score
      value: 65.59700000000001
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification (default)
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 74.2565
    - type: f1
      value: 74.0291
    - type: f1_weighted
      value: 74.0291
    - type: ap
      value: 68.7595
    - type: ap_weighted
      value: 68.7595
    - type: main_score
      value: 74.2565
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 34.946
    - type: f1
      value: 34.2853
    - type: f1_weighted
      value: 34.2853
    - type: main_score
      value: 34.946
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna (default)
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: ndcg_at_1
      value: 33.286
    - type: ndcg_at_3
      value: 49.051
    - type: ndcg_at_5
      value: 54.107000000000006
    - type: ndcg_at_10
      value: 59.146
    - type: ndcg_at_20
      value: 60.897999999999996
    - type: ndcg_at_100
      value: 61.78399999999999
    - type: ndcg_at_1000
      value: 61.845000000000006
    - type: map_at_1
      value: 33.286
    - type: map_at_3
      value: 45.14
    - type: map_at_5
      value: 47.939
    - type: map_at_10
      value: 50.046
    - type: map_at_20
      value: 50.56
    - type: map_at_100
      value: 50.708
    - type: map_at_1000
      value: 50.712
    - type: recall_at_1
      value: 33.286
    - type: recall_at_3
      value: 60.38400000000001
    - type: recall_at_5
      value: 72.688
    - type: recall_at_10
      value: 88.122
    - type: recall_at_20
      value: 94.808
    - type: recall_at_100
      value: 99.21799999999999
    - type: recall_at_1000
      value: 99.644
    - type: precision_at_1
      value: 33.286
    - type: precision_at_3
      value: 20.128
    - type: precision_at_5
      value: 14.538
    - type: precision_at_10
      value: 8.812000000000001
    - type: precision_at_20
      value: 4.74
    - type: precision_at_100
      value: 0.992
    - type: precision_at_1000
      value: 0.1
    - type: mrr_at_1
      value: 33.926
    - type: mrr_at_3
      value: 45.3414
    - type: mrr_at_5
      value: 48.1828
    - type: mrr_at_10
      value: 50.270700000000005
    - type: mrr_at_20
      value: 50.7844
    - type: mrr_at_100
      value: 50.9259
    - type: mrr_at_1000
      value: 50.9294
    - type: nauc_ndcg_at_1_max
      value: -10.305
    - type: nauc_ndcg_at_1_std
      value: -15.674199999999999
    - type: nauc_ndcg_at_1_diff1
      value: 18.6355
    - type: nauc_ndcg_at_3_max
      value: -7.744
    - type: nauc_ndcg_at_3_std
      value: -16.894000000000002
    - type: nauc_ndcg_at_3_diff1
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    - type: nauc_ndcg_at_5_max
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    - type: nauc_ndcg_at_5_std
      value: -16.1382
    - type: nauc_ndcg_at_5_diff1
      value: 13.8214
    - type: nauc_ndcg_at_10_max
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    - type: nauc_ndcg_at_10_std
      value: -15.8073
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    - type: nauc_ndcg_at_20_max
      value: -6.9801
    - type: nauc_ndcg_at_20_std
      value: -15.068699999999998
    - type: nauc_ndcg_at_20_diff1
      value: 14.2013
    - type: nauc_ndcg_at_100_max
      value: -7.5221
    - type: nauc_ndcg_at_100_std
      value: -15.417200000000001
    - type: nauc_ndcg_at_100_diff1
      value: 15.1072
    - type: nauc_ndcg_at_1000_max
      value: -7.6931
    - type: nauc_ndcg_at_1000_std
      value: -15.5367
    - type: nauc_ndcg_at_1000_diff1
      value: 15.001700000000001
    - type: nauc_map_at_1_max
      value: -10.305
    - type: nauc_map_at_1_std
      value: -15.674199999999999
    - type: nauc_map_at_1_diff1
      value: 18.6355
    - type: nauc_map_at_3_max
      value: -8.4505
    - type: nauc_map_at_3_std
      value: -16.5487
    - type: nauc_map_at_3_diff1
      value: 15.965599999999998
    - type: nauc_map_at_5_max
      value: -7.8429
    - type: nauc_map_at_5_std
      value: -16.1332
    - type: nauc_map_at_5_diff1
      value: 15.0893
    - type: nauc_map_at_10_max
      value: -8.3186
    - type: nauc_map_at_10_std
      value: -15.979399999999998
    - type: nauc_map_at_10_diff1
      value: 15.136199999999999
    - type: nauc_map_at_20_max
      value: -8.1697
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      value: -15.8241
    - type: nauc_map_at_20_diff1
      value: 15.260599999999998
    - type: nauc_map_at_100_max
      value: -8.2285
    - type: nauc_map_at_100_std
      value: -15.8624
    - type: nauc_map_at_100_diff1
      value: 15.412600000000001
    - type: nauc_map_at_1000_max
      value: -8.2359
    - type: nauc_map_at_1000_std
      value: -15.867
    - type: nauc_map_at_1000_diff1
      value: 15.408
    - type: nauc_recall_at_1_max
      value: -10.305
    - type: nauc_recall_at_1_std
      value: -15.674199999999999
    - type: nauc_recall_at_1_diff1
      value: 18.6355
    - type: nauc_recall_at_3_max
      value: -5.5097
    - type: nauc_recall_at_3_std
      value: -17.9896
    - type: nauc_recall_at_3_diff1
      value: 13.9525
    - type: nauc_recall_at_5_max
      value: -0.9383
    - type: nauc_recall_at_5_std
      value: -16.035
    - type: nauc_recall_at_5_diff1
      value: 8.8431
    - type: nauc_recall_at_10_max
      value: -2.8548
    - type: nauc_recall_at_10_std
      value: -14.1203
    - type: nauc_recall_at_10_diff1
      value: 3.2265
    - type: nauc_recall_at_20_max
      value: 14.2043
    - type: nauc_recall_at_20_std
      value: 2.1298999999999997
    - type: nauc_recall_at_20_diff1
      value: -1.9900000000000002
    - type: nauc_recall_at_100_max
      value: 44.0173
    - type: nauc_recall_at_100_std
      value: 42.131800000000005
    - type: nauc_recall_at_100_diff1
      value: 29.9983
    - type: nauc_recall_at_1000_max
      value: 25.9434
    - type: nauc_recall_at_1000_std
      value: 53.9252
    - type: nauc_recall_at_1000_diff1
      value: -0.9778
    - type: nauc_precision_at_1_max
      value: -10.305
    - type: nauc_precision_at_1_std
      value: -15.674199999999999
    - type: nauc_precision_at_1_diff1
      value: 18.6355
    - type: nauc_precision_at_3_max
      value: -5.5097
    - type: nauc_precision_at_3_std
      value: -17.9896
    - type: nauc_precision_at_3_diff1
      value: 13.9525
    - type: nauc_precision_at_5_max
      value: -0.9383
    - type: nauc_precision_at_5_std
      value: -16.035
    - type: nauc_precision_at_5_diff1
      value: 8.8431
    - type: nauc_precision_at_10_max
      value: -2.8548
    - type: nauc_precision_at_10_std
      value: -14.1203
    - type: nauc_precision_at_10_diff1
      value: 3.2265
    - type: nauc_precision_at_20_max
      value: 14.2043
    - type: nauc_precision_at_20_std
      value: 2.1298999999999997
    - type: nauc_precision_at_20_diff1
      value: -1.9900000000000002
    - type: nauc_precision_at_100_max
      value: 44.0173
    - type: nauc_precision_at_100_std
      value: 42.131800000000005
    - type: nauc_precision_at_100_diff1
      value: 29.9983
    - type: nauc_precision_at_1000_max
      value: 25.9434
    - type: nauc_precision_at_1000_std
      value: 53.9252
    - type: nauc_precision_at_1000_diff1
      value: -0.9778
    - type: nauc_mrr_at_1_max
      value: -9.833
    - type: nauc_mrr_at_1_std
      value: -14.8351
    - type: nauc_mrr_at_1_diff1
      value: 16.7604
    - type: nauc_mrr_at_3_max
      value: -9.0116
    - type: nauc_mrr_at_3_std
      value: -16.296
    - type: nauc_mrr_at_3_diff1
      value: 14.178199999999999
    - type: nauc_mrr_at_5_max
      value: -8.308300000000001
    - type: nauc_mrr_at_5_std
      value: -15.751999999999999
    - type: nauc_mrr_at_5_diff1
      value: 13.306299999999998
    - type: nauc_mrr_at_10_max
      value: -8.7962
    - type: nauc_mrr_at_10_std
      value: -15.688099999999999
    - type: nauc_mrr_at_10_diff1
      value: 13.2589
    - type: nauc_mrr_at_20_max
      value: -8.6773
    - type: nauc_mrr_at_20_std
      value: -15.479499999999998
    - type: nauc_mrr_at_20_diff1
      value: 13.354
    - type: nauc_mrr_at_100_max
      value: -8.7533
    - type: nauc_mrr_at_100_std
      value: -15.553600000000001
    - type: nauc_mrr_at_100_diff1
      value: 13.4796
    - type: nauc_mrr_at_1000_max
      value: -8.7608
    - type: nauc_mrr_at_1000_std
      value: -15.5582
    - type: nauc_mrr_at_1000_diff1
      value: 13.4748
    - type: main_score
      value: 59.146
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P (default)
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 43.9715
    - type: v_measure_std
      value: 13.4325
    - type: main_score
      value: 43.9715
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S (default)
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 34.775800000000004
    - type: v_measure_std
      value: 13.922799999999999
    - type: main_score
      value: 34.775800000000004
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions (default)
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 63.3521
    - type: mrr
      value: 77.5965
    - type: nAUC_map_max
      value: 21.2353
    - type: nAUC_map_std
      value: 17.002100000000002
    - type: nAUC_map_diff1
      value: 3.8135000000000003
    - type: nAUC_mrr_max
      value: 35.058299999999996
    - type: nAUC_mrr_std
      value: 20.432
    - type: nAUC_mrr_diff1
      value: 9.2584
    - type: main_score
      value: 63.3521
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES (default)
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: pearson
      value: 89.8072
    - type: spearman
      value: 87.2875
    - type: cosine_pearson
      value: 89.8072
    - type: cosine_spearman
      value: 87.2875
    - type: manhattan_pearson
      value: 87.9173
    - type: manhattan_spearman
      value: 86.7327
    - type: euclidean_pearson
      value: 88.21600000000001
    - type: euclidean_spearman
      value: 87.2875
    - type: main_score
      value: 87.2875
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification (default)
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 81.8149
    - type: f1
      value: 81.2226
    - type: f1_weighted
      value: 81.2226
    - type: main_score
      value: 81.8149
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P (default)
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 35.0927
    - type: v_measure_std
      value: 0.7048
    - type: main_score
      value: 35.0927
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S (default)
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 30.220999999999997
    - type: v_measure_std
      value: 1.107
    - type: main_score
      value: 30.220999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval (default)
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
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      value: 44.349
    - type: ndcg_at_3
      value: 50.109
    - type: ndcg_at_5
      value: 52.88699999999999
    - type: ndcg_at_10
      value: 55.799
    - type: ndcg_at_20
      value: 57.589999999999996
    - type: ndcg_at_100
      value: 60.539
    - type: ndcg_at_1000
      value: 61.897000000000006
    - type: map_at_1
      value: 36.230000000000004
    - type: map_at_3
      value: 44.929
    - type: map_at_5
      value: 47.191
    - type: map_at_10
      value: 48.88
    - type: map_at_20
      value: 49.685
    - type: map_at_100
      value: 50.327
    - type: map_at_1000
      value: 50.431000000000004
    - type: recall_at_1
      value: 36.230000000000004
    - type: recall_at_3
      value: 53.173
    - type: recall_at_5
      value: 60.35
    - type: recall_at_10
      value: 69.07
    - type: recall_at_20
      value: 75.371
    - type: recall_at_100
      value: 88.736
    - type: recall_at_1000
      value: 96.75399999999999
    - type: precision_at_1
      value: 44.349
    - type: precision_at_3
      value: 23.748
    - type: precision_at_5
      value: 17.368
    - type: precision_at_10
      value: 10.629
    - type: precision_at_20
      value: 6.152
    - type: precision_at_100
      value: 1.6150000000000002
    - type: precision_at_1000
      value: 0.201
    - type: mrr_at_1
      value: 44.3491
    - type: mrr_at_3
      value: 52.0744
    - type: mrr_at_5
      value: 53.9628
    - type: mrr_at_10
      value: 54.9072
    - type: mrr_at_20
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    - type: mrr_at_100
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    - type: mrr_at_1000
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      type: CQADupstackRetrieval_is_a_combined_dataset
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      revision: CQADupstackRetrieval_is_a_combined_dataset
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  - task:
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  - task:
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  - task:
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    dataset:
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      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
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    - type: main_score
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  - task:
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    dataset:
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      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
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  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
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      value: 93.5317
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
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      value: 67.7907
    - type: f1
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    - type: f1_weighted
      value: 70.3225
    - type: main_score
      value: 67.7907
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 71.456
    - type: f1
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    - type: f1_weighted
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      value: 71.456
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
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      value: 76.21719999999999
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      value: 75.14189999999999
    - type: f1_weighted
      value: 76.0733
    - type: main_score
      value: 76.21719999999999
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P (default)
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
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      value: 31.3917
    - type: v_measure_std
      value: 1.4778
    - type: main_score
      value: 31.3917
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S (default)
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
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      value: 28.2408
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      value: 1.1622999999999999
    - type: main_score
      value: 28.2408
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking (default)
      type: mteb/mind_small
      config: default
      split: test
      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
    metrics:
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    - type: mrr
      value: 30.3081
    - type: nAUC_map_max
      value: -24.9194
    - type: nAUC_map_std
      value: -9.042
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      value: 12.1611
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      value: -19.3867
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      value: -6.3873
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      value: 11.8078
    - type: main_score
      value: 29.5796
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus (default)
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
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      value: 45.046
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      value: 41.704
    - type: ndcg_at_5
      value: 39.296
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    - type: ndcg_at_1000
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    - type: map_at_1
      value: 5.833
    - type: map_at_3
      value: 9.953
    - type: map_at_5
      value: 11.549
    - type: map_at_10
      value: 13.38
    - type: map_at_20
      value: 14.706
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  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering (default)
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
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    - type: v_measure_std
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    - type: main_score
      value: 51.208600000000004
  - task:
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    dataset:
      name: MTEB RedditClusteringP2P (default)
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
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    - type: main_score
      value: 60.372899999999994
  - task:
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    dataset:
      name: MTEB SCIDOCS (default)
      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
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    - type: precision_at_1000
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  - task:
      type: STS
    dataset:
      name: MTEB SICK-R (default)
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
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    - type: spearman
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    - type: cosine_pearson
      value: 79.5908
    - type: cosine_spearman
      value: 73.9888
    - type: manhattan_pearson
      value: 77.0623
    - type: manhattan_spearman
      value: 73.7724
    - type: euclidean_pearson
      value: 77.30890000000001
    - type: euclidean_spearman
      value: 73.9888
    - type: main_score
      value: 73.9888
  - task:
      type: STS
    dataset:
      name: MTEB STS12 (default)
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
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      value: 74.0752
    - type: spearman
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    - type: cosine_pearson
      value: 74.0752
    - type: cosine_spearman
      value: 71.22699999999999
    - type: manhattan_pearson
      value: 70.6037
    - type: manhattan_spearman
      value: 70.9916
    - type: euclidean_pearson
      value: 70.922
    - type: euclidean_spearman
      value: 71.22699999999999
    - type: main_score
      value: 71.22699999999999
  - task:
      type: STS
    dataset:
      name: MTEB STS13 (default)
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
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      value: 77.8946
    - type: spearman
      value: 80.4405
    - type: cosine_pearson
      value: 77.8946
    - type: cosine_spearman
      value: 80.4405
    - type: manhattan_pearson
      value: 79.6856
    - type: manhattan_spearman
      value: 80.1236
    - type: euclidean_pearson
      value: 80.0315
    - type: euclidean_spearman
      value: 80.44059999999999
    - type: main_score
      value: 80.4405
  - task:
      type: STS
    dataset:
      name: MTEB STS14 (default)
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
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      value: 76.2196
    - type: spearman
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    - type: cosine_pearson
      value: 76.2196
    - type: cosine_spearman
      value: 75.10419999999999
    - type: manhattan_pearson
      value: 75.4647
    - type: manhattan_spearman
      value: 74.81179999999999
    - type: euclidean_pearson
      value: 75.8091
    - type: euclidean_spearman
      value: 75.10419999999999
    - type: main_score
      value: 75.10419999999999
  - task:
      type: STS
    dataset:
      name: MTEB STS15 (default)
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
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      value: 81.2455
    - type: spearman
      value: 82.8681
    - type: cosine_pearson
      value: 81.2455
    - type: cosine_spearman
      value: 82.8681
    - type: manhattan_pearson
      value: 82.4327
    - type: manhattan_spearman
      value: 82.7513
    - type: euclidean_pearson
      value: 82.5635
    - type: euclidean_spearman
      value: 82.8681
    - type: main_score
      value: 82.8681
  - task:
      type: STS
    dataset:
      name: MTEB STS16 (default)
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
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      value: 81.6322
    - type: spearman
      value: 83.487
    - type: cosine_pearson
      value: 81.6322
    - type: cosine_spearman
      value: 83.487
    - type: manhattan_pearson
      value: 83.0048
    - type: manhattan_spearman
      value: 83.4064
    - type: euclidean_pearson
      value: 83.0938
    - type: euclidean_spearman
      value: 83.487
    - type: main_score
      value: 83.487
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
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      value: 81.1124
    - type: spearman
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    - type: cosine_pearson
      value: 81.1124
    - type: cosine_spearman
      value: 84.5436
    - type: manhattan_pearson
      value: 83.5158
    - type: manhattan_spearman
      value: 84.596
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      value: 83.4429
    - type: euclidean_spearman
      value: 84.5436
    - type: main_score
      value: 84.5436
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-tr)
      type: mteb/sts17-crosslingual-sts
      config: en-tr
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 62.0001
    - type: spearman
      value: 63.631099999999996
    - type: cosine_pearson
      value: 62.0001
    - type: cosine_spearman
      value: 63.631099999999996
    - type: manhattan_pearson
      value: 62.239599999999996
    - type: manhattan_spearman
      value: 62.892199999999995
    - type: euclidean_pearson
      value: 62.9809
    - type: euclidean_spearman
      value: 63.631099999999996
    - type: main_score
      value: 63.631099999999996
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (it-en)
      type: mteb/sts17-crosslingual-sts
      config: it-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 75.1556
    - type: spearman
      value: 76.8807
    - type: cosine_pearson
      value: 75.1556
    - type: cosine_spearman
      value: 76.8807
    - type: manhattan_pearson
      value: 76.2428
    - type: manhattan_spearman
      value: 76.8101
    - type: euclidean_pearson
      value: 76.107
    - type: euclidean_spearman
      value: 76.8807
    - type: main_score
      value: 76.8807
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-en)
      type: mteb/sts17-crosslingual-sts
      config: es-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 69.85719999999999
    - type: spearman
      value: 71.0489
    - type: cosine_pearson
      value: 69.85719999999999
    - type: cosine_spearman
      value: 71.0489
    - type: manhattan_pearson
      value: 71.08449999999999
    - type: manhattan_spearman
      value: 71.0051
    - type: euclidean_pearson
      value: 71.19760000000001
    - type: euclidean_spearman
      value: 71.0489
    - type: main_score
      value: 71.0489
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (nl-en)
      type: mteb/sts17-crosslingual-sts
      config: nl-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 76.1131
    - type: spearman
      value: 78.2714
    - type: cosine_pearson
      value: 76.1131
    - type: cosine_spearman
      value: 78.2714
    - type: manhattan_pearson
      value: 76.70270000000001
    - type: manhattan_spearman
      value: 77.7803
    - type: euclidean_pearson
      value: 77.14269999999999
    - type: euclidean_spearman
      value: 78.2714
    - type: main_score
      value: 78.2714
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (fr-en)
      type: mteb/sts17-crosslingual-sts
      config: fr-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 74.49719999999999
    - type: spearman
      value: 76.2747
    - type: cosine_pearson
      value: 74.49719999999999
    - type: cosine_spearman
      value: 76.2747
    - type: manhattan_pearson
      value: 75.071
    - type: manhattan_spearman
      value: 75.8969
    - type: euclidean_pearson
      value: 75.289
    - type: euclidean_spearman
      value: 76.2747
    - type: main_score
      value: 76.2747
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-de)
      type: mteb/sts17-crosslingual-sts
      config: en-de
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 76.7073
    - type: spearman
      value: 79.3107
    - type: cosine_pearson
      value: 76.7073
    - type: cosine_spearman
      value: 79.3107
    - type: manhattan_pearson
      value: 77.9578
    - type: manhattan_spearman
      value: 79.3195
    - type: euclidean_pearson
      value: 77.7386
    - type: euclidean_spearman
      value: 79.3107
    - type: main_score
      value: 79.3107
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-ar)
      type: mteb/sts17-crosslingual-sts
      config: en-ar
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 60.5826
    - type: spearman
      value: 61.0502
    - type: cosine_pearson
      value: 60.5826
    - type: cosine_spearman
      value: 61.0502
    - type: manhattan_pearson
      value: 61.202
    - type: manhattan_spearman
      value: 61.2039
    - type: euclidean_pearson
      value: 61.1915
    - type: euclidean_spearman
      value: 61.0502
    - type: main_score
      value: 61.0502
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 69.2521
    - type: spearman
      value: 68.06219999999999
    - type: cosine_pearson
      value: 69.2521
    - type: cosine_spearman
      value: 68.06219999999999
    - type: manhattan_pearson
      value: 70.5115
    - type: manhattan_spearman
      value: 67.8705
    - type: euclidean_pearson
      value: 70.68480000000001
    - type: euclidean_spearman
      value: 68.06219999999999
    - type: main_score
      value: 68.06219999999999
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl-en)
      type: mteb/sts22-crosslingual-sts
      config: pl-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 77.97500000000001
    - type: spearman
      value: 76.848
    - type: cosine_pearson
      value: 77.97500000000001
    - type: cosine_spearman
      value: 76.848
    - type: manhattan_pearson
      value: 76.4098
    - type: manhattan_spearman
      value: 76.6188
    - type: euclidean_pearson
      value: 77.17500000000001
    - type: euclidean_spearman
      value: 76.848
    - type: main_score
      value: 76.848
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh-en)
      type: mteb/sts22-crosslingual-sts
      config: zh-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 71.3604
    - type: spearman
      value: 70.7891
    - type: cosine_pearson
      value: 71.3604
    - type: cosine_spearman
      value: 70.7891
    - type: manhattan_pearson
      value: 73.0185
    - type: manhattan_spearman
      value: 70.79299999999999
    - type: euclidean_pearson
      value: 73.17620000000001
    - type: euclidean_spearman
      value: 70.7891
    - type: main_score
      value: 70.7891
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-en)
      type: mteb/sts22-crosslingual-sts
      config: es-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 77.58239999999999
    - type: spearman
      value: 78.5907
    - type: cosine_pearson
      value: 77.58239999999999
    - type: cosine_spearman
      value: 78.5907
    - type: manhattan_pearson
      value: 79.25720000000001
    - type: manhattan_spearman
      value: 78.6249
    - type: euclidean_pearson
      value: 79.3724
    - type: euclidean_spearman
      value: 78.5907
    - type: main_score
      value: 78.5907
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-en)
      type: mteb/sts22-crosslingual-sts
      config: de-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 63.324000000000005
    - type: spearman
      value: 55.1099
    - type: cosine_pearson
      value: 63.324000000000005
    - type: cosine_spearman
      value: 55.1099
    - type: manhattan_pearson
      value: 67.3128
    - type: manhattan_spearman
      value: 56.340199999999996
    - type: euclidean_pearson
      value: 67.12089999999999
    - type: euclidean_spearman
      value: 55.1099
    - type: main_score
      value: 55.1099
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark (default)
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: pearson
      value: 78.02329999999999
    - type: spearman
      value: 79.1887
    - type: cosine_pearson
      value: 78.02329999999999
    - type: cosine_spearman
      value: 79.1887
    - type: manhattan_pearson
      value: 78.8951
    - type: manhattan_spearman
      value: 78.9444
    - type: euclidean_pearson
      value: 79.1499
    - type: euclidean_spearman
      value: 79.1888
    - type: main_score
      value: 79.1887
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR (default)
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 78.7501
    - type: mrr
      value: 93.9748
    - type: nAUC_map_max
      value: 54.495599999999996
    - type: nAUC_map_std
      value: 70.0377
    - type: nAUC_map_diff1
      value: 6.0146999999999995
    - type: nAUC_mrr_max
      value: 81.1486
    - type: nAUC_mrr_std
      value: 78.3478
    - type: nAUC_mrr_diff1
      value: 50.7613
    - type: main_score
      value: 78.7501
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact (default)
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: ndcg_at_1
      value: 58.667
    - type: ndcg_at_3
      value: 66.022
    - type: ndcg_at_5
      value: 68.508
    - type: ndcg_at_10
      value: 70.586
    - type: ndcg_at_20
      value: 71.714
    - type: ndcg_at_100
      value: 72.81
    - type: ndcg_at_1000
      value: 73.482
    - type: map_at_1
      value: 55.594
    - type: map_at_3
      value: 63.2
    - type: map_at_5
      value: 64.996
    - type: map_at_10
      value: 65.988
    - type: map_at_20
      value: 66.347
    - type: map_at_100
      value: 66.526
    - type: map_at_1000
      value: 66.547
    - type: recall_at_1
      value: 55.594
    - type: recall_at_3
      value: 71.22800000000001
    - type: recall_at_5
      value: 77.078
    - type: recall_at_10
      value: 83.172
    - type: recall_at_20
      value: 87.422
    - type: recall_at_100
      value: 93.167
    - type: recall_at_1000
      value: 98.667
    - type: precision_at_1
      value: 58.667
    - type: precision_at_3
      value: 25.778000000000002
    - type: precision_at_5
      value: 17.333000000000002
    - type: precision_at_10
      value: 9.433
    - type: precision_at_20
      value: 4.967
    - type: precision_at_100
      value: 1.06
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: mrr_at_1
      value: 58.666700000000006
    - type: mrr_at_3
      value: 65.3889
    - type: mrr_at_5
      value: 66.62219999999999
    - type: mrr_at_10
      value: 67.3364
    - type: mrr_at_20
      value: 67.6046
    - type: mrr_at_100
      value: 67.73320000000001
    - type: mrr_at_1000
      value: 67.7526
    - type: nauc_ndcg_at_1_max
      value: 60.2511
    - type: nauc_ndcg_at_1_std
      value: 12.422
    - type: nauc_ndcg_at_1_diff1
      value: 74.4289
    - type: nauc_ndcg_at_3_max
      value: 60.2109
    - type: nauc_ndcg_at_3_std
      value: 11.0152
    - type: nauc_ndcg_at_3_diff1
      value: 71.0436
    - type: nauc_ndcg_at_5_max
      value: 62.690999999999995
    - type: nauc_ndcg_at_5_std
      value: 13.585700000000001
    - type: nauc_ndcg_at_5_diff1
      value: 70.4007
    - type: nauc_ndcg_at_10_max
      value: 62.740899999999996
    - type: nauc_ndcg_at_10_std
      value: 13.980400000000001
    - type: nauc_ndcg_at_10_diff1
      value: 70.0506
    - type: nauc_ndcg_at_20_max
      value: 62.271699999999996
    - type: nauc_ndcg_at_20_std
      value: 15.9756
    - type: nauc_ndcg_at_20_diff1
      value: 70.3237
    - type: nauc_ndcg_at_100_max
      value: 62.125
    - type: nauc_ndcg_at_100_std
      value: 15.5809
    - type: nauc_ndcg_at_100_diff1
      value: 70.4151
    - type: nauc_ndcg_at_1000_max
      value: 61.9259
    - type: nauc_ndcg_at_1000_std
      value: 15.3462
    - type: nauc_ndcg_at_1000_diff1
      value: 70.7346
    - type: nauc_map_at_1_max
      value: 53.6767
    - type: nauc_map_at_1_std
      value: 3.7751
    - type: nauc_map_at_1_diff1
      value: 74.60329999999999
    - type: nauc_map_at_3_max
      value: 57.0403
    - type: nauc_map_at_3_std
      value: 8.2272
    - type: nauc_map_at_3_diff1
      value: 71.7906
    - type: nauc_map_at_5_max
      value: 59.6713
    - type: nauc_map_at_5_std
      value: 10.8346
    - type: nauc_map_at_5_diff1
      value: 71.3356
    - type: nauc_map_at_10_max
      value: 60.0086
    - type: nauc_map_at_10_std
      value: 11.4394
    - type: nauc_map_at_10_diff1
      value: 71.14869999999999
    - type: nauc_map_at_20_max
      value: 59.940599999999996
    - type: nauc_map_at_20_std
      value: 12.0728
    - type: nauc_map_at_20_diff1
      value: 71.31
    - type: nauc_map_at_100_max
      value: 59.95589999999999
    - type: nauc_map_at_100_std
      value: 12.148299999999999
    - type: nauc_map_at_100_diff1
      value: 71.2142
    - type: nauc_map_at_1000_max
      value: 59.9486
    - type: nauc_map_at_1000_std
      value: 12.139
    - type: nauc_map_at_1000_diff1
      value: 71.2225
    - type: nauc_recall_at_1_max
      value: 53.6767
    - type: nauc_recall_at_1_std
      value: 3.7751
    - type: nauc_recall_at_1_diff1
      value: 74.60329999999999
    - type: nauc_recall_at_3_max
      value: 60.4078
    - type: nauc_recall_at_3_std
      value: 9.038300000000001
    - type: nauc_recall_at_3_diff1
      value: 67.60119999999999
    - type: nauc_recall_at_5_max
      value: 68.0179
    - type: nauc_recall_at_5_std
      value: 16.061600000000002
    - type: nauc_recall_at_5_diff1
      value: 65.54759999999999
    - type: nauc_recall_at_10_max
      value: 68.7372
    - type: nauc_recall_at_10_std
      value: 16.8637
    - type: nauc_recall_at_10_diff1
      value: 62.7613
    - type: nauc_recall_at_20_max
      value: 67.1403
    - type: nauc_recall_at_20_std
      value: 31.3919
    - type: nauc_recall_at_20_diff1
      value: 62.66929999999999
    - type: nauc_recall_at_100_max
      value: 68.6366
    - type: nauc_recall_at_100_std
      value: 32.4577
    - type: nauc_recall_at_100_diff1
      value: 64.52029999999999
    - type: nauc_recall_at_1000_max
      value: 70.7166
    - type: nauc_recall_at_1000_std
      value: 70.47149999999999
    - type: nauc_recall_at_1000_diff1
      value: 85.58590000000001
    - type: nauc_precision_at_1_max
      value: 60.2511
    - type: nauc_precision_at_1_std
      value: 12.422
    - type: nauc_precision_at_1_diff1
      value: 74.4289
    - type: nauc_precision_at_3_max
      value: 58.75280000000001
    - type: nauc_precision_at_3_std
      value: 27.605400000000003
    - type: nauc_precision_at_3_diff1
      value: 49.1523
    - type: nauc_precision_at_5_max
      value: 56.4694
    - type: nauc_precision_at_5_std
      value: 39.080799999999996
    - type: nauc_precision_at_5_diff1
      value: 28.8162
    - type: nauc_precision_at_10_max
      value: 48.8894
    - type: nauc_precision_at_10_std
      value: 43.8149
    - type: nauc_precision_at_10_diff1
      value: 15.0093
    - type: nauc_precision_at_20_max
      value: 41.4059
    - type: nauc_precision_at_20_std
      value: 50.7143
    - type: nauc_precision_at_20_diff1
      value: 8.3552
    - type: nauc_precision_at_100_max
      value: 33.5064
    - type: nauc_precision_at_100_std
      value: 52.8775
    - type: nauc_precision_at_100_diff1
      value: -5.0870999999999995
    - type: nauc_precision_at_1000_max
      value: 23.9064
    - type: nauc_precision_at_1000_std
      value: 57.784800000000004
    - type: nauc_precision_at_1000_diff1
      value: -20.1246
    - type: nauc_mrr_at_1_max
      value: 60.2511
    - type: nauc_mrr_at_1_std
      value: 12.422
    - type: nauc_mrr_at_1_diff1
      value: 74.4289
    - type: nauc_mrr_at_3_max
      value: 62.663199999999996
    - type: nauc_mrr_at_3_std
      value: 14.7348
    - type: nauc_mrr_at_3_diff1
      value: 72.1185
    - type: nauc_mrr_at_5_max
      value: 63.3871
    - type: nauc_mrr_at_5_std
      value: 15.773000000000001
    - type: nauc_mrr_at_5_diff1
      value: 71.6722
    - type: nauc_mrr_at_10_max
      value: 62.8474
    - type: nauc_mrr_at_10_std
      value: 15.1896
    - type: nauc_mrr_at_10_diff1
      value: 71.64110000000001
    - type: nauc_mrr_at_20_max
      value: 62.699400000000004
    - type: nauc_mrr_at_20_std
      value: 15.554499999999999
    - type: nauc_mrr_at_20_diff1
      value: 71.6049
    - type: nauc_mrr_at_100_max
      value: 62.6665
    - type: nauc_mrr_at_100_std
      value: 15.4586
    - type: nauc_mrr_at_100_diff1
      value: 71.6217
    - type: nauc_mrr_at_1000_max
      value: 62.6641
    - type: nauc_mrr_at_1000_std
      value: 15.4535
    - type: nauc_mrr_at_1000_diff1
      value: 71.6307
    - type: main_score
      value: 70.586
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions (default)
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: similarity_accuracy
      value: 99.8416
    - type: similarity_accuracy_threshold
      value: 74.52069999999999
    - type: similarity_f1
      value: 92.008
    - type: similarity_f1_threshold
      value: 74.4529
    - type: similarity_precision
      value: 91.9162
    - type: similarity_recall
      value: 92.10000000000001
    - type: similarity_ap
      value: 96.54209999999999
    - type: cosine_accuracy
      value: 99.8416
    - type: cosine_accuracy_threshold
      value: 74.52069999999999
    - type: cosine_f1
      value: 92.008
    - type: cosine_f1_threshold
      value: 74.4529
    - type: cosine_precision
      value: 91.9162
    - type: cosine_recall
      value: 92.10000000000001
    - type: cosine_ap
      value: 96.54209999999999
    - type: manhattan_accuracy
      value: 99.8446
    - type: manhattan_accuracy_threshold
      value: 1784.866
    - type: manhattan_f1
      value: 92.1539
    - type: manhattan_f1_threshold
      value: 1787.6774
    - type: manhattan_precision
      value: 92.1079
    - type: manhattan_recall
      value: 92.2
    - type: manhattan_ap
      value: 96.5207
    - type: euclidean_accuracy
      value: 99.8416
    - type: euclidean_accuracy_threshold
      value: 71.3853
    - type: euclidean_f1
      value: 92.008
    - type: euclidean_f1_threshold
      value: 71.4803
    - type: euclidean_precision
      value: 91.9162
    - type: euclidean_recall
      value: 92.10000000000001
    - type: euclidean_ap
      value: 96.54209999999999
    - type: dot_accuracy
      value: 99.8416
    - type: dot_accuracy_threshold
      value: 74.52069999999999
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    - type: max_accuracy
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      value: 92.1079
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      value: 92.2
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      value: 96.54209999999999
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering (default)
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
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      value: 4.758
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      value: 63.4035
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P (default)
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
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      value: 36.288599999999995
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      value: 1.3107
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      value: 36.288599999999995
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions (default)
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
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      value: 6.4524
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      value: 37.2785
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  - task:
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      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
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      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
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  - task:
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    dataset:
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      type: mteb/touche2020
      config: default
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      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
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    - type: nauc_mrr_at_20_diff1
      value: -5.7068
    - type: nauc_mrr_at_100_max
      value: -23.0016
    - type: nauc_mrr_at_100_std
      value: -22.488
    - type: nauc_mrr_at_100_diff1
      value: -5.3738
    - type: nauc_mrr_at_1000_max
      value: -23.0016
    - type: nauc_mrr_at_1000_std
      value: -22.488
    - type: nauc_mrr_at_1000_diff1
      value: -5.3738
    - type: main_score
      value: 29.499
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification (default)
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 65.8643
    - type: f1
      value: 50.6764
    - type: f1_weighted
      value: 73.2472
    - type: ap
      value: 12.2658
    - type: ap_weighted
      value: 12.2658
    - type: main_score
      value: 65.8643
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification (default)
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 59.6633
    - type: f1
      value: 59.935700000000004
    - type: f1_weighted
      value: 59.0249
    - type: main_score
      value: 59.6633
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering (default)
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 43.2311
    - type: v_measure_std
      value: 2.3994999999999997
    - type: main_score
      value: 43.2311
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015 (default)
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: similarity_accuracy
      value: 83.8469
    - type: similarity_accuracy_threshold
      value: 77.6695
    - type: similarity_f1
      value: 62.3159
    - type: similarity_f1_threshold
      value: 71.6554
    - type: similarity_precision
      value: 59.114599999999996
    - type: similarity_recall
      value: 65.8839
    - type: similarity_ap
      value: 67.00930000000001
    - type: cosine_accuracy
      value: 83.8469
    - type: cosine_accuracy_threshold
      value: 77.6695
    - type: cosine_f1
      value: 62.3159
    - type: cosine_f1_threshold
      value: 71.6554
    - type: cosine_precision
      value: 59.114599999999996
    - type: cosine_recall
      value: 65.8839
    - type: cosine_ap
      value: 67.00930000000001
    - type: manhattan_accuracy
      value: 83.7694
    - type: manhattan_accuracy_threshold
      value: 1677.8293999999999
    - type: manhattan_f1
      value: 62.1324
    - type: manhattan_f1_threshold
      value: 1848.6641
    - type: manhattan_precision
      value: 61.839999999999996
    - type: manhattan_recall
      value: 62.4274
    - type: manhattan_ap
      value: 66.8849
    - type: euclidean_accuracy
      value: 83.8469
    - type: euclidean_accuracy_threshold
      value: 66.8288
    - type: euclidean_f1
      value: 62.3159
    - type: euclidean_f1_threshold
      value: 75.2922
    - type: euclidean_precision
      value: 59.114599999999996
    - type: euclidean_recall
      value: 65.8839
    - type: euclidean_ap
      value: 67.00930000000001
    - type: dot_accuracy
      value: 83.8469
    - type: dot_accuracy_threshold
      value: 77.6695
    - type: dot_f1
      value: 62.3159
    - type: dot_f1_threshold
      value: 71.6554
    - type: dot_precision
      value: 59.114599999999996
    - type: dot_recall
      value: 65.8839
    - type: dot_ap
      value: 67.00930000000001
    - type: max_accuracy
      value: 83.8469
    - type: max_f1
      value: 62.3159
    - type: max_precision
      value: 61.839999999999996
    - type: max_recall
      value: 65.8839
    - type: max_ap
      value: 67.00930000000001
    - type: main_score
      value: 67.00930000000001
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus (default)
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: similarity_accuracy
      value: 88.8811
    - type: similarity_accuracy_threshold
      value: 71.1053
    - type: similarity_f1
      value: 77.9005
    - type: similarity_f1_threshold
      value: 67.5068
    - type: similarity_precision
      value: 75.5609
    - type: similarity_recall
      value: 80.3896
    - type: similarity_ap
      value: 85.459
    - type: cosine_accuracy
      value: 88.8811
    - type: cosine_accuracy_threshold
      value: 71.1053
    - type: cosine_f1
      value: 77.9005
    - type: cosine_f1_threshold
      value: 67.5068
    - type: cosine_precision
      value: 75.5609
    - type: cosine_recall
      value: 80.3896
    - type: cosine_ap
      value: 85.459
    - type: manhattan_accuracy
      value: 88.8598
    - type: manhattan_accuracy_threshold
      value: 1928.9173
    - type: manhattan_f1
      value: 77.9172
    - type: manhattan_f1_threshold
      value: 2007.8883999999998
    - type: manhattan_precision
      value: 76.29310000000001
    - type: manhattan_recall
      value: 79.6119
    - type: manhattan_ap
      value: 85.4464
    - type: euclidean_accuracy
      value: 88.8811
    - type: euclidean_accuracy_threshold
      value: 76.0193
    - type: euclidean_f1
      value: 77.9005
    - type: euclidean_f1_threshold
      value: 80.6141
    - type: euclidean_precision
      value: 75.5609
    - type: euclidean_recall
      value: 80.3896
    - type: euclidean_ap
      value: 85.459
    - type: dot_accuracy
      value: 88.8811
    - type: dot_accuracy_threshold
      value: 71.1053
    - type: dot_f1
      value: 77.9005
    - type: dot_f1_threshold
      value: 67.5068
    - type: dot_precision
      value: 75.5609
    - type: dot_recall
      value: 80.3896
    - type: dot_ap
      value: 85.459
    - type: max_accuracy
      value: 88.8811
    - type: max_f1
      value: 77.9172
    - type: max_precision
      value: 76.29310000000001
    - type: max_recall
      value: 80.3896
    - type: max_ap
      value: 85.459
    - type: main_score
      value: 85.459
---

# mlx-community/snowflake-arctic-embed-l-v2.0-6bit

The Model [mlx-community/snowflake-arctic-embed-l-v2.0-6bit](https://huggingface.co/mlx-community/snowflake-arctic-embed-l-v2.0-6bit) was converted to MLX format from [Snowflake/snowflake-arctic-embed-l-v2.0](https://huggingface.co/Snowflake/snowflake-arctic-embed-l-v2.0) using mlx-lm version **0.0.3**.

## Use with mlx

```bash
pip install mlx-embeddings
```

```python
from mlx_embeddings import load, generate
import mlx.core as mx

model, tokenizer = load("mlx-community/snowflake-arctic-embed-l-v2.0-6bit")

# For text embeddings
output = generate(model, processor, texts=["I like grapes", "I like fruits"])
embeddings = output.text_embeds  # Normalized embeddings

# Compute dot product between normalized embeddings
similarity_matrix = mx.matmul(embeddings, embeddings.T)

print("Similarity matrix between texts:")
print(similarity_matrix)


```