transformers safetensors feature-extraction sentence-similarity mteb sentence-transformers custom_code multilingual af am ar as az be bg bn br bs ca cs cy da de el en eo es et eu fa fi fr fy ga gd gl gu ha he hi hr hu hy id is it ja jv ka kk km kn ko ku ky la lo lt lv mg mk ml mn mr ms my ne nl no om or pa pl ps pt ro ru sa sd si sk sl so sq sr su sv sw ta te th tl tr ug uk ur uz vi xh yi zh arxiv:2409.10173 license:cc-by-nc-4.0 model-index region:us
---
language:
- multilingual
- af
- am
- ar
- as
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lo
- lt
- lv
- mg
- mk
- ml
- mn
- mr
- ms
- my
- ne
- nl
- false
- om
- or
- pa
- pl
- ps
- pt
- ro
- ru
- sa
- sd
- si
- sk
- sl
- so
- sq
- sr
- su
- sv
- sw
- ta
- te
- th
- tl
- tr
- ug
- uk
- ur
- uz
- vi
- xh
- yi
- zh
library_name: transformers
license: cc-by-nc-4.0
tags:
- feature-extraction
- sentence-similarity
- mteb
- sentence-transformers
inference: false
model-index:
- name: jina-embeddings-v3
  results:
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      type: STS
    dataset:
      name: MTEB AFQMC (default)
      type: C-MTEB/AFQMC
      config: default
      split: validation
      revision: b44c3b011063adb25877c13823db83bb193913c4
    metrics:
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    - type: main_score
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    - type: manhattan_pearson
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    - type: manhattan_spearman
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    - type: pearson
      value: 41.74237700998808
    - type: spearman
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  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna-PL (default)
      type: clarin-knext/arguana-pl
      config: default
      split: test
      revision: 63fc86750af76253e8c760fc9e534bbf24d260a2
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  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia-PL (default)
      type: clarin-knext/dbpedia-pl
      config: default
      split: test
      revision: 76afe41d9af165cc40999fcaa92312b8b012064a
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      value: 5.623890124328387
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      value: 50.55620076865238
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      value: 51.3316854622085
    - type: nauc_recall_at_5_std
      value: 8.995457887269255
    - type: ndcg_at_1
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    - type: ndcg_at_10
      value: 64.764
    - type: ndcg_at_100
      value: 68.167
    - type: ndcg_at_1000
      value: 68.816
    - type: ndcg_at_20
      value: 66.457
    - type: ndcg_at_3
      value: 60.346
    - type: ndcg_at_5
      value: 62.365
    - type: precision_at_1
      value: 52.333
    - type: precision_at_10
      value: 8.799999999999999
    - type: precision_at_100
      value: 1.057
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_20
      value: 4.8
    - type: precision_at_3
      value: 23.889
    - type: precision_at_5
      value: 15.6
    - type: recall_at_1
      value: 49.778
    - type: recall_at_10
      value: 78.206
    - type: recall_at_100
      value: 93.10000000000001
    - type: recall_at_1000
      value: 98.333
    - type: recall_at_20
      value: 84.467
    - type: recall_at_3
      value: 66.367
    - type: recall_at_5
      value: 71.35000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID-PL (default)
      type: clarin-knext/trec-covid-pl
      config: default
      split: test
      revision: 81bcb408f33366c2a20ac54adafad1ae7e877fdd
    metrics:
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    - type: map_at_1
      value: 0.214
    - type: map_at_10
      value: 1.755
    - type: map_at_100
      value: 9.944
    - type: map_at_1000
      value: 24.205
    - type: map_at_20
      value: 3.1510000000000002
    - type: map_at_3
      value: 0.6
    - type: map_at_5
      value: 0.9560000000000001
    - type: mrr_at_1
      value: 82.0
    - type: mrr_at_10
      value: 89.06666666666666
    - type: mrr_at_100
      value: 89.06666666666666
    - type: mrr_at_1000
      value: 89.06666666666666
    - type: mrr_at_20
      value: 89.06666666666666
    - type: mrr_at_3
      value: 87.66666666666666
    - type: mrr_at_5
      value: 89.06666666666666
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      value: 76.86482845196852
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      value: 36.097801891181604
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      value: 9.564437521432714
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      value: 21.8377319336476
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      value: 3.482498491294516
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      value: 25.960597782099605
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      value: 5.094341897886072
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      value: 11.266045616925698
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      value: 3.482498491294516
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      value: 15.663700985336124
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      value: 17.154099587904913
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      value: 3.7245972450393507
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      value: 0.4063857187240345
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      value: -1.4266586618013566
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      value: 7.311601874411205
    - type: ndcg_at_1
      value: 75.0
    - type: ndcg_at_10
      value: 72.18900000000001
    - type: ndcg_at_100
      value: 54.022999999999996
    - type: ndcg_at_1000
      value: 49.492000000000004
    - type: ndcg_at_20
      value: 68.51
    - type: ndcg_at_3
      value: 73.184
    - type: ndcg_at_5
      value: 72.811
    - type: precision_at_1
      value: 82.0
    - type: precision_at_10
      value: 77.4
    - type: precision_at_100
      value: 55.24
    - type: precision_at_1000
      value: 21.822
    - type: precision_at_20
      value: 73.0
    - type: precision_at_3
      value: 79.333
    - type: precision_at_5
      value: 79.2
    - type: recall_at_1
      value: 0.214
    - type: recall_at_10
      value: 1.9980000000000002
    - type: recall_at_100
      value: 13.328999999999999
    - type: recall_at_1000
      value: 47.204
    - type: recall_at_20
      value: 3.7310000000000003
    - type: recall_at_3
      value: 0.628
    - type: recall_at_5
      value: 1.049
  - task:
      type: MultilabelClassification
    dataset:
      name: MTEB CEDRClassification (default)
      type: ai-forever/cedr-classification
      config: default
      split: test
      revision: c0ba03d058e3e1b2f3fd20518875a4563dd12db4
    metrics:
    - type: accuracy
      value: 47.30605738575983
    - type: f1
      value: 41.26091043925065
    - type: lrap
      value: 72.89452709883206
    - type: main_score
      value: 47.30605738575983
  - task:
      type: Reranking
    dataset:
      name: MTEB MIRACLReranking (ru)
      type: miracl/mmteb-miracl-reranking
      config: ru
      split: dev
      revision: 6d1962c527217f8927fca80f890f14f36b2802af
    metrics:
    - type: MAP@1(MIRACL)
      value: 20.721999999999998
    - type: MAP@10(MIRACL)
      value: 33.900999999999996
    - type: MAP@100(MIRACL)
      value: 36.813
    - type: MAP@1000(MIRACL)
      value: 36.813
    - type: MAP@20(MIRACL)
      value: 35.684
    - type: MAP@3(MIRACL)
      value: 28.141
    - type: MAP@5(MIRACL)
      value: 31.075000000000003
    - type: NDCG@1(MIRACL)
      value: 32.799
    - type: NDCG@10(MIRACL)
      value: 42.065000000000005
    - type: NDCG@100(MIRACL)
      value: 49.730999999999995
    - type: NDCG@1000(MIRACL)
      value: 49.730999999999995
    - type: NDCG@20(MIRACL)
      value: 46.0
    - type: NDCG@3(MIRACL)
      value: 34.481
    - type: NDCG@5(MIRACL)
      value: 37.452999999999996
    - type: P@1(MIRACL)
      value: 32.799
    - type: P@10(MIRACL)
      value: 11.668000000000001
    - type: P@100(MIRACL)
      value: 1.9529999999999998
    - type: P@1000(MIRACL)
      value: 0.19499999999999998
    - type: P@20(MIRACL)
      value: 7.51
    - type: P@3(MIRACL)
      value: 20.823
    - type: P@5(MIRACL)
      value: 16.728
    - type: Recall@1(MIRACL)
      value: 20.721999999999998
    - type: Recall@10(MIRACL)
      value: 54.762
    - type: Recall@100(MIRACL)
      value: 79.952
    - type: Recall@1000(MIRACL)
      value: 79.952
    - type: Recall@20(MIRACL)
      value: 66.26100000000001
    - type: Recall@3(MIRACL)
      value: 34.410000000000004
    - type: Recall@5(MIRACL)
      value: 42.659000000000006
    - type: main_score
      value: 42.065000000000005
    - type: nAUC_MAP@1000_diff1(MIRACL)
      value: 14.33534992502818
    - type: nAUC_MAP@1000_max(MIRACL)
      value: 12.367998764646115
    - type: nAUC_MAP@1000_std(MIRACL)
      value: 4.569686002935006
    - type: nAUC_MAP@100_diff1(MIRACL)
      value: 14.33534992502818
    - type: nAUC_MAP@100_max(MIRACL)
      value: 12.367998764646115
    - type: nAUC_MAP@100_std(MIRACL)
      value: 4.569686002935006
    - type: nAUC_MAP@10_diff1(MIRACL)
      value: 16.920323975680027
    - type: nAUC_MAP@10_max(MIRACL)
      value: 9.327171297204082
    - type: nAUC_MAP@10_std(MIRACL)
      value: 3.2039133783079015
    - type: nAUC_MAP@1_diff1(MIRACL)
      value: 28.698973487482206
    - type: nAUC_MAP@1_max(MIRACL)
      value: 2.9217687660885034
    - type: nAUC_MAP@1_std(MIRACL)
      value: -1.1247408800976524
    - type: nAUC_MAP@20_diff1(MIRACL)
      value: 15.359083081640476
    - type: nAUC_MAP@20_max(MIRACL)
      value: 11.310494233946345
    - type: nAUC_MAP@20_std(MIRACL)
      value: 4.4171898386022885
    - type: nAUC_MAP@3_diff1(MIRACL)
      value: 22.27430591851617
    - type: nAUC_MAP@3_max(MIRACL)
      value: 6.407438291284658
    - type: nAUC_MAP@3_std(MIRACL)
      value: 0.9799184530397409
    - type: nAUC_MAP@5_diff1(MIRACL)
      value: 19.20571689941054
    - type: nAUC_MAP@5_max(MIRACL)
      value: 7.987468654026893
    - type: nAUC_MAP@5_std(MIRACL)
      value: 1.8324246565938962
    - type: nAUC_NDCG@1000_diff1(MIRACL)
      value: 3.7537669018914768
    - type: nAUC_NDCG@1000_max(MIRACL)
      value: 20.7944707840533
    - type: nAUC_NDCG@1000_std(MIRACL)
      value: 8.444837055303063
    - type: nAUC_NDCG@100_diff1(MIRACL)
      value: 3.7537669018914768
    - type: nAUC_NDCG@100_max(MIRACL)
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    - type: nAUC_NDCG@100_std(MIRACL)
      value: 8.444837055303063
    - type: nAUC_NDCG@10_diff1(MIRACL)
      value: 10.829575656103888
    - type: nAUC_NDCG@10_max(MIRACL)
      value: 13.0445496498929
    - type: nAUC_NDCG@10_std(MIRACL)
      value: 6.050412212625362
    - type: nAUC_NDCG@1_diff1(MIRACL)
      value: 19.1388712233292
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      value: 10.871900994781642
    - type: nAUC_NDCG@1_std(MIRACL)
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      value: 7.093172181746442
    - type: nAUC_NDCG@20_max(MIRACL)
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    - type: nAUC_NDCG@20_std(MIRACL)
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    - type: nAUC_NDCG@3_diff1(MIRACL)
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    - type: nAUC_P@1000_diff1(MIRACL)
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      value: 28.450694137240458
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      value: 9.892993775474912
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    - type: nAUC_P@100_max(MIRACL)
      value: 28.45069413724051
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      value: 9.892993775474928
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    - type: nAUC_P@10_max(MIRACL)
      value: 24.327018012947857
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      value: 11.78803527706634
    - type: nAUC_P@1_diff1(MIRACL)
      value: 19.1388712233292
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    - type: nAUC_P@1_std(MIRACL)
      value: 3.218568248751811
    - type: nAUC_P@20_diff1(MIRACL)
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    - type: nAUC_P@20_max(MIRACL)
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    - type: nAUC_P@20_std(MIRACL)
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    - type: nAUC_P@3_diff1(MIRACL)
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    - type: nAUC_P@3_max(MIRACL)
      value: 17.397472872058845
    - type: nAUC_P@3_std(MIRACL)
      value: 8.240008229861875
    - type: nAUC_P@5_diff1(MIRACL)
      value: -7.971349332207021
    - type: nAUC_P@5_max(MIRACL)
      value: 22.198441167940963
    - type: nAUC_P@5_std(MIRACL)
      value: 9.00265164460082
    - type: nAUC_Recall@1000_diff1(MIRACL)
      value: -38.69835271863148
    - type: nAUC_Recall@1000_max(MIRACL)
      value: 50.9545152809108
    - type: nAUC_Recall@1000_std(MIRACL)
      value: 20.44270887092116
    - type: nAUC_Recall@100_diff1(MIRACL)
      value: -38.69835271863148
    - type: nAUC_Recall@100_max(MIRACL)
      value: 50.9545152809108
    - type: nAUC_Recall@100_std(MIRACL)
      value: 20.44270887092116
    - type: nAUC_Recall@10_diff1(MIRACL)
      value: -0.08109036309433801
    - type: nAUC_Recall@10_max(MIRACL)
      value: 12.696619907773568
    - type: nAUC_Recall@10_std(MIRACL)
      value: 8.791982704261589
    - type: nAUC_Recall@1_diff1(MIRACL)
      value: 28.698973487482206
    - type: nAUC_Recall@1_max(MIRACL)
      value: 2.9217687660885034
    - type: nAUC_Recall@1_std(MIRACL)
      value: -1.1247408800976524
    - type: nAUC_Recall@20_diff1(MIRACL)
      value: -13.312171017942623
    - type: nAUC_Recall@20_max(MIRACL)
      value: 24.19847346821666
    - type: nAUC_Recall@20_std(MIRACL)
      value: 15.8157702609797
    - type: nAUC_Recall@3_diff1(MIRACL)
      value: 16.909128321353343
    - type: nAUC_Recall@3_max(MIRACL)
      value: 6.552122731902991
    - type: nAUC_Recall@3_std(MIRACL)
      value: 1.9963898223457228
    - type: nAUC_Recall@5_diff1(MIRACL)
      value: 9.990292655247721
    - type: nAUC_Recall@5_max(MIRACL)
      value: 9.361722273507574
    - type: nAUC_Recall@5_std(MIRACL)
      value: 3.270918827854495
  - task:
      type: MultilabelClassification
    dataset:
      name: MTEB SensitiveTopicsClassification (default)
      type: ai-forever/sensitive-topics-classification
      config: default
      split: test
      revision: 416b34a802308eac30e4192afc0ff99bb8dcc7f2
    metrics:
    - type: accuracy
      value: 30.634765625
    - type: f1
      value: 32.647559808678665
    - type: lrap
      value: 45.94319661458259
    - type: main_score
      value: 30.634765625
  - task:
      type: STS
    dataset:
      name: MTEB ATEC (default)
      type: C-MTEB/ATEC
      config: default
      split: test
      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
    metrics:
    - type: cosine_pearson
      value: 47.541497334563296
    - type: cosine_spearman
      value: 49.06268944206629
    - type: euclidean_pearson
      value: 51.838926748581635
    - type: euclidean_spearman
      value: 48.930697157135356
    - type: main_score
      value: 49.06268944206629
    - type: manhattan_pearson
      value: 51.835306769406365
    - type: manhattan_spearman
      value: 48.86135493444834
    - type: pearson
      value: 47.541497334563296
    - type: spearman
      value: 49.06268944206629
  - task:
      type: Classification
    dataset:
      name: MTEB AllegroReviews (default)
      type: PL-MTEB/allegro-reviews
      config: default
      split: test
      revision: b89853e6de927b0e3bfa8ecc0e56fe4e02ceafc6
    metrics:
    - type: accuracy
      value: 49.51292246520874
    - type: f1
      value: 44.14350234332397
    - type: f1_weighted
      value: 51.65508998354552
    - type: main_score
      value: 49.51292246520874
  - task:
      type: Clustering
    dataset:
      name: MTEB AlloProfClusteringP2P (default)
      type: lyon-nlp/alloprof
      config: default
      split: test
      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
    metrics:
    - type: main_score
      value: 63.883383458621665
    - type: v_measure
      value: 63.883383458621665
    - type: v_measure_std
      value: 2.693666879958465
    - type: main_score
      value: 46.85924588755251
    - type: v_measure
      value: 46.85924588755251
    - type: v_measure_std
      value: 2.1918258880872377
  - task:
      type: Clustering
    dataset:
      name: MTEB 8TagsClustering
      type: PL-MTEB/8tags-clustering
      config: default
      split: test
      revision: None
    metrics:
    - type: v_measure
      value: 43.65721212452554
  - task:
      type: Reranking
    dataset:
      name: MTEB AlloprofReranking (default)
      type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
      config: default
      split: test
      revision: e40c8a63ce02da43200eccb5b0846fcaa888f562
    metrics:
    - type: map
      value: 66.39013753839347
    - type: mrr
      value: 67.68045617786551
    - type: main_score
      value: 66.39013753839347
  - task:
      type: Retrieval
    dataset:
      name: MTEB AlloprofRetrieval (default)
      type: lyon-nlp/alloprof
      config: default
      split: test
      revision: fcf295ea64c750f41fadbaa37b9b861558e1bfbd
    metrics:
    - type: main_score
      value: 54.284
    - type: map_at_1
      value: 37.047000000000004
    - type: map_at_10
      value: 48.53
    - type: map_at_100
      value: 49.357
    - type: map_at_1000
      value: 49.39
    - type: map_at_20
      value: 49.064
    - type: map_at_3
      value: 45.675
    - type: map_at_5
      value: 47.441
    - type: mrr_at_1
      value: 37.04663212435233
    - type: mrr_at_10
      value: 48.5300326232969
    - type: mrr_at_100
      value: 49.35708199037581
    - type: mrr_at_1000
      value: 49.39005824603193
    - type: mrr_at_20
      value: 49.06417416464799
    - type: mrr_at_3
      value: 45.67501439263105
    - type: mrr_at_5
      value: 47.44099021301103
    - type: nauc_map_at_1000_diff1
      value: 43.32474221868009
    - type: nauc_map_at_1000_max
      value: 39.407334029058575
    - type: nauc_map_at_1000_std
      value: -2.3728154448932606
    - type: nauc_map_at_100_diff1
      value: 43.32336300929909
    - type: nauc_map_at_100_max
      value: 39.432174777554835
    - type: nauc_map_at_100_std
      value: -2.356396922384349
    - type: nauc_map_at_10_diff1
      value: 43.1606520154482
    - type: nauc_map_at_10_max
      value: 39.33734650558226
    - type: nauc_map_at_10_std
      value: -2.5156222475075256
    - type: nauc_map_at_1_diff1
      value: 46.2178975214499
    - type: nauc_map_at_1_max
      value: 36.26173199049361
    - type: nauc_map_at_1_std
      value: -3.0897555582816443
    - type: nauc_map_at_20_diff1
      value: 43.272980702916456
    - type: nauc_map_at_20_max
      value: 39.4896977052276
    - type: nauc_map_at_20_std
      value: -2.3305501742917043
    - type: nauc_map_at_3_diff1
      value: 43.49525042967079
    - type: nauc_map_at_3_max
      value: 38.66352501824728
    - type: nauc_map_at_3_std
      value: -3.202794391620473
    - type: nauc_map_at_5_diff1
      value: 43.2266692546611
    - type: nauc_map_at_5_max
      value: 38.77368661115743
    - type: nauc_map_at_5_std
      value: -3.0897532130127954
    - type: nauc_mrr_at_1000_diff1
      value: 43.32474221868009
    - type: nauc_mrr_at_1000_max
      value: 39.407334029058575
    - type: nauc_mrr_at_1000_std
      value: -2.3728154448932606
    - type: nauc_mrr_at_100_diff1
      value: 43.32336300929909
    - type: nauc_mrr_at_100_max
      value: 39.432174777554835
    - type: nauc_mrr_at_100_std
      value: -2.356396922384349
    - type: nauc_mrr_at_10_diff1
      value: 43.1606520154482
    - type: nauc_mrr_at_10_max
      value: 39.33734650558226
    - type: nauc_mrr_at_10_std
      value: -2.5156222475075256
    - type: nauc_mrr_at_1_diff1
      value: 46.2178975214499
    - type: nauc_mrr_at_1_max
      value: 36.26173199049361
    - type: nauc_mrr_at_1_std
      value: -3.0897555582816443
    - type: nauc_mrr_at_20_diff1
      value: 43.272980702916456
    - type: nauc_mrr_at_20_max
      value: 39.4896977052276
    - type: nauc_mrr_at_20_std
      value: -2.3305501742917043
    - type: nauc_mrr_at_3_diff1
      value: 43.49525042967079
    - type: nauc_mrr_at_3_max
      value: 38.66352501824728
    - type: nauc_mrr_at_3_std
      value: -3.202794391620473
    - type: nauc_mrr_at_5_diff1
      value: 43.2266692546611
    - type: nauc_mrr_at_5_max
      value: 38.77368661115743
    - type: nauc_mrr_at_5_std
      value: -3.0897532130127954
    - type: nauc_ndcg_at_1000_diff1
      value: 43.01903168202974
    - type: nauc_ndcg_at_1000_max
      value: 40.75496622942232
    - type: nauc_ndcg_at_1000_std
      value: -1.3150412981845496
    - type: nauc_ndcg_at_100_diff1
      value: 42.98016493758145
    - type: nauc_ndcg_at_100_max
      value: 41.55869635162325
    - type: nauc_ndcg_at_100_std
      value: -0.5355252976886055
    - type: nauc_ndcg_at_10_diff1
      value: 42.218755211347506
    - type: nauc_ndcg_at_10_max
      value: 41.305042275175765
    - type: nauc_ndcg_at_10_std
      value: -1.4034484444573714
    - type: nauc_ndcg_at_1_diff1
      value: 46.2178975214499
    - type: nauc_ndcg_at_1_max
      value: 36.26173199049361
    - type: nauc_ndcg_at_1_std
      value: -3.0897555582816443
    - type: nauc_ndcg_at_20_diff1
      value: 42.66574440095576
    - type: nauc_ndcg_at_20_max
      value: 42.014620115124515
    - type: nauc_ndcg_at_20_std
      value: -0.5176162553751498
    - type: nauc_ndcg_at_3_diff1
      value: 42.837450505106055
    - type: nauc_ndcg_at_3_max
      value: 39.525369733082414
    - type: nauc_ndcg_at_3_std
      value: -3.1605948245795155
    - type: nauc_ndcg_at_5_diff1
      value: 42.37951815451173
    - type: nauc_ndcg_at_5_max
      value: 39.78840132935179
    - type: nauc_ndcg_at_5_std
      value: -2.936898430768135
    - type: nauc_precision_at_1000_diff1
      value: 49.69224988612385
    - type: nauc_precision_at_1000_max
      value: 79.57897547128005
    - type: nauc_precision_at_1000_std
      value: 45.040371354764645
    - type: nauc_precision_at_100_diff1
      value: 42.70597486048422
    - type: nauc_precision_at_100_max
      value: 65.74628759606188
    - type: nauc_precision_at_100_std
      value: 25.49157745244855
    - type: nauc_precision_at_10_diff1
      value: 38.565609931689345
    - type: nauc_precision_at_10_max
      value: 50.0239696180852
    - type: nauc_precision_at_10_std
      value: 3.976354829503967
    - type: nauc_precision_at_1_diff1
      value: 46.2178975214499
    - type: nauc_precision_at_1_max
      value: 36.26173199049361
    - type: nauc_precision_at_1_std
      value: -3.0897555582816443
    - type: nauc_precision_at_20_diff1
      value: 40.4134718566864
    - type: nauc_precision_at_20_max
      value: 57.121778108665374
    - type: nauc_precision_at_20_std
      value: 11.46021975428544
    - type: nauc_precision_at_3_diff1
      value: 40.90538379461529
    - type: nauc_precision_at_3_max
      value: 42.18393248057992
    - type: nauc_precision_at_3_std
      value: -3.005249943837297
    - type: nauc_precision_at_5_diff1
      value: 39.60162965860782
    - type: nauc_precision_at_5_max
      value: 43.28317158174058
    - type: nauc_precision_at_5_std
      value: -2.3469094487738054
    - type: nauc_recall_at_1000_diff1
      value: 49.69224988612252
    - type: nauc_recall_at_1000_max
      value: 79.57897547127862
    - type: nauc_recall_at_1000_std
      value: 45.04037135476256
    - type: nauc_recall_at_100_diff1
      value: 42.70597486048432
    - type: nauc_recall_at_100_max
      value: 65.74628759606213
    - type: nauc_recall_at_100_std
      value: 25.491577452448727
    - type: nauc_recall_at_10_diff1
      value: 38.56560993168935
    - type: nauc_recall_at_10_max
      value: 50.02396961808522
    - type: nauc_recall_at_10_std
      value: 3.9763548295040314
    - type: nauc_recall_at_1_diff1
      value: 46.2178975214499
    - type: nauc_recall_at_1_max
      value: 36.26173199049361
    - type: nauc_recall_at_1_std
      value: -3.0897555582816443
    - type: nauc_recall_at_20_diff1
      value: 40.41347185668637
    - type: nauc_recall_at_20_max
      value: 57.12177810866533
    - type: nauc_recall_at_20_std
      value: 11.460219754285431
    - type: nauc_recall_at_3_diff1
      value: 40.90538379461527
    - type: nauc_recall_at_3_max
      value: 42.18393248057989
    - type: nauc_recall_at_3_std
      value: -3.005249943837297
    - type: nauc_recall_at_5_diff1
      value: 39.601629658607784
    - type: nauc_recall_at_5_max
      value: 43.28317158174053
    - type: nauc_recall_at_5_std
      value: -2.3469094487738054
    - type: ndcg_at_1
      value: 37.047000000000004
    - type: ndcg_at_10
      value: 54.284
    - type: ndcg_at_100
      value: 58.34
    - type: ndcg_at_1000
      value: 59.303
    - type: ndcg_at_20
      value: 56.235
    - type: ndcg_at_3
      value: 48.503
    - type: ndcg_at_5
      value: 51.686
    - type: precision_at_1
      value: 37.047000000000004
    - type: precision_at_10
      value: 7.237
    - type: precision_at_100
      value: 0.914
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_20
      value: 4.005
    - type: precision_at_3
      value: 18.898
    - type: precision_at_5
      value: 12.884
    - type: recall_at_1
      value: 37.047000000000004
    - type: recall_at_10
      value: 72.366
    - type: recall_at_100
      value: 91.408
    - type: recall_at_1000
      value: 99.136
    - type: recall_at_20
      value: 80.095
    - type: recall_at_3
      value: 56.693000000000005
    - type: recall_at_5
      value: 64.42099999999999
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 89.49253731343283
    - type: ap
      value: 61.88098616359918
    - type: ap_weighted
      value: 61.88098616359918
    - type: f1
      value: 84.76516623679144
    - type: f1_weighted
      value: 89.92745276292968
    - type: main_score
      value: 89.49253731343283
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (de)
      type: mteb/amazon_counterfactual
      config: de
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 89.61456102783727
    - type: ap
      value: 93.11816566733742
    - type: ap_weighted
      value: 93.11816566733742
    - type: f1
      value: 88.27635757733722
    - type: f1_weighted
      value: 89.82581568285453
    - type: main_score
      value: 89.61456102783727
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification (default)
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 95.3825
    - type: ap
      value: 93.393033869502
    - type: ap_weighted
      value: 93.393033869502
    - type: f1
      value: 95.38109007966307
    - type: f1_weighted
      value: 95.38109007966305
    - type: main_score
      value: 95.3825
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 49.768
    - type: f1
      value: 48.95084821944411
    - type: f1_weighted
      value: 48.9508482194441
    - type: main_score
      value: 49.768
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (de)
      type: mteb/amazon_reviews_multi
      config: de
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 48.071999999999996
    - type: f1
      value: 47.24171107487612
    - type: f1_weighted
      value: 47.24171107487612
    - type: main_score
      value: 48.071999999999996
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (es)
      type: mteb/amazon_reviews_multi
      config: es
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 48.102000000000004
    - type: f1
      value: 47.27193805278696
    - type: f1_weighted
      value: 47.27193805278696
    - type: main_score
      value: 48.102000000000004
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (fr)
      type: mteb/amazon_reviews_multi
      config: fr
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 47.30800000000001
    - type: f1
      value: 46.41683358017851
    - type: f1_weighted
      value: 46.41683358017851
    - type: main_score
      value: 47.30800000000001
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (zh)
      type: mteb/amazon_reviews_multi
      config: zh
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 44.944
    - type: f1
      value: 44.223824487744395
    - type: f1_weighted
      value: 44.22382448774439
    - type: main_score
      value: 44.944
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna (default)
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 29.232000000000003
    - type: map_at_10
      value: 45.117000000000004
    - type: map_at_100
      value: 45.977000000000004
    - type: map_at_1000
      value: 45.98
    - type: map_at_20
      value: 45.815
    - type: map_at_3
      value: 39.912
    - type: map_at_5
      value: 42.693
    - type: mrr_at_1
      value: 29.659000000000002
    - type: mrr_at_10
      value: 45.253
    - type: mrr_at_100
      value: 46.125
    - type: mrr_at_1000
      value: 46.129
    - type: mrr_at_20
      value: 45.964
    - type: mrr_at_3
      value: 40.043
    - type: mrr_at_5
      value: 42.870000000000005
    - type: ndcg_at_1
      value: 29.232000000000003
    - type: ndcg_at_10
      value: 54.327999999999996
    - type: ndcg_at_100
      value: 57.86
    - type: ndcg_at_1000
      value: 57.935
    - type: ndcg_at_20
      value: 56.794
    - type: ndcg_at_3
      value: 43.516
    - type: ndcg_at_5
      value: 48.512
    - type: precision_at_1
      value: 29.232000000000003
    - type: precision_at_10
      value: 8.393
    - type: precision_at_100
      value: 0.991
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 4.676
    - type: precision_at_3
      value: 17.994
    - type: precision_at_5
      value: 13.215
    - type: recall_at_1
      value: 29.232000000000003
    - type: recall_at_10
      value: 83.926
    - type: recall_at_100
      value: 99.075
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_20
      value: 93.528
    - type: recall_at_3
      value: 53.983000000000004
    - type: recall_at_5
      value: 66.074
    - type: main_score
      value: 54.327999999999996
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P (default)
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: main_score
      value: 46.6636824632419
    - type: v_measure
      value: 46.6636824632419
    - type: v_measure_std
      value: 13.817129140714963
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S (default)
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: main_score
      value: 39.271141892800024
    - type: v_measure
      value: 39.271141892800024
    - type: v_measure_std
      value: 14.276782483454827
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions (default)
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 65.04363277324629
    - type: mrr
      value: 78.2372598162072
    - type: main_score
      value: 65.04363277324629
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking (default)
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.83
    - type: main_score
      value: 30.83
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES (default)
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cosine_pearson
      value: 88.80382082011027
    - type: cosine_spearman
      value: 88.68876782169106
    - type: euclidean_pearson
      value: 87.00802890147176
    - type: euclidean_spearman
      value: 87.43211268192712
    - type: main_score
      value: 88.68876782169106
    - type: manhattan_pearson
      value: 87.14062537179474
    - type: manhattan_spearman
      value: 87.59115245033443
    - type: pearson
      value: 88.80382082011027
    - type: spearman
      value: 88.68876782169106
  - task:
      type: STS
    dataset:
      name: MTEB BQ (default)
      type: C-MTEB/BQ
      config: default
      split: test
      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
    metrics:
    - type: cosine_pearson
      value: 61.588006604878196
    - type: cosine_spearman
      value: 63.20615427154465
    - type: euclidean_pearson
      value: 61.818547092516496
    - type: euclidean_spearman
      value: 63.21558009151778
    - type: main_score
      value: 63.20615427154465
    - type: manhattan_pearson
      value: 61.665588158487616
    - type: manhattan_spearman
      value: 63.051544488238584
    - type: pearson
      value: 61.588006604878196
    - type: spearman
      value: 63.20615427154465
  - task:
      type: Retrieval
    dataset:
      name: MTEB BSARDRetrieval (default)
      type: maastrichtlawtech/bsard
      config: default
      split: test
      revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
    metrics:
    - type: main_score
      value: 64.414
    - type: map_at_1
      value: 14.865
    - type: map_at_10
      value: 21.605
    - type: map_at_100
      value: 22.762
    - type: map_at_1000
      value: 22.854
    - type: map_at_20
      value: 22.259999999999998
    - type: map_at_3
      value: 20.119999999999997
    - type: map_at_5
      value: 20.931
    - type: mrr_at_1
      value: 14.864864864864865
    - type: mrr_at_10
      value: 21.605176605176606
    - type: mrr_at_100
      value: 22.7622306460065
    - type: mrr_at_1000
      value: 22.85383406410312
    - type: mrr_at_20
      value: 22.259528463088845
    - type: mrr_at_3
      value: 20.12012012012012
    - type: mrr_at_5
      value: 20.930930930930934
    - type: nauc_map_at_1000_diff1
      value: 17.486265968689338
    - type: nauc_map_at_1000_max
      value: 22.736799291688836
    - type: nauc_map_at_1000_std
      value: 9.831687441977147
    - type: nauc_map_at_100_diff1
      value: 17.50754492049086
    - type: nauc_map_at_100_max
      value: 22.77693662806787
    - type: nauc_map_at_100_std
      value: 9.853899509675395
    - type: nauc_map_at_10_diff1
      value: 17.42133968580952
    - type: nauc_map_at_10_max
      value: 22.45861793882279
    - type: nauc_map_at_10_std
      value: 8.964888472915938
    - type: nauc_map_at_1_diff1
      value: 19.433947086968093
    - type: nauc_map_at_1_max
      value: 24.75657047550517
    - type: nauc_map_at_1_std
      value: 15.122329157218505
    - type: nauc_map_at_20_diff1
      value: 17.429856756008785
    - type: nauc_map_at_20_max
      value: 22.438850987431017
    - type: nauc_map_at_20_std
      value: 9.172746012213558
    - type: nauc_map_at_3_diff1
      value: 18.218182689678475
    - type: nauc_map_at_3_max
      value: 23.57169444088667
    - type: nauc_map_at_3_std
      value: 10.464473559366356
    - type: nauc_map_at_5_diff1
      value: 18.6075342519133
    - type: nauc_map_at_5_max
      value: 23.308845973576673
    - type: nauc_map_at_5_std
      value: 9.364009996445652
    - type: nauc_mrr_at_1000_diff1
      value: 17.486265968689338
    - type: nauc_mrr_at_1000_max
      value: 22.736799291688836
    - type: nauc_mrr_at_1000_std
      value: 9.831687441977147
    - type: nauc_mrr_at_100_diff1
      value: 17.50754492049086
    - type: nauc_mrr_at_100_max
      value: 22.77693662806787
    - type: nauc_mrr_at_100_std
      value: 9.853899509675395
    - type: nauc_mrr_at_10_diff1
      value: 17.42133968580952
    - type: nauc_mrr_at_10_max
      value: 22.45861793882279
    - type: nauc_mrr_at_10_std
      value: 8.964888472915938
    - type: nauc_mrr_at_1_diff1
      value: 19.433947086968093
    - type: nauc_mrr_at_1_max
      value: 24.75657047550517
    - type: nauc_mrr_at_1_std
      value: 15.122329157218505
    - type: nauc_mrr_at_20_diff1
      value: 17.429856756008785
    - type: nauc_mrr_at_20_max
      value: 22.438850987431017
    - type: nauc_mrr_at_20_std
      value: 9.172746012213558
    - type: nauc_mrr_at_3_diff1
      value: 18.218182689678475
    - type: nauc_mrr_at_3_max
      value: 23.57169444088667
    - type: nauc_mrr_at_3_std
      value: 10.464473559366356
    - type: nauc_mrr_at_5_diff1
      value: 18.6075342519133
    - type: nauc_mrr_at_5_max
      value: 23.308845973576673
    - type: nauc_mrr_at_5_std
      value: 9.364009996445652
    - type: nauc_ndcg_at_1000_diff1
      value: 16.327871824135745
    - type: nauc_ndcg_at_1000_max
      value: 23.308241052911495
    - type: nauc_ndcg_at_1000_std
      value: 11.50905911184097
    - type: nauc_ndcg_at_100_diff1
      value: 16.676226744692773
    - type: nauc_ndcg_at_100_max
      value: 24.323253721240974
    - type: nauc_ndcg_at_100_std
      value: 11.952612443651557
    - type: nauc_ndcg_at_10_diff1
      value: 16.030325121764594
    - type: nauc_ndcg_at_10_max
      value: 21.306799242079542
    - type: nauc_ndcg_at_10_std
      value: 6.63359364302513
    - type: nauc_ndcg_at_1_diff1
      value: 19.433947086968093
    - type: nauc_ndcg_at_1_max
      value: 24.75657047550517
    - type: nauc_ndcg_at_1_std
      value: 15.122329157218505
    - type: nauc_ndcg_at_20_diff1
      value: 16.013173605999857
    - type: nauc_ndcg_at_20_max
      value: 21.607217260736576
    - type: nauc_ndcg_at_20_std
      value: 7.319482417138996
    - type: nauc_ndcg_at_3_diff1
      value: 17.97958548328493
    - type: nauc_ndcg_at_3_max
      value: 23.58346522810145
    - type: nauc_ndcg_at_3_std
      value: 9.392582854708314
    - type: nauc_ndcg_at_5_diff1
      value: 18.734733324685287
    - type: nauc_ndcg_at_5_max
      value: 23.273244317623742
    - type: nauc_ndcg_at_5_std
      value: 7.638611545253834
    - type: nauc_precision_at_1000_diff1
      value: 7.919843339380295
    - type: nauc_precision_at_1000_max
      value: 31.575386234270486
    - type: nauc_precision_at_1000_std
      value: 39.332224386769404
    - type: nauc_precision_at_100_diff1
      value: 15.018050960000052
    - type: nauc_precision_at_100_max
      value: 34.98209513759861
    - type: nauc_precision_at_100_std
      value: 26.970034484359022
    - type: nauc_precision_at_10_diff1
      value: 12.102191084210922
    - type: nauc_precision_at_10_max
      value: 18.112541150340675
    - type: nauc_precision_at_10_std
      value: 0.7358784689406018
    - type: nauc_precision_at_1_diff1
      value: 19.433947086968093
    - type: nauc_precision_at_1_max
      value: 24.75657047550517
    - type: nauc_precision_at_1_std
      value: 15.122329157218505
    - type: nauc_precision_at_20_diff1
      value: 12.018814361204328
    - type: nauc_precision_at_20_max
      value: 19.75123746049928
    - type: nauc_precision_at_20_std
      value: 3.012204650582264
    - type: nauc_precision_at_3_diff1
      value: 17.41375604940955
    - type: nauc_precision_at_3_max
      value: 23.699834627021037
    - type: nauc_precision_at_3_std
      value: 6.793486779050103
    - type: nauc_precision_at_5_diff1
      value: 19.194631963780257
    - type: nauc_precision_at_5_max
      value: 23.31708702442155
    - type: nauc_precision_at_5_std
      value: 3.4591358279667332
    - type: nauc_recall_at_1000_diff1
      value: 7.919843339380378
    - type: nauc_recall_at_1000_max
      value: 31.57538623427063
    - type: nauc_recall_at_1000_std
      value: 39.332224386769546
    - type: nauc_recall_at_100_diff1
      value: 15.018050960000085
    - type: nauc_recall_at_100_max
      value: 34.9820951375986
    - type: nauc_recall_at_100_std
      value: 26.97003448435901
    - type: nauc_recall_at_10_diff1
      value: 12.102191084210837
    - type: nauc_recall_at_10_max
      value: 18.112541150340594
    - type: nauc_recall_at_10_std
      value: 0.7358784689405188
    - type: nauc_recall_at_1_diff1
      value: 19.433947086968093
    - type: nauc_recall_at_1_max
      value: 24.75657047550517
    - type: nauc_recall_at_1_std
      value: 15.122329157218505
    - type: nauc_recall_at_20_diff1
      value: 12.01881436120429
    - type: nauc_recall_at_20_max
      value: 19.751237460499222
    - type: nauc_recall_at_20_std
      value: 3.0122046505822135
    - type: nauc_recall_at_3_diff1
      value: 17.413756049409503
    - type: nauc_recall_at_3_max
      value: 23.699834627020998
    - type: nauc_recall_at_3_std
      value: 6.793486779050083
    - type: nauc_recall_at_5_diff1
      value: 19.194631963780203
    - type: nauc_recall_at_5_max
      value: 23.3170870244215
    - type: nauc_recall_at_5_std
      value: 3.459135827966664
    - type: ndcg_at_1
      value: 14.865
    - type: ndcg_at_10
      value: 24.764
    - type: ndcg_at_100
      value: 30.861
    - type: ndcg_at_1000
      value: 33.628
    - type: ndcg_at_20
      value: 27.078000000000003
    - type: ndcg_at_3
      value: 21.675
    - type: ndcg_at_5
      value: 23.148
    - type: precision_at_1
      value: 14.865
    - type: precision_at_10
      value: 3.4680000000000004
    - type: precision_at_100
      value: 0.644
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_20
      value: 2.185
    - type: precision_at_3
      value: 8.709
    - type: precision_at_5
      value: 5.946
    - type: recall_at_1
      value: 14.865
    - type: recall_at_10
      value: 34.685
    - type: recall_at_100
      value: 64.414
    - type: recall_at_1000
      value: 86.937
    - type: recall_at_20
      value: 43.694
    - type: recall_at_3
      value: 26.125999999999998
    - type: recall_at_5
      value: 29.73
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification (default)
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 84.08116883116882
    - type: f1
      value: 84.05587055990273
    - type: f1_weighted
      value: 84.05587055990274
    - type: main_score
      value: 84.08116883116882
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P (default)
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: main_score
      value: 38.1941007822277
    - type: v_measure
      value: 38.1941007822277
    - type: v_measure_std
      value: 0.7502113547288178
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S (default)
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: main_score
      value: 34.42075599178318
    - type: v_measure
      value: 34.42075599178318
    - type: v_measure_std
      value: 0.600256720497283
  - task:
      type: Clustering
    dataset:
      name: MTEB BlurbsClusteringP2P (default)
      type: slvnwhrl/blurbs-clustering-p2p
      config: default
      split: test
      revision: a2dd5b02a77de3466a3eaa98ae586b5610314496
    metrics:
    - type: main_score
      value: 41.634627363047265
    - type: v_measure
      value: 41.634627363047265
    - type: v_measure_std
      value: 9.726923191225307
  - task:
      type: Clustering
    dataset:
      name: MTEB BlurbsClusteringS2S (default)
      type: slvnwhrl/blurbs-clustering-s2s
      config: default
      split: test
      revision: 22793b6a6465bf00120ad525e38c51210858132c
    metrics:
    - type: main_score
      value: 20.996468295584197
    - type: v_measure
      value: 20.996468295584197
    - type: v_measure_std
      value: 9.225766688272197
  - task:
      type: Classification
    dataset:
      name: MTEB CBD (default)
      type: PL-MTEB/cbd
      config: default
      split: test
      revision: 36ddb419bcffe6a5374c3891957912892916f28d
    metrics:
    - type: accuracy
      value: 69.99
    - type: ap
      value: 22.57826353116948
    - type: ap_weighted
      value: 22.57826353116948
    - type: f1
      value: 59.04574955548393
    - type: f1_weighted
      value: 74.36235022309789
    - type: main_score
      value: 69.99
  - task:
      type: PairClassification
    dataset:
      name: MTEB CDSC-E (default)
      type: PL-MTEB/cdsce-pairclassification
      config: default
      split: test
      revision: 0a3d4aa409b22f80eb22cbf59b492637637b536d
    metrics:
    - type: cosine_accuracy
      value: 88.7
    - type: cosine_accuracy_threshold
      value: 97.37848043441772
    - type: cosine_ap
      value: 73.0405088928302
    - type: cosine_f1
      value: 63.52201257861635
    - type: cosine_f1_threshold
      value: 96.98888063430786
    - type: cosine_precision
      value: 78.90625
    - type: cosine_recall
      value: 53.1578947368421
    - type: dot_accuracy
      value: 84.89999999999999
    - type: dot_accuracy_threshold
      value: 43603.09753417969
    - type: dot_ap
      value: 56.98157569085279
    - type: dot_f1
      value: 57.606490872210955
    - type: dot_f1_threshold
      value: 40406.23779296875
    - type: dot_precision
      value: 46.864686468646866
    - type: dot_recall
      value: 74.73684210526315
    - type: euclidean_accuracy
      value: 88.5
    - type: euclidean_accuracy_threshold
      value: 498.0483055114746
    - type: euclidean_ap
      value: 72.97328234816734
    - type: euclidean_f1
      value: 63.722397476340696
    - type: euclidean_f1_threshold
      value: 508.6186408996582
    - type: euclidean_precision
      value: 79.52755905511812
    - type: euclidean_recall
      value: 53.1578947368421
    - type: main_score
      value: 73.0405088928302
    - type: manhattan_accuracy
      value: 88.6
    - type: manhattan_accuracy_threshold
      value: 12233.079528808594
    - type: manhattan_ap
      value: 72.92148503992615
    - type: manhattan_f1
      value: 63.69426751592356
    - type: manhattan_f1_threshold
      value: 12392.754364013672
    - type: manhattan_precision
      value: 80.64516129032258
    - type: manhattan_recall
      value: 52.63157894736842
    - type: max_accuracy
      value: 88.7
    - type: max_ap
      value: 73.0405088928302
    - type: max_f1
      value: 63.722397476340696
    - type: max_precision
      value: 80.64516129032258
    - type: max_recall
      value: 74.73684210526315
    - type: similarity_accuracy
      value: 88.7
    - type: similarity_accuracy_threshold
      value: 97.37848043441772
    - type: similarity_ap
      value: 73.0405088928302
    - type: similarity_f1
      value: 63.52201257861635
    - type: similarity_f1_threshold
      value: 96.98888063430786
    - type: similarity_precision
      value: 78.90625
    - type: similarity_recall
      value: 53.1578947368421
  - task:
      type: STS
    dataset:
      name: MTEB CDSC-R (default)
      type: PL-MTEB/cdscr-sts
      config: default
      split: test
      revision: 1cd6abbb00df7d14be3dbd76a7dcc64b3a79a7cd
    metrics:
    - type: cosine_pearson
      value: 92.97492495289738
    - type: cosine_spearman
      value: 92.63248098608472
    - type: euclidean_pearson
      value: 92.04712487782031
    - type: euclidean_spearman
      value: 92.19679486755008
    - type: main_score
      value: 92.63248098608472
    - type: manhattan_pearson
      value: 92.0101187740438
    - type: manhattan_spearman
      value: 92.20926859332754
    - type: pearson
      value: 92.97492495289738
    - type: spearman
      value: 92.63248098608472
  - task:
      type: Clustering
    dataset:
      name: MTEB CLSClusteringP2P (default)
      type: C-MTEB/CLSClusteringP2P
      config: default
      split: test
      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
    metrics:
    - type: main_score
      value: 39.96377851800628
    - type: v_measure
      value: 39.96377851800628
    - type: v_measure_std
      value: 0.9793033243093288
  - task:
      type: Clustering
    dataset:
      name: MTEB CLSClusteringS2S (default)
      type: C-MTEB/CLSClusteringS2S
      config: default
      split: test
      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
    metrics:
    - type: main_score
      value: 38.788850224595784
    - type: v_measure
      value: 38.788850224595784
    - type: v_measure_std
      value: 1.0712604145916924
  - task:
      type: Reranking
    dataset:
      name: MTEB CMedQAv1
      type: C-MTEB/CMedQAv1-reranking
      config: default
      split: test
      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
    metrics:
    - type: map
      value: 77.95952507806115
    - type: mrr
      value: 80.8643253968254
    - type: main_score
      value: 77.95952507806115
  - task:
      type: Reranking
    dataset:
      name: MTEB CMedQAv2
      type: C-MTEB/CMedQAv2-reranking
      config: default
      split: test
      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
    metrics:
    - type: map
      value: 78.21522500165045
    - type: mrr
      value: 81.28194444444443
    - type: main_score
      value: 78.21522500165045
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval (default)
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 33.377
    - type: map_at_10
      value: 46.371
    - type: map_at_100
      value: 47.829
    - type: map_at_1000
      value: 47.94
    - type: map_at_20
      value: 47.205000000000005
    - type: map_at_3
      value: 42.782
    - type: map_at_5
      value: 44.86
    - type: mrr_at_1
      value: 41.345
    - type: mrr_at_10
      value: 52.187
    - type: mrr_at_100
      value: 52.893
    - type: mrr_at_1000
      value: 52.929
    - type: mrr_at_20
      value: 52.637
    - type: mrr_at_3
      value: 49.714000000000006
    - type: mrr_at_5
      value: 51.373000000000005
    - type: ndcg_at_1
      value: 41.345
    - type: ndcg_at_10
      value: 52.946000000000005
    - type: ndcg_at_100
      value: 57.92699999999999
    - type: ndcg_at_1000
      value: 59.609
    - type: ndcg_at_20
      value: 54.900999999999996
    - type: ndcg_at_3
      value: 48.357
    - type: ndcg_at_5
      value: 50.739000000000004
    - type: precision_at_1
      value: 41.345
    - type: precision_at_10
      value: 10.186
    - type: precision_at_100
      value: 1.554
    - type: precision_at_1000
      value: 0.2
    - type: precision_at_20
      value: 5.959
    - type: precision_at_3
      value: 23.796
    - type: precision_at_5
      value: 17.024
    - type: recall_at_1
      value: 33.377
    - type: recall_at_10
      value: 65.067
    - type: recall_at_100
      value: 86.04899999999999
    - type: recall_at_1000
      value: 96.54899999999999
    - type: recall_at_20
      value: 72.071
    - type: recall_at_3
      value: 51.349999999999994
    - type: recall_at_5
      value: 58.41
    - type: main_score
      value: 52.946000000000005
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval (default)
      type: mteb/cqadupstack-english
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 31.097
    - type: map_at_10
      value: 42.183
    - type: map_at_100
      value: 43.580999999999996
    - type: map_at_1000
      value: 43.718
    - type: map_at_20
      value: 42.921
    - type: map_at_3
      value: 38.963
    - type: map_at_5
      value: 40.815
    - type: mrr_at_1
      value: 39.745000000000005
    - type: mrr_at_10
      value: 48.736000000000004
    - type: mrr_at_100
      value: 49.405
    - type: mrr_at_1000
      value: 49.452
    - type: mrr_at_20
      value: 49.118
    - type: mrr_at_3
      value: 46.497
    - type: mrr_at_5
      value: 47.827999999999996
    - type: ndcg_at_1
      value: 39.745000000000005
    - type: ndcg_at_10
      value: 48.248000000000005
    - type: ndcg_at_100
      value: 52.956
    - type: ndcg_at_1000
      value: 54.99699999999999
    - type: ndcg_at_20
      value: 50.01
    - type: ndcg_at_3
      value: 43.946000000000005
    - type: ndcg_at_5
      value: 46.038000000000004
    - type: precision_at_1
      value: 39.745000000000005
    - type: precision_at_10
      value: 9.229
    - type: precision_at_100
      value: 1.5070000000000001
    - type: precision_at_1000
      value: 0.199
    - type: precision_at_20
      value: 5.489999999999999
    - type: precision_at_3
      value: 21.38
    - type: precision_at_5
      value: 15.274
    - type: recall_at_1
      value: 31.097
    - type: recall_at_10
      value: 58.617
    - type: recall_at_100
      value: 78.55199999999999
    - type: recall_at_1000
      value: 91.13900000000001
    - type: recall_at_20
      value: 64.92
    - type: recall_at_3
      value: 45.672000000000004
    - type: recall_at_5
      value: 51.669
    - type: main_score
      value: 48.248000000000005
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval (default)
      type: mteb/cqadupstack-gaming
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 39.745000000000005
    - type: map_at_10
      value: 52.063
    - type: map_at_100
      value: 53.077
    - type: map_at_1000
      value: 53.13
    - type: map_at_20
      value: 52.66
    - type: map_at_3
      value: 48.662
    - type: map_at_5
      value: 50.507000000000005
    - type: mrr_at_1
      value: 45.391999999999996
    - type: mrr_at_10
      value: 55.528
    - type: mrr_at_100
      value: 56.16100000000001
    - type: mrr_at_1000
      value: 56.192
    - type: mrr_at_20
      value: 55.923
    - type: mrr_at_3
      value: 52.93600000000001
    - type: mrr_at_5
      value: 54.435
    - type: ndcg_at_1
      value: 45.391999999999996
    - type: ndcg_at_10
      value: 58.019
    - type: ndcg_at_100
      value: 61.936
    - type: ndcg_at_1000
      value: 63.015
    - type: ndcg_at_20
      value: 59.691
    - type: ndcg_at_3
      value: 52.294
    - type: ndcg_at_5
      value: 55.017
    - type: precision_at_1
      value: 45.391999999999996
    - type: precision_at_10
      value: 9.386
    - type: precision_at_100
      value: 1.232
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_20
      value: 5.223
    - type: precision_at_3
      value: 23.177
    - type: precision_at_5
      value: 15.9
    - type: recall_at_1
      value: 39.745000000000005
    - type: recall_at_10
      value: 72.08099999999999
    - type: recall_at_100
      value: 88.85300000000001
    - type: recall_at_1000
      value: 96.569
    - type: recall_at_20
      value: 78.203
    - type: recall_at_3
      value: 56.957
    - type: recall_at_5
      value: 63.63100000000001
    - type: main_score
      value: 58.019
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval (default)
      type: mteb/cqadupstack-gis
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 26.651999999999997
    - type: map_at_10
      value: 35.799
    - type: map_at_100
      value: 36.846000000000004
    - type: map_at_1000
      value: 36.931000000000004
    - type: map_at_20
      value: 36.341
    - type: map_at_3
      value: 32.999
    - type: map_at_5
      value: 34.597
    - type: mrr_at_1
      value: 28.814
    - type: mrr_at_10
      value: 37.869
    - type: mrr_at_100
      value: 38.728
    - type: mrr_at_1000
      value: 38.795
    - type: mrr_at_20
      value: 38.317
    - type: mrr_at_3
      value: 35.235
    - type: mrr_at_5
      value: 36.738
    - type: ndcg_at_1
      value: 28.814
    - type: ndcg_at_10
      value: 41.028
    - type: ndcg_at_100
      value: 46.162
    - type: ndcg_at_1000
      value: 48.15
    - type: ndcg_at_20
      value: 42.824
    - type: ndcg_at_3
      value: 35.621
    - type: ndcg_at_5
      value: 38.277
    - type: precision_at_1
      value: 28.814
    - type: precision_at_10
      value: 6.361999999999999
    - type: precision_at_100
      value: 0.9450000000000001
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_20
      value: 3.6159999999999997
    - type: precision_at_3
      value: 15.140999999999998
    - type: precision_at_5
      value: 10.712000000000002
    - type: recall_at_1
      value: 26.651999999999997
    - type: recall_at_10
      value: 55.038
    - type: recall_at_100
      value: 78.806
    - type: recall_at_1000
      value: 93.485
    - type: recall_at_20
      value: 61.742
    - type: recall_at_3
      value: 40.682
    - type: recall_at_5
      value: 46.855000000000004
    - type: main_score
      value: 41.028
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval (default)
      type: mteb/cqadupstack-mathematica
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 17.627000000000002
    - type: map_at_10
      value: 26.436999999999998
    - type: map_at_100
      value: 27.85
    - type: map_at_1000
      value: 27.955999999999996
    - type: map_at_20
      value: 27.233
    - type: map_at_3
      value: 23.777
    - type: map_at_5
      value: 25.122
    - type: mrr_at_1
      value: 22.387999999999998
    - type: mrr_at_10
      value: 31.589
    - type: mrr_at_100
      value: 32.641999999999996
    - type: mrr_at_1000
      value: 32.696999999999996
    - type: mrr_at_20
      value: 32.201
    - type: mrr_at_3
      value: 28.98
    - type: mrr_at_5
      value: 30.342000000000002
    - type: ndcg_at_1
      value: 22.387999999999998
    - type: ndcg_at_10
      value: 32.129999999999995
    - type: ndcg_at_100
      value: 38.562999999999995
    - type: ndcg_at_1000
      value: 40.903
    - type: ndcg_at_20
      value: 34.652
    - type: ndcg_at_3
      value: 27.26
    - type: ndcg_at_5
      value: 29.235
    - type: precision_at_1
      value: 22.387999999999998
    - type: precision_at_10
      value: 5.970000000000001
    - type: precision_at_100
      value: 1.068
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_20
      value: 3.6999999999999997
    - type: precision_at_3
      value: 13.267000000000001
    - type: precision_at_5
      value: 9.403
    - type: recall_at_1
      value: 17.627000000000002
    - type: recall_at_10
      value: 44.71
    - type: recall_at_100
      value: 72.426
    - type: recall_at_1000
      value: 88.64699999999999
    - type: recall_at_20
      value: 53.65
    - type: recall_at_3
      value: 30.989
    - type: recall_at_5
      value: 36.237
    - type: main_score
      value: 32.129999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval (default)
      type: mteb/cqadupstack-physics
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 30.891000000000002
    - type: map_at_10
      value: 41.519
    - type: map_at_100
      value: 42.896
    - type: map_at_1000
      value: 42.992999999999995
    - type: map_at_20
      value: 42.287
    - type: map_at_3
      value: 37.822
    - type: map_at_5
      value: 39.976
    - type: mrr_at_1
      value: 37.921
    - type: mrr_at_10
      value: 47.260999999999996
    - type: mrr_at_100
      value: 48.044
    - type: mrr_at_1000
      value: 48.08
    - type: mrr_at_20
      value: 47.699999999999996
    - type: mrr_at_3
      value: 44.513999999999996
    - type: mrr_at_5
      value: 46.064
    - type: ndcg_at_1
      value: 37.921
    - type: ndcg_at_10
      value: 47.806
    - type: ndcg_at_100
      value: 53.274
    - type: ndcg_at_1000
      value: 55.021
    - type: ndcg_at_20
      value: 49.973
    - type: ndcg_at_3
      value: 42.046
    - type: ndcg_at_5
      value: 44.835
    - type: precision_at_1
      value: 37.921
    - type: precision_at_10
      value: 8.767999999999999
    - type: precision_at_100
      value: 1.353
    - type: precision_at_1000
      value: 0.168
    - type: precision_at_20
      value: 5.135
    - type: precision_at_3
      value: 20.051
    - type: precision_at_5
      value: 14.398
    - type: recall_at_1
      value: 30.891000000000002
    - type: recall_at_10
      value: 60.897999999999996
    - type: recall_at_100
      value: 83.541
    - type: recall_at_1000
      value: 94.825
    - type: recall_at_20
      value: 68.356
    - type: recall_at_3
      value: 44.65
    - type: recall_at_5
      value: 51.919000000000004
    - type: main_score
      value: 47.806
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval (default)
      type: mteb/cqadupstack-programmers
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 27.654
    - type: map_at_10
      value: 38.025999999999996
    - type: map_at_100
      value: 39.425
    - type: map_at_1000
      value: 39.528
    - type: map_at_20
      value: 38.838
    - type: map_at_3
      value: 34.745
    - type: map_at_5
      value: 36.537
    - type: mrr_at_1
      value: 34.018
    - type: mrr_at_10
      value: 43.314
    - type: mrr_at_100
      value: 44.283
    - type: mrr_at_1000
      value: 44.327
    - type: mrr_at_20
      value: 43.929
    - type: mrr_at_3
      value: 40.868
    - type: mrr_at_5
      value: 42.317
    - type: ndcg_at_1
      value: 34.018
    - type: ndcg_at_10
      value: 43.887
    - type: ndcg_at_100
      value: 49.791000000000004
    - type: ndcg_at_1000
      value: 51.834
    - type: ndcg_at_20
      value: 46.376
    - type: ndcg_at_3
      value: 38.769999999999996
    - type: ndcg_at_5
      value: 41.144
    - type: precision_at_1
      value: 34.018
    - type: precision_at_10
      value: 8.001999999999999
    - type: precision_at_100
      value: 1.2630000000000001
    - type: precision_at_1000
      value: 0.16
    - type: precision_at_20
      value: 4.737
    - type: precision_at_3
      value: 18.417
    - type: precision_at_5
      value: 13.150999999999998
    - type: recall_at_1
      value: 27.654
    - type: recall_at_10
      value: 56.111
    - type: recall_at_100
      value: 81.136
    - type: recall_at_1000
      value: 94.788
    - type: recall_at_20
      value: 65.068
    - type: recall_at_3
      value: 41.713
    - type: recall_at_5
      value: 48.106
    - type: main_score
      value: 43.887
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval (default)
      type: CQADupstackRetrieval_is_a_combined_dataset
      config: default
      split: test
      revision: CQADupstackRetrieval_is_a_combined_dataset
    metrics:
    - type: main_score
      value: 42.58858333333333
    - type: ndcg_at_10
      value: 42.58858333333333
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval (default)
      type: mteb/cqadupstack-stats
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 24.501
    - type: map_at_10
      value: 32.814
    - type: map_at_100
      value: 33.754
    - type: map_at_1000
      value: 33.859
    - type: map_at_20
      value: 33.324
    - type: map_at_3
      value: 30.758000000000003
    - type: map_at_5
      value: 31.936999999999998
    - type: mrr_at_1
      value: 27.761000000000003
    - type: mrr_at_10
      value: 35.662
    - type: mrr_at_100
      value: 36.443999999999996
    - type: mrr_at_1000
      value: 36.516999999999996
    - type: mrr_at_20
      value: 36.085
    - type: mrr_at_3
      value: 33.742
    - type: mrr_at_5
      value: 34.931
    - type: ndcg_at_1
      value: 27.761000000000003
    - type: ndcg_at_10
      value: 37.208000000000006
    - type: ndcg_at_100
      value: 41.839
    - type: ndcg_at_1000
      value: 44.421
    - type: ndcg_at_20
      value: 38.917
    - type: ndcg_at_3
      value: 33.544000000000004
    - type: ndcg_at_5
      value: 35.374
    - type: precision_at_1
      value: 27.761000000000003
    - type: precision_at_10
      value: 5.92
    - type: precision_at_100
      value: 0.899
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_20
      value: 3.4130000000000003
    - type: precision_at_3
      value: 15.031
    - type: precision_at_5
      value: 10.306999999999999
    - type: recall_at_1
      value: 24.501
    - type: recall_at_10
      value: 47.579
    - type: recall_at_100
      value: 69.045
    - type: recall_at_1000
      value: 88.032
    - type: recall_at_20
      value: 54.125
    - type: recall_at_3
      value: 37.202
    - type: recall_at_5
      value: 41.927
    - type: main_score
      value: 37.208000000000006
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval (default)
      type: mteb/cqadupstack-tex
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 18.29
    - type: map_at_10
      value: 26.183
    - type: map_at_100
      value: 27.351999999999997
    - type: map_at_1000
      value: 27.483999999999998
    - type: map_at_20
      value: 26.798
    - type: map_at_3
      value: 23.629
    - type: map_at_5
      value: 24.937
    - type: mrr_at_1
      value: 22.299
    - type: mrr_at_10
      value: 30.189
    - type: mrr_at_100
      value: 31.098
    - type: mrr_at_1000
      value: 31.177
    - type: mrr_at_20
      value: 30.697000000000003
    - type: mrr_at_3
      value: 27.862
    - type: mrr_at_5
      value: 29.066
    - type: ndcg_at_1
      value: 22.299
    - type: ndcg_at_10
      value: 31.202
    - type: ndcg_at_100
      value: 36.617
    - type: ndcg_at_1000
      value: 39.544000000000004
    - type: ndcg_at_20
      value: 33.177
    - type: ndcg_at_3
      value: 26.639000000000003
    - type: ndcg_at_5
      value: 28.526
    - type: precision_at_1
      value: 22.299
    - type: precision_at_10
      value: 5.8020000000000005
    - type: precision_at_100
      value: 1.0070000000000001
    - type: precision_at_1000
      value: 0.14400000000000002
    - type: precision_at_20
      value: 3.505
    - type: precision_at_3
      value: 12.698
    - type: precision_at_5
      value: 9.174
    - type: recall_at_1
      value: 18.29
    - type: recall_at_10
      value: 42.254999999999995
    - type: recall_at_100
      value: 66.60000000000001
    - type: recall_at_1000
      value: 87.31400000000001
    - type: recall_at_20
      value: 49.572
    - type: recall_at_3
      value: 29.342000000000002
    - type: recall_at_5
      value: 34.221000000000004
    - type: main_score
      value: 31.202
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval (default)
      type: mteb/cqadupstack-unix
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 27.722
    - type: map_at_10
      value: 37.698
    - type: map_at_100
      value: 38.899
    - type: map_at_1000
      value: 38.998
    - type: map_at_20
      value: 38.381
    - type: map_at_3
      value: 34.244
    - type: map_at_5
      value: 36.295
    - type: mrr_at_1
      value: 32.183
    - type: mrr_at_10
      value: 41.429
    - type: mrr_at_100
      value: 42.308
    - type: mrr_at_1000
      value: 42.358000000000004
    - type: mrr_at_20
      value: 41.957
    - type: mrr_at_3
      value: 38.401999999999994
    - type: mrr_at_5
      value: 40.294999999999995
    - type: ndcg_at_1
      value: 32.183
    - type: ndcg_at_10
      value: 43.519000000000005
    - type: ndcg_at_100
      value: 48.786
    - type: ndcg_at_1000
      value: 50.861999999999995
    - type: ndcg_at_20
      value: 45.654
    - type: ndcg_at_3
      value: 37.521
    - type: ndcg_at_5
      value: 40.615
    - type: precision_at_1
      value: 32.183
    - type: precision_at_10
      value: 7.603
    - type: precision_at_100
      value: 1.135
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_20
      value: 4.408
    - type: precision_at_3
      value: 17.071
    - type: precision_at_5
      value: 12.668
    - type: recall_at_1
      value: 27.722
    - type: recall_at_10
      value: 57.230000000000004
    - type: recall_at_100
      value: 79.97999999999999
    - type: recall_at_1000
      value: 94.217
    - type: recall_at_20
      value: 64.864
    - type: recall_at_3
      value: 41.215
    - type: recall_at_5
      value: 48.774
    - type: main_score
      value: 43.519000000000005
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval (default)
      type: mteb/cqadupstack-webmasters
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
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      value: 25.852999999999998
    - type: map_at_10
      value: 35.394999999999996
    - type: map_at_100
      value: 37.291999999999994
    - type: map_at_1000
      value: 37.495
    - type: map_at_20
      value: 36.372
    - type: map_at_3
      value: 32.336
    - type: map_at_5
      value: 34.159
    - type: mrr_at_1
      value: 31.818
    - type: mrr_at_10
      value: 40.677
    - type: mrr_at_100
      value: 41.728
    - type: mrr_at_1000
      value: 41.778
    - type: mrr_at_20
      value: 41.301
    - type: mrr_at_3
      value: 38.208
    - type: mrr_at_5
      value: 39.592
    - type: ndcg_at_1
      value: 31.818
    - type: ndcg_at_10
      value: 41.559000000000005
    - type: ndcg_at_100
      value: 48.012
    - type: ndcg_at_1000
      value: 50.234
    - type: ndcg_at_20
      value: 44.15
    - type: ndcg_at_3
      value: 36.918
    - type: ndcg_at_5
      value: 39.227000000000004
    - type: precision_at_1
      value: 31.818
    - type: precision_at_10
      value: 8.043
    - type: precision_at_100
      value: 1.625
    - type: precision_at_1000
      value: 0.245
    - type: precision_at_20
      value: 5.2170000000000005
    - type: precision_at_3
      value: 17.655
    - type: precision_at_5
      value: 12.845999999999998
    - type: recall_at_1
      value: 25.852999999999998
    - type: recall_at_10
      value: 53.093
    - type: recall_at_100
      value: 81.05799999999999
    - type: recall_at_1000
      value: 94.657
    - type: recall_at_20
      value: 62.748000000000005
    - type: recall_at_3
      value: 39.300000000000004
    - type: recall_at_5
      value: 45.754
    - type: main_score
      value: 41.559000000000005
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval (default)
      type: mteb/cqadupstack-wordpress
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
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      value: 19.23
    - type: map_at_10
      value: 28.128999999999998
    - type: map_at_100
      value: 29.195
    - type: map_at_1000
      value: 29.310000000000002
    - type: map_at_20
      value: 28.713
    - type: map_at_3
      value: 25.191000000000003
    - type: map_at_5
      value: 26.69
    - type: mrr_at_1
      value: 21.257
    - type: mrr_at_10
      value: 30.253999999999998
    - type: mrr_at_100
      value: 31.195
    - type: mrr_at_1000
      value: 31.270999999999997
    - type: mrr_at_20
      value: 30.747999999999998
    - type: mrr_at_3
      value: 27.633999999999997
    - type: mrr_at_5
      value: 28.937
    - type: ndcg_at_1
      value: 21.257
    - type: ndcg_at_10
      value: 33.511
    - type: ndcg_at_100
      value: 38.733000000000004
    - type: ndcg_at_1000
      value: 41.489
    - type: ndcg_at_20
      value: 35.476
    - type: ndcg_at_3
      value: 27.845
    - type: ndcg_at_5
      value: 30.264999999999997
    - type: precision_at_1
      value: 21.257
    - type: precision_at_10
      value: 5.619
    - type: precision_at_100
      value: 0.893
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_20
      value: 3.29
    - type: precision_at_3
      value: 12.508
    - type: precision_at_5
      value: 8.946
    - type: recall_at_1
      value: 19.23
    - type: recall_at_10
      value: 48.185
    - type: recall_at_100
      value: 71.932
    - type: recall_at_1000
      value: 92.587
    - type: recall_at_20
      value: 55.533
    - type: recall_at_3
      value: 32.865
    - type: recall_at_5
      value: 38.577
    - type: main_score
      value: 33.511
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER (default)
      type: mteb/climate-fever
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
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      value: 19.594
    - type: map_at_10
      value: 32.519
    - type: map_at_100
      value: 34.1
    - type: map_at_1000
      value: 34.263
    - type: map_at_20
      value: 33.353
    - type: map_at_3
      value: 27.898
    - type: map_at_5
      value: 30.524
    - type: mrr_at_1
      value: 46.515
    - type: mrr_at_10
      value: 56.958
    - type: mrr_at_100
      value: 57.54899999999999
    - type: mrr_at_1000
      value: 57.574999999999996
    - type: mrr_at_20
      value: 57.315000000000005
    - type: mrr_at_3
      value: 54.852999999999994
    - type: mrr_at_5
      value: 56.153
    - type: ndcg_at_1
      value: 46.515
    - type: ndcg_at_10
      value: 42.363
    - type: ndcg_at_100
      value: 48.233
    - type: ndcg_at_1000
      value: 50.993
    - type: ndcg_at_20
      value: 44.533
    - type: ndcg_at_3
      value: 37.297000000000004
    - type: ndcg_at_5
      value: 38.911
    - type: precision_at_1
      value: 46.515
    - type: precision_at_10
      value: 12.520999999999999
    - type: precision_at_100
      value: 1.8980000000000001
    - type: precision_at_1000
      value: 0.242
    - type: precision_at_20
      value: 7.212000000000001
    - type: precision_at_3
      value: 27.752
    - type: precision_at_5
      value: 20.391000000000002
    - type: recall_at_1
      value: 19.594
    - type: recall_at_10
      value: 46.539
    - type: recall_at_100
      value: 66.782
    - type: recall_at_1000
      value: 82.049
    - type: recall_at_20
      value: 52.611
    - type: recall_at_3
      value: 32.528
    - type: recall_at_5
      value: 38.933
    - type: main_score
      value: 42.363
  - task:
      type: Retrieval
    dataset:
      name: MTEB CmedqaRetrieval (default)
      type: C-MTEB/CmedqaRetrieval
      config: default
      split: dev
      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
    metrics:
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      value: 35.927
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      value: 20.144000000000002
    - type: map_at_10
      value: 29.94
    - type: map_at_100
      value: 31.630000000000003
    - type: map_at_1000
      value: 31.778000000000002
    - type: map_at_20
      value: 30.798
    - type: map_at_3
      value: 26.534999999999997
    - type: map_at_5
      value: 28.33
    - type: mrr_at_1
      value: 31.23280820205051
    - type: mrr_at_10
      value: 38.66781179421835
    - type: mrr_at_100
      value: 39.656936166081785
    - type: mrr_at_1000
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    - type: mrr_at_20
      value: 39.21272461558451
    - type: mrr_at_3
      value: 36.30907726931729
    - type: mrr_at_5
      value: 37.59814953738436
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      value: 40.726916781400746
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    - type: ndcg_at_10
      value: 35.927
    - type: ndcg_at_100
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      value: 45.900999999999996
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    - type: precision_at_1
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    - type: precision_at_100
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    - type: precision_at_1000
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    - type: precision_at_20
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    - type: precision_at_3
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    - type: precision_at_5
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    - type: recall_at_1
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    - type: recall_at_10
      value: 44.985
    - type: recall_at_100
      value: 74.866
    - type: recall_at_1000
      value: 94.477
    - type: recall_at_20
      value: 53.37
    - type: recall_at_3
      value: 31.141000000000002
    - type: recall_at_5
      value: 36.721
  - task:
      type: PairClassification
    dataset:
      name: MTEB Cmnli (default)
      type: C-MTEB/CMNLI
      config: default
      split: validation
      revision: None
    metrics:
    - type: cos_sim_accuracy
      value: 71.25676488274203
    - type: cos_sim_accuracy_threshold
      value: 78.11152935028076
    - type: cos_sim_ap
      value: 79.10444825556077
    - type: cos_sim_f1
      value: 74.10750923266312
    - type: cos_sim_f1_threshold
      value: 75.2312421798706
    - type: cos_sim_precision
      value: 66.02083714129044
    - type: cos_sim_recall
      value: 84.45171849427169
    - type: dot_accuracy
      value: 68.11785929043896
    - type: dot_accuracy_threshold
      value: 34783.23974609375
    - type: dot_ap
      value: 75.80201827987712
    - type: dot_f1
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    - type: dot_f1_threshold
      value: 31978.036499023438
    - type: dot_precision
      value: 61.386623164763456
    - type: dot_recall
      value: 87.98223053542202
    - type: euclidean_accuracy
      value: 71.41310883944678
    - type: euclidean_accuracy_threshold
      value: 1374.9353408813477
    - type: euclidean_ap
      value: 79.23359768836457
    - type: euclidean_f1
      value: 74.38512297540491
    - type: euclidean_f1_threshold
      value: 1512.6035690307617
    - type: euclidean_precision
      value: 64.97816593886463
    - type: euclidean_recall
      value: 86.97685293429974
    - type: manhattan_accuracy
      value: 71.32892363199038
    - type: manhattan_accuracy_threshold
      value: 33340.49072265625
    - type: manhattan_ap
      value: 79.11973684118587
    - type: manhattan_f1
      value: 74.29401993355481
    - type: manhattan_f1_threshold
      value: 36012.52746582031
    - type: manhattan_precision
      value: 66.81605975723622
    - type: manhattan_recall
      value: 83.65676876315175
    - type: max_accuracy
      value: 71.41310883944678
    - type: max_ap
      value: 79.23359768836457
    - type: max_f1
      value: 74.38512297540491
  - task:
      type: Retrieval
    dataset:
      name: MTEB CovidRetrieval (default)
      type: C-MTEB/CovidRetrieval
      config: default
      split: dev
      revision: 1271c7809071a13532e05f25fb53511ffce77117
    metrics:
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      value: 78.917
    - type: map_at_1
      value: 67.281
    - type: map_at_10
      value: 75.262
    - type: map_at_100
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    - type: map_at_1000
      value: 75.618
    - type: map_at_20
      value: 75.50200000000001
    - type: map_at_3
      value: 73.455
    - type: map_at_5
      value: 74.657
    - type: mrr_at_1
      value: 67.43940990516333
    - type: mrr_at_10
      value: 75.27367989696756
    - type: mrr_at_100
      value: 75.62029353306437
    - type: mrr_at_1000
      value: 75.62934741874726
    - type: mrr_at_20
      value: 75.51356607409173
    - type: mrr_at_3
      value: 73.5159817351598
    - type: mrr_at_5
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    - type: nauc_map_at_1000_diff1
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  - task:
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    dataset:
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      type: C-MTEB/EcomRetrieval
      config: default
      split: dev
      revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
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    - type: recall_at_1
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    - type: recall_at_1000
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    - type: recall_at_5
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  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification (default)
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
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    - type: f1
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    - type: f1_weighted
      value: 74.83537255312045
    - type: main_score
      value: 73.29999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER (default)
      type: mteb/fever
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
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    - type: map_at_100
      value: 85.954
    - type: map_at_1000
      value: 85.966
    - type: map_at_20
      value: 85.887
    - type: map_at_3
      value: 84.854
    - type: map_at_5
      value: 85.408
    - type: mrr_at_1
      value: 84.443
    - type: mrr_at_10
      value: 90.432
    - type: mrr_at_100
      value: 90.483
    - type: mrr_at_1000
      value: 90.484
    - type: mrr_at_20
      value: 90.473
    - type: mrr_at_3
      value: 89.89399999999999
    - type: mrr_at_5
      value: 90.244
    - type: ndcg_at_1
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    - type: ndcg_at_1000
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      value: 87.73100000000001
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      value: 88.425
    - type: precision_at_1
      value: 84.443
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      value: 1.103
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      value: 33.198
    - type: precision_at_5
      value: 20.441000000000003
    - type: recall_at_1
      value: 78.371
    - type: recall_at_10
      value: 94.594
    - type: recall_at_100
      value: 96.97099999999999
    - type: recall_at_1000
      value: 98.18
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      value: 95.707
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      value: 90.853
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      value: 92.74799999999999
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  - task:
      type: Retrieval
    dataset:
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      type: mteb/fiqa
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
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  - task:
      type: Classification
    dataset:
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      type: ai-forever/georeview-classification
      config: default
      split: test
      revision: 3765c0d1de6b7d264bc459433c45e5a75513839c
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  - task:
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      type: ai-forever/georeview-clustering-p2p
      config: default
      split: test
      revision: 97a313c8fc85b47f13f33e7e9a95c1ad888c7fec
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  - task:
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      type: jinaai/ger_da_lir
      config: default
      split: test
      revision: 0bb47f1d73827e96964edb84dfe552f62f4fd5eb
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      value: 74.33539303365968
    - type: nauc_ndcg_at_100_std
      value: -11.469413615851936
    - type: nauc_ndcg_at_10_diff1
      value: 89.21496710661724
    - type: nauc_ndcg_at_10_max
      value: 75.02035398490516
    - type: nauc_ndcg_at_10_std
      value: -9.903255803665814
    - type: nauc_ndcg_at_1_diff1
      value: 89.35436544117584
    - type: nauc_ndcg_at_1_max
      value: 70.35936815057701
    - type: nauc_ndcg_at_1_std
      value: -13.598996360976903
    - type: nauc_ndcg_at_20_diff1
      value: 89.03561289544179
    - type: nauc_ndcg_at_20_max
      value: 74.4006766600049
    - type: nauc_ndcg_at_20_std
      value: -11.129237862587743
    - type: nauc_ndcg_at_3_diff1
      value: 89.46540193201693
    - type: nauc_ndcg_at_3_max
      value: 76.87093548368378
    - type: nauc_ndcg_at_3_std
      value: -12.484902872086767
    - type: nauc_ndcg_at_5_diff1
      value: 89.39924941584766
    - type: nauc_ndcg_at_5_max
      value: 75.96975269092722
    - type: nauc_ndcg_at_5_std
      value: -8.180295581144833
    - type: nauc_precision_at_1000_diff1
      value: 100.0
    - type: nauc_precision_at_1000_max
      value: 100.0
    - type: nauc_precision_at_1000_std
      value: 100.0
    - type: nauc_precision_at_100_diff1
      value: 86.93074003795302
    - type: nauc_precision_at_100_max
      value: 100.0
    - type: nauc_precision_at_100_std
      value: -174.07785375176616
    - type: nauc_precision_at_10_diff1
      value: 87.43064119412082
    - type: nauc_precision_at_10_max
      value: 90.60785783417448
    - type: nauc_precision_at_10_std
      value: 15.378710059645906
    - type: nauc_precision_at_1_diff1
      value: 89.35436544117584
    - type: nauc_precision_at_1_max
      value: 70.35936815057701
    - type: nauc_precision_at_1_std
      value: -13.598996360976903
    - type: nauc_precision_at_20_diff1
      value: 78.78206037685919
    - type: nauc_precision_at_20_max
      value: 82.52264166455923
    - type: nauc_precision_at_20_std
      value: -5.95806599216658
    - type: nauc_precision_at_3_diff1
      value: 90.12709256456401
    - type: nauc_precision_at_3_max
      value: 90.72678805838154
    - type: nauc_precision_at_3_std
      value: -11.047599315631993
    - type: nauc_precision_at_5_diff1
      value: 89.9066873566561
    - type: nauc_precision_at_5_max
      value: 93.51571626543664
    - type: nauc_precision_at_5_std
      value: 22.632403279126162
    - type: nauc_recall_at_1000_diff1
      value: .nan
    - type: nauc_recall_at_1000_max
      value: .nan
    - type: nauc_recall_at_1000_std
      value: .nan
    - type: nauc_recall_at_100_diff1
      value: 86.93074003793416
    - type: nauc_recall_at_100_max
      value: 100.0
    - type: nauc_recall_at_100_std
      value: -174.07785375175723
    - type: nauc_recall_at_10_diff1
      value: 87.43064119411991
    - type: nauc_recall_at_10_max
      value: 90.60785783417579
    - type: nauc_recall_at_10_std
      value: 15.378710059643607
    - type: nauc_recall_at_1_diff1
      value: 89.35436544117584
    - type: nauc_recall_at_1_max
      value: 70.35936815057701
    - type: nauc_recall_at_1_std
      value: -13.598996360976903
    - type: nauc_recall_at_20_diff1
      value: 78.78206037685645
    - type: nauc_recall_at_20_max
      value: 82.52264166455791
    - type: nauc_recall_at_20_std
      value: -5.958065992168697
    - type: nauc_recall_at_3_diff1
      value: 90.12709256456463
    - type: nauc_recall_at_3_max
      value: 90.7267880583832
    - type: nauc_recall_at_3_std
      value: -11.047599315631881
    - type: nauc_recall_at_5_diff1
      value: 89.90668735665676
    - type: nauc_recall_at_5_max
      value: 93.51571626543753
    - type: nauc_recall_at_5_std
      value: 22.632403279126112
    - type: ndcg_at_1
      value: 90.789
    - type: ndcg_at_10
      value: 95.46
    - type: ndcg_at_100
      value: 95.652
    - type: ndcg_at_1000
      value: 95.659
    - type: ndcg_at_20
      value: 95.575
    - type: ndcg_at_3
      value: 94.82000000000001
    - type: ndcg_at_5
      value: 95.26400000000001
    - type: precision_at_1
      value: 90.789
    - type: precision_at_10
      value: 9.908999999999999
    - type: precision_at_100
      value: 1.0
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 4.977
    - type: precision_at_3
      value: 32.471
    - type: precision_at_5
      value: 19.701
    - type: recall_at_1
      value: 90.789
    - type: recall_at_10
      value: 99.093
    - type: recall_at_100
      value: 99.955
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 99.546
    - type: recall_at_3
      value: 97.414
    - type: recall_at_5
      value: 98.503
  - task:
      type: STS
    dataset:
      name: MTEB GermanSTSBenchmark (default)
      type: jinaai/german-STSbenchmark
      config: default
      split: test
      revision: e36907544d44c3a247898ed81540310442329e20
    metrics:
    - type: cosine_pearson
      value: 86.55319003300265
    - type: cosine_spearman
      value: 87.50267373081324
    - type: euclidean_pearson
      value: 87.41630636501863
    - type: euclidean_spearman
      value: 88.02170803409365
    - type: main_score
      value: 87.50267373081324
    - type: manhattan_pearson
      value: 87.33703179056744
    - type: manhattan_spearman
      value: 87.99192826922514
    - type: pearson
      value: 86.55319003300265
    - type: spearman
      value: 87.50267373081324
  - task:
      type: Clustering
    dataset:
      name: MTEB HALClusteringS2S (default)
      type: lyon-nlp/clustering-hal-s2s
      config: default
      split: test
      revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
    metrics:
    - type: main_score
      value: 27.477557517301303
    - type: v_measure
      value: 27.477557517301303
    - type: v_measure_std
      value: 3.3525736581861336
  - task:
      type: Classification
    dataset:
      name: MTEB HeadlineClassification (default)
      type: ai-forever/headline-classification
      config: default
      split: test
      revision: 2fe05ee6b5832cda29f2ef7aaad7b7fe6a3609eb
    metrics:
    - type: accuracy
      value: 75.0830078125
    - type: f1
      value: 75.08863209267814
    - type: f1_weighted
      value: 75.08895979060917
    - type: main_score
      value: 75.0830078125
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA (default)
      type: mteb/hotpotqa
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 38.143
    - type: map_at_10
      value: 55.916999999999994
    - type: map_at_100
      value: 56.706
    - type: map_at_1000
      value: 56.77100000000001
    - type: map_at_20
      value: 56.367
    - type: map_at_3
      value: 53.111
    - type: map_at_5
      value: 54.839000000000006
    - type: mrr_at_1
      value: 76.286
    - type: mrr_at_10
      value: 81.879
    - type: mrr_at_100
      value: 82.09100000000001
    - type: mrr_at_1000
      value: 82.101
    - type: mrr_at_20
      value: 82.01
    - type: mrr_at_3
      value: 80.972
    - type: mrr_at_5
      value: 81.537
    - type: ndcg_at_1
      value: 76.286
    - type: ndcg_at_10
      value: 64.673
    - type: ndcg_at_100
      value: 67.527
    - type: ndcg_at_1000
      value: 68.857
    - type: ndcg_at_20
      value: 65.822
    - type: ndcg_at_3
      value: 60.616
    - type: ndcg_at_5
      value: 62.827999999999996
    - type: precision_at_1
      value: 76.286
    - type: precision_at_10
      value: 13.196
    - type: precision_at_100
      value: 1.544
    - type: precision_at_1000
      value: 0.172
    - type: precision_at_20
      value: 6.968000000000001
    - type: precision_at_3
      value: 37.992
    - type: precision_at_5
      value: 24.54
    - type: recall_at_1
      value: 38.143
    - type: recall_at_10
      value: 65.982
    - type: recall_at_100
      value: 77.225
    - type: recall_at_1000
      value: 86.077
    - type: recall_at_20
      value: 69.68299999999999
    - type: recall_at_3
      value: 56.989000000000004
    - type: recall_at_5
      value: 61.35
    - type: main_score
      value: 64.673
  - task:
      type: Classification
    dataset:
      name: MTEB IFlyTek (default)
      type: C-MTEB/IFlyTek-classification
      config: default
      split: validation
      revision: 421605374b29664c5fc098418fe20ada9bd55f8a
    metrics:
    - type: accuracy
      value: 41.67756829549827
    - type: f1
      value: 33.929325579581636
    - type: f1_weighted
      value: 43.03952025643197
    - type: main_score
      value: 41.67756829549827
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification (default)
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 91.90440000000001
    - type: ap
      value: 88.78663714603425
    - type: ap_weighted
      value: 88.78663714603425
    - type: f1
      value: 91.89564361975891
    - type: f1_weighted
      value: 91.89564361975891
    - type: main_score
      value: 91.90440000000001
  - task:
      type: Classification
    dataset:
      name: MTEB InappropriatenessClassification (default)
      type: ai-forever/inappropriateness-classification
      config: default
      split: test
      revision: 601651fdc45ef243751676e62dd7a19f491c0285
    metrics:
    - type: accuracy
      value: 61.0498046875
    - type: ap
      value: 57.04240566648215
    - type: ap_weighted
      value: 57.04240566648215
    - type: f1
      value: 60.867630038606954
    - type: f1_weighted
      value: 60.867630038606954
    - type: main_score
      value: 61.0498046875
  - task:
      type: Classification
    dataset:
      name: MTEB JDReview (default)
      type: C-MTEB/JDReview-classification
      config: default
      split: test
      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
    metrics:
    - type: accuracy
      value: 83.50844277673546
    - type: ap
      value: 48.46732380712268
    - type: ap_weighted
      value: 48.46732380712268
    - type: f1
      value: 77.43967451387445
    - type: f1_weighted
      value: 84.78462929014114
    - type: main_score
      value: 83.50844277673546
  - task:
      type: Classification
    dataset:
      name: MTEB KinopoiskClassification (default)
      type: ai-forever/kinopoisk-sentiment-classification
      config: default
      split: test
      revision: 5911f26666ac11af46cb9c6849d0dc80a378af24
    metrics:
    - type: accuracy
      value: 62.393333333333324
    - type: f1
      value: 61.35940129568015
    - type: f1_weighted
      value: 61.35940129568015
    - type: main_score
      value: 62.393333333333324
  - task:
      type: STS
    dataset:
      name: MTEB LCQMC (default)
      type: C-MTEB/LCQMC
      config: default
      split: test
      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
    metrics:
    - type: cosine_pearson
      value: 67.74375505907872
    - type: cosine_spearman
      value: 75.94582231399434
    - type: euclidean_pearson
      value: 74.52501692443582
    - type: euclidean_spearman
      value: 75.88428434746646
    - type: main_score
      value: 75.94582231399434
    - type: manhattan_pearson
      value: 74.55015441749529
    - type: manhattan_spearman
      value: 75.83288262176175
    - type: pearson
      value: 67.74375505907872
    - type: spearman
      value: 75.94582231399434
  - task:
      type: Retrieval
    dataset:
      name: MTEB LEMBNarrativeQARetrieval (default)
      type: dwzhu/LongEmbed
      config: default
      split: test
      revision: 6e346642246bfb4928c560ee08640dc84d074e8c
    metrics:
    - type: map_at_1
      value: 23.093
    - type: map_at_10
      value: 30.227999999999998
    - type: map_at_100
      value: 31.423000000000002
    - type: map_at_1000
      value: 31.533
    - type: map_at_20
      value: 30.835
    - type: map_at_3
      value: 27.983999999999998
    - type: map_at_5
      value: 29.253
    - type: mrr_at_1
      value: 23.093
    - type: mrr_at_10
      value: 30.227999999999998
    - type: mrr_at_100
      value: 31.423000000000002
    - type: mrr_at_1000
      value: 31.533
    - type: mrr_at_20
      value: 30.835
    - type: mrr_at_3
      value: 27.983999999999998
    - type: mrr_at_5
      value: 29.253
    - type: ndcg_at_1
      value: 23.093
    - type: ndcg_at_10
      value: 34.297
    - type: ndcg_at_100
      value: 41.049
    - type: ndcg_at_1000
      value: 43.566
    - type: ndcg_at_20
      value: 36.52
    - type: ndcg_at_3
      value: 29.629
    - type: ndcg_at_5
      value: 31.926
    - type: precision_at_1
      value: 23.093
    - type: precision_at_10
      value: 4.735
    - type: precision_at_100
      value: 0.8109999999999999
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 2.8080000000000003
    - type: precision_at_3
      value: 11.468
    - type: precision_at_5
      value: 8.001
    - type: recall_at_1
      value: 23.093
    - type: recall_at_10
      value: 47.354
    - type: recall_at_100
      value: 81.147
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 56.16799999999999
    - type: recall_at_3
      value: 34.405
    - type: recall_at_5
      value: 40.004
    - type: main_score
      value: 34.297
    - type: map_at_1
      value: 24.361
    - type: map_at_10
      value: 33.641
    - type: map_at_100
      value: 35.104
    - type: map_at_1000
      value: 35.127
    - type: map_at_20
      value: 34.388999999999996
    - type: map_at_3
      value: 30.255
    - type: map_at_5
      value: 32.079
    - type: mrr_at_1
      value: 24.361
    - type: mrr_at_10
      value: 33.641
    - type: mrr_at_100
      value: 35.104
    - type: mrr_at_1000
      value: 35.127
    - type: mrr_at_20
      value: 34.388999999999996
    - type: mrr_at_3
      value: 30.255
    - type: mrr_at_5
      value: 32.079
    - type: ndcg_at_1
      value: 24.361
    - type: ndcg_at_10
      value: 39.337
    - type: ndcg_at_100
      value: 47.384
    - type: ndcg_at_1000
      value: 47.75
    - type: ndcg_at_20
      value: 42.077999999999996
    - type: ndcg_at_3
      value: 32.235
    - type: ndcg_at_5
      value: 35.524
    - type: precision_at_1
      value: 24.361
    - type: precision_at_10
      value: 5.783
    - type: precision_at_100
      value: 0.975
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 3.435
    - type: precision_at_3
      value: 12.661
    - type: precision_at_5
      value: 9.193999999999999
    - type: recall_at_1
      value: 24.361
    - type: recall_at_10
      value: 57.826
    - type: recall_at_100
      value: 97.51100000000001
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 68.697
    - type: recall_at_3
      value: 37.983
    - type: recall_at_5
      value: 45.972
    - type: main_score
      value: 39.337
    - type: map_at_1
      value: 53.667
    - type: map_at_10
      value: 61.719
    - type: map_at_100
      value: 62.471
    - type: map_at_1000
      value: 62.492000000000004
    - type: map_at_20
      value: 62.153000000000006
    - type: map_at_3
      value: 59.167
    - type: map_at_5
      value: 60.95
    - type: mrr_at_1
      value: 53.667
    - type: mrr_at_10
      value: 61.719
    - type: mrr_at_100
      value: 62.471
    - type: mrr_at_1000
      value: 62.492000000000004
    - type: mrr_at_20
      value: 62.153000000000006
    - type: mrr_at_3
      value: 59.167
    - type: mrr_at_5
      value: 60.95
    - type: ndcg_at_1
      value: 53.667
    - type: ndcg_at_10
      value: 66.018
    - type: ndcg_at_100
      value: 69.726
    - type: ndcg_at_1000
      value: 70.143
    - type: ndcg_at_20
      value: 67.61399999999999
    - type: ndcg_at_3
      value: 60.924
    - type: ndcg_at_5
      value: 64.10900000000001
    - type: precision_at_1
      value: 53.667
    - type: precision_at_10
      value: 7.9670000000000005
    - type: precision_at_100
      value: 0.97
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 4.3
    - type: precision_at_3
      value: 22.0
    - type: precision_at_5
      value: 14.732999999999999
    - type: recall_at_1
      value: 53.667
    - type: recall_at_10
      value: 79.667
    - type: recall_at_100
      value: 97.0
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 86.0
    - type: recall_at_3
      value: 66.0
    - type: recall_at_5
      value: 73.667
    - type: main_score
      value: 66.018
  - task:
      type: Retrieval
    dataset:
      name: MTEB LEMBNeedleRetrieval (default)
      type: dwzhu/LongEmbed
      config: default
      split: test_256
      revision: 6e346642246bfb4928c560ee08640dc84d074e8c
    metrics:
    - type: map_at_1
      value: 64.0
    - type: map_at_10
      value: 77.083
    - type: map_at_100
      value: 77.265
    - type: map_at_1000
      value: 77.265
    - type: map_at_20
      value: 77.265
    - type: map_at_3
      value: 76.333
    - type: map_at_5
      value: 76.833
    - type: mrr_at_1
      value: 64.0
    - type: mrr_at_10
      value: 77.083
    - type: mrr_at_100
      value: 77.265
    - type: mrr_at_1000
      value: 77.265
    - type: mrr_at_20
      value: 77.265
    - type: mrr_at_3
      value: 76.333
    - type: mrr_at_5
      value: 76.833
    - type: ndcg_at_1
      value: 64.0
    - type: ndcg_at_10
      value: 82.325
    - type: ndcg_at_100
      value: 82.883
    - type: ndcg_at_1000
      value: 82.883
    - type: ndcg_at_20
      value: 82.883
    - type: ndcg_at_3
      value: 80.833
    - type: ndcg_at_5
      value: 81.694
    - type: precision_at_1
      value: 64.0
    - type: precision_at_10
      value: 9.8
    - type: precision_at_100
      value: 1.0
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 5.0
    - type: precision_at_3
      value: 31.333
    - type: precision_at_5
      value: 19.2
    - type: recall_at_1
      value: 64.0
    - type: recall_at_10
      value: 98.0
    - type: recall_at_100
      value: 100.0
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 100.0
    - type: recall_at_3
      value: 94.0
    - type: recall_at_5
      value: 96.0
    - type: main_score
      value: 64.0
    - type: map_at_1
      value: 100.0
    - type: map_at_10
      value: 100.0
    - type: map_at_100
      value: 100.0
    - type: map_at_1000
      value: 100.0
    - type: map_at_20
      value: 100.0
    - type: map_at_3
      value: 100.0
    - type: map_at_5
      value: 100.0
    - type: mrr_at_1
      value: 100.0
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      type: dwzhu/LongEmbed
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  - task:
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      type: facebook/mlqa
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  - task:
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    dataset:
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      type: facebook/mlqa
      config: eng-eng
      split: test
      revision: 397ed406c1a7902140303e7faf60fff35b58d285
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  - task:
      type: Clustering
    dataset:
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      type: reciTAL/mlsum
      config: de
      split: test
      revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
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  - task:
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    dataset:
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      type: reciTAL/mlsum
      config: fr
      split: test
      revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
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  - task:
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      type: reciTAL/mlsum
      config: ru
      split: test
      revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
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  - task:
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      type: reciTAL/mlsum
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      revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
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  - task:
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      type: C-MTEB/Mmarco-reranking
      config: default
      split: dev
      revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6
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  - task:
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      type: C-MTEB/MMarcoRetrieval
      config: default
      split: dev
      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
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    - type: nauc_precision_at_1000_std
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    - type: nauc_precision_at_20_max
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    - type: nauc_precision_at_5_max
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    - type: nauc_precision_at_5_std
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    - type: nauc_recall_at_1000_diff1
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    - type: nauc_recall_at_1000_max
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    - type: nauc_recall_at_1000_std
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    - type: nauc_recall_at_100_diff1
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    - type: nauc_recall_at_100_max
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    - type: nauc_recall_at_100_std
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    - type: nauc_recall_at_10_diff1
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    - type: nauc_recall_at_10_std
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    - type: nauc_recall_at_3_diff1
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    - type: nauc_recall_at_3_max
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    - type: nauc_recall_at_3_std
      value: -11.55542913578436
    - type: nauc_recall_at_5_diff1
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    - type: nauc_recall_at_5_max
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    - type: nauc_recall_at_5_std
      value: -3.280167584070396
    - type: ndcg_at_1
      value: 69.18299999999999
    - type: ndcg_at_10
      value: 79.687
    - type: ndcg_at_100
      value: 81.062
    - type: ndcg_at_1000
      value: 81.312
    - type: ndcg_at_20
      value: 80.34599999999999
    - type: ndcg_at_3
      value: 75.98700000000001
    - type: ndcg_at_5
      value: 78.039
    - type: precision_at_1
      value: 69.18299999999999
    - type: precision_at_10
      value: 9.636
    - type: precision_at_100
      value: 1.0330000000000001
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_20
      value: 4.958
    - type: precision_at_3
      value: 28.515
    - type: precision_at_5
      value: 18.201
    - type: recall_at_1
      value: 66.872
    - type: recall_at_10
      value: 90.688
    - type: recall_at_100
      value: 96.99
    - type: recall_at_1000
      value: 98.958
    - type: recall_at_20
      value: 93.21199999999999
    - type: recall_at_3
      value: 80.84599999999999
    - type: recall_at_5
      value: 85.732
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO (default)
      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 21.861
    - type: map_at_10
      value: 34.008
    - type: map_at_100
      value: 35.174
    - type: map_at_1000
      value: 35.224
    - type: map_at_20
      value: 34.705999999999996
    - type: map_at_3
      value: 30.209000000000003
    - type: map_at_5
      value: 32.351
    - type: mrr_at_1
      value: 22.493
    - type: mrr_at_10
      value: 34.583999999999996
    - type: mrr_at_100
      value: 35.691
    - type: mrr_at_1000
      value: 35.736000000000004
    - type: mrr_at_20
      value: 35.257
    - type: mrr_at_3
      value: 30.85
    - type: mrr_at_5
      value: 32.962
    - type: ndcg_at_1
      value: 22.493
    - type: ndcg_at_10
      value: 40.815
    - type: ndcg_at_100
      value: 46.483999999999995
    - type: ndcg_at_1000
      value: 47.73
    - type: ndcg_at_20
      value: 43.302
    - type: ndcg_at_3
      value: 33.056000000000004
    - type: ndcg_at_5
      value: 36.879
    - type: precision_at_1
      value: 22.493
    - type: precision_at_10
      value: 6.465999999999999
    - type: precision_at_100
      value: 0.932
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_20
      value: 3.752
    - type: precision_at_3
      value: 14.069
    - type: precision_at_5
      value: 10.384
    - type: recall_at_1
      value: 21.861
    - type: recall_at_10
      value: 61.781
    - type: recall_at_100
      value: 88.095
    - type: recall_at_1000
      value: 97.625
    - type: recall_at_20
      value: 71.44500000000001
    - type: recall_at_3
      value: 40.653
    - type: recall_at_5
      value: 49.841
    - type: main_score
      value: 40.815
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 97.4874601003192
    - type: f1
      value: 97.19067544931094
    - type: f1_weighted
      value: 97.49331776181019
    - type: main_score
      value: 97.4874601003192
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (de)
      type: mteb/mtop_domain
      config: de
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 96.89489997182305
    - type: f1
      value: 96.51138586512977
    - type: f1_weighted
      value: 96.89723065967186
    - type: main_score
      value: 96.89489997182305
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (es)
      type: mteb/mtop_domain
      config: es
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 97.17144763175452
    - type: f1
      value: 96.81785681878274
    - type: f1_weighted
      value: 97.1778974586874
    - type: main_score
      value: 97.17144763175452
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (fr)
      type: mteb/mtop_domain
      config: fr
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 96.30128405887879
    - type: f1
      value: 95.94555923088487
    - type: f1_weighted
      value: 96.30399416794926
    - type: main_score
      value: 96.30128405887879
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 84.53488372093022
    - type: f1
      value: 61.77995074251401
    - type: f1_weighted
      value: 86.8005170485101
    - type: main_score
      value: 84.53488372093022
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (de)
      type: mteb/mtop_intent
      config: de
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 80.79459002535924
    - type: f1
      value: 56.08938302001448
    - type: f1_weighted
      value: 83.66582131948252
    - type: main_score
      value: 80.79459002535924
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (es)
      type: mteb/mtop_intent
      config: es
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 84.7765176784523
    - type: f1
      value: 61.39860057885528
    - type: f1_weighted
      value: 86.94881745670745
    - type: main_score
      value: 84.7765176784523
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (fr)
      type: mteb/mtop_intent
      config: fr
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 82.2079549013467
    - type: f1
      value: 59.90260478749016
    - type: f1_weighted
      value: 84.36861708593257
    - type: main_score
      value: 82.2079549013467
  - task:
      type: Classification
    dataset:
      name: MTEB MasakhaNEWSClassification (eng)
      type: mteb/masakhanews
      config: eng
      split: test
      revision: 18193f187b92da67168c655c9973a165ed9593dd
    metrics:
    - type: accuracy
      value: 74.98945147679325
    - type: f1
      value: 74.3157483560261
    - type: f1_weighted
      value: 75.01179008904884
    - type: main_score
      value: 74.98945147679325
  - task:
      type: Classification
    dataset:
      name: MTEB MasakhaNEWSClassification (fra)
      type: mteb/masakhanews
      config: fra
      split: test
      revision: 18193f187b92da67168c655c9973a165ed9593dd
    metrics:
    - type: accuracy
      value: 74.02843601895735
    - type: f1
      value: 70.40326349620732
    - type: f1_weighted
      value: 74.6596277063484
    - type: main_score
      value: 74.02843601895735
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (amh)
      type: masakhane/masakhanews
      config: amh
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 69.45780291725053
    - type: v_measure
      value: 69.45780291725053
    - type: v_measure_std
      value: 36.54340055904091
    - type: main_score
      value: 60.95132147787602
    - type: v_measure
      value: 60.95132147787602
    - type: v_measure_std
      value: 37.330148394033365
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (eng)
      type: masakhane/masakhanews
      config: eng
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 64.88996119332239
    - type: v_measure
      value: 64.88996119332239
    - type: v_measure_std
      value: 30.017223408197268
    - type: main_score
      value: 60.974810831426595
    - type: v_measure
      value: 60.974810831426595
    - type: v_measure_std
      value: 24.934675467507827
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (fra)
      type: masakhane/masakhanews
      config: fra
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 42.362383958691666
    - type: v_measure
      value: 42.362383958691666
    - type: v_measure_std
      value: 37.61076788039063
    - type: main_score
      value: 44.479206673553335
    - type: v_measure
      value: 44.479206673553335
    - type: v_measure_std
      value: 32.58254804499339
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (hau)
      type: masakhane/masakhanews
      config: hau
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 43.29201252405562
    - type: v_measure
      value: 43.29201252405562
    - type: v_measure_std
      value: 34.31987945146255
    - type: main_score
      value: 26.4742082741682
    - type: v_measure
      value: 26.4742082741682
    - type: v_measure_std
      value: 22.344929192323097
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (ibo)
      type: masakhane/masakhanews
      config: ibo
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 33.59926542995238
    - type: v_measure
      value: 33.59926542995238
    - type: v_measure_std
      value: 35.70048601084112
    - type: main_score
      value: 38.906129911741985
    - type: v_measure
      value: 38.906129911741985
    - type: v_measure_std
      value: 34.785601792668444
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (lin)
      type: masakhane/masakhanews
      config: lin
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 67.58487601893106
    - type: v_measure
      value: 67.58487601893106
    - type: v_measure_std
      value: 35.16784970777931
    - type: main_score
      value: 62.60982020876592
    - type: v_measure
      value: 62.60982020876592
    - type: v_measure_std
      value: 40.7368955715045
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (lug)
      type: masakhane/masakhanews
      config: lug
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 50.01220872023533
    - type: v_measure
      value: 50.01220872023533
    - type: v_measure_std
      value: 41.87411574676182
    - type: main_score
      value: 42.70424106365967
    - type: v_measure
      value: 42.70424106365967
    - type: v_measure_std
      value: 46.80946241135087
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (orm)
      type: masakhane/masakhanews
      config: orm
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 29.007847502598317
    - type: v_measure
      value: 29.007847502598317
    - type: v_measure_std
      value: 38.374997395079994
    - type: main_score
      value: 28.609942199922322
    - type: v_measure
      value: 28.609942199922322
    - type: v_measure_std
      value: 38.46685040191088
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (pcm)
      type: masakhane/masakhanews
      config: pcm
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 79.13520228554611
    - type: v_measure
      value: 79.13520228554611
    - type: v_measure_std
      value: 18.501843848275183
    - type: main_score
      value: 76.83901348810822
    - type: v_measure
      value: 76.83901348810822
    - type: v_measure_std
      value: 17.57617141269189
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (run)
      type: masakhane/masakhanews
      config: run
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 60.317213909746656
    - type: v_measure
      value: 60.317213909746656
    - type: v_measure_std
      value: 36.500281823747386
    - type: main_score
      value: 46.89757547846193
    - type: v_measure
      value: 46.89757547846193
    - type: v_measure_std
      value: 44.58903590203438
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (sna)
      type: masakhane/masakhanews
      config: sna
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 59.395277358240946
    - type: v_measure
      value: 59.395277358240946
    - type: v_measure_std
      value: 37.500916816164654
    - type: main_score
      value: 55.37185207068829
    - type: v_measure
      value: 55.37185207068829
    - type: v_measure_std
      value: 36.944574863543004
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (som)
      type: masakhane/masakhanews
      config: som
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 38.18638688704302
    - type: v_measure
      value: 38.18638688704302
    - type: v_measure_std
      value: 35.453681137564466
    - type: main_score
      value: 37.44211021681754
    - type: v_measure
      value: 37.44211021681754
    - type: v_measure_std
      value: 33.41469994463241
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (swa)
      type: masakhane/masakhanews
      config: swa
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 29.49230755729658
    - type: v_measure
      value: 29.49230755729658
    - type: v_measure_std
      value: 28.284313285264645
    - type: main_score
      value: 26.020680621216062
    - type: v_measure
      value: 26.020680621216062
    - type: v_measure_std
      value: 25.480037522570413
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (tir)
      type: masakhane/masakhanews
      config: tir
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 60.632258622750115
    - type: v_measure
      value: 60.632258622750115
    - type: v_measure_std
      value: 34.429711214740564
    - type: main_score
      value: 63.74306846771303
    - type: v_measure
      value: 63.74306846771303
    - type: v_measure_std
      value: 32.19119631078685
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (xho)
      type: masakhane/masakhanews
      config: xho
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 41.76322918806381
    - type: v_measure
      value: 41.76322918806381
    - type: v_measure_std
      value: 36.43245296200775
    - type: main_score
      value: 24.580890519243777
    - type: v_measure
      value: 24.580890519243777
    - type: v_measure_std
      value: 37.941836363967106
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (yor)
      type: masakhane/masakhanews
      config: yor
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 33.17083910808645
    - type: v_measure
      value: 33.17083910808645
    - type: v_measure_std
      value: 34.87547994284835
    - type: main_score
      value: 43.63458888828314
    - type: v_measure
      value: 43.63458888828314
    - type: v_measure_std
      value: 31.28169350649098
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (pl)
      type: mteb/amazon_massive_intent
      config: pl
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 75.37323470073974
    - type: f1
      value: 71.1836877753734
    - type: f1_weighted
      value: 75.72073213955457
    - type: main_score
      value: 75.37323470073974
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (de)
      type: mteb/amazon_massive_intent
      config: de
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 74.83523873570948
    - type: f1
      value: 70.72375821116886
    - type: f1_weighted
      value: 75.20800490010755
    - type: main_score
      value: 74.83523873570948
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (es)
      type: mteb/amazon_massive_intent
      config: es
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 75.31607262945528
    - type: f1
      value: 72.06063554897662
    - type: f1_weighted
      value: 75.72438161355252
    - type: main_score
      value: 75.31607262945528
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ru)
      type: mteb/amazon_massive_intent
      config: ru
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 76.7955615332885
    - type: f1
      value: 73.08099648499756
    - type: f1_weighted
      value: 77.18482068239668
    - type: main_score
      value: 76.7955615332885
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 77.60591795561534
    - type: f1
      value: 74.46676705370395
    - type: f1_weighted
      value: 77.69888062336614
    - type: main_score
      value: 77.60591795561534
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fr)
      type: mteb/amazon_massive_intent
      config: fr
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 76.32145258910558
    - type: f1
      value: 72.89824154178328
    - type: f1_weighted
      value: 76.6539327979472
    - type: main_score
      value: 76.32145258910558
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (zh-CN)
      type: mteb/amazon_massive_intent
      config: zh-CN
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 73.21788836583724
    - type: f1
      value: 70.45594512246377
    - type: f1_weighted
      value: 73.67862536499393
    - type: main_score
      value: 73.21788836583724
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (zh-CN)
      type: mteb/amazon_massive_scenario
      config: zh-CN
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
    - type: accuracy
      value: 80.82044384667114
    - type: f1
      value: 80.53217664465089
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      value: 80.94535087010512
    - type: main_score
      value: 80.82044384667114
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (pl)
      type: mteb/amazon_massive_scenario
      config: pl
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
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      value: 82.1049092131809
    - type: f1
      value: 81.55343463694733
    - type: f1_weighted
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    - type: main_score
      value: 82.1049092131809
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (es)
      type: mteb/amazon_massive_scenario
      config: es
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
    - type: accuracy
      value: 82.58238063214526
    - type: f1
      value: 82.27974449333072
    - type: f1_weighted
      value: 82.81337569618209
    - type: main_score
      value: 82.58238063214526
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (de)
      type: mteb/amazon_massive_scenario
      config: de
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
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      value: 83.97108271687962
    - type: f1
      value: 83.56285606936076
    - type: f1_weighted
      value: 84.10198745390771
    - type: main_score
      value: 83.97108271687962
  - 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: 84.71082716879623
    - type: f1
      value: 84.09447062371402
    - type: f1_weighted
      value: 84.73765765551342
    - type: main_score
      value: 84.71082716879623
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (fr)
      type: mteb/amazon_massive_scenario
      config: fr
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
    - type: accuracy
      value: 83.093476798924
    - type: f1
      value: 82.72656900752943
    - type: f1_weighted
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    - type: main_score
      value: 83.093476798924
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ru)
      type: mteb/amazon_massive_scenario
      config: ru
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
    - type: accuracy
      value: 84.05850706119705
    - type: f1
      value: 83.64234048881222
    - type: f1_weighted
      value: 84.17315768381876
    - type: main_score
      value: 84.05850706119705
  - task:
      type: Retrieval
    dataset:
      name: MTEB MedicalRetrieval (default)
      type: C-MTEB/MedicalRetrieval
      config: default
      split: dev
      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
    metrics:
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    - type: map_at_10
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    - type: map_at_100
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    - type: map_at_1000
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    - type: map_at_20
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    - type: map_at_3
      value: 52.833
    - type: map_at_5
      value: 53.503
    - type: mrr_at_1
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    - type: mrr_at_10
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    - type: mrr_at_100
      value: 54.45008993448266
    - type: mrr_at_1000
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    - type: mrr_at_20
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    - type: mrr_at_3
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    - type: mrr_at_5
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    - type: ndcg_at_1
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    - type: ndcg_at_10
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    - type: ndcg_at_100
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    - type: ndcg_at_1000
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    - type: ndcg_at_20
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    - type: ndcg_at_3
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    - type: ndcg_at_5
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    - type: precision_at_1
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    - type: precision_at_10
      value: 6.5
    - type: precision_at_100
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    - type: precision_at_1000
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    - type: precision_at_20
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    - type: precision_at_3
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    - type: precision_at_5
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    - type: recall_at_1
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    - type: recall_at_10
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    - type: recall_at_100
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    - type: recall_at_1000
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    - type: recall_at_20
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    - type: recall_at_3
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    - type: recall_at_5
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  - 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: 34.80188561439236
    - type: v_measure
      value: 34.80188561439236
    - type: v_measure_std
      value: 1.5703148841573102
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S (default)
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: main_score
      value: 32.42285513996236
    - type: v_measure
      value: 32.42285513996236
    - type: v_measure_std
      value: 1.3769867487457566
  - task:
      type: Retrieval
    dataset:
      name: MTEB MintakaRetrieval (de)
      type: jinaai/mintakaqa
      config: de
      split: test
      revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
    metrics:
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      value: 27.025
    - type: map_at_1
      value: 14.532
    - type: map_at_10
      value: 22.612
    - type: map_at_100
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    - type: map_at_1000
      value: 23.9
    - type: map_at_20
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    - type: map_at_3
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    - type: map_at_5
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    - type: mrr_at_1
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    - type: mrr_at_10
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    - type: mrr_at_100
      value: 23.801523356874675
    - type: mrr_at_1000
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    - type: mrr_at_20
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    - type: mrr_at_3
      value: 20.22606009547877
    - type: mrr_at_5
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    - type: nauc_map_at_1000_diff1
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    - type: nauc_map_at_1000_max
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    - type: nauc_map_at_1000_std
      value: 15.868006767707637
    - type: nauc_map_at_100_diff1
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  - task:
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    - type: nauc_mrr_at_1000_max
      value: 47.240929150603336
    - type: nauc_mrr_at_1000_std
      value: 20.559244258100275
    - type: nauc_mrr_at_100_diff1
      value: 17.029461792796777
    - type: nauc_mrr_at_100_max
      value: 47.207381115550696
    - type: nauc_mrr_at_100_std
      value: 20.581498156895265
    - type: nauc_mrr_at_10_diff1
      value: 17.351456007804536
    - type: nauc_mrr_at_10_max
      value: 47.815880040221344
    - type: nauc_mrr_at_10_std
      value: 20.292999107555794
    - type: nauc_mrr_at_1_diff1
      value: 27.297525357600776
    - type: nauc_mrr_at_1_max
      value: 47.18835074959486
    - type: nauc_mrr_at_1_std
      value: 18.304203168281834
    - type: nauc_mrr_at_20_diff1
      value: 17.157460199542136
    - type: nauc_mrr_at_20_max
      value: 47.4776610667456
    - type: nauc_mrr_at_20_std
      value: 20.499186342964478
    - type: nauc_mrr_at_3_diff1
      value: 19.393119961356277
    - type: nauc_mrr_at_3_max
      value: 49.02841822452882
    - type: nauc_mrr_at_3_std
      value: 19.293122796321292
    - type: nauc_mrr_at_5_diff1
      value: 17.76275044752008
    - type: nauc_mrr_at_5_max
      value: 48.01292548040298
    - type: nauc_mrr_at_5_std
      value: 19.928449977400504
    - type: nauc_ndcg_at_1000_diff1
      value: 13.989496006047975
    - type: nauc_ndcg_at_1000_max
      value: 45.626323944336114
    - type: nauc_ndcg_at_1000_std
      value: 22.125600410796515
    - type: nauc_ndcg_at_100_diff1
      value: 12.302204843705244
    - type: nauc_ndcg_at_100_max
      value: 44.46856314559079
    - type: nauc_ndcg_at_100_std
      value: 23.084984546328677
    - type: nauc_ndcg_at_10_diff1
      value: 14.001226213368275
    - type: nauc_ndcg_at_10_max
      value: 47.37780636546918
    - type: nauc_ndcg_at_10_std
      value: 21.702709032840637
    - type: nauc_ndcg_at_1_diff1
      value: 27.297525357600776
    - type: nauc_ndcg_at_1_max
      value: 47.18835074959486
    - type: nauc_ndcg_at_1_std
      value: 18.304203168281834
    - type: nauc_ndcg_at_20_diff1
      value: 13.317759910171056
    - type: nauc_ndcg_at_20_max
      value: 46.25171251043813
    - type: nauc_ndcg_at_20_std
      value: 22.309331575402595
    - type: nauc_ndcg_at_3_diff1
      value: 17.555381234893872
    - type: nauc_ndcg_at_3_max
      value: 49.48635590260059
    - type: nauc_ndcg_at_3_std
      value: 19.734570962933674
    - type: nauc_ndcg_at_5_diff1
      value: 14.844841165765061
    - type: nauc_ndcg_at_5_max
      value: 47.76437065028708
    - type: nauc_ndcg_at_5_std
      value: 20.816034479453954
    - type: nauc_precision_at_1000_diff1
      value: -15.591898698252546
    - type: nauc_precision_at_1000_max
      value: 20.545984285353892
    - type: nauc_precision_at_1000_std
      value: 38.9013414992826
    - type: nauc_precision_at_100_diff1
      value: -5.290395978742176
    - type: nauc_precision_at_100_max
      value: 31.340480360546845
    - type: nauc_precision_at_100_std
      value: 33.6897935720505
    - type: nauc_precision_at_10_diff1
      value: 5.965001997926562
    - type: nauc_precision_at_10_max
      value: 46.12515296162247
    - type: nauc_precision_at_10_std
      value: 25.409433135253558
    - type: nauc_precision_at_1_diff1
      value: 27.297525357600776
    - type: nauc_precision_at_1_max
      value: 47.18835074959486
    - type: nauc_precision_at_1_std
      value: 18.304203168281834
    - type: nauc_precision_at_20_diff1
      value: 3.4438127279827744
    - type: nauc_precision_at_20_max
      value: 42.36095587714494
    - type: nauc_precision_at_20_std
      value: 27.367900512797906
    - type: nauc_precision_at_3_diff1
      value: 13.165017224718916
    - type: nauc_precision_at_3_max
      value: 50.58931825484506
    - type: nauc_precision_at_3_std
      value: 20.852009214609442
    - type: nauc_precision_at_5_diff1
      value: 7.840087177549876
    - type: nauc_precision_at_5_max
      value: 46.99388755575109
    - type: nauc_precision_at_5_std
      value: 23.048702393099834
    - type: nauc_recall_at_1000_diff1
      value: -15.591898698252932
    - type: nauc_recall_at_1000_max
      value: 20.5459842853537
    - type: nauc_recall_at_1000_std
      value: 38.901341499282395
    - type: nauc_recall_at_100_diff1
      value: -5.290395978742165
    - type: nauc_recall_at_100_max
      value: 31.340480360546863
    - type: nauc_recall_at_100_std
      value: 33.68979357205046
    - type: nauc_recall_at_10_diff1
      value: 5.96500199792656
    - type: nauc_recall_at_10_max
      value: 46.1251529616225
    - type: nauc_recall_at_10_std
      value: 25.409433135253543
    - type: nauc_recall_at_1_diff1
      value: 27.297525357600776
    - type: nauc_recall_at_1_max
      value: 47.18835074959486
    - type: nauc_recall_at_1_std
      value: 18.304203168281834
    - type: nauc_recall_at_20_diff1
      value: 3.4438127279827833
    - type: nauc_recall_at_20_max
      value: 42.36095587714498
    - type: nauc_recall_at_20_std
      value: 27.36790051279787
    - type: nauc_recall_at_3_diff1
      value: 13.165017224718916
    - type: nauc_recall_at_3_max
      value: 50.589318254845054
    - type: nauc_recall_at_3_std
      value: 20.852009214609435
    - type: nauc_recall_at_5_diff1
      value: 7.840087177549891
    - type: nauc_recall_at_5_max
      value: 46.99388755575112
    - type: nauc_recall_at_5_std
      value: 23.048702393099845
    - type: ndcg_at_1
      value: 14.701
    - type: ndcg_at_10
      value: 26.909
    - type: ndcg_at_100
      value: 32.727000000000004
    - type: ndcg_at_1000
      value: 36.086
    - type: ndcg_at_20
      value: 29.236
    - type: ndcg_at_3
      value: 22.004
    - type: ndcg_at_5
      value: 24.615000000000002
    - type: precision_at_1
      value: 14.701
    - type: precision_at_10
      value: 4.062
    - type: precision_at_100
      value: 0.688
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_20
      value: 2.488
    - type: precision_at_3
      value: 9.036
    - type: precision_at_5
      value: 6.699
    - type: recall_at_1
      value: 14.701
    - type: recall_at_10
      value: 40.622
    - type: recall_at_100
      value: 68.796
    - type: recall_at_1000
      value: 96.314
    - type: recall_at_20
      value: 49.754
    - type: recall_at_3
      value: 27.108999999999998
    - type: recall_at_5
      value: 33.497
  - task:
      type: Classification
    dataset:
      name: MTEB MultilingualSentiment (default)
      type: C-MTEB/MultilingualSentiment-classification
      config: default
      split: test
      revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
    metrics:
    - type: accuracy
      value: 73.20999999999998
    - type: f1
      value: 73.18755986777474
    - type: f1_weighted
      value: 73.18755986777475
    - type: main_score
      value: 73.20999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus (default)
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.822
    - type: map_at_10
      value: 13.144
    - type: map_at_100
      value: 17.254
    - type: map_at_1000
      value: 18.931
    - type: map_at_20
      value: 14.834
    - type: map_at_3
      value: 8.975
    - type: map_at_5
      value: 10.922
    - type: mrr_at_1
      value: 47.059
    - type: mrr_at_10
      value: 55.806999999999995
    - type: mrr_at_100
      value: 56.286
    - type: mrr_at_1000
      value: 56.327000000000005
    - type: mrr_at_20
      value: 56.00000000000001
    - type: mrr_at_3
      value: 54.17999999999999
    - type: mrr_at_5
      value: 55.155
    - type: ndcg_at_1
      value: 44.427
    - type: ndcg_at_10
      value: 36.623
    - type: ndcg_at_100
      value: 33.664
    - type: ndcg_at_1000
      value: 42.538
    - type: ndcg_at_20
      value: 34.066
    - type: ndcg_at_3
      value: 41.118
    - type: ndcg_at_5
      value: 39.455
    - type: precision_at_1
      value: 46.44
    - type: precision_at_10
      value: 28.607
    - type: precision_at_100
      value: 9.189
    - type: precision_at_1000
      value: 2.261
    - type: precision_at_20
      value: 21.238
    - type: precision_at_3
      value: 39.628
    - type: precision_at_5
      value: 35.604
    - type: recall_at_1
      value: 4.822
    - type: recall_at_10
      value: 17.488999999999997
    - type: recall_at_100
      value: 35.052
    - type: recall_at_1000
      value: 66.67999999999999
    - type: recall_at_20
      value: 21.343999999999998
    - type: recall_at_3
      value: 10.259
    - type: recall_at_5
      value: 13.406
    - type: main_score
      value: 36.623
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ (default)
      type: mteb/nq
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 41.411
    - type: map_at_10
      value: 57.179
    - type: map_at_100
      value: 57.945
    - type: map_at_1000
      value: 57.967999999999996
    - type: map_at_20
      value: 57.687
    - type: map_at_3
      value: 53.46300000000001
    - type: map_at_5
      value: 55.696999999999996
    - type: mrr_at_1
      value: 46.233999999999995
    - type: mrr_at_10
      value: 59.831999999999994
    - type: mrr_at_100
      value: 60.33500000000001
    - type: mrr_at_1000
      value: 60.348
    - type: mrr_at_20
      value: 60.167
    - type: mrr_at_3
      value: 56.972
    - type: mrr_at_5
      value: 58.74
    - type: ndcg_at_1
      value: 46.205
    - type: ndcg_at_10
      value: 64.23100000000001
    - type: ndcg_at_100
      value: 67.242
    - type: ndcg_at_1000
      value: 67.72500000000001
    - type: ndcg_at_20
      value: 65.77300000000001
    - type: ndcg_at_3
      value: 57.516
    - type: ndcg_at_5
      value: 61.11600000000001
    - type: precision_at_1
      value: 46.205
    - type: precision_at_10
      value: 9.873
    - type: precision_at_100
      value: 1.158
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_20
      value: 5.319
    - type: precision_at_3
      value: 25.424999999999997
    - type: precision_at_5
      value: 17.375
    - type: recall_at_1
      value: 41.411
    - type: recall_at_10
      value: 82.761
    - type: recall_at_100
      value: 95.52199999999999
    - type: recall_at_1000
      value: 99.02499999999999
    - type: recall_at_20
      value: 88.34
    - type: recall_at_3
      value: 65.73
    - type: recall_at_5
      value: 73.894
    - type: main_score
      value: 64.23100000000001
  - task:
      type: PairClassification
    dataset:
      name: MTEB Ocnli (default)
      type: C-MTEB/OCNLI
      config: default
      split: validation
      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
    metrics:
    - type: cosine_accuracy
      value: 62.3714131023281
    - type: cosine_accuracy_threshold
      value: 79.70921993255615
    - type: cosine_ap
      value: 66.41380155495659
    - type: cosine_f1
      value: 68.89547185780786
    - type: cosine_f1_threshold
      value: 72.91591167449951
    - type: cosine_precision
      value: 57.485875706214685
    - type: cosine_recall
      value: 85.95564941921859
    - type: dot_accuracy
      value: 60.47644829453167
    - type: dot_accuracy_threshold
      value: 36627.362060546875
    - type: dot_ap
      value: 63.696303449293204
    - type: dot_f1
      value: 68.3986041101202
    - type: dot_f1_threshold
      value: 30452.72216796875
    - type: dot_precision
      value: 54.04411764705882
    - type: dot_recall
      value: 93.13621964097149
    - type: euclidean_accuracy
      value: 63.02111532214402
    - type: euclidean_accuracy_threshold
      value: 1392.76762008667
    - type: euclidean_ap
      value: 66.65907089443218
    - type: euclidean_f1
      value: 69.05036524413688
    - type: euclidean_f1_threshold
      value: 1711.5310668945312
    - type: euclidean_precision
      value: 54.29262394195889
    - type: euclidean_recall
      value: 94.82576557550159
    - type: main_score
      value: 63.02111532214402
    - type: manhattan_accuracy
      value: 62.75040606388739
    - type: manhattan_accuracy_threshold
      value: 32475.347900390625
    - type: manhattan_ap
      value: 66.50943585125434
    - type: manhattan_f1
      value: 69.08382066276802
    - type: manhattan_f1_threshold
      value: 41238.470458984375
    - type: manhattan_precision
      value: 54.75896168108776
    - type: manhattan_recall
      value: 93.55860612460401
    - type: max_accuracy
      value: 63.02111532214402
    - type: max_ap
      value: 66.65907089443218
    - type: max_f1
      value: 69.08382066276802
    - type: max_precision
      value: 57.485875706214685
    - type: max_recall
      value: 94.82576557550159
    - type: similarity_accuracy
      value: 62.3714131023281
    - type: similarity_accuracy_threshold
      value: 79.70921993255615
    - type: similarity_ap
      value: 66.41380155495659
    - type: similarity_f1
      value: 68.89547185780786
    - type: similarity_f1_threshold
      value: 72.91591167449951
    - type: similarity_precision
      value: 57.485875706214685
    - type: similarity_recall
      value: 85.95564941921859
  - task:
      type: Classification
    dataset:
      name: MTEB OnlineShopping (default)
      type: C-MTEB/OnlineShopping-classification
      config: default
      split: test
      revision: e610f2ebd179a8fda30ae534c3878750a96db120
    metrics:
    - type: accuracy
      value: 91.88000000000001
    - type: ap
      value: 89.52463684448476
    - type: ap_weighted
      value: 89.52463684448476
    - type: f1
      value: 91.86313022306673
    - type: f1_weighted
      value: 91.87806318146912
    - type: main_score
      value: 91.88000000000001
  - task:
      type: PairClassification
    dataset:
      name: MTEB OpusparcusPC (en)
      type: GEM/opusparcus
      config: en
      split: test.full
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    metrics:
    - type: cosine_accuracy
      value: 92.65578635014838
    - type: cosine_accuracy_threshold
      value: 74.02530312538147
    - type: cosine_ap
      value: 98.3834226153613
    - type: cosine_f1
      value: 94.92567913890312
    - type: cosine_f1_threshold
      value: 74.02530312538147
    - type: cosine_precision
      value: 95.562435500516
    - type: cosine_recall
      value: 94.29735234215886
    - type: dot_accuracy
      value: 91.54302670623146
    - type: dot_accuracy_threshold
      value: 34452.29187011719
    - type: dot_ap
      value: 98.1237257754439
    - type: dot_f1
      value: 94.22400803616273
    - type: dot_f1_threshold
      value: 33670.41931152344
    - type: dot_precision
      value: 92.9633300297324
    - type: dot_recall
      value: 95.5193482688391
    - type: euclidean_accuracy
      value: 92.28486646884274
    - type: euclidean_accuracy_threshold
      value: 1602.8022766113281
    - type: euclidean_ap
      value: 98.3099021504706
    - type: euclidean_f1
      value: 94.75277497477296
    - type: euclidean_f1_threshold
      value: 1604.7462463378906
    - type: euclidean_precision
      value: 93.89999999999999
    - type: euclidean_recall
      value: 95.62118126272912
    - type: main_score
      value: 98.3834226153613
    - type: manhattan_accuracy
      value: 92.2106824925816
    - type: manhattan_accuracy_threshold
      value: 38872.90954589844
    - type: manhattan_ap
      value: 98.28694101230218
    - type: manhattan_f1
      value: 94.67815509376584
    - type: manhattan_f1_threshold
      value: 38872.90954589844
    - type: manhattan_precision
      value: 94.24823410696267
    - type: manhattan_recall
      value: 95.11201629327903
    - type: max_accuracy
      value: 92.65578635014838
    - type: max_ap
      value: 98.3834226153613
    - type: max_f1
      value: 94.92567913890312
    - type: max_precision
      value: 95.562435500516
    - type: max_recall
      value: 95.62118126272912
    - type: similarity_accuracy
      value: 92.65578635014838
    - type: similarity_accuracy_threshold
      value: 74.02530312538147
    - type: similarity_ap
      value: 98.3834226153613
    - type: similarity_f1
      value: 94.92567913890312
    - type: similarity_f1_threshold
      value: 74.02530312538147
    - type: similarity_precision
      value: 95.562435500516
    - type: similarity_recall
      value: 94.29735234215886
  - task:
      type: PairClassification
    dataset:
      name: MTEB OpusparcusPC (de)
      type: GEM/opusparcus
      config: de
      split: test.full
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    metrics:
    - type: cosine_accuracy
      value: 87.72178850248403
    - type: cosine_accuracy_threshold
      value: 73.33863377571106
    - type: cosine_ap
      value: 96.98901408834976
    - type: cosine_f1
      value: 91.89944134078212
    - type: cosine_f1_threshold
      value: 71.45810127258301
    - type: cosine_precision
      value: 89.64577656675749
    - type: cosine_recall
      value: 94.26934097421203
    - type: dot_accuracy
      value: 86.30234208658624
    - type: dot_accuracy_threshold
      value: 32027.130126953125
    - type: dot_ap
      value: 96.12260574893256
    - type: dot_f1
      value: 91.31602506714414
    - type: dot_f1_threshold
      value: 30804.376220703125
    - type: dot_precision
      value: 85.93091828138164
    - type: dot_recall
      value: 97.42120343839542
    - type: euclidean_accuracy
      value: 87.9347054648687
    - type: euclidean_accuracy_threshold
      value: 1609.6670150756836
    - type: euclidean_ap
      value: 97.00238860358252
    - type: euclidean_f1
      value: 92.1089063221043
    - type: euclidean_f1_threshold
      value: 1641.8487548828125
    - type: euclidean_precision
      value: 89.10714285714286
    - type: euclidean_recall
      value: 95.31996179560649
    - type: main_score
      value: 97.00238860358252
    - type: manhattan_accuracy
      value: 87.72178850248403
    - type: manhattan_accuracy_threshold
      value: 40137.060546875
    - type: manhattan_ap
      value: 96.98653728159941
    - type: manhattan_f1
      value: 92.03865623561896
    - type: manhattan_f1_threshold
      value: 40137.060546875
    - type: manhattan_precision
      value: 88.80994671403198
    - type: manhattan_recall
      value: 95.51098376313276
    - type: max_accuracy
      value: 87.9347054648687
    - type: max_ap
      value: 97.00238860358252
    - type: max_f1
      value: 92.1089063221043
    - type: max_precision
      value: 89.64577656675749
    - type: max_recall
      value: 97.42120343839542
    - type: similarity_accuracy
      value: 87.72178850248403
    - type: similarity_accuracy_threshold
      value: 73.33863377571106
    - type: similarity_ap
      value: 96.98901408834976
    - type: similarity_f1
      value: 91.89944134078212
    - type: similarity_f1_threshold
      value: 71.45810127258301
    - type: similarity_precision
      value: 89.64577656675749
    - type: similarity_recall
      value: 94.26934097421203
  - task:
      type: PairClassification
    dataset:
      name: MTEB OpusparcusPC (fr)
      type: GEM/opusparcus
      config: fr
      split: test.full
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    metrics:
    - type: cosine_accuracy
      value: 80.92643051771117
    - type: cosine_accuracy_threshold
      value: 76.68856382369995
    - type: cosine_ap
      value: 93.74622381534307
    - type: cosine_f1
      value: 87.12328767123287
    - type: cosine_f1_threshold
      value: 71.64022922515869
    - type: cosine_precision
      value: 80.64243448858834
    - type: cosine_recall
      value: 94.73684210526315
    - type: dot_accuracy
      value: 80.858310626703
    - type: dot_accuracy_threshold
      value: 34028.3935546875
    - type: dot_ap
      value: 91.18448457633308
    - type: dot_f1
      value: 86.82606657290202
    - type: dot_f1_threshold
      value: 34028.3935546875
    - type: dot_precision
      value: 82.2380106571936
    - type: dot_recall
      value: 91.9563058589871
    - type: euclidean_accuracy
      value: 80.858310626703
    - type: euclidean_accuracy_threshold
      value: 1595.7651138305664
    - type: euclidean_ap
      value: 93.8182717829648
    - type: euclidean_f1
      value: 87.04044117647058
    - type: euclidean_f1_threshold
      value: 1609.2475891113281
    - type: euclidean_precision
      value: 81.00940975192472
    - type: euclidean_recall
      value: 94.04170804369414
    - type: main_score
      value: 93.8182717829648
    - type: manhattan_accuracy
      value: 80.99455040871935
    - type: manhattan_accuracy_threshold
      value: 38092.132568359375
    - type: manhattan_ap
      value: 93.77563401151711
    - type: manhattan_f1
      value: 86.91983122362869
    - type: manhattan_f1_threshold
      value: 38092.132568359375
    - type: manhattan_precision
      value: 82.32682060390763
    - type: manhattan_recall
      value: 92.05561072492551
    - type: max_accuracy
      value: 80.99455040871935
    - type: max_ap
      value: 93.8182717829648
    - type: max_f1
      value: 87.12328767123287
    - type: max_precision
      value: 82.32682060390763
    - type: max_recall
      value: 94.73684210526315
    - type: similarity_accuracy
      value: 80.92643051771117
    - type: similarity_accuracy_threshold
      value: 76.68856382369995
    - type: similarity_ap
      value: 93.74622381534307
    - type: similarity_f1
      value: 87.12328767123287
    - type: similarity_f1_threshold
      value: 71.64022922515869
    - type: similarity_precision
      value: 80.64243448858834
    - type: similarity_recall
      value: 94.73684210526315
  - task:
      type: PairClassification
    dataset:
      name: MTEB OpusparcusPC (ru)
      type: GEM/opusparcus
      config: ru
      split: test.full
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    metrics:
    - type: cosine_accuracy
      value: 76.83823529411765
    - type: cosine_accuracy_threshold
      value: 72.70769476890564
    - type: cosine_ap
      value: 89.56692049908222
    - type: cosine_f1
      value: 83.99832003359934
    - type: cosine_f1_threshold
      value: 70.9052324295044
    - type: cosine_precision
      value: 76.16146230007617
    - type: cosine_recall
      value: 93.63295880149812
    - type: dot_accuracy
      value: 76.28676470588235
    - type: dot_accuracy_threshold
      value: 33740.68908691406
    - type: dot_ap
      value: 87.77185177141567
    - type: dot_f1
      value: 83.62251375370292
    - type: dot_f1_threshold
      value: 32726.611328125
    - type: dot_precision
      value: 76.29343629343629
    - type: dot_recall
      value: 92.50936329588015
    - type: euclidean_accuracy
      value: 77.32843137254902
    - type: euclidean_accuracy_threshold
      value: 1566.510009765625
    - type: euclidean_ap
      value: 89.60605626791111
    - type: euclidean_f1
      value: 84.06546080964686
    - type: euclidean_f1_threshold
      value: 1576.4202117919922
    - type: euclidean_precision
      value: 77.83094098883574
    - type: euclidean_recall
      value: 91.38576779026218
    - type: main_score
      value: 89.60605626791111
    - type: manhattan_accuracy
      value: 76.89950980392157
    - type: manhattan_accuracy_threshold
      value: 38202.215576171875
    - type: manhattan_ap
      value: 89.55766894104868
    - type: manhattan_f1
      value: 83.80462724935732
    - type: manhattan_f1_threshold
      value: 38934.375
    - type: manhattan_precision
      value: 77.25118483412322
    - type: manhattan_recall
      value: 91.57303370786516
    - type: max_accuracy
      value: 77.32843137254902
    - type: max_ap
      value: 89.60605626791111
    - type: max_f1
      value: 84.06546080964686
    - type: max_precision
      value: 77.83094098883574
    - type: max_recall
      value: 93.63295880149812
    - type: similarity_accuracy
      value: 76.83823529411765
    - type: similarity_accuracy_threshold
      value: 72.70769476890564
    - type: similarity_ap
      value: 89.56692049908222
    - type: similarity_f1
      value: 83.99832003359934
    - type: similarity_f1_threshold
      value: 70.9052324295044
    - type: similarity_precision
      value: 76.16146230007617
    - type: similarity_recall
      value: 93.63295880149812
  - task:
      type: Classification
    dataset:
      name: MTEB PAC (default)
      type: laugustyniak/abusive-clauses-pl
      config: default
      split: test
      revision: fc69d1c153a8ccdcf1eef52f4e2a27f88782f543
    metrics:
    - type: accuracy
      value: 68.39559803069794
    - type: ap
      value: 77.68074206719457
    - type: ap_weighted
      value: 77.68074206719457
    - type: f1
      value: 66.23485605467732
    - type: f1_weighted
      value: 69.03201442129347
    - type: main_score
      value: 68.39559803069794
  - task:
      type: STS
    dataset:
      name: MTEB PAWSX (default)
      type: C-MTEB/PAWSX
      config: default
      split: test
      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
    metrics:
    - type: cosine_pearson
      value: 13.161523266433587
    - type: cosine_spearman
      value: 15.557333873773386
    - type: euclidean_pearson
      value: 17.147508431907525
    - type: euclidean_spearman
      value: 15.664112857732146
    - type: main_score
      value: 15.557333873773386
    - type: manhattan_pearson
      value: 17.130875906264386
    - type: manhattan_spearman
      value: 15.624397342229637
    - type: pearson
      value: 13.161523266433587
    - type: spearman
      value: 15.557333873773386
  - task:
      type: PairClassification
    dataset:
      name: MTEB PSC (default)
      type: PL-MTEB/psc-pairclassification
      config: default
      split: test
      revision: d05a294af9e1d3ff2bfb6b714e08a24a6cabc669
    metrics:
    - type: cosine_accuracy
      value: 97.86641929499072
    - type: cosine_accuracy_threshold
      value: 79.0391206741333
    - type: cosine_ap
      value: 99.19403807771533
    - type: cosine_f1
      value: 96.45608628659475
    - type: cosine_f1_threshold
      value: 79.0391206741333
    - type: cosine_precision
      value: 97.50778816199377
    - type: cosine_recall
      value: 95.42682926829268
    - type: dot_accuracy
      value: 98.14471243042672
    - type: dot_accuracy_threshold
      value: 29808.1787109375
    - type: dot_ap
      value: 99.331999859971
    - type: dot_f1
      value: 97.01492537313433
    - type: dot_f1_threshold
      value: 29808.1787109375
    - type: dot_precision
      value: 95.02923976608187
    - type: dot_recall
      value: 99.08536585365853
    - type: euclidean_accuracy
      value: 97.49536178107606
    - type: euclidean_accuracy_threshold
      value: 1276.227855682373
    - type: euclidean_ap
      value: 98.91056467717377
    - type: euclidean_f1
      value: 95.83975346687212
    - type: euclidean_f1_threshold
      value: 1276.227855682373
    - type: euclidean_precision
      value: 96.88473520249221
    - type: euclidean_recall
      value: 94.8170731707317
    - type: main_score
      value: 99.331999859971
    - type: manhattan_accuracy
      value: 97.49536178107606
    - type: manhattan_accuracy_threshold
      value: 31097.674560546875
    - type: manhattan_ap
      value: 98.95694691792707
    - type: manhattan_f1
      value: 95.83975346687212
    - type: manhattan_f1_threshold
      value: 31097.674560546875
    - type: manhattan_precision
      value: 96.88473520249221
    - type: manhattan_recall
      value: 94.8170731707317
    - type: max_accuracy
      value: 98.14471243042672
    - type: max_ap
      value: 99.331999859971
    - type: max_f1
      value: 97.01492537313433
    - type: max_precision
      value: 97.50778816199377
    - type: max_recall
      value: 99.08536585365853
    - type: similarity_accuracy
      value: 97.86641929499072
    - type: similarity_accuracy_threshold
      value: 79.0391206741333
    - type: similarity_ap
      value: 99.19403807771533
    - type: similarity_f1
      value: 96.45608628659475
    - type: similarity_f1_threshold
      value: 79.0391206741333
    - type: similarity_precision
      value: 97.50778816199377
    - type: similarity_recall
      value: 95.42682926829268
  - task:
      type: PairClassification
    dataset:
      name: MTEB PawsXPairClassification (en)
      type: google-research-datasets/paws-x
      config: en
      split: test
      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
    metrics:
    - type: cosine_accuracy
      value: 61.8
    - type: cosine_accuracy_threshold
      value: 99.5664119720459
    - type: cosine_ap
      value: 60.679317786040585
    - type: cosine_f1
      value: 63.17354143441101
    - type: cosine_f1_threshold
      value: 97.22164869308472
    - type: cosine_precision
      value: 47.6457399103139
    - type: cosine_recall
      value: 93.71554575523705
    - type: dot_accuracy
      value: 55.7
    - type: dot_accuracy_threshold
      value: 48353.62548828125
    - type: dot_ap
      value: 48.53805970536875
    - type: dot_f1
      value: 62.42214532871972
    - type: dot_f1_threshold
      value: 38215.53955078125
    - type: dot_precision
      value: 45.48663640948058
    - type: dot_recall
      value: 99.44873208379272
    - type: euclidean_accuracy
      value: 61.75000000000001
    - type: euclidean_accuracy_threshold
      value: 189.0761137008667
    - type: euclidean_ap
      value: 60.55517418691518
    - type: euclidean_f1
      value: 63.07977736549165
    - type: euclidean_f1_threshold
      value: 504.3168067932129
    - type: euclidean_precision
      value: 47.53914988814318
    - type: euclidean_recall
      value: 93.71554575523705
    - type: main_score
      value: 60.679317786040585
    - type: manhattan_accuracy
      value: 61.9
    - type: manhattan_accuracy_threshold
      value: 4695.778274536133
    - type: manhattan_ap
      value: 60.48686620413608
    - type: manhattan_f1
      value: 62.92880855772778
    - type: manhattan_f1_threshold
      value: 12542.36831665039
    - type: manhattan_precision
      value: 47.28381374722838
    - type: manhattan_recall
      value: 94.04630650496141
    - type: max_accuracy
      value: 61.9
    - type: max_ap
      value: 60.679317786040585
    - type: max_f1
      value: 63.17354143441101
    - type: max_precision
      value: 47.6457399103139
    - type: max_recall
      value: 99.44873208379272
    - type: similarity_accuracy
      value: 61.8
    - type: similarity_accuracy_threshold
      value: 99.5664119720459
    - type: similarity_ap
      value: 60.679317786040585
    - type: similarity_f1
      value: 63.17354143441101
    - type: similarity_f1_threshold
      value: 97.22164869308472
    - type: similarity_precision
      value: 47.6457399103139
    - type: similarity_recall
      value: 93.71554575523705
  - task:
      type: PairClassification
    dataset:
      name: MTEB PawsXPairClassification (de)
      type: google-research-datasets/paws-x
      config: de
      split: test
      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
    metrics:
    - type: cosine_accuracy
      value: 60.25
    - type: cosine_accuracy_threshold
      value: 99.54338073730469
    - type: cosine_ap
      value: 56.7863613689054
    - type: cosine_f1
      value: 62.23499820337766
    - type: cosine_f1_threshold
      value: 89.95014429092407
    - type: cosine_precision
      value: 45.86864406779661
    - type: cosine_recall
      value: 96.75977653631284
    - type: dot_accuracy
      value: 56.8
    - type: dot_accuracy_threshold
      value: 47349.78332519531
    - type: dot_ap
      value: 49.7857806061729
    - type: dot_f1
      value: 62.31225986727209
    - type: dot_f1_threshold
      value: 30143.206787109375
    - type: dot_precision
      value: 45.32520325203252
    - type: dot_recall
      value: 99.66480446927373
    - type: euclidean_accuracy
      value: 60.3
    - type: euclidean_accuracy_threshold
      value: 219.78106498718262
    - type: euclidean_ap
      value: 56.731544327179606
    - type: euclidean_f1
      value: 62.19895287958115
    - type: euclidean_f1_threshold
      value: 1792.1623229980469
    - type: euclidean_precision
      value: 45.22842639593909
    - type: euclidean_recall
      value: 99.55307262569832
    - type: main_score
      value: 56.7863613689054
    - type: manhattan_accuracy
      value: 60.150000000000006
    - type: manhattan_accuracy_threshold
      value: 5104.503631591797
    - type: manhattan_ap
      value: 56.70304479768734
    - type: manhattan_f1
      value: 62.22067039106145
    - type: manhattan_f1_threshold
      value: 42839.471435546875
    - type: manhattan_precision
      value: 45.2513966480447
    - type: manhattan_recall
      value: 99.55307262569832
    - type: max_accuracy
      value: 60.3
    - type: max_ap
      value: 56.7863613689054
    - type: max_f1
      value: 62.31225986727209
    - type: max_precision
      value: 45.86864406779661
    - type: max_recall
      value: 99.66480446927373
    - type: similarity_accuracy
      value: 60.25
    - type: similarity_accuracy_threshold
      value: 99.54338073730469
    - type: similarity_ap
      value: 56.7863613689054
    - type: similarity_f1
      value: 62.23499820337766
    - type: similarity_f1_threshold
      value: 89.95014429092407
    - type: similarity_precision
      value: 45.86864406779661
    - type: similarity_recall
      value: 96.75977653631284
  - task:
      type: PairClassification
    dataset:
      name: MTEB PawsXPairClassification (es)
      type: google-research-datasets/paws-x
      config: es
      split: test
      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
    metrics:
    - type: cosine_accuracy
      value: 59.699999999999996
    - type: cosine_accuracy_threshold
      value: 99.55930709838867
    - type: cosine_ap
      value: 57.31662248806265
    - type: cosine_f1
      value: 62.444061962134256
    - type: cosine_f1_threshold
      value: 74.75898265838623
    - type: cosine_precision
      value: 45.3953953953954
    - type: cosine_recall
      value: 100.0
    - type: dot_accuracy
      value: 55.900000000000006
    - type: dot_accuracy_threshold
      value: 47512.90283203125
    - type: dot_ap
      value: 49.39339147787568
    - type: dot_f1
      value: 62.487082328625554
    - type: dot_f1_threshold
      value: 34989.03503417969
    - type: dot_precision
      value: 45.44088176352705
    - type: dot_recall
      value: 100.0
    - type: euclidean_accuracy
      value: 59.599999999999994
    - type: euclidean_accuracy_threshold
      value: 200.82547664642334
    - type: euclidean_ap
      value: 57.19737488445163
    - type: euclidean_f1
      value: 62.444061962134256
    - type: euclidean_f1_threshold
      value: 1538.8837814331055
    - type: euclidean_precision
      value: 45.3953953953954
    - type: euclidean_recall
      value: 100.0
    - type: main_score
      value: 57.31662248806265
    - type: manhattan_accuracy
      value: 59.550000000000004
    - type: manhattan_accuracy_threshold
      value: 5016.501617431641
    - type: manhattan_ap
      value: 57.089959907945065
    - type: manhattan_f1
      value: 62.444061962134256
    - type: manhattan_f1_threshold
      value: 37523.53515625
    - type: manhattan_precision
      value: 45.3953953953954
    - type: manhattan_recall
      value: 100.0
    - type: max_accuracy
      value: 59.699999999999996
    - type: max_ap
      value: 57.31662248806265
    - type: max_f1
      value: 62.487082328625554
    - type: max_precision
      value: 45.44088176352705
    - type: max_recall
      value: 100.0
    - type: similarity_accuracy
      value: 59.699999999999996
    - type: similarity_accuracy_threshold
      value: 99.55930709838867
    - type: similarity_ap
      value: 57.31662248806265
    - type: similarity_f1
      value: 62.444061962134256
    - type: similarity_f1_threshold
      value: 74.75898265838623
    - type: similarity_precision
      value: 45.3953953953954
    - type: similarity_recall
      value: 100.0
  - task:
      type: PairClassification
    dataset:
      name: MTEB PawsXPairClassification (fr)
      type: google-research-datasets/paws-x
      config: fr
      split: test
      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
    metrics:
    - type: cosine_accuracy
      value: 61.150000000000006
    - type: cosine_accuracy_threshold
      value: 99.36153888702393
    - type: cosine_ap
      value: 59.43845317938599
    - type: cosine_f1
      value: 62.51298026998961
    - type: cosine_f1_threshold
      value: 76.77866220474243
    - type: cosine_precision
      value: 45.468277945619334
    - type: cosine_recall
      value: 100.0
    - type: dot_accuracy
      value: 55.75
    - type: dot_accuracy_threshold
      value: 48931.55212402344
    - type: dot_ap
      value: 50.15949290538757
    - type: dot_f1
      value: 62.53462603878117
    - type: dot_f1_threshold
      value: 34415.7958984375
    - type: dot_precision
      value: 45.4911838790932
    - type: dot_recall
      value: 100.0
    - type: euclidean_accuracy
      value: 61.050000000000004
    - type: euclidean_accuracy_threshold
      value: 240.8097267150879
    - type: euclidean_ap
      value: 59.367971294226216
    - type: euclidean_f1
      value: 62.51298026998961
    - type: euclidean_f1_threshold
      value: 1444.132423400879
    - type: euclidean_precision
      value: 45.468277945619334
    - type: euclidean_recall
      value: 100.0
    - type: main_score
      value: 59.43845317938599
    - type: manhattan_accuracy
      value: 60.95
    - type: manhattan_accuracy_threshold
      value: 5701.206207275391
    - type: manhattan_ap
      value: 59.30094096378774
    - type: manhattan_f1
      value: 62.53462603878117
    - type: manhattan_f1_threshold
      value: 33445.672607421875
    - type: manhattan_precision
      value: 45.4911838790932
    - type: manhattan_recall
      value: 100.0
    - type: max_accuracy
      value: 61.150000000000006
    - type: max_ap
      value: 59.43845317938599
    - type: max_f1
      value: 62.53462603878117
    - type: max_precision
      value: 45.4911838790932
    - type: max_recall
      value: 100.0
    - type: similarity_accuracy
      value: 61.150000000000006
    - type: similarity_accuracy_threshold
      value: 99.36153888702393
    - type: similarity_ap
      value: 59.43845317938599
    - type: similarity_f1
      value: 62.51298026998961
    - type: similarity_f1_threshold
      value: 76.77866220474243
    - type: similarity_precision
      value: 45.468277945619334
    - type: similarity_recall
      value: 100.0
  - task:
      type: PairClassification
    dataset:
      name: MTEB PawsXPairClassification (zh)
      type: google-research-datasets/paws-x
      config: zh
      split: test
      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
    metrics:
    - type: cosine_accuracy
      value: 58.85
    - type: cosine_accuracy_threshold
      value: 99.73838329315186
    - type: cosine_ap
      value: 54.66913160570546
    - type: cosine_f1
      value: 62.32136632973162
    - type: cosine_f1_threshold
      value: 76.4499306678772
    - type: cosine_precision
      value: 45.265822784810126
    - type: cosine_recall
      value: 100.0
    - type: dot_accuracy
      value: 56.25
    - type: dot_accuracy_threshold
      value: 47351.9287109375
    - type: dot_ap
      value: 48.5266232989438
    - type: dot_f1
      value: 62.277951933124356
    - type: dot_f1_threshold
      value: 31325.28076171875
    - type: dot_precision
      value: 45.220030349013655
    - type: dot_recall
      value: 100.0
    - type: euclidean_accuracy
      value: 58.9
    - type: euclidean_accuracy_threshold
      value: 144.24468278884888
    - type: euclidean_ap
      value: 54.66981490353506
    - type: euclidean_f1
      value: 62.32136632973162
    - type: euclidean_f1_threshold
      value: 1484.908676147461
    - type: euclidean_precision
      value: 45.265822784810126
    - type: euclidean_recall
      value: 100.0
    - type: main_score
      value: 54.66981490353506
    - type: manhattan_accuracy
      value: 58.9
    - type: manhattan_accuracy_threshold
      value: 3586.785125732422
    - type: manhattan_ap
      value: 54.668355260247736
    - type: manhattan_f1
      value: 62.32136632973162
    - type: manhattan_f1_threshold
      value: 36031.22863769531
    - type: manhattan_precision
      value: 45.265822784810126
    - type: manhattan_recall
      value: 100.0
    - type: max_accuracy
      value: 58.9
    - type: max_ap
      value: 54.66981490353506
    - type: max_f1
      value: 62.32136632973162
    - type: max_precision
      value: 45.265822784810126
    - type: max_recall
      value: 100.0
    - type: similarity_accuracy
      value: 58.85
    - type: similarity_accuracy_threshold
      value: 99.73838329315186
    - type: similarity_ap
      value: 54.66913160570546
    - type: similarity_f1
      value: 62.32136632973162
    - type: similarity_f1_threshold
      value: 76.4499306678772
    - type: similarity_precision
      value: 45.265822784810126
    - type: similarity_recall
      value: 100.0
  - task:
      type: Classification
    dataset:
      name: MTEB PolEmo2.0-IN (default)
      type: PL-MTEB/polemo2_in
      config: default
      split: test
      revision: d90724373c70959f17d2331ad51fb60c71176b03
    metrics:
    - type: accuracy
      value: 83.75346260387812
    - type: f1
      value: 81.98304891214909
    - type: f1_weighted
      value: 84.29623200830078
    - type: main_score
      value: 83.75346260387812
  - task:
      type: Classification
    dataset:
      name: MTEB PolEmo2.0-OUT (default)
      type: PL-MTEB/polemo2_out
      config: default
      split: test
      revision: 6a21ab8716e255ab1867265f8b396105e8aa63d4
    metrics:
    - type: accuracy
      value: 66.53846153846153
    - type: f1
      value: 52.71826064368638
    - type: f1_weighted
      value: 69.10010124630334
    - type: main_score
      value: 66.53846153846153
  - task:
      type: PairClassification
    dataset:
      name: MTEB PPC
      type: PL-MTEB/ppc-pairclassification
      config: default
      split: test
      revision: None
    metrics:
    - type: cosine_accuracy
      value: 81.8
    - type: cosine_accuracy_threshold
      value: 90.47793745994568
    - type: cosine_ap
      value: 91.42490266080884
    - type: cosine_f1
      value: 85.4632587859425
    - type: cosine_f1_threshold
      value: 90.47793745994568
    - type: cosine_precision
      value: 82.56172839506173
    - type: cosine_recall
      value: 88.57615894039735
    - type: dot_accuracy
      value: 74.6
    - type: dot_accuracy_threshold
      value: 42102.23693847656
    - type: dot_ap
      value: 86.20060009096979
    - type: dot_f1
      value: 80.02842928216063
    - type: dot_f1_threshold
      value: 38970.16906738281
    - type: dot_precision
      value: 70.1120797011208
    - type: dot_recall
      value: 93.21192052980133
    - type: euclidean_accuracy
      value: 81.5
    - type: euclidean_accuracy_threshold
      value: 880.433464050293
    - type: euclidean_ap
      value: 91.33143477982087
    - type: euclidean_f1
      value: 85.44600938967135
    - type: euclidean_f1_threshold
      value: 964.0384674072266
    - type: euclidean_precision
      value: 81.00890207715133
    - type: euclidean_recall
      value: 90.39735099337747
    - type: main_score
      value: 91.42490266080884
    - type: manhattan_accuracy
      value: 81.3
    - type: manhattan_accuracy_threshold
      value: 22100.830078125
    - type: manhattan_ap
      value: 91.25996158651282
    - type: manhattan_f1
      value: 85.38102643856921
    - type: manhattan_f1_threshold
      value: 24043.515014648438
    - type: manhattan_precision
      value: 80.49853372434018
    - type: manhattan_recall
      value: 90.89403973509934
    - type: max_accuracy
      value: 81.8
    - type: max_ap
      value: 91.42490266080884
    - type: max_f1
      value: 85.4632587859425
    - type: max_precision
      value: 82.56172839506173
    - type: max_recall
      value: 93.21192052980133
    - type: similarity_accuracy
      value: 81.8
    - type: similarity_accuracy_threshold
      value: 90.47793745994568
    - type: similarity_ap
      value: 91.42490266080884
    - type: similarity_f1
      value: 85.4632587859425
    - type: similarity_f1_threshold
      value: 90.47793745994568
    - type: similarity_precision
      value: 82.56172839506173
    - type: similarity_recall
      value: 88.57615894039735
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval (default)
      type: mteb/quora
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 71.419
    - type: map_at_10
      value: 85.542
    - type: map_at_100
      value: 86.161
    - type: map_at_1000
      value: 86.175
    - type: map_at_20
      value: 85.949
    - type: map_at_3
      value: 82.623
    - type: map_at_5
      value: 84.5
    - type: mrr_at_1
      value: 82.27
    - type: mrr_at_10
      value: 88.21900000000001
    - type: mrr_at_100
      value: 88.313
    - type: mrr_at_1000
      value: 88.31400000000001
    - type: mrr_at_20
      value: 88.286
    - type: mrr_at_3
      value: 87.325
    - type: mrr_at_5
      value: 87.97500000000001
    - type: ndcg_at_1
      value: 82.3
    - type: ndcg_at_10
      value: 89.088
    - type: ndcg_at_100
      value: 90.217
    - type: ndcg_at_1000
      value: 90.29700000000001
    - type: ndcg_at_20
      value: 89.697
    - type: ndcg_at_3
      value: 86.435
    - type: ndcg_at_5
      value: 87.966
    - type: precision_at_1
      value: 82.3
    - type: precision_at_10
      value: 13.527000000000001
    - type: precision_at_100
      value: 1.537
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_20
      value: 7.165000000000001
    - type: precision_at_3
      value: 37.92
    - type: precision_at_5
      value: 24.914
    - type: recall_at_1
      value: 71.419
    - type: recall_at_10
      value: 95.831
    - type: recall_at_100
      value: 99.64
    - type: recall_at_1000
      value: 99.988
    - type: recall_at_20
      value: 97.76599999999999
    - type: recall_at_3
      value: 88.081
    - type: recall_at_5
      value: 92.50500000000001
    - type: main_score
      value: 89.088
  - task:
      type: STS
    dataset:
      name: MTEB RUParaPhraserSTS (default)
      type: merionum/ru_paraphraser
      config: default
      split: test
      revision: 43265056790b8f7c59e0139acb4be0a8dad2c8f4
    metrics:
    - type: cosine_pearson
      value: 67.91177744712421
    - type: cosine_spearman
      value: 76.77113726753656
    - type: euclidean_pearson
      value: 73.81454206068638
    - type: euclidean_spearman
      value: 76.92529493599028
    - type: main_score
      value: 76.77113726753656
    - type: manhattan_pearson
      value: 73.81690454439168
    - type: manhattan_spearman
      value: 76.87333776705002
    - type: pearson
      value: 67.91177744712421
    - type: spearman
      value: 76.77113726753656
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering (default)
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: main_score
      value: 55.39924225216962
    - type: v_measure
      value: 55.39924225216962
    - type: v_measure_std
      value: 4.723802279292467
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P (default)
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: main_score
      value: 62.87465161304012
    - type: v_measure
      value: 62.87465161304012
    - type: v_measure_std
      value: 12.082670914488473
  - task:
      type: Retrieval
    dataset:
      name: MTEB RiaNewsRetrieval (default)
      type: ai-forever/ria-news-retrieval
      config: default
      split: test
      revision: 82374b0bbacda6114f39ff9c5b925fa1512ca5d7
    metrics:
    - type: main_score
      value: 79.209
    - type: map_at_1
      value: 67.33
    - type: map_at_10
      value: 75.633
    - type: map_at_100
      value: 75.897
    - type: map_at_1000
      value: 75.907
    - type: map_at_20
      value: 75.804
    - type: map_at_3
      value: 74.2
    - type: map_at_5
      value: 75.13300000000001
    - type: mrr_at_1
      value: 67.31
    - type: mrr_at_10
      value: 75.62709126984095
    - type: mrr_at_100
      value: 75.89105697041113
    - type: mrr_at_1000
      value: 75.90115653883124
    - type: mrr_at_20
      value: 75.79802332308172
    - type: mrr_at_3
      value: 74.19499999999961
    - type: mrr_at_5
      value: 75.12849999999939
    - type: nauc_map_at_1000_diff1
      value: 74.30304869630591
    - type: nauc_map_at_1000_max
      value: 36.477146725784046
    - type: nauc_map_at_1000_std
      value: -20.862772498461723
    - type: nauc_map_at_100_diff1
      value: 74.29833058090355
    - type: nauc_map_at_100_max
      value: 36.483678619667884
    - type: nauc_map_at_100_std
      value: -20.856274849980135
    - type: nauc_map_at_10_diff1
      value: 74.20729220697967
    - type: nauc_map_at_10_max
      value: 36.56543146170092
    - type: nauc_map_at_10_std
      value: -20.991081015484728
    - type: nauc_map_at_1_diff1
      value: 77.38899022125185
    - type: nauc_map_at_1_max
      value: 32.45918619669731
    - type: nauc_map_at_1_std
      value: -22.149586336167324
    - type: nauc_map_at_20_diff1
      value: 74.2447573558587
    - type: nauc_map_at_20_max
      value: 36.50383130240387
    - type: nauc_map_at_20_std
      value: -20.87013743041831
    - type: nauc_map_at_3_diff1
      value: 74.3054577294586
    - type: nauc_map_at_3_max
      value: 36.484530586652724
    - type: nauc_map_at_3_std
      value: -21.90543024607988
    - type: nauc_map_at_5_diff1
      value: 74.21062368961503
    - type: nauc_map_at_5_max
      value: 36.55670532498779
    - type: nauc_map_at_5_std
      value: -21.488786900676942
    - type: nauc_mrr_at_1000_diff1
      value: 74.31619177956684
    - type: nauc_mrr_at_1000_max
      value: 36.53498918453189
    - type: nauc_mrr_at_1000_std
      value: -20.75986704931237
    - type: nauc_mrr_at_100_diff1
      value: 74.31146790382356
    - type: nauc_mrr_at_100_max
      value: 36.54149252857106
    - type: nauc_mrr_at_100_std
      value: -20.75341959250079
    - type: nauc_mrr_at_10_diff1
      value: 74.22027806145095
    - type: nauc_mrr_at_10_max
      value: 36.622542969971725
    - type: nauc_mrr_at_10_std
      value: -20.889417384064117
    - type: nauc_mrr_at_1_diff1
      value: 77.4306709551449
    - type: nauc_mrr_at_1_max
      value: 32.57259463438259
    - type: nauc_mrr_at_1_std
      value: -21.964402859613937
    - type: nauc_mrr_at_20_diff1
      value: 74.25784396230718
    - type: nauc_mrr_at_20_max
      value: 36.561412224507336
    - type: nauc_mrr_at_20_std
      value: -20.767665000065723
    - type: nauc_mrr_at_3_diff1
      value: 74.31423253547214
    - type: nauc_mrr_at_3_max
      value: 36.537745749488906
    - type: nauc_mrr_at_3_std
      value: -21.81259529019546
    - type: nauc_mrr_at_5_diff1
      value: 74.22404613312771
    - type: nauc_mrr_at_5_max
      value: 36.60743768455219
    - type: nauc_mrr_at_5_std
      value: -21.39479216331971
    - type: nauc_ndcg_at_1000_diff1
      value: 73.48182819705742
    - type: nauc_ndcg_at_1000_max
      value: 37.86991608461793
    - type: nauc_ndcg_at_1000_std
      value: -19.021499322688904
    - type: nauc_ndcg_at_100_diff1
      value: 73.34941250585759
    - type: nauc_ndcg_at_100_max
      value: 38.11150275625829
    - type: nauc_ndcg_at_100_std
      value: -18.70624087206104
    - type: nauc_ndcg_at_10_diff1
      value: 72.82520265115987
    - type: nauc_ndcg_at_10_max
      value: 38.43323357650525
    - type: nauc_ndcg_at_10_std
      value: -19.410953792830878
    - type: nauc_ndcg_at_1_diff1
      value: 77.38899022125185
    - type: nauc_ndcg_at_1_max
      value: 32.45918619669731
    - type: nauc_ndcg_at_1_std
      value: -22.149586336167324
    - type: nauc_ndcg_at_20_diff1
      value: 72.93309285256507
    - type: nauc_ndcg_at_20_max
      value: 38.217372819067755
    - type: nauc_ndcg_at_20_std
      value: -18.864113576359333
    - type: nauc_ndcg_at_3_diff1
      value: 73.18253776744112
    - type: nauc_ndcg_at_3_max
      value: 38.008109328364
    - type: nauc_ndcg_at_3_std
      value: -21.68785687594153
    - type: nauc_ndcg_at_5_diff1
      value: 72.90474739784793
    - type: nauc_ndcg_at_5_max
      value: 38.29483039202184
    - type: nauc_ndcg_at_5_std
      value: -20.833049811453474
    - type: nauc_precision_at_1000_diff1
      value: 59.306217613750334
    - type: nauc_precision_at_1000_max
      value: 72.20747948302262
    - type: nauc_precision_at_1000_std
      value: 45.58837180096227
    - type: nauc_precision_at_100_diff1
      value: 62.87286844562389
    - type: nauc_precision_at_100_max
      value: 61.33108214045868
    - type: nauc_precision_at_100_std
      value: 20.67481963545654
    - type: nauc_precision_at_10_diff1
      value: 64.11222984256685
    - type: nauc_precision_at_10_max
      value: 50.323697746037496
    - type: nauc_precision_at_10_std
      value: -7.9994544634332625
    - type: nauc_precision_at_1_diff1
      value: 77.38899022125185
    - type: nauc_precision_at_1_max
      value: 32.45918619669731
    - type: nauc_precision_at_1_std
      value: -22.149586336167324
    - type: nauc_precision_at_20_diff1
      value: 62.30228127286973
    - type: nauc_precision_at_20_max
      value: 52.02090746208407
    - type: nauc_precision_at_20_std
      value: 0.7629898806370331
    - type: nauc_precision_at_3_diff1
      value: 68.82856645994157
    - type: nauc_precision_at_3_max
      value: 43.94171571306625
    - type: nauc_precision_at_3_std
      value: -20.78595255410148
    - type: nauc_precision_at_5_diff1
      value: 66.62157622497887
    - type: nauc_precision_at_5_max
      value: 46.69398173603811
    - type: nauc_precision_at_5_std
      value: -17.412423571163057
    - type: nauc_recall_at_1000_diff1
      value: 59.30621761375148
    - type: nauc_recall_at_1000_max
      value: 72.20747948302191
    - type: nauc_recall_at_1000_std
      value: 45.588371800962655
    - type: nauc_recall_at_100_diff1
      value: 62.872868445623894
    - type: nauc_recall_at_100_max
      value: 61.33108214045813
    - type: nauc_recall_at_100_std
      value: 20.67481963545666
    - type: nauc_recall_at_10_diff1
      value: 64.11222984256698
    - type: nauc_recall_at_10_max
      value: 50.32369774603755
    - type: nauc_recall_at_10_std
      value: -7.999454463433321
    - type: nauc_recall_at_1_diff1
      value: 77.38899022125185
    - type: nauc_recall_at_1_max
      value: 32.45918619669731
    - type: nauc_recall_at_1_std
      value: -22.149586336167324
    - type: nauc_recall_at_20_diff1
      value: 62.3022812728695
    - type: nauc_recall_at_20_max
      value: 52.02090746208397
    - type: nauc_recall_at_20_std
      value: 0.7629898806369458
    - type: nauc_recall_at_3_diff1
      value: 68.82856645994157
    - type: nauc_recall_at_3_max
      value: 43.94171571306612
    - type: nauc_recall_at_3_std
      value: -20.78595255410157
    - type: nauc_recall_at_5_diff1
      value: 66.62157622497897
    - type: nauc_recall_at_5_max
      value: 46.693981736038246
    - type: nauc_recall_at_5_std
      value: -17.412423571162954
    - type: ndcg_at_1
      value: 67.33
    - type: ndcg_at_10
      value: 79.209
    - type: ndcg_at_100
      value: 80.463
    - type: ndcg_at_1000
      value: 80.74799999999999
    - type: ndcg_at_20
      value: 79.81899999999999
    - type: ndcg_at_3
      value: 76.335
    - type: ndcg_at_5
      value: 78.011
    - type: precision_at_1
      value: 67.33
    - type: precision_at_10
      value: 9.020999999999999
    - type: precision_at_100
      value: 0.96
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_20
      value: 4.63
    - type: precision_at_3
      value: 27.493000000000002
    - type: precision_at_5
      value: 17.308
    - type: recall_at_1
      value: 67.33
    - type: recall_at_10
      value: 90.21000000000001
    - type: recall_at_100
      value: 96.00999999999999
    - type: recall_at_1000
      value: 98.29
    - type: recall_at_20
      value: 92.60000000000001
    - type: recall_at_3
      value: 82.48
    - type: recall_at_5
      value: 86.53999999999999
  - task:
      type: Reranking
    dataset:
      name: MTEB RuBQReranking (default)
      type: ai-forever/rubq-reranking
      config: default
      split: test
      revision: 2e96b8f098fa4b0950fc58eacadeb31c0d0c7fa2
    metrics:
    - type: main_score
      value: 65.57453932493252
    - type: map
      value: 65.57453932493252
    - type: mrr
      value: 70.51408205663526
    - type: nAUC_map_diff1
      value: 26.69583260609023
    - type: nAUC_map_max
      value: 12.928262749610663
    - type: nAUC_map_std
      value: 11.702468857903128
    - type: nAUC_mrr_diff1
      value: 28.5206955462174
    - type: nAUC_mrr_max
      value: 14.207162454694227
    - type: nAUC_mrr_std
      value: 10.725721001555296
  - task:
      type: Retrieval
    dataset:
      name: MTEB RuBQRetrieval (default)
      type: ai-forever/rubq-retrieval
      config: default
      split: test
      revision: e19b6ffa60b3bc248e0b41f4cc37c26a55c2a67b
    metrics:
    - type: main_score
      value: 72.306
    - type: map_at_1
      value: 44.187
    - type: map_at_10
      value: 64.836
    - type: map_at_100
      value: 65.771
    - type: map_at_1000
      value: 65.8
    - type: map_at_20
      value: 65.497
    - type: map_at_3
      value: 59.692
    - type: map_at_5
      value: 63.105
    - type: mrr_at_1
      value: 62.23404255319149
    - type: mrr_at_10
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    - type: ndcg_at_100
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    - type: ndcg_at_1000
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    - type: ndcg_at_20
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    - type: ndcg_at_3
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    - type: precision_at_1
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    - type: precision_at_10
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    - type: precision_at_100
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    - type: precision_at_1000
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    - type: precision_at_20
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    - type: precision_at_3
      value: 35.619
    - type: precision_at_5
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    - type: recall_at_1
      value: 44.187
    - type: recall_at_10
      value: 85.10600000000001
    - type: recall_at_100
      value: 95.488
    - type: recall_at_1000
      value: 98.831
    - type: recall_at_20
      value: 90.22200000000001
    - type: recall_at_3
      value: 68.789
    - type: recall_at_5
      value: 77.85499999999999
  - task:
      type: Classification
    dataset:
      name: MTEB RuReviewsClassification (default)
      type: ai-forever/ru-reviews-classification
      config: default
      split: test
      revision: f6d2c31f4dc6b88f468552750bfec05b4b41b05a
    metrics:
    - type: accuracy
      value: 67.5830078125
    - type: f1
      value: 67.56931936632446
    - type: f1_weighted
      value: 67.57137733752779
    - type: main_score
      value: 67.5830078125
  - task:
      type: STS
    dataset:
      name: MTEB RuSTSBenchmarkSTS (default)
      type: ai-forever/ru-stsbenchmark-sts
      config: default
      split: test
      revision: 7cf24f325c6da6195df55bef3d86b5e0616f3018
    metrics:
    - type: cosine_pearson
      value: 85.90493484626788
    - type: cosine_spearman
      value: 86.21965691667411
    - type: euclidean_pearson
      value: 86.07499842984909
    - type: euclidean_spearman
      value: 86.55506818735688
    - type: main_score
      value: 86.21965691667411
    - type: manhattan_pearson
      value: 85.95976420231729
    - type: manhattan_spearman
      value: 86.48604243661234
    - type: pearson
      value: 85.90493484626788
    - type: spearman
      value: 86.21965691667411
  - task:
      type: Classification
    dataset:
      name: MTEB RuSciBenchGRNTIClassification (default)
      type: ai-forever/ru-scibench-grnti-classification
      config: default
      split: test
      revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1
    metrics:
    - type: accuracy
      value: 59.1943359375
    - type: f1
      value: 58.894480861440414
    - type: f1_weighted
      value: 58.903615560240866
    - type: main_score
      value: 59.1943359375
  - task:
      type: Clustering
    dataset:
      name: MTEB RuSciBenchGRNTIClusteringP2P (default)
      type: ai-forever/ru-scibench-grnti-classification
      config: default
      split: test
      revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1
    metrics:
    - type: main_score
      value: 57.99209448663228
    - type: v_measure
      value: 57.99209448663228
    - type: v_measure_std
      value: 1.0381163861993816
  - task:
      type: Classification
    dataset:
      name: MTEB RuSciBenchOECDClassification (default)
      type: ai-forever/ru-scibench-oecd-classification
      config: default
      split: test
      revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471
    metrics:
    - type: accuracy
      value: 45.556640625
    - type: f1
      value: 45.159163104085906
    - type: f1_weighted
      value: 45.16098316398626
    - type: main_score
      value: 45.556640625
  - task:
      type: Clustering
    dataset:
      name: MTEB RuSciBenchOECDClusteringP2P (default)
      type: ai-forever/ru-scibench-oecd-classification
      config: default
      split: test
      revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471
    metrics:
    - type: main_score
      value: 50.787548070488974
    - type: v_measure
      value: 50.787548070488974
    - type: v_measure_std
      value: 0.8569958168946827
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS (default)
      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
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      value: 4.843
    - type: map_at_10
      value: 11.752
    - type: map_at_100
      value: 13.919
    - type: map_at_1000
      value: 14.198
    - type: map_at_20
      value: 12.898000000000001
    - type: map_at_3
      value: 8.603
    - type: map_at_5
      value: 10.069
    - type: mrr_at_1
      value: 23.799999999999997
    - type: mrr_at_10
      value: 34.449999999999996
    - type: mrr_at_100
      value: 35.64
    - type: mrr_at_1000
      value: 35.691
    - type: mrr_at_20
      value: 35.213
    - type: mrr_at_3
      value: 31.383
    - type: mrr_at_5
      value: 33.062999999999995
    - type: ndcg_at_1
      value: 23.799999999999997
    - type: ndcg_at_10
      value: 19.811
    - type: ndcg_at_100
      value: 28.108
    - type: ndcg_at_1000
      value: 33.1
    - type: ndcg_at_20
      value: 22.980999999999998
    - type: ndcg_at_3
      value: 19.153000000000002
    - type: ndcg_at_5
      value: 16.408
    - type: precision_at_1
      value: 23.799999999999997
    - type: precision_at_10
      value: 10.16
    - type: precision_at_100
      value: 2.1999999999999997
    - type: precision_at_1000
      value: 0.34099999999999997
    - type: precision_at_20
      value: 6.915
    - type: precision_at_3
      value: 17.8
    - type: precision_at_5
      value: 14.14
    - type: recall_at_1
      value: 4.843
    - type: recall_at_10
      value: 20.595
    - type: recall_at_100
      value: 44.66
    - type: recall_at_1000
      value: 69.152
    - type: recall_at_20
      value: 28.04
    - type: recall_at_3
      value: 10.833
    - type: recall_at_5
      value: 14.346999999999998
    - type: main_score
      value: 19.811
  - task:
      type: PairClassification
    dataset:
      name: MTEB SICK-E-PL (default)
      type: PL-MTEB/sicke-pl-pairclassification
      config: default
      split: test
      revision: 71bba34b0ece6c56dfcf46d9758a27f7a90f17e9
    metrics:
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      value: 80.90093762739502
    - type: cosine_accuracy_threshold
      value: 94.40930485725403
    - type: cosine_ap
      value: 71.15400909912427
    - type: cosine_f1
      value: 66.8213457076566
    - type: cosine_f1_threshold
      value: 91.53673648834229
    - type: cosine_precision
      value: 62.4922504649721
    - type: cosine_recall
      value: 71.7948717948718
    - type: dot_accuracy
      value: 78.41418671015083
    - type: dot_accuracy_threshold
      value: 42924.45068359375
    - type: dot_ap
      value: 63.34003025365763
    - type: dot_f1
      value: 62.518258837277244
    - type: dot_f1_threshold
      value: 40900.738525390625
    - type: dot_precision
      value: 52.99653293709758
    - type: dot_recall
      value: 76.21082621082621
    - type: euclidean_accuracy
      value: 80.67672238075826
    - type: euclidean_accuracy_threshold
      value: 696.0524559020996
    - type: euclidean_ap
      value: 70.88762835990224
    - type: euclidean_f1
      value: 66.711051930759
    - type: euclidean_f1_threshold
      value: 878.5581588745117
    - type: euclidean_precision
      value: 62.625
    - type: euclidean_recall
      value: 71.36752136752136
    - type: main_score
      value: 71.15400909912427
    - type: manhattan_accuracy
      value: 80.65633917651854
    - type: manhattan_accuracy_threshold
      value: 17277.72674560547
    - type: manhattan_ap
      value: 70.67105336611716
    - type: manhattan_f1
      value: 66.51346027577151
    - type: manhattan_f1_threshold
      value: 21687.957763671875
    - type: manhattan_precision
      value: 61.69305724725944
    - type: manhattan_recall
      value: 72.15099715099716
    - type: max_accuracy
      value: 80.90093762739502
    - type: max_ap
      value: 71.15400909912427
    - type: max_f1
      value: 66.8213457076566
    - type: max_precision
      value: 62.625
    - type: max_recall
      value: 76.21082621082621
    - type: similarity_accuracy
      value: 80.90093762739502
    - type: similarity_accuracy_threshold
      value: 94.40930485725403
    - type: similarity_ap
      value: 71.15400909912427
    - type: similarity_f1
      value: 66.8213457076566
    - type: similarity_f1_threshold
      value: 91.53673648834229
    - type: similarity_precision
      value: 62.4922504649721
    - type: similarity_recall
      value: 71.7948717948718
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R (default)
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cosine_pearson
      value: 92.3339946866199
    - type: cosine_spearman
      value: 89.61697355115497
    - type: euclidean_pearson
      value: 90.3264916449669
    - type: euclidean_spearman
      value: 89.36270451308866
    - type: main_score
      value: 89.61697355115497
    - type: manhattan_pearson
      value: 90.18909339052534
    - type: manhattan_spearman
      value: 89.28337093097377
    - type: pearson
      value: 92.3339946866199
    - type: spearman
      value: 89.61697355115497
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R-PL (default)
      type: PL-MTEB/sickr-pl-sts
      config: default
      split: test
      revision: fd5c2441b7eeff8676768036142af4cfa42c1339
    metrics:
    - type: cosine_pearson
      value: 85.27883048457821
    - type: cosine_spearman
      value: 80.53204892678619
    - type: euclidean_pearson
      value: 82.78520705216168
    - type: euclidean_spearman
      value: 80.27848359873212
    - type: main_score
      value: 80.53204892678619
    - type: manhattan_pearson
      value: 82.63270640583454
    - type: manhattan_spearman
      value: 80.21507977473146
    - type: pearson
      value: 85.27883048457821
    - type: spearman
      value: 80.53204892678619
  - task:
      type: STS
    dataset:
      name: MTEB SICKFr (default)
      type: Lajavaness/SICK-fr
      config: default
      split: test
      revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
    metrics:
    - type: cosine_pearson
      value: 88.77029361817212
    - type: cosine_spearman
      value: 83.9453600346894
    - type: euclidean_pearson
      value: 85.85331086208573
    - type: euclidean_spearman
      value: 83.70852031985308
    - type: main_score
      value: 83.9453600346894
    - type: manhattan_pearson
      value: 85.66222265885914
    - type: manhattan_spearman
      value: 83.60833111525962
    - type: pearson
      value: 88.77029361817212
    - type: spearman
      value: 83.9453600346894
  - task:
      type: STS
    dataset:
      name: MTEB STS12 (default)
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cosine_pearson
      value: 88.76435859522375
    - type: cosine_spearman
      value: 82.43768167804375
    - type: euclidean_pearson
      value: 87.43566183874832
    - type: euclidean_spearman
      value: 82.82166873757507
    - type: main_score
      value: 82.43768167804375
    - type: manhattan_pearson
      value: 87.39450871380951
    - type: manhattan_spearman
      value: 82.89253043430163
    - type: pearson
      value: 88.76435859522375
    - type: spearman
      value: 82.43768167804375
  - task:
      type: STS
    dataset:
      name: MTEB STS13 (default)
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cosine_pearson
      value: 88.86627241652141
    - type: cosine_spearman
      value: 89.49011599120688
    - type: euclidean_pearson
      value: 89.3314120073772
    - type: euclidean_spearman
      value: 89.8226502776963
    - type: main_score
      value: 89.49011599120688
    - type: manhattan_pearson
      value: 89.2252179076963
    - type: manhattan_spearman
      value: 89.74573844021225
    - type: pearson
      value: 88.86627241652141
    - type: spearman
      value: 89.49011599120688
  - task:
      type: STS
    dataset:
      name: MTEB STS14 (default)
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cosine_pearson
      value: 87.22891405215968
    - type: cosine_spearman
      value: 84.9467188157614
    - type: euclidean_pearson
      value: 87.20330004726237
    - type: euclidean_spearman
      value: 85.34806059461808
    - type: main_score
      value: 84.9467188157614
    - type: manhattan_pearson
      value: 87.15224666107623
    - type: manhattan_spearman
      value: 85.34596898699708
    - type: pearson
      value: 87.22891405215968
    - type: spearman
      value: 84.9467188157614
  - task:
      type: STS
    dataset:
      name: MTEB STS15 (default)
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cosine_pearson
      value: 88.14066430111033
    - type: cosine_spearman
      value: 89.31337445552545
    - type: euclidean_pearson
      value: 89.08039335366983
    - type: euclidean_spearman
      value: 89.6658762856415
    - type: main_score
      value: 89.31337445552545
    - type: manhattan_pearson
      value: 89.08057438154486
    - type: manhattan_spearman
      value: 89.68673984203022
    - type: pearson
      value: 88.14066430111033
    - type: spearman
      value: 89.31337445552545
  - task:
      type: STS
    dataset:
      name: MTEB STS16 (default)
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cosine_pearson
      value: 85.14908856657084
    - type: cosine_spearman
      value: 86.84648320786727
    - type: euclidean_pearson
      value: 86.11454713131947
    - type: euclidean_spearman
      value: 86.77738862047961
    - type: main_score
      value: 86.84648320786727
    - type: manhattan_pearson
      value: 86.07804821916372
    - type: manhattan_spearman
      value: 86.78676064310474
    - type: pearson
      value: 85.14908856657084
    - type: spearman
      value: 86.84648320786727
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 89.61633502468356
    - type: cosine_spearman
      value: 89.99772663224805
    - type: euclidean_pearson
      value: 90.14056501501044
    - type: euclidean_spearman
      value: 90.04496896837503
    - type: main_score
      value: 89.99772663224805
    - type: manhattan_pearson
      value: 90.08964860311801
    - type: manhattan_spearman
      value: 90.00091712362196
    - type: pearson
      value: 89.61633502468356
    - type: spearman
      value: 89.99772663224805
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-en)
      type: mteb/sts17-crosslingual-sts
      config: es-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 86.44548026840202
    - type: cosine_spearman
      value: 87.26263108768539
    - type: euclidean_pearson
      value: 86.42844593583838
    - type: euclidean_spearman
      value: 86.89388428664364
    - type: main_score
      value: 87.26263108768539
    - type: manhattan_pearson
      value: 86.47186940800881
    - type: manhattan_spearman
      value: 87.02163091089946
    - type: pearson
      value: 86.44548026840202
    - type: spearman
      value: 87.26263108768539
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-de)
      type: mteb/sts17-crosslingual-sts
      config: en-de
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 87.89345132532758
    - type: cosine_spearman
      value: 87.96246221327699
    - type: euclidean_pearson
      value: 88.49013032701419
    - type: euclidean_spearman
      value: 87.81981265317344
    - type: main_score
      value: 87.96246221327699
    - type: manhattan_pearson
      value: 88.31360914178538
    - type: manhattan_spearman
      value: 87.62734530005075
    - type: pearson
      value: 87.89345132532758
    - type: spearman
      value: 87.96246221327699
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-es)
      type: mteb/sts17-crosslingual-sts
      config: es-es
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 88.4084678497171
    - type: cosine_spearman
      value: 88.77640638748285
    - type: euclidean_pearson
      value: 89.60124312475843
    - type: euclidean_spearman
      value: 88.4321442688528
    - type: main_score
      value: 88.77640638748285
    - type: manhattan_pearson
      value: 89.62375118021299
    - type: manhattan_spearman
      value: 88.46998118661577
    - type: pearson
      value: 88.4084678497171
    - type: spearman
      value: 88.77640638748285
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (fr-en)
      type: mteb/sts17-crosslingual-sts
      config: fr-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 87.30688801326498
    - type: cosine_spearman
      value: 87.55684697258378
    - type: euclidean_pearson
      value: 87.89672951056794
    - type: euclidean_spearman
      value: 87.28050429201674
    - type: main_score
      value: 87.55684697258378
    - type: manhattan_pearson
      value: 87.74292745320572
    - type: manhattan_spearman
      value: 87.16383993876582
    - type: pearson
      value: 87.30688801326498
    - type: spearman
      value: 87.55684697258378
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh-en)
      type: mteb/sts22-crosslingual-sts
      config: zh-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 73.46180375170147
    - type: cosine_spearman
      value: 73.39559590127081
    - type: euclidean_pearson
      value: 73.72613901293681
    - type: euclidean_spearman
      value: 71.85465165176795
    - type: main_score
      value: 73.39559590127081
    - type: manhattan_pearson
      value: 73.07859140869076
    - type: manhattan_spearman
      value: 71.22047343718893
    - type: pearson
      value: 73.46180375170147
    - type: spearman
      value: 73.39559590127081
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh)
      type: mteb/sts22-crosslingual-sts
      config: zh
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 62.47531620842637
    - type: cosine_spearman
      value: 66.22504667157702
    - type: euclidean_pearson
      value: 66.76201254783692
    - type: euclidean_spearman
      value: 66.86115760269463
    - type: main_score
      value: 66.22504667157702
    - type: manhattan_pearson
      value: 66.73847836793489
    - type: manhattan_spearman
      value: 66.7677116377695
    - type: pearson
      value: 62.47531620842637
    - type: spearman
      value: 66.22504667157702
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es)
      type: mteb/sts22-crosslingual-sts
      config: es
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 69.89707002436481
    - type: cosine_spearman
      value: 72.2054865735116
    - type: euclidean_pearson
      value: 71.81856615570756
    - type: euclidean_spearman
      value: 72.72593304629407
    - type: main_score
      value: 72.2054865735116
    - type: manhattan_pearson
      value: 72.00362684700072
    - type: manhattan_spearman
      value: 72.62783534769964
    - type: pearson
      value: 69.89707002436481
    - type: spearman
      value: 72.2054865735116
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr)
      type: mteb/sts22-crosslingual-sts
      config: fr
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 81.59623734395916
    - type: cosine_spearman
      value: 83.28946105111358
    - type: euclidean_pearson
      value: 79.377330171466
    - type: euclidean_spearman
      value: 81.81029781662205
    - type: main_score
      value: 83.28946105111358
    - type: manhattan_pearson
      value: 78.96970881689698
    - type: manhattan_spearman
      value: 81.91773236079703
    - type: pearson
      value: 81.59623734395916
    - type: spearman
      value: 83.28946105111358
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-fr)
      type: mteb/sts22-crosslingual-sts
      config: de-fr
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 55.03825643126142
    - type: cosine_spearman
      value: 58.25792501780429
    - type: euclidean_pearson
      value: 50.38007603973409
    - type: euclidean_spearman
      value: 59.39961789383097
    - type: main_score
      value: 58.25792501780429
    - type: manhattan_pearson
      value: 50.518568927999155
    - type: manhattan_spearman
      value: 59.84185466003894
    - type: pearson
      value: 55.03825643126142
    - type: spearman
      value: 58.25792501780429
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl-en)
      type: mteb/sts22-crosslingual-sts
      config: pl-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 77.77233721490776
    - type: cosine_spearman
      value: 76.17596588017625
    - type: euclidean_pearson
      value: 74.47600468156611
    - type: euclidean_spearman
      value: 72.61278728057012
    - type: main_score
      value: 76.17596588017625
    - type: manhattan_pearson
      value: 74.48118910099699
    - type: manhattan_spearman
      value: 73.33167419101696
    - type: pearson
      value: 77.77233721490776
    - type: spearman
      value: 76.17596588017625
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl)
      type: mteb/sts22-crosslingual-sts
      config: pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 42.87453608131507
    - type: cosine_spearman
      value: 45.137849894401185
    - type: euclidean_pearson
      value: 31.66964197694796
    - type: euclidean_spearman
      value: 44.1014900837869
    - type: main_score
      value: 45.137849894401185
    - type: manhattan_pearson
      value: 31.007199259384745
    - type: manhattan_spearman
      value: 43.48181523288926
    - type: pearson
      value: 42.87453608131507
    - type: spearman
      value: 45.137849894401185
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 66.87400150638176
    - type: cosine_spearman
      value: 67.27861354834066
    - type: euclidean_pearson
      value: 66.81789582140216
    - type: euclidean_spearman
      value: 66.44220479858708
    - type: main_score
      value: 67.27861354834066
    - type: manhattan_pearson
      value: 66.92509859033235
    - type: manhattan_spearman
      value: 66.46841124185076
    - type: pearson
      value: 66.87400150638176
    - type: spearman
      value: 67.27861354834066
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ru)
      type: mteb/sts22-crosslingual-sts
      config: ru
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 61.819804551576084
    - type: cosine_spearman
      value: 65.0864146772135
    - type: euclidean_pearson
      value: 62.518151090361876
    - type: euclidean_spearman
      value: 65.13608138548017
    - type: main_score
      value: 65.0864146772135
    - type: manhattan_pearson
      value: 62.51413246915267
    - type: manhattan_spearman
      value: 65.19077543064323
    - type: pearson
      value: 61.819804551576084
    - type: spearman
      value: 65.0864146772135
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de)
      type: mteb/sts22-crosslingual-sts
      config: de
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 54.85728696035389
    - type: cosine_spearman
      value: 61.60906359227576
    - type: euclidean_pearson
      value: 52.57582587901851
    - type: euclidean_spearman
      value: 61.41823097598308
    - type: main_score
      value: 61.60906359227576
    - type: manhattan_pearson
      value: 52.500978361080506
    - type: manhattan_spearman
      value: 61.30365596659758
    - type: pearson
      value: 54.85728696035389
    - type: spearman
      value: 61.60906359227576
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr-pl)
      type: mteb/sts22-crosslingual-sts
      config: fr-pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 67.68016005631422
    - type: cosine_spearman
      value: 84.51542547285167
    - type: euclidean_pearson
      value: 66.19871164667245
    - type: euclidean_spearman
      value: 73.24670207647144
    - type: main_score
      value: 84.51542547285167
    - type: manhattan_pearson
      value: 67.0443525268974
    - type: manhattan_spearman
      value: 73.24670207647144
    - type: pearson
      value: 67.68016005631422
    - type: spearman
      value: 84.51542547285167
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-pl)
      type: mteb/sts22-crosslingual-sts
      config: de-pl
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 47.49467414030747
    - type: cosine_spearman
      value: 56.81512095681289
    - type: euclidean_pearson
      value: 48.42860221765214
    - type: euclidean_spearman
      value: 58.63197306329092
    - type: main_score
      value: 56.81512095681289
    - type: manhattan_pearson
      value: 48.39594959260441
    - type: manhattan_spearman
      value: 58.63197306329092
    - type: pearson
      value: 47.49467414030747
    - type: spearman
      value: 56.81512095681289
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-en)
      type: mteb/sts22-crosslingual-sts
      config: es-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 76.8364678896155
    - type: cosine_spearman
      value: 78.45516413087114
    - type: euclidean_pearson
      value: 78.62779318576634
    - type: euclidean_spearman
      value: 78.88760695649488
    - type: main_score
      value: 78.45516413087114
    - type: manhattan_pearson
      value: 78.62131335760031
    - type: manhattan_spearman
      value: 78.81861844200388
    - type: pearson
      value: 76.8364678896155
    - type: spearman
      value: 78.45516413087114
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-en)
      type: mteb/sts22-crosslingual-sts
      config: de-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 65.16640313911604
    - type: cosine_spearman
      value: 60.887608967403914
    - type: euclidean_pearson
      value: 67.49902244990913
    - type: euclidean_spearman
      value: 59.2458787136538
    - type: main_score
      value: 60.887608967403914
    - type: manhattan_pearson
      value: 67.34313506388378
    - type: manhattan_spearman
      value: 59.05283429200166
    - type: pearson
      value: 65.16640313911604
    - type: spearman
      value: 60.887608967403914
  - task:
      type: STS
    dataset:
      name: MTEB STSB (default)
      type: C-MTEB/STSB
      config: default
      split: test
      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
    metrics:
    - type: cosine_pearson
      value: 81.5092853013241
    - type: cosine_spearman
      value: 83.54005474244292
    - type: euclidean_pearson
      value: 83.7246578378554
    - type: euclidean_spearman
      value: 84.46767551087716
    - type: main_score
      value: 83.54005474244292
    - type: manhattan_pearson
      value: 83.65922665594636
    - type: manhattan_spearman
      value: 84.42431449101848
    - type: pearson
      value: 81.5092853013241
    - type: spearman
      value: 83.54005474244292
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark (default)
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cosine_pearson
      value: 87.70246866744966
    - type: cosine_spearman
      value: 89.44070045346106
    - type: euclidean_pearson
      value: 89.56956519641007
    - type: euclidean_spearman
      value: 89.95830112784283
    - type: main_score
      value: 89.44070045346106
    - type: manhattan_pearson
      value: 89.48264471425145
    - type: manhattan_spearman
      value: 89.87900732483114
    - type: pearson
      value: 87.70246866744966
    - type: spearman
      value: 89.44070045346106
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmarkMultilingualSTS (de)
      type: mteb/stsb_multi_mt
      config: de
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    metrics:
    - type: cosine_pearson
      value: 86.83701990805217
    - type: cosine_spearman
      value: 87.80280785492258
    - type: euclidean_pearson
      value: 87.77325330043514
    - type: euclidean_spearman
      value: 88.3564607283144
    - type: main_score
      value: 87.80280785492258
    - type: manhattan_pearson
      value: 87.6745449945946
    - type: manhattan_spearman
      value: 88.30660465978795
    - type: pearson
      value: 86.83701990805217
    - type: spearman
      value: 87.80280785492258
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmarkMultilingualSTS (zh)
      type: mteb/stsb_multi_mt
      config: zh
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    metrics:
    - type: cosine_pearson
      value: 84.27751020600267
    - type: cosine_spearman
      value: 85.63500407412486
    - type: euclidean_pearson
      value: 85.21829891649696
    - type: euclidean_spearman
      value: 85.9384575715382
    - type: main_score
      value: 85.63500407412486
    - type: manhattan_pearson
      value: 85.10797194089801
    - type: manhattan_spearman
      value: 85.8770162042784
    - type: pearson
      value: 84.27751020600267
    - type: spearman
      value: 85.63500407412486
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmarkMultilingualSTS (fr)
      type: mteb/stsb_multi_mt
      config: fr
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    metrics:
    - type: cosine_pearson
      value: 86.56833656723254
    - type: cosine_spearman
      value: 87.4393978501382
    - type: euclidean_pearson
      value: 87.45171512751267
    - type: euclidean_spearman
      value: 88.13106516566947
    - type: main_score
      value: 87.4393978501382
    - type: manhattan_pearson
      value: 87.33010961793333
    - type: manhattan_spearman
      value: 88.06707425102182
    - type: pearson
      value: 86.56833656723254
    - type: spearman
      value: 87.4393978501382
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmarkMultilingualSTS (pl)
      type: mteb/stsb_multi_mt
      config: pl
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    metrics:
    - type: cosine_pearson
      value: 85.45065540325523
    - type: cosine_spearman
      value: 85.47881076789359
    - type: euclidean_pearson
      value: 85.1999493863155
    - type: euclidean_spearman
      value: 85.7874947669187
    - type: main_score
      value: 85.47881076789359
    - type: manhattan_pearson
      value: 85.06075305990376
    - type: manhattan_spearman
      value: 85.71563015639558
    - type: pearson
      value: 85.45065540325523
    - type: spearman
      value: 85.47881076789359
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmarkMultilingualSTS (es)
      type: mteb/stsb_multi_mt
      config: es
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    metrics:
    - type: cosine_pearson
      value: 87.11952824079832
    - type: cosine_spearman
      value: 87.9643473573153
    - type: euclidean_pearson
      value: 88.11750364639971
    - type: euclidean_spearman
      value: 88.63695109016498
    - type: main_score
      value: 87.9643473573153
    - type: manhattan_pearson
      value: 88.00294453126699
    - type: manhattan_spearman
      value: 88.53750241758391
    - type: pearson
      value: 87.11952824079832
    - type: spearman
      value: 87.9643473573153
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmarkMultilingualSTS (ru)
      type: mteb/stsb_multi_mt
      config: ru
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    metrics:
    - type: cosine_pearson
      value: 85.99804354414991
    - type: cosine_spearman
      value: 86.30252111551002
    - type: euclidean_pearson
      value: 86.1880652037762
    - type: euclidean_spearman
      value: 86.69556223944502
    - type: main_score
      value: 86.30252111551002
    - type: manhattan_pearson
      value: 86.0736400320898
    - type: manhattan_spearman
      value: 86.61747927593393
    - type: pearson
      value: 85.99804354414991
    - type: spearman
      value: 86.30252111551002
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmarkMultilingualSTS (en)
      type: mteb/stsb_multi_mt
      config: en
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    metrics:
    - type: cosine_pearson
      value: 87.70246861738103
    - type: cosine_spearman
      value: 89.44070045346106
    - type: euclidean_pearson
      value: 89.56956518833663
    - type: euclidean_spearman
      value: 89.95830112784283
    - type: main_score
      value: 89.44070045346106
    - type: manhattan_pearson
      value: 89.48264470792915
    - type: manhattan_spearman
      value: 89.87900732483114
    - type: pearson
      value: 87.70246861738103
    - type: spearman
      value: 89.44070045346106
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR (default)
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 84.88064122814694
    - type: mrr
      value: 95.84832651009123
    - type: main_score
      value: 84.88064122814694
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact (default)
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 57.289
    - type: map_at_10
      value: 67.88499999999999
    - type: map_at_100
      value: 68.477
    - type: map_at_1000
      value: 68.50500000000001
    - type: map_at_20
      value: 68.33500000000001
    - type: map_at_3
      value: 65.08
    - type: map_at_5
      value: 67.001
    - type: mrr_at_1
      value: 59.667
    - type: mrr_at_10
      value: 68.626
    - type: mrr_at_100
      value: 69.082
    - type: mrr_at_1000
      value: 69.108
    - type: mrr_at_20
      value: 68.958
    - type: mrr_at_3
      value: 66.667
    - type: mrr_at_5
      value: 67.983
    - type: ndcg_at_1
      value: 59.667
    - type: ndcg_at_10
      value: 72.309
    - type: ndcg_at_100
      value: 74.58399999999999
    - type: ndcg_at_1000
      value: 75.25500000000001
    - type: ndcg_at_20
      value: 73.656
    - type: ndcg_at_3
      value: 67.791
    - type: ndcg_at_5
      value: 70.45
    - type: precision_at_1
      value: 59.667
    - type: precision_at_10
      value: 9.567
    - type: precision_at_100
      value: 1.073
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_20
      value: 5.083
    - type: precision_at_3
      value: 26.333000000000002
    - type: precision_at_5
      value: 17.666999999999998
    - type: recall_at_1
      value: 57.289
    - type: recall_at_10
      value: 84.756
    - type: recall_at_100
      value: 94.5
    - type: recall_at_1000
      value: 99.667
    - type: recall_at_20
      value: 89.7
    - type: recall_at_3
      value: 73.22800000000001
    - type: recall_at_5
      value: 79.444
    - type: main_score
      value: 72.309
  - task:
      type: Clustering
    dataset:
      name: MTEB SpanishNewsClusteringP2P (default)
      type: jinaai/spanish_news_clustering
      config: default
      split: test
      revision: bf8ca8ddc5b7da4f7004720ddf99bbe0483480e6
    metrics:
    - type: main_score
      value: 45.04477709795154
    - type: v_measure
      value: 45.04477709795154
    - type: v_measure_std
      value: 0.0
  - task:
      type: Retrieval
    dataset:
      name: MTEB SpanishPassageRetrievalS2S (default)
      type: jinaai/spanish_passage_retrieval
      config: default
      split: test
      revision: 9cddf2ce5209ade52c2115ccfa00eb22c6d3a837
    metrics:
    - type: main_score
      value: 69.83
    - type: map_at_1
      value: 15.736
    - type: map_at_10
      value: 52.027
    - type: map_at_100
      value: 65.08800000000001
    - type: map_at_1000
      value: 65.08800000000001
    - type: map_at_20
      value: 60.79900000000001
    - type: map_at_3
      value: 32.869
    - type: map_at_5
      value: 41.436
    - type: mrr_at_1
      value: 75.44910179640718
    - type: mrr_at_10
      value: 84.43446440452426
    - type: mrr_at_100
      value: 84.48052612723271
    - type: mrr_at_1000
      value: 84.48052612723271
    - type: mrr_at_20
      value: 84.48052612723271
    - type: mrr_at_3
      value: 83.13373253493013
    - type: mrr_at_5
      value: 84.3013972055888
    - type: nauc_map_at_1000_diff1
      value: 50.611540149694356
    - type: nauc_map_at_1000_max
      value: 2.1102430434260238
    - type: nauc_map_at_1000_std
      value: -18.88993521335793
    - type: nauc_map_at_100_diff1
      value: 50.611540149694356
    - type: nauc_map_at_100_max
      value: 2.1102430434260238
    - type: nauc_map_at_100_std
      value: -18.88993521335793
    - type: nauc_map_at_10_diff1
      value: 59.13518981755268
    - type: nauc_map_at_10_max
      value: -9.810386627392807
    - type: nauc_map_at_10_std
      value: -38.31810152345078
    - type: nauc_map_at_1_diff1
      value: 74.96782567287174
    - type: nauc_map_at_1_max
      value: -29.648279252607875
    - type: nauc_map_at_1_std
      value: -54.017459339141595
    - type: nauc_map_at_20_diff1
      value: 55.26694458629849
    - type: nauc_map_at_20_max
      value: -1.9490244535020729
    - type: nauc_map_at_20_std
      value: -25.22211659104076
    - type: nauc_map_at_3_diff1
      value: 71.67607885031732
    - type: nauc_map_at_3_max
      value: -25.078101661694507
    - type: nauc_map_at_3_std
      value: -50.55408861920259
    - type: nauc_map_at_5_diff1
      value: 61.50111515417668
    - type: nauc_map_at_5_max
      value: -16.4114670513168
    - type: nauc_map_at_5_std
      value: -44.391416134859135
    - type: nauc_mrr_at_1000_diff1
      value: 74.18848063283234
    - type: nauc_mrr_at_1000_max
      value: 21.929205946778005
    - type: nauc_mrr_at_1000_std
      value: -36.27399268489433
    - type: nauc_mrr_at_100_diff1
      value: 74.18848063283234
    - type: nauc_mrr_at_100_max
      value: 21.929205946778005
    - type: nauc_mrr_at_100_std
      value: -36.27399268489433
    - type: nauc_mrr_at_10_diff1
      value: 74.27231582268745
    - type: nauc_mrr_at_10_max
      value: 21.481133301135337
    - type: nauc_mrr_at_10_std
      value: -36.72070854872902
    - type: nauc_mrr_at_1_diff1
      value: 76.54855950439561
    - type: nauc_mrr_at_1_max
      value: 26.99938321212366
    - type: nauc_mrr_at_1_std
      value: -33.098742603429635
    - type: nauc_mrr_at_20_diff1
      value: 74.18848063283234
    - type: nauc_mrr_at_20_max
      value: 21.929205946778005
    - type: nauc_mrr_at_20_std
      value: -36.27399268489433
    - type: nauc_mrr_at_3_diff1
      value: 72.05379526740143
    - type: nauc_mrr_at_3_max
      value: 18.875831185752528
    - type: nauc_mrr_at_3_std
      value: -37.27302006456391
    - type: nauc_mrr_at_5_diff1
      value: 74.25342356682029
    - type: nauc_mrr_at_5_max
      value: 20.756340085088738
    - type: nauc_mrr_at_5_std
      value: -37.99507208540703
    - type: nauc_ndcg_at_1000_diff1
      value: 53.259363764380275
    - type: nauc_ndcg_at_1000_max
      value: 12.936954959423218
    - type: nauc_ndcg_at_1000_std
      value: -16.953898675672153
    - type: nauc_ndcg_at_100_diff1
      value: 53.259363764380275
    - type: nauc_ndcg_at_100_max
      value: 12.936954959423218
    - type: nauc_ndcg_at_100_std
      value: -16.953898675672153
    - type: nauc_ndcg_at_10_diff1
      value: 53.70942345413554
    - type: nauc_ndcg_at_10_max
      value: -3.8465093347016186
    - type: nauc_ndcg_at_10_std
      value: -31.208127919994755
    - type: nauc_ndcg_at_1_diff1
      value: 75.30551289259554
    - type: nauc_ndcg_at_1_max
      value: 25.53292054129834
    - type: nauc_ndcg_at_1_std
      value: -33.285498788395145
    - type: nauc_ndcg_at_20_diff1
      value: 57.62409278278133
    - type: nauc_ndcg_at_20_max
      value: 2.8040586426056233
    - type: nauc_ndcg_at_20_std
      value: -26.270875776221704
    - type: nauc_ndcg_at_3_diff1
      value: 48.42294834754225
    - type: nauc_ndcg_at_3_max
      value: 16.912467881065822
    - type: nauc_ndcg_at_3_std
      value: -13.324841189277873
    - type: nauc_ndcg_at_5_diff1
      value: 47.512819802794596
    - type: nauc_ndcg_at_5_max
      value: 14.645518203506594
    - type: nauc_ndcg_at_5_std
      value: -17.641450435599275
    - type: nauc_precision_at_1000_diff1
      value: -34.43320975829637
    - type: nauc_precision_at_1000_max
      value: 29.08585622578186
    - type: nauc_precision_at_1000_std
      value: 46.55117940162061
    - type: nauc_precision_at_100_diff1
      value: -34.433209758296364
    - type: nauc_precision_at_100_max
      value: 29.085856225781885
    - type: nauc_precision_at_100_std
      value: 46.55117940162065
    - type: nauc_precision_at_10_diff1
      value: -21.895306304096902
    - type: nauc_precision_at_10_max
      value: 33.190476527593745
    - type: nauc_precision_at_10_std
      value: 37.64916268614298
    - type: nauc_precision_at_1_diff1
      value: 75.30551289259554
    - type: nauc_precision_at_1_max
      value: 25.53292054129834
    - type: nauc_precision_at_1_std
      value: -33.285498788395145
    - type: nauc_precision_at_20_diff1
      value: -27.63076748060466
    - type: nauc_precision_at_20_max
      value: 30.689810416086154
    - type: nauc_precision_at_20_std
      value: 46.164191636131626
    - type: nauc_precision_at_3_diff1
      value: 20.547345067837288
    - type: nauc_precision_at_3_max
      value: 26.177050942827528
    - type: nauc_precision_at_3_std
      value: 5.960466052973099
    - type: nauc_precision_at_5_diff1
      value: -8.928755534002669
    - type: nauc_precision_at_5_max
      value: 40.83262650073459
    - type: nauc_precision_at_5_std
      value: 26.158537031161494
    - type: nauc_recall_at_1000_diff1
      value: .nan
    - type: nauc_recall_at_1000_max
      value: .nan
    - type: nauc_recall_at_1000_std
      value: .nan
    - type: nauc_recall_at_100_diff1
      value: .nan
    - type: nauc_recall_at_100_max
      value: .nan
    - type: nauc_recall_at_100_std
      value: .nan
    - type: nauc_recall_at_10_diff1
      value: 53.08654386169444
    - type: nauc_recall_at_10_max
      value: -23.276269379519356
    - type: nauc_recall_at_10_std
      value: -50.80707792706157
    - type: nauc_recall_at_1_diff1
      value: 74.96782567287174
    - type: nauc_recall_at_1_max
      value: -29.648279252607875
    - type: nauc_recall_at_1_std
      value: -54.017459339141595
    - type: nauc_recall_at_20_diff1
      value: 51.60121897059633
    - type: nauc_recall_at_20_max
      value: -14.241779530735387
    - type: nauc_recall_at_20_std
      value: -37.877451525215456
    - type: nauc_recall_at_3_diff1
      value: 66.99474984329694
    - type: nauc_recall_at_3_max
      value: -30.802787353187966
    - type: nauc_recall_at_3_std
      value: -53.58737792129713
    - type: nauc_recall_at_5_diff1
      value: 54.64214444958567
    - type: nauc_recall_at_5_max
      value: -23.341309362104703
    - type: nauc_recall_at_5_std
      value: -51.381363923145265
    - type: ndcg_at_1
      value: 76.048
    - type: ndcg_at_10
      value: 69.83
    - type: ndcg_at_100
      value: 82.11500000000001
    - type: ndcg_at_1000
      value: 82.11500000000001
    - type: ndcg_at_20
      value: 75.995
    - type: ndcg_at_3
      value: 69.587
    - type: ndcg_at_5
      value: 69.062
    - type: precision_at_1
      value: 76.048
    - type: precision_at_10
      value: 43.653
    - type: precision_at_100
      value: 7.718999999999999
    - type: precision_at_1000
      value: 0.772
    - type: precision_at_20
      value: 31.108000000000004
    - type: precision_at_3
      value: 63.87199999999999
    - type: precision_at_5
      value: 56.407
    - type: recall_at_1
      value: 15.736
    - type: recall_at_10
      value: 66.873
    - type: recall_at_100
      value: 100.0
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 85.01100000000001
    - type: recall_at_3
      value: 36.441
    - type: recall_at_5
      value: 49.109
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions (default)
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cosine_accuracy
      value: 99.87326732673267
    - type: cosine_accuracy_threshold
      value: 86.0752820968628
    - type: cosine_ap
      value: 96.98758090713252
    - type: cosine_f1
      value: 93.52881698685542
    - type: cosine_f1_threshold
      value: 86.0752820968628
    - type: cosine_precision
      value: 94.58077709611452
    - type: cosine_recall
      value: 92.5
    - type: dot_accuracy
      value: 99.82574257425742
    - type: dot_accuracy_threshold
      value: 40484.73815917969
    - type: dot_ap
      value: 95.68959907254845
    - type: dot_f1
      value: 91.31293188548865
    - type: dot_f1_threshold
      value: 40336.810302734375
    - type: dot_precision
      value: 90.15594541910332
    - type: dot_recall
      value: 92.5
    - type: euclidean_accuracy
      value: 99.87128712871286
    - type: euclidean_accuracy_threshold
      value: 1162.5749588012695
    - type: euclidean_ap
      value: 96.92640435656577
    - type: euclidean_f1
      value: 93.4475806451613
    - type: euclidean_f1_threshold
      value: 1162.5749588012695
    - type: euclidean_precision
      value: 94.20731707317073
    - type: euclidean_recall
      value: 92.7
    - type: main_score
      value: 96.98758090713252
    - type: manhattan_accuracy
      value: 99.86930693069307
    - type: manhattan_accuracy_threshold
      value: 28348.71826171875
    - type: manhattan_ap
      value: 96.93832673967925
    - type: manhattan_f1
      value: 93.33333333333333
    - type: manhattan_f1_threshold
      value: 28348.71826171875
    - type: manhattan_precision
      value: 94.28571428571428
    - type: manhattan_recall
      value: 92.4
    - type: max_accuracy
      value: 99.87326732673267
    - type: max_ap
      value: 96.98758090713252
    - type: max_f1
      value: 93.52881698685542
    - type: max_precision
      value: 94.58077709611452
    - type: max_recall
      value: 92.7
    - type: similarity_accuracy
      value: 99.87326732673267
    - type: similarity_accuracy_threshold
      value: 86.0752820968628
    - type: similarity_ap
      value: 96.98758090713252
    - type: similarity_f1
      value: 93.52881698685542
    - type: similarity_f1_threshold
      value: 86.0752820968628
    - type: similarity_precision
      value: 94.58077709611452
    - type: similarity_recall
      value: 92.5
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering (default)
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: main_score
      value: 65.6560129719848
    - type: v_measure
      value: 65.6560129719848
    - type: v_measure_std
      value: 4.781229811487539
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P (default)
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: main_score
      value: 35.07546243853692
    - type: v_measure
      value: 35.07546243853692
    - type: v_measure_std
      value: 1.1978740356240998
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions (default)
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
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  - task:
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    dataset:
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      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
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  - task:
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    dataset:
      name: MTEB SummEvalFr (default)
      type: lyon-nlp/summarization-summeval-fr-p2p
      config: default
      split: test
      revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
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    - type: pearson
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    - type: spearman
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  - task:
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    dataset:
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      type: lyon-nlp/mteb-fr-reranking-syntec-s2p
      config: default
      split: test
      revision: b205c5084a0934ce8af14338bf03feb19499c84d
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    - type: mrr
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  - task:
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      type: lyon-nlp/mteb-fr-retrieval-syntec-s2p
      config: default
      split: test
      revision: 19661ccdca4dfc2d15122d776b61685f48c68ca9
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  - task:
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      type: C-MTEB/T2Reranking
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      split: dev
      revision: 76631901a18387f85eaa53e5450019b87ad58ef9
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  - task:
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      type: C-MTEB/T2Retrieval
      config: default
      split: dev
      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
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      value: -38.11345358035342
    - type: nauc_recall_at_20_diff1
      value: 10.35772828627265
    - type: nauc_recall_at_20_max
      value: 43.06420839754062
    - type: nauc_recall_at_20_std
      value: 15.040522218235692
    - type: nauc_recall_at_3_diff1
      value: 36.23953684770224
    - type: nauc_recall_at_3_max
      value: -11.709269151700374
    - type: nauc_recall_at_3_std
      value: -38.13943178150384
    - type: nauc_recall_at_5_diff1
      value: 28.644872415763384
    - type: nauc_recall_at_5_max
      value: 2.062151266111129
    - type: nauc_recall_at_5_std
      value: -30.81114034774277
    - type: ndcg_at_1
      value: 88.901
    - type: ndcg_at_10
      value: 83.163
    - type: ndcg_at_100
      value: 86.854
    - type: ndcg_at_1000
      value: 87.602
    - type: ndcg_at_20
      value: 84.908
    - type: ndcg_at_3
      value: 84.848
    - type: ndcg_at_5
      value: 83.372
    - type: precision_at_1
      value: 88.901
    - type: precision_at_10
      value: 41.343
    - type: precision_at_100
      value: 4.957000000000001
    - type: precision_at_1000
      value: 0.513
    - type: precision_at_20
      value: 22.955000000000002
    - type: precision_at_3
      value: 74.29599999999999
    - type: precision_at_5
      value: 62.251999999999995
    - type: recall_at_1
      value: 26.875
    - type: recall_at_10
      value: 81.902
    - type: recall_at_100
      value: 93.988
    - type: recall_at_1000
      value: 97.801
    - type: recall_at_20
      value: 87.809
    - type: recall_at_3
      value: 54.869
    - type: recall_at_5
      value: 68.728
  - task:
      type: PairClassification
    dataset:
      name: MTEB TERRa (default)
      type: ai-forever/terra-pairclassification
      config: default
      split: dev
      revision: 7b58f24536063837d644aab9a023c62199b2a612
    metrics:
    - type: cosine_accuracy
      value: 60.586319218241044
    - type: cosine_accuracy_threshold
      value: 82.49806761741638
    - type: cosine_ap
      value: 58.73198048427448
    - type: cosine_f1
      value: 67.37967914438502
    - type: cosine_f1_threshold
      value: 77.46461033821106
    - type: cosine_precision
      value: 57.01357466063348
    - type: cosine_recall
      value: 82.35294117647058
    - type: dot_accuracy
      value: 60.26058631921825
    - type: dot_accuracy_threshold
      value: 35627.020263671875
    - type: dot_ap
      value: 57.418783612898224
    - type: dot_f1
      value: 66.51982378854623
    - type: dot_f1_threshold
      value: 27620.843505859375
    - type: dot_precision
      value: 50.16611295681063
    - type: dot_recall
      value: 98.69281045751634
    - type: euclidean_accuracy
      value: 60.26058631921825
    - type: euclidean_accuracy_threshold
      value: 1255.4466247558594
    - type: euclidean_ap
      value: 58.748656145387955
    - type: euclidean_f1
      value: 66.99029126213591
    - type: euclidean_f1_threshold
      value: 1565.1330947875977
    - type: euclidean_precision
      value: 53.28185328185329
    - type: euclidean_recall
      value: 90.19607843137256
    - type: main_score
      value: 58.8479126365766
    - type: manhattan_accuracy
      value: 59.934853420195445
    - type: manhattan_accuracy_threshold
      value: 29897.271728515625
    - type: manhattan_ap
      value: 58.8479126365766
    - type: manhattan_f1
      value: 66.81318681318683
    - type: manhattan_f1_threshold
      value: 46291.802978515625
    - type: manhattan_precision
      value: 50.331125827814574
    - type: manhattan_recall
      value: 99.34640522875817
    - type: max_accuracy
      value: 60.586319218241044
    - type: max_ap
      value: 58.8479126365766
    - type: max_f1
      value: 67.37967914438502
    - type: max_precision
      value: 57.01357466063348
    - type: max_recall
      value: 99.34640522875817
    - type: similarity_accuracy
      value: 60.586319218241044
    - type: similarity_accuracy_threshold
      value: 82.49806761741638
    - type: similarity_ap
      value: 58.73198048427448
    - type: similarity_f1
      value: 67.37967914438502
    - type: similarity_f1_threshold
      value: 77.46461033821106
    - type: similarity_precision
      value: 57.01357466063348
    - type: similarity_recall
      value: 82.35294117647058
  - task:
      type: Classification
    dataset:
      name: MTEB TNews (default)
      type: C-MTEB/TNews-classification
      config: default
      split: validation
      revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
    metrics:
    - type: accuracy
      value: 45.967999999999996
    - type: f1
      value: 44.699306100915706
    - type: f1_weighted
      value: 46.03730319014832
    - type: main_score
      value: 45.967999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID (default)
      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.251
    - type: map_at_10
      value: 1.9480000000000002
    - type: map_at_100
      value: 11.082
    - type: map_at_1000
      value: 26.700000000000003
    - type: map_at_20
      value: 3.3529999999999998
    - type: map_at_3
      value: 0.679
    - type: map_at_5
      value: 1.079
    - type: mrr_at_1
      value: 94.0
    - type: mrr_at_10
      value: 95.786
    - type: mrr_at_100
      value: 95.786
    - type: mrr_at_1000
      value: 95.786
    - type: mrr_at_20
      value: 95.786
    - type: mrr_at_3
      value: 95.0
    - type: mrr_at_5
      value: 95.5
    - type: ndcg_at_1
      value: 91.0
    - type: ndcg_at_10
      value: 77.71900000000001
    - type: ndcg_at_100
      value: 57.726
    - type: ndcg_at_1000
      value: 52.737
    - type: ndcg_at_20
      value: 72.54
    - type: ndcg_at_3
      value: 83.397
    - type: ndcg_at_5
      value: 80.806
    - type: precision_at_1
      value: 94.0
    - type: precision_at_10
      value: 81.0
    - type: precision_at_100
      value: 59.199999999999996
    - type: precision_at_1000
      value: 23.244
    - type: precision_at_20
      value: 75.2
    - type: precision_at_3
      value: 88.0
    - type: precision_at_5
      value: 84.8
    - type: recall_at_1
      value: 0.251
    - type: recall_at_10
      value: 2.1229999999999998
    - type: recall_at_100
      value: 14.496999999999998
    - type: recall_at_1000
      value: 50.09
    - type: recall_at_20
      value: 3.8309999999999995
    - type: recall_at_3
      value: 0.696
    - type: recall_at_5
      value: 1.1400000000000001
    - type: main_score
      value: 77.71900000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB TenKGnadClusteringP2P (default)
      type: slvnwhrl/tenkgnad-clustering-p2p
      config: default
      split: test
      revision: 5c59e41555244b7e45c9a6be2d720ab4bafae558
    metrics:
    - type: main_score
      value: 43.763609722295215
    - type: v_measure
      value: 43.763609722295215
    - type: v_measure_std
      value: 2.8751199473862457
  - task:
      type: Clustering
    dataset:
      name: MTEB TenKGnadClusteringS2S (default)
      type: slvnwhrl/tenkgnad-clustering-s2s
      config: default
      split: test
      revision: 6cddbe003f12b9b140aec477b583ac4191f01786
    metrics:
    - type: main_score
      value: 39.762424448504355
    - type: v_measure
      value: 39.762424448504355
    - type: v_measure_std
      value: 3.30146124979502
  - task:
      type: Clustering
    dataset:
      name: MTEB ThuNewsClusteringP2P (default)
      type: C-MTEB/ThuNewsClusteringP2P
      config: default
      split: test
      revision: 5798586b105c0434e4f0fe5e767abe619442cf93
    metrics:
    - type: main_score
      value: 63.133819258289456
    - type: v_measure
      value: 63.133819258289456
    - type: v_measure_std
      value: 1.8854253356479695
  - task:
      type: Clustering
    dataset:
      name: MTEB ThuNewsClusteringS2S (default)
      type: C-MTEB/ThuNewsClusteringS2S
      config: default
      split: test
      revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
    metrics:
    - type: main_score
      value: 58.98195851785808
    - type: v_measure
      value: 58.98195851785808
    - type: v_measure_std
      value: 1.6237600076393737
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020 (default)
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 3.3550000000000004
    - type: map_at_10
      value: 10.08
    - type: map_at_100
      value: 16.136
    - type: map_at_1000
      value: 17.605
    - type: map_at_20
      value: 12.561
    - type: map_at_3
      value: 5.641
    - type: map_at_5
      value: 7.3260000000000005
    - type: mrr_at_1
      value: 46.939
    - type: mrr_at_10
      value: 58.152
    - type: mrr_at_100
      value: 58.594
    - type: mrr_at_1000
      value: 58.601000000000006
    - type: mrr_at_20
      value: 58.279
    - type: mrr_at_3
      value: 55.102
    - type: mrr_at_5
      value: 56.531
    - type: ndcg_at_1
      value: 44.897999999999996
    - type: ndcg_at_10
      value: 26.298
    - type: ndcg_at_100
      value: 37.596000000000004
    - type: ndcg_at_1000
      value: 49.424
    - type: ndcg_at_20
      value: 27.066000000000003
    - type: ndcg_at_3
      value: 31.528
    - type: ndcg_at_5
      value: 28.219
    - type: precision_at_1
      value: 46.939
    - type: precision_at_10
      value: 22.245
    - type: precision_at_100
      value: 7.531000000000001
    - type: precision_at_1000
      value: 1.5350000000000001
    - type: precision_at_20
      value: 17.041
    - type: precision_at_3
      value: 30.612000000000002
    - type: precision_at_5
      value: 26.122
    - type: recall_at_1
      value: 3.3550000000000004
    - type: recall_at_10
      value: 16.41
    - type: recall_at_100
      value: 47.272
    - type: recall_at_1000
      value: 83.584
    - type: recall_at_20
      value: 24.091
    - type: recall_at_3
      value: 6.8180000000000005
    - type: recall_at_5
      value: 9.677
    - type: main_score
      value: 26.298
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification (default)
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 91.2890625
    - type: ap
      value: 33.95547153875715
    - type: ap_weighted
      value: 33.95547153875715
    - type: f1
      value: 75.10768597556462
    - type: f1_weighted
      value: 92.00161208992606
    - type: main_score
      value: 91.2890625
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification (default)
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 71.3978494623656
    - type: f1
      value: 71.7194818511814
    - type: f1_weighted
      value: 71.13860187349744
    - type: main_score
      value: 71.3978494623656
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering (default)
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: main_score
      value: 52.4921688720602
    - type: v_measure
      value: 52.4921688720602
    - type: v_measure_std
      value: 0.992768152658908
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015 (default)
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cosine_accuracy
      value: 85.11652858079513
    - type: cosine_accuracy_threshold
      value: 87.90839910507202
    - type: cosine_ap
      value: 70.90459908851724
    - type: cosine_f1
      value: 65.66581227877457
    - type: cosine_f1_threshold
      value: 85.13308763504028
    - type: cosine_precision
      value: 61.094708153531684
    - type: cosine_recall
      value: 70.97625329815304
    - type: dot_accuracy
      value: 83.41181379269239
    - type: dot_accuracy_threshold
      value: 43110.113525390625
    - type: dot_ap
      value: 65.64869491143095
    - type: dot_f1
      value: 62.05308447460914
    - type: dot_f1_threshold
      value: 41412.542724609375
    - type: dot_precision
      value: 57.38623626989464
    - type: dot_recall
      value: 67.54617414248021
    - type: euclidean_accuracy
      value: 85.15229182809799
    - type: euclidean_accuracy_threshold
      value: 1043.08500289917
    - type: euclidean_ap
      value: 70.71204383269375
    - type: euclidean_f1
      value: 65.20304568527919
    - type: euclidean_f1_threshold
      value: 1179.2595863342285
    - type: euclidean_precision
      value: 62.81173594132029
    - type: euclidean_recall
      value: 67.78364116094987
    - type: main_score
      value: 70.90459908851724
    - type: manhattan_accuracy
      value: 85.1820945341837
    - type: manhattan_accuracy_threshold
      value: 26115.0390625
    - type: manhattan_ap
      value: 70.66113937117431
    - type: manhattan_f1
      value: 65.33383628819313
    - type: manhattan_f1_threshold
      value: 29105.181884765625
    - type: manhattan_precision
      value: 62.40691808791736
    - type: manhattan_recall
      value: 68.54881266490766
    - type: max_accuracy
      value: 85.1820945341837
    - type: max_ap
      value: 70.90459908851724
    - type: max_f1
      value: 65.66581227877457
    - type: max_precision
      value: 62.81173594132029
    - type: max_recall
      value: 70.97625329815304
    - type: similarity_accuracy
      value: 85.11652858079513
    - type: similarity_accuracy_threshold
      value: 87.90839910507202
    - type: similarity_ap
      value: 70.90459908851724
    - type: similarity_f1
      value: 65.66581227877457
    - type: similarity_f1_threshold
      value: 85.13308763504028
    - type: similarity_precision
      value: 61.094708153531684
    - type: similarity_recall
      value: 70.97625329815304
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus (default)
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cosine_accuracy
      value: 88.10299996119068
    - type: cosine_accuracy_threshold
      value: 84.34982895851135
    - type: cosine_ap
      value: 84.13755787769226
    - type: cosine_f1
      value: 76.0967548076923
    - type: cosine_f1_threshold
      value: 82.8936219215393
    - type: cosine_precision
      value: 74.28864769727193
    - type: cosine_recall
      value: 77.99507237449954
    - type: dot_accuracy
      value: 86.64182869561843
    - type: dot_accuracy_threshold
      value: 38794.677734375
    - type: dot_ap
      value: 80.20301567411457
    - type: dot_f1
      value: 73.50650291634967
    - type: dot_f1_threshold
      value: 37447.23205566406
    - type: dot_precision
      value: 69.41498460485802
    - type: dot_recall
      value: 78.11056359716662
    - type: euclidean_accuracy
      value: 87.9361198432103
    - type: euclidean_accuracy_threshold
      value: 1184.421157836914
    - type: euclidean_ap
      value: 83.79582690117218
    - type: euclidean_f1
      value: 75.81431709042175
    - type: euclidean_f1_threshold
      value: 1258.2727432250977
    - type: euclidean_precision
      value: 73.39099099099099
    - type: euclidean_recall
      value: 78.40314136125654
    - type: main_score
      value: 84.13755787769226
    - type: manhattan_accuracy
      value: 87.96134590755618
    - type: manhattan_accuracy_threshold
      value: 29077.291870117188
    - type: manhattan_ap
      value: 83.79487172269923
    - type: manhattan_f1
      value: 75.82421603424935
    - type: manhattan_f1_threshold
      value: 31224.124145507812
    - type: manhattan_precision
      value: 72.24740255212329
    - type: manhattan_recall
      value: 79.77363720357253
    - type: max_accuracy
      value: 88.10299996119068
    - type: max_ap
      value: 84.13755787769226
    - type: max_f1
      value: 76.0967548076923
    - type: max_precision
      value: 74.28864769727193
    - type: max_recall
      value: 79.77363720357253
    - type: similarity_accuracy
      value: 88.10299996119068
    - type: similarity_accuracy_threshold
      value: 84.34982895851135
    - type: similarity_ap
      value: 84.13755787769226
    - type: similarity_f1
      value: 76.0967548076923
    - type: similarity_f1_threshold
      value: 82.8936219215393
    - type: similarity_precision
      value: 74.28864769727193
    - type: similarity_recall
      value: 77.99507237449954
  - task:
      type: Retrieval
    dataset:
      name: MTEB VideoRetrieval (default)
      type: C-MTEB/VideoRetrieval
      config: default
      split: dev
      revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
    metrics:
    - type: main_score
      value: 70.433
    - type: map_at_1
      value: 55.7
    - type: map_at_10
      value: 66.013
    - type: map_at_100
      value: 66.534
    - type: map_at_1000
      value: 66.547
    - type: map_at_20
      value: 66.334
    - type: map_at_3
      value: 64.2
    - type: map_at_5
      value: 65.445
    - type: mrr_at_1
      value: 55.7
    - type: mrr_at_10
      value: 66.01329365079364
    - type: mrr_at_100
      value: 66.53350061744233
    - type: mrr_at_1000
      value: 66.54744831962995
    - type: mrr_at_20
      value: 66.3335147364675
    - type: mrr_at_3
      value: 64.2
    - type: mrr_at_5
      value: 65.44500000000002
    - type: nauc_map_at_1000_diff1
      value: 76.26428836976245
    - type: nauc_map_at_1000_max
      value: 35.41847367373575
    - type: nauc_map_at_1000_std
      value: -33.04639860831992
    - type: nauc_map_at_100_diff1
      value: 76.25793229023193
    - type: nauc_map_at_100_max
      value: 35.43663260110076
    - type: nauc_map_at_100_std
      value: -33.04238139882945
    - type: nauc_map_at_10_diff1
      value: 76.2108281297711
    - type: nauc_map_at_10_max
      value: 35.59442419423183
    - type: nauc_map_at_10_std
      value: -33.32346518997277
    - type: nauc_map_at_1_diff1
      value: 79.17728405262736
    - type: nauc_map_at_1_max
      value: 31.880738163589527
    - type: nauc_map_at_1_std
      value: -30.891888718004584
    - type: nauc_map_at_20_diff1
      value: 76.2181333410193
    - type: nauc_map_at_20_max
      value: 35.43448818430876
    - type: nauc_map_at_20_std
      value: -33.35682442863193
    - type: nauc_map_at_3_diff1
      value: 76.10046541433466
    - type: nauc_map_at_3_max
      value: 34.6831278555291
    - type: nauc_map_at_3_std
      value: -34.030826044831116
    - type: nauc_map_at_5_diff1
      value: 75.96513023582064
    - type: nauc_map_at_5_max
      value: 34.66920832438069
    - type: nauc_map_at_5_std
      value: -33.79799777830796
    - type: nauc_mrr_at_1000_diff1
      value: 76.26428836976245
    - type: nauc_mrr_at_1000_max
      value: 35.41847367373575
    - type: nauc_mrr_at_1000_std
      value: -33.04639860831992
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---

<br><br>

<p align="center">
<img src="https://aeiljuispo.cloudimg.io/v7/https://cdn-uploads.huggingface.co/production/uploads/603763514de52ff951d89793/AFoybzd5lpBQXEBrQHuTt.png?w=200&h=200&f=face" alt="Finetuner logo: Finetuner helps you to create experiments in order to improve embeddings on search tasks. It accompanies you to deliver the last mile of performance-tuning for neural search applications." width="150px">
</p>


<p align="center">
<b>The embedding model trained by <a href="https://jina.ai/"><b>Jina AI</b></a>.</b>
</p>

<p align="center">
<b>jina-embeddings-v3: Multilingual Embeddings With Task LoRA</b>
</p>

## Quick Start

[Blog](https://jina.ai/news/jina-embeddings-v3-a-frontier-multilingual-embedding-model/#parameter-dimensions) | [Azure](https://azuremarketplace.microsoft.com/en-us/marketplace/apps/jinaai.jina-embeddings-v3) | [AWS SageMaker](https://aws.amazon.com/marketplace/pp/prodview-kdi3xkt62lo32) | [API](https://jina.ai/embeddings)


## Intended Usage & Model Info


`jina-embeddings-v3` is a **multilingual multi-task text embedding model** designed for a variety of NLP applications.
Based on the [Jina-XLM-RoBERTa architecture](https://huggingface.co/jinaai/xlm-roberta-flash-implementation), 
this model supports Rotary Position Embeddings to handle long input sequences up to **8192 tokens**.
Additionally, it features 5 LoRA adapters to generate task-specific embeddings efficiently.

### Key Features:
- **Extended Sequence Length:** Supports up to 8192 tokens with RoPE.
- **Task-Specific Embedding:** Customize embeddings through the `task` argument with the following options:
    - `retrieval.query`: Used for query embeddings in asymmetric retrieval tasks
    - `retrieval.passage`: Used for passage embeddings in asymmetric retrieval tasks
    - `separation`: Used for embeddings in clustering and re-ranking applications
    - `classification`: Used for embeddings in classification tasks
    - `text-matching`: Used for embeddings in tasks that quantify similarity between two texts, such as STS or symmetric retrieval tasks
- **Matryoshka Embeddings**: Supports flexible embedding sizes (`32, 64, 128, 256, 512, 768, 1024`), allowing for truncating embeddings to fit your application.

### Supported Languages:
While the foundation model supports 100 languages, we've focused our tuning efforts on the following 30 languages: 
**Arabic, Bengali, Chinese, Danish, Dutch, English, Finnish, French, Georgian, German, Greek, 
Hindi, Indonesian, Italian, Japanese, Korean, Latvian, Norwegian, Polish, Portuguese, Romanian, 
Russian, Slovak, Spanish, Swedish, Thai, Turkish, Ukrainian, Urdu,** and **Vietnamese.**

## Usage

**<details><summary>Apply mean pooling when integrating the model.</summary>**
<p>

### Why Use Mean Pooling?

Mean pooling takes all token embeddings from the model's output and averages them at the sentence or paragraph level. 
This approach has been shown to produce high-quality sentence embeddings.

We provide an `encode` function that handles this for you automatically.

However, if you're working with the model directly, outside of the `encode` function, 
you'll need to apply mean pooling manually. Here's how you can do it:


```python
import torch
import torch.nn.functional as F
from transformers import AutoTokenizer, AutoModel


def mean_pooling(model_output, attention_mask):
    token_embeddings = model_output[0]
    input_mask_expanded = (
        attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
    )
    return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(
        input_mask_expanded.sum(1), min=1e-9
    )


sentences = ["How is the weather today?", "What is the current weather like today?"]

tokenizer = AutoTokenizer.from_pretrained("jinaai/jina-embeddings-v3")
model = AutoModel.from_pretrained("jinaai/jina-embeddings-v3", trust_remote_code=True)

encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors="pt")
task = 'retrieval.query'
task_id = model._adaptation_map[task]
adapter_mask = torch.full((len(sentences),), task_id, dtype=torch.int32)
with torch.no_grad():
    model_output = model(**encoded_input, adapter_mask=adapter_mask)

embeddings = mean_pooling(model_output, encoded_input["attention_mask"])
embeddings = F.normalize(embeddings, p=2, dim=1)

```

</p>
</details>

The easiest way to start using `jina-embeddings-v3` is with the [Jina Embedding API](https://jina.ai/embeddings/).

Alternatively, you can use `jina-embeddings-v3` directly via Transformers package:
```bash
!pip install transformers torch einops
!pip install 'numpy<2'
```
If you run it on a GPU that support [FlashAttention-2](https://github.com/Dao-AILab/flash-attention). By 2024.9.12, it supports Ampere, Ada, or Hopper GPUs (e.g., A100, RTX 3090, RTX 4090, H100),

```bash
!pip install flash-attn --no-build-isolation
```

```python
from transformers import AutoModel

# Initialize the model
model = AutoModel.from_pretrained("jinaai/jina-embeddings-v3", trust_remote_code=True)

texts = [
    "Follow the white rabbit.",  # English
    "Sigue al conejo blanco.",  # Spanish
    "Suis le lapin blanc.",  # French
    "跟着白兔走。",  # Chinese
    "اتبع الأرنب الأبيض.",  # Arabic
    "Folge dem weißen Kaninchen.",  # German
]

# When calling the `encode` function, you can choose a `task` based on the use case:
# 'retrieval.query', 'retrieval.passage', 'separation', 'classification', 'text-matching'
# Alternatively, you can choose not to pass a `task`, and no specific LoRA adapter will be used.
embeddings = model.encode(texts, task="text-matching")

# Compute similarities
print(embeddings[0] @ embeddings[1].T)
```

By default, the model supports a maximum sequence length of 8192 tokens. 
However, if you want to truncate your input texts to a shorter length, you can pass the `max_length` parameter to the `encode` function:
```python
embeddings = model.encode(["Very long ... document"], max_length=2048)

```

In case you want to use **Matryoshka embeddings** and switch to a different dimension, 
you can adjust it by passing the `truncate_dim` parameter to the `encode` function:
```python
embeddings = model.encode(['Sample text'], truncate_dim=256)
```


The latest version (3.1.0) of [SentenceTransformers](https://github.com/UKPLab/sentence-transformers) also supports `jina-embeddings-v3`:

```bash
!pip install -U sentence-transformers
```

```python
from sentence_transformers import SentenceTransformer

model = SentenceTransformer("jinaai/jina-embeddings-v3", trust_remote_code=True)

task = "retrieval.query"
embeddings = model.encode(
    ["What is the weather like in Berlin today?"],
    task=task,
    prompt_name=task,
)
```

You can fine-tune `jina-embeddings-v3` using [SentenceTransformerTrainer](https://sbert.net/docs/package_reference/sentence_transformer/trainer.html). 
To fine-tune for a specific task, you should set the task before passing the model to the ST Trainer, either during initialization:
```python
model = SentenceTransformer("jinaai/jina-embeddings-v3", trust_remote_code=True, model_kwargs={'default_task': 'classification'})
```
Or afterwards:
```python
model = SentenceTransformer("jinaai/jina-embeddings-v3", trust_remote_code=True)
model[0].default_task = 'classification'
```
This way you can fine-tune the LoRA adapter for the chosen task.

However, If you want to fine-tune the entire model, make sure the main parameters are set as trainable when loading the model:
```python
model = SentenceTransformer("jinaai/jina-embeddings-v3", trust_remote_code=True, model_kwargs={'lora_main_params_trainable': True})
```
This will allow fine-tuning the whole model instead of just the LoRA adapters.


**<details><summary>ONNX Inference.</summary>**
<p>

You can use ONNX for efficient inference with `jina-embeddings-v3`:
```python
import onnxruntime
import numpy as np
from transformers import AutoTokenizer, PretrainedConfig

# Load tokenizer and model config
tokenizer = AutoTokenizer.from_pretrained('jinaai/jina-embeddings-v3')
config = PretrainedConfig.from_pretrained('jinaai/jina-embeddings-v3')

# Tokenize input
input_text = tokenizer('sample text', return_tensors='np')

# ONNX session
model_path = 'jina-embeddings-v3/onnx/model.onnx'
session = onnxruntime.InferenceSession(model_path)

# Prepare inputs for ONNX model
task_type = 'text-matching'
task_id = np.array(config.lora_adaptations.index(task_type), dtype=np.int64)
inputs = {
    'input_ids': input_text['input_ids'],
    'attention_mask': input_text['attention_mask'],
    'task_id': task_id
}

# Run model
outputs = session.run(None, inputs)
```

</p>
</details>


## Contact

Join our [Discord community](https://discord.jina.ai) and chat with other community members about ideas.

## License

`jina-embeddings-v3` is listed on AWS & Azure. If you need to use it beyond those platforms or on-premises within your company, note that the models is licensed under CC BY-NC 4.0. For commercial usage inquiries, feel free to [contact us](https://jina.ai/contact-sales/).

## Citation

If you find `jina-embeddings-v3` useful in your research, please cite the following paper:

```bibtex
@misc{sturua2024jinaembeddingsv3multilingualembeddingstask,
      title={jina-embeddings-v3: Multilingual Embeddings With Task LoRA}, 
      author={Saba Sturua and Isabelle Mohr and Mohammad Kalim Akram and Michael Günther and Bo Wang and Markus Krimmel and Feng Wang and Georgios Mastrapas and Andreas Koukounas and Andreas Koukounas and Nan Wang and Han Xiao},
      year={2024},
      eprint={2409.10173},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2409.10173}, 
}

```
