README.md

metadata

pipeline_tag: sentence-similarity
tags:
  - sentence-transformers
  - feature-extraction
  - sentence-similarity
  - mteb
  - arctic
  - snowflake-arctic-embed
  - transformers.js
license: apache-2.0
language:
  - af
  - ar
  - az
  - be
  - bg
  - bn
  - ca
  - ceb
  - cs
  - cy
  - da
  - de
  - el
  - en
  - es
  - et
  - eu
  - fa
  - fi
  - fr
  - gl
  - gu
  - he
  - hi
  - hr
  - ht
  - hu
  - hy
  - id
  - is
  - it
  - ja
  - jv
  - ka
  - kk
  - km
  - kn
  - ko
  - ky
  - lo
  - lt
  - lv
  - mk
  - ml
  - mn
  - mr
  - ms
  - my
  - ne
  - nl
  - pa
  - pl
  - pt
  - qu
  - ro
  - ru
  - si
  - sk
  - sl
  - so
  - sq
  - sr
  - sv
  - sw
  - ta
  - te
  - th
  - tl
  - tr
  - uk
  - ur
  - vi
  - yo
  - zh
model-index:
  - name: snowflake-arctic-embed-m-v2.0
    results:
      - dataset:
          config: en-ext
          name: MTEB AmazonCounterfactualClassification (en-ext)
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
          split: test
          type: mteb/amazon_counterfactual
        metrics:
          - type: accuracy
            value: 66.6867
          - type: f1
            value: 55.0373
          - type: f1_weighted
            value: 73.07430000000001
          - type: ap
            value: 18.077399999999997
          - type: ap_weighted
            value: 18.077399999999997
          - type: main_score
            value: 66.6867
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB AmazonCounterfactualClassification (en)
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
          split: test
          type: mteb/amazon_counterfactual
        metrics:
          - type: accuracy
            value: 66.194
          - type: f1
            value: 60.854299999999995
          - type: f1_weighted
            value: 69.57339999999999
          - type: ap
            value: 30.279099999999996
          - type: ap_weighted
            value: 30.279099999999996
          - type: main_score
            value: 66.194
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB AmazonPolarityClassification (default)
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
          split: test
          type: mteb/amazon_polarity
        metrics:
          - type: accuracy
            value: 70.3589
          - type: f1
            value: 70.0409
          - type: f1_weighted
            value: 70.0409
          - type: ap
            value: 64.81949999999999
          - type: ap_weighted
            value: 64.81949999999999
          - type: main_score
            value: 70.3589
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB AmazonReviewsClassification (en)
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
          split: test
          type: mteb/amazon_reviews_multi
        metrics:
          - type: accuracy
            value: 33.766
          - type: f1
            value: 33.3656
          - type: f1_weighted
            value: 33.3656
          - type: main_score
            value: 33.766
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB ArguAna (default)
          revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
          split: test
          type: mteb/arguana
        metrics:
          - type: ndcg_at_1
            value: 33.144
          - type: ndcg_at_3
            value: 47.909
          - type: ndcg_at_5
            value: 52.932
          - type: ndcg_at_10
            value: 58.011
          - type: ndcg_at_20
            value: 60.168
          - type: ndcg_at_100
            value: 60.928000000000004
          - type: ndcg_at_1000
            value: 61.046
          - type: map_at_1
            value: 33.144
          - type: map_at_3
            value: 44.156
          - type: map_at_5
            value: 46.951
          - type: map_at_10
            value: 49.071999999999996
          - type: map_at_20
            value: 49.692
          - type: map_at_100
            value: 49.809
          - type: map_at_1000
            value: 49.815
          - type: recall_at_1
            value: 33.144
          - type: recall_at_3
            value: 58.819
          - type: recall_at_5
            value: 70.982
          - type: recall_at_10
            value: 86.558
          - type: recall_at_20
            value: 94.879
          - type: recall_at_100
            value: 98.791
          - type: recall_at_1000
            value: 99.644
          - type: precision_at_1
            value: 33.144
          - type: precision_at_3
            value: 19.606
          - type: precision_at_5
            value: 14.196
          - type: precision_at_10
            value: 8.656
          - type: precision_at_20
            value: 4.744000000000001
          - type: precision_at_100
            value: 0.988
          - type: precision_at_1000
            value: 0.1
          - type: mrr_at_1
            value: 33.4993
          - type: mrr_at_3
            value: 44.393100000000004
          - type: mrr_at_5
            value: 47.131299999999996
          - type: mrr_at_10
            value: 49.264599999999994
          - type: mrr_at_20
            value: 49.8707
          - type: mrr_at_100
            value: 49.987700000000004
          - type: mrr_at_1000
            value: 49.993700000000004
          - type: nauc_ndcg_at_1_max
            value: -10.8287
          - type: nauc_ndcg_at_1_std
            value: -17.1177
          - type: nauc_ndcg_at_1_diff1
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          - type: nauc_ndcg_at_3_max
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          - type: nauc_ndcg_at_5_max
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          - type: nauc_ndcg_at_5_std
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          - type: nauc_ndcg_at_5_diff1
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          - type: nauc_ndcg_at_10_max
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          - type: nauc_ndcg_at_10_std
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          - type: nauc_ndcg_at_10_diff1
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          - type: nauc_ndcg_at_20_max
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          - type: nauc_ndcg_at_20_std
            value: -14.688399999999998
          - type: nauc_ndcg_at_20_diff1
            value: 9.7605
          - type: nauc_ndcg_at_100_max
            value: -7.5599
          - type: nauc_ndcg_at_100_std
            value: -15.0565
          - type: nauc_ndcg_at_100_diff1
            value: 10.2688
          - type: nauc_ndcg_at_1000_max
            value: -7.675800000000001
          - type: nauc_ndcg_at_1000_std
            value: -15.223500000000001
          - type: nauc_ndcg_at_1000_diff1
            value: 10.32
          - type: nauc_map_at_1_max
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          - type: nauc_map_at_1_std
            value: -17.1177
          - type: nauc_map_at_1_diff1
            value: 14.4508
          - type: nauc_map_at_3_max
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          - type: nauc_map_at_3_std
            value: -16.6674
          - type: nauc_map_at_3_diff1
            value: 11.1004
          - type: nauc_map_at_5_max
            value: -8.1927
          - type: nauc_map_at_5_std
            value: -16.2275
          - type: nauc_map_at_5_diff1
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            value: -8.3855
          - type: nauc_map_at_10_std
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          - type: nauc_map_at_10_diff1
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          - type: nauc_map_at_20_max
            value: -8.277700000000001
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            value: -15.824
          - type: nauc_map_at_20_diff1
            value: 10.8494
          - type: nauc_map_at_100_max
            value: -8.3178
          - type: nauc_map_at_100_std
            value: -15.848300000000002
          - type: nauc_map_at_100_diff1
            value: 10.9384
          - type: nauc_map_at_1000_max
            value: -8.319799999999999
          - type: nauc_map_at_1000_std
            value: -15.8522
          - type: nauc_map_at_1000_diff1
            value: 10.9401
          - type: nauc_recall_at_1_max
            value: -10.8287
          - type: nauc_recall_at_1_std
            value: -17.1177
          - type: nauc_recall_at_1_diff1
            value: 14.4508
          - type: nauc_recall_at_3_max
            value: -5.0587
          - type: nauc_recall_at_3_std
            value: -16.730800000000002
          - type: nauc_recall_at_3_diff1
            value: 6.8079
          - type: nauc_recall_at_5_max
            value: -2.6783
          - type: nauc_recall_at_5_std
            value: -14.5046
          - type: nauc_recall_at_5_diff1
            value: 3.096
          - type: nauc_recall_at_10_max
            value: -1.5855000000000001
          - type: nauc_recall_at_10_std
            value: -8.2276
          - type: nauc_recall_at_10_diff1
            value: -6.1741
          - type: nauc_recall_at_20_max
            value: 15.754299999999999
          - type: nauc_recall_at_20_std
            value: 8.1974
          - type: nauc_recall_at_20_diff1
            value: -4.9207
          - type: nauc_recall_at_100_max
            value: 20.4574
          - type: nauc_recall_at_100_std
            value: 36.3741
          - type: nauc_recall_at_100_diff1
            value: -7.9483
          - type: nauc_recall_at_1000_max
            value: 21.6023
          - type: nauc_recall_at_1000_std
            value: 68.7296
          - type: nauc_recall_at_1000_diff1
            value: -24.9261
          - type: nauc_precision_at_1_max
            value: -10.8287
          - type: nauc_precision_at_1_std
            value: -17.1177
          - type: nauc_precision_at_1_diff1
            value: 14.4508
          - type: nauc_precision_at_3_max
            value: -5.0587
          - type: nauc_precision_at_3_std
            value: -16.730800000000002
          - type: nauc_precision_at_3_diff1
            value: 6.8079
          - type: nauc_precision_at_5_max
            value: -2.6783
          - type: nauc_precision_at_5_std
            value: -14.5046
          - type: nauc_precision_at_5_diff1
            value: 3.096
          - type: nauc_precision_at_10_max
            value: -1.5855000000000001
          - type: nauc_precision_at_10_std
            value: -8.2276
          - type: nauc_precision_at_10_diff1
            value: -6.1741
          - type: nauc_precision_at_20_max
            value: 15.754299999999999
          - type: nauc_precision_at_20_std
            value: 8.1974
          - type: nauc_precision_at_20_diff1
            value: -4.9207
          - type: nauc_precision_at_100_max
            value: 20.4574
          - type: nauc_precision_at_100_std
            value: 36.3741
          - type: nauc_precision_at_100_diff1
            value: -7.9483
          - type: nauc_precision_at_1000_max
            value: 21.6023
          - type: nauc_precision_at_1000_std
            value: 68.7296
          - type: nauc_precision_at_1000_diff1
            value: -24.9261
          - type: nauc_mrr_at_1_max
            value: -11.251999999999999
          - type: nauc_mrr_at_1_std
            value: -17.4386
          - type: nauc_mrr_at_1_diff1
            value: 13.414200000000001
          - type: nauc_mrr_at_3_max
            value: -9.7985
          - type: nauc_mrr_at_3_std
            value: -16.650000000000002
          - type: nauc_mrr_at_3_diff1
            value: 9.5099
          - type: nauc_mrr_at_5_max
            value: -9.064
          - type: nauc_mrr_at_5_std
            value: -16.4409
          - type: nauc_mrr_at_5_diff1
            value: 9.4773
          - type: nauc_mrr_at_10_max
            value: -9.310400000000001
          - type: nauc_mrr_at_10_std
            value: -16.0546
          - type: nauc_mrr_at_10_diff1
            value: 9.2528
          - type: nauc_mrr_at_20_max
            value: -9.223099999999999
          - type: nauc_mrr_at_20_std
            value: -16.0659
          - type: nauc_mrr_at_20_diff1
            value: 9.5259
          - type: nauc_mrr_at_100_max
            value: -9.2678
          - type: nauc_mrr_at_100_std
            value: -16.0911
          - type: nauc_mrr_at_100_diff1
            value: 9.608600000000001
          - type: nauc_mrr_at_1000_max
            value: -9.2699
          - type: nauc_mrr_at_1000_std
            value: -16.095100000000002
          - type: nauc_mrr_at_1000_diff1
            value: 9.6099
          - type: main_score
            value: 58.011
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB ArxivClusteringP2P (default)
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
          split: test
          type: mteb/arxiv-clustering-p2p
        metrics:
          - type: v_measure
            value: 44.684400000000004
          - type: v_measure_std
            value: 13.5064
          - type: main_score
            value: 44.684400000000004
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB ArxivClusteringS2S (default)
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
          split: test
          type: mteb/arxiv-clustering-s2s
        metrics:
          - type: v_measure
            value: 35.0503
          - type: v_measure_std
            value: 13.9543
          - type: main_score
            value: 35.0503
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB AskUbuntuDupQuestions (default)
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
          split: test
          type: mteb/askubuntudupquestions-reranking
        metrics:
          - type: map
            value: 60.648500000000006
          - type: mrr
            value: 74.528
          - type: nAUC_map_max
            value: 19.4239
          - type: nAUC_map_std
            value: 20.0729
          - type: nAUC_map_diff1
            value: 10.0382
          - type: nAUC_mrr_max
            value: 30.693199999999997
          - type: nAUC_mrr_std
            value: 27.1279
          - type: nAUC_mrr_diff1
            value: 23.0291
          - type: main_score
            value: 60.648500000000006
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB BIOSSES (default)
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
          split: test
          type: mteb/biosses-sts
        metrics:
          - type: pearson
            value: 89.5081
          - type: spearman
            value: 87.0568
          - type: cosine_pearson
            value: 89.5081
          - type: cosine_spearman
            value: 87.0568
          - type: manhattan_pearson
            value: 88.1247
          - type: manhattan_spearman
            value: 87.2556
          - type: euclidean_pearson
            value: 88.3266
          - type: euclidean_spearman
            value: 87.0568
          - type: main_score
            value: 87.0568
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB Banking77Classification (default)
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
          split: test
          type: mteb/banking77
        metrics:
          - type: accuracy
            value: 80.18180000000001
          - type: f1
            value: 79.5538
          - type: f1_weighted
            value: 79.5538
          - type: main_score
            value: 80.18180000000001
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB BiorxivClusteringP2P (default)
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
          split: test
          type: mteb/biorxiv-clustering-p2p
        metrics:
          - type: v_measure
            value: 36.0126
          - type: v_measure_std
            value: 0.47019999999999995
          - type: main_score
            value: 36.0126
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB BiorxivClusteringS2S (default)
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
          split: test
          type: mteb/biorxiv-clustering-s2s
        metrics:
          - type: v_measure
            value: 28.6331
          - type: v_measure_std
            value: 0.8607999999999999
          - type: main_score
            value: 28.6331
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB CQADupstackAndroidRetrieval (default)
          revision: f46a197baaae43b4f621051089b82a364682dfeb
          split: test
          type: mteb/cqadupstack-android
        metrics:
          - type: ndcg_at_1
            value: 45.207
          - type: ndcg_at_3
            value: 51.31400000000001
          - type: ndcg_at_5
            value: 54.093999999999994
          - type: ndcg_at_10
            value: 56.31
          - type: ndcg_at_20
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          - type: ndcg_at_100
            value: 61.307
          - type: ndcg_at_1000
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          - type: map_at_1
            value: 37.732
          - type: map_at_3
            value: 46.263
          - type: map_at_5
            value: 48.553000000000004
          - type: map_at_10
            value: 49.984
          - type: map_at_20
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          - type: map_at_100
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          - type: map_at_1000
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          - type: recall_at_1
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          - type: recall_at_3
            value: 53.736
          - type: recall_at_5
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          - type: recall_at_10
            value: 68.062
          - type: recall_at_20
            value: 75.149
          - type: recall_at_100
            value: 88.075
          - type: recall_at_1000
            value: 96.878
          - type: precision_at_1
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          - type: precision_at_3
            value: 24.368000000000002
          - type: precision_at_5
            value: 17.854
          - type: precision_at_10
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          - type: precision_at_20
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          - type: precision_at_100
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          - type: precision_at_1000
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          - type: mrr_at_1
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          - type: mrr_at_3
            value: 52.9804
          - type: mrr_at_5
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          - type: mrr_at_10
            value: 55.5713
          - type: mrr_at_20
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          - type: mrr_at_100
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          - type: mrr_at_1000
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          revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
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          revision: CQADupstackRetrieval_is_a_combined_dataset
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          type: CQADupstackRetrieval_is_a_combined_dataset
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          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
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          name: MTEB MassiveIntentClassification (en)
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          type: mteb/amazon_massive_intent
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          revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
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          type: mteb/nfcorpus
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      - dataset:
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          revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
          split: test
          type: mteb/sickr-sts
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          revision: a0d554a64d88156834ff5ae9920b964011b16384
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          type: mteb/sts12-sts
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          name: MTEB STS13 (default)
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
          split: test
          type: mteb/sts13-sts
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      - dataset:
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          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
          split: test
          type: mteb/sts14-sts
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      - dataset:
          config: default
          name: MTEB STS15 (default)
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
          split: test
          type: mteb/sts15-sts
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      - dataset:
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          name: MTEB STS16 (default)
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
          split: test
          type: mteb/sts16-sts
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        task:
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      - dataset:
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          name: MTEB STS17 (es-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
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            value: 67.9751
          - type: spearman
            value: 68.92099999999999
          - type: cosine_pearson
            value: 67.9751
          - type: cosine_spearman
            value: 68.92099999999999
          - type: manhattan_pearson
            value: 68.9355
          - type: manhattan_spearman
            value: 68.777
          - type: euclidean_pearson
            value: 69.11410000000001
          - type: euclidean_spearman
            value: 68.92099999999999
          - type: main_score
            value: 68.92099999999999
        task:
          type: STS
      - dataset:
          config: fr-en
          name: MTEB STS17 (fr-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: pearson
            value: 72.08449999999999
          - type: spearman
            value: 74.6931
          - type: cosine_pearson
            value: 72.08449999999999
          - type: cosine_spearman
            value: 74.6931
          - type: manhattan_pearson
            value: 73.52
          - type: manhattan_spearman
            value: 74.7097
          - type: euclidean_pearson
            value: 73.62180000000001
          - type: euclidean_spearman
            value: 74.6931
          - type: main_score
            value: 74.6931
        task:
          type: STS
      - dataset:
          config: en-en
          name: MTEB STS17 (en-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: pearson
            value: 80.528
          - type: spearman
            value: 84.10459999999999
          - type: cosine_pearson
            value: 80.528
          - type: cosine_spearman
            value: 84.10459999999999
          - type: manhattan_pearson
            value: 83.1537
          - type: manhattan_spearman
            value: 84.0952
          - type: euclidean_pearson
            value: 83.337
          - type: euclidean_spearman
            value: 84.10459999999999
          - type: main_score
            value: 84.10459999999999
        task:
          type: STS
      - dataset:
          config: en-tr
          name: MTEB STS17 (en-tr)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: pearson
            value: 49.641400000000004
          - type: spearman
            value: 48.9413
          - type: cosine_pearson
            value: 49.641400000000004
          - type: cosine_spearman
            value: 48.9413
          - type: manhattan_pearson
            value: 51.434000000000005
          - type: manhattan_spearman
            value: 49.1595
          - type: euclidean_pearson
            value: 50.867799999999995
          - type: euclidean_spearman
            value: 48.9413
          - type: main_score
            value: 48.9413
        task:
          type: STS
      - dataset:
          config: it-en
          name: MTEB STS17 (it-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: pearson
            value: 71.2577
          - type: spearman
            value: 73.82419999999999
          - type: cosine_pearson
            value: 71.2577
          - type: cosine_spearman
            value: 73.82419999999999
          - type: manhattan_pearson
            value: 71.9329
          - type: manhattan_spearman
            value: 73.4651
          - type: euclidean_pearson
            value: 72.2771
          - type: euclidean_spearman
            value: 73.82419999999999
          - type: main_score
            value: 73.82419999999999
        task:
          type: STS
      - dataset:
          config: nl-en
          name: MTEB STS17 (nl-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: pearson
            value: 64.1562
          - type: spearman
            value: 64.8766
          - type: cosine_pearson
            value: 64.1562
          - type: cosine_spearman
            value: 64.8766
          - type: manhattan_pearson
            value: 64.16579999999999
          - type: manhattan_spearman
            value: 64.1931
          - type: euclidean_pearson
            value: 64.6169
          - type: euclidean_spearman
            value: 64.8766
          - type: main_score
            value: 64.8766
        task:
          type: STS
      - dataset:
          config: en-ar
          name: MTEB STS17 (en-ar)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: pearson
            value: 42.257400000000004
          - type: spearman
            value: 43.2176
          - type: cosine_pearson
            value: 42.257400000000004
          - type: cosine_spearman
            value: 43.2176
          - type: manhattan_pearson
            value: 43.5359
          - type: manhattan_spearman
            value: 42.4143
          - type: euclidean_pearson
            value: 43.6717
          - type: euclidean_spearman
            value: 43.2176
          - type: main_score
            value: 43.2176
        task:
          type: STS
      - dataset:
          config: en-de
          name: MTEB STS17 (en-de)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: pearson
            value: 74.0088
          - type: spearman
            value: 75.8687
          - type: cosine_pearson
            value: 74.0088
          - type: cosine_spearman
            value: 75.8687
          - type: manhattan_pearson
            value: 74.8505
          - type: manhattan_spearman
            value: 75.6101
          - type: euclidean_pearson
            value: 75.1303
          - type: euclidean_spearman
            value: 75.8687
          - type: main_score
            value: 75.8687
        task:
          type: STS
      - dataset:
          config: zh-en
          name: MTEB STS22 (zh-en)
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
          split: test
          type: mteb/sts22-crosslingual-sts
        metrics:
          - type: pearson
            value: 68.0842
          - type: spearman
            value: 69.4346
          - type: cosine_pearson
            value: 68.0842
          - type: cosine_spearman
            value: 69.4346
          - type: manhattan_pearson
            value: 69.9982
          - type: manhattan_spearman
            value: 69.8952
          - type: euclidean_pearson
            value: 69.6375
          - type: euclidean_spearman
            value: 69.4346
          - type: main_score
            value: 69.4346
        task:
          type: STS
      - dataset:
          config: es-en
          name: MTEB STS22 (es-en)
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
          split: test
          type: mteb/sts22-crosslingual-sts
        metrics:
          - type: pearson
            value: 76.3695
          - type: spearman
            value: 78.88730000000001
          - type: cosine_pearson
            value: 76.3695
          - type: cosine_spearman
            value: 78.88730000000001
          - type: manhattan_pearson
            value: 79.0721
          - type: manhattan_spearman
            value: 79.1151
          - type: euclidean_pearson
            value: 78.783
          - type: euclidean_spearman
            value: 78.88730000000001
          - type: main_score
            value: 78.88730000000001
        task:
          type: STS
      - dataset:
          config: de-en
          name: MTEB STS22 (de-en)
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
          split: test
          type: mteb/sts22-crosslingual-sts
        metrics:
          - type: pearson
            value: 60.59139999999999
          - type: spearman
            value: 52.692099999999996
          - type: cosine_pearson
            value: 60.59139999999999
          - type: cosine_spearman
            value: 52.692099999999996
          - type: manhattan_pearson
            value: 64.66499999999999
          - type: manhattan_spearman
            value: 53.09009999999999
          - type: euclidean_pearson
            value: 64.5541
          - type: euclidean_spearman
            value: 52.692099999999996
          - type: main_score
            value: 52.692099999999996
        task:
          type: STS
      - dataset:
          config: pl-en
          name: MTEB STS22 (pl-en)
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
          split: test
          type: mteb/sts22-crosslingual-sts
        metrics:
          - type: pearson
            value: 77.8405
          - type: spearman
            value: 76.6188
          - type: cosine_pearson
            value: 77.8405
          - type: cosine_spearman
            value: 76.6188
          - type: manhattan_pearson
            value: 76.6598
          - type: manhattan_spearman
            value: 76.3583
          - type: euclidean_pearson
            value: 77.1442
          - type: euclidean_spearman
            value: 76.6188
          - type: main_score
            value: 76.6188
        task:
          type: STS
      - dataset:
          config: en
          name: MTEB STS22 (en)
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
          split: test
          type: mteb/sts22-crosslingual-sts
        metrics:
          - type: pearson
            value: 69.8017
          - type: spearman
            value: 68.7734
          - type: cosine_pearson
            value: 69.8017
          - type: cosine_spearman
            value: 68.7734
          - type: manhattan_pearson
            value: 70.6884
          - type: manhattan_spearman
            value: 68.2974
          - type: euclidean_pearson
            value: 70.7968
          - type: euclidean_spearman
            value: 68.7734
          - type: main_score
            value: 68.7734
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STSBenchmark (default)
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
          split: test
          type: mteb/stsbenchmark-sts
        metrics:
          - type: pearson
            value: 73.3293
          - type: spearman
            value: 76.00919999999999
          - type: cosine_pearson
            value: 73.3293
          - type: cosine_spearman
            value: 76.00919999999999
          - type: manhattan_pearson
            value: 75.0184
          - type: manhattan_spearman
            value: 75.8014
          - type: euclidean_pearson
            value: 75.2638
          - type: euclidean_spearman
            value: 76.00919999999999
          - type: main_score
            value: 76.00919999999999
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB SciDocsRR (default)
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
          split: test
          type: mteb/scidocs-reranking
        metrics:
          - type: map
            value: 77.3669
          - type: mrr
            value: 93.5985
          - type: nAUC_map_max
            value: 50.2355
          - type: nAUC_map_std
            value: 65.5401
          - type: nAUC_map_diff1
            value: 9.6333
          - type: nAUC_mrr_max
            value: 76.5201
          - type: nAUC_mrr_std
            value: 74.7401
          - type: nAUC_mrr_diff1
            value: 53.170899999999996
          - type: main_score
            value: 77.3669
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB SciFact (default)
          revision: 0228b52cf27578f30900b9e5271d331663a030d7
          split: test
          type: mteb/scifact
        metrics:
          - type: ndcg_at_1
            value: 61
          - type: ndcg_at_3
            value: 67.589
          - type: ndcg_at_5
            value: 68.948
          - type: ndcg_at_10
            value: 71.8
          - type: ndcg_at_20
            value: 72.595
          - type: ndcg_at_100
            value: 74.138
          - type: ndcg_at_1000
            value: 74.83800000000001
          - type: map_at_1
            value: 57.74399999999999
          - type: map_at_3
            value: 64.866
          - type: map_at_5
            value: 66.018
          - type: map_at_10
            value: 67.535
          - type: map_at_20
            value: 67.77
          - type: map_at_100
            value: 68.011
          - type: map_at_1000
            value: 68.042
          - type: recall_at_1
            value: 57.74399999999999
          - type: recall_at_3
            value: 71.906
          - type: recall_at_5
            value: 75.344
          - type: recall_at_10
            value: 83.2
          - type: recall_at_20
            value: 86.26700000000001
          - type: recall_at_100
            value: 94.333
          - type: recall_at_1000
            value: 99.667
          - type: precision_at_1
            value: 61
          - type: precision_at_3
            value: 26.111
          - type: precision_at_5
            value: 16.8
          - type: precision_at_10
            value: 9.5
          - type: precision_at_20
            value: 4.933
          - type: precision_at_100
            value: 1.073
          - type: precision_at_1000
            value: 0.11299999999999999
          - type: mrr_at_1
            value: 61
          - type: mrr_at_3
            value: 67.4444
          - type: mrr_at_5
            value: 68.0778
          - type: mrr_at_10
            value: 69.0483
          - type: mrr_at_20
            value: 69.2333
          - type: mrr_at_100
            value: 69.4403
          - type: mrr_at_1000
            value: 69.4708
          - type: nauc_ndcg_at_1_max
            value: 53.481500000000004
          - type: nauc_ndcg_at_1_std
            value: 8.227
          - type: nauc_ndcg_at_1_diff1
            value: 72.0771
          - type: nauc_ndcg_at_3_max
            value: 57.0147
          - type: nauc_ndcg_at_3_std
            value: 5.2435
          - type: nauc_ndcg_at_3_diff1
            value: 68.8841
          - type: nauc_ndcg_at_5_max
            value: 57.4675
          - type: nauc_ndcg_at_5_std
            value: 8.4709
          - type: nauc_ndcg_at_5_diff1
            value: 67.2977
          - type: nauc_ndcg_at_10_max
            value: 60.3957
          - type: nauc_ndcg_at_10_std
            value: 11.3174
          - type: nauc_ndcg_at_10_diff1
            value: 67.8332
          - type: nauc_ndcg_at_20_max
            value: 60.3607
          - type: nauc_ndcg_at_20_std
            value: 11.9948
          - type: nauc_ndcg_at_20_diff1
            value: 68.1122
          - type: nauc_ndcg_at_100_max
            value: 59.5293
          - type: nauc_ndcg_at_100_std
            value: 11.697799999999999
          - type: nauc_ndcg_at_100_diff1
            value: 68.453
          - type: nauc_ndcg_at_1000_max
            value: 58.8931
          - type: nauc_ndcg_at_1000_std
            value: 10.876199999999999
          - type: nauc_ndcg_at_1000_diff1
            value: 68.5746
          - type: nauc_map_at_1_max
            value: 49.762299999999996
          - type: nauc_map_at_1_std
            value: -0.2785
          - type: nauc_map_at_1_diff1
            value: 71.9072
          - type: nauc_map_at_3_max
            value: 54.108599999999996
          - type: nauc_map_at_3_std
            value: 2.0995
          - type: nauc_map_at_3_diff1
            value: 69.3459
          - type: nauc_map_at_5_max
            value: 55.257
          - type: nauc_map_at_5_std
            value: 5.5776
          - type: nauc_map_at_5_diff1
            value: 68.3314
          - type: nauc_map_at_10_max
            value: 57.1506
          - type: nauc_map_at_10_std
            value: 7.4561
          - type: nauc_map_at_10_diff1
            value: 68.8482
          - type: nauc_map_at_20_max
            value: 57.126200000000004
          - type: nauc_map_at_20_std
            value: 7.6833
          - type: nauc_map_at_20_diff1
            value: 68.9132
          - type: nauc_map_at_100_max
            value: 56.9874
          - type: nauc_map_at_100_std
            value: 7.7405
          - type: nauc_map_at_100_diff1
            value: 68.9371
          - type: nauc_map_at_1000_max
            value: 56.959199999999996
          - type: nauc_map_at_1000_std
            value: 7.709499999999999
          - type: nauc_map_at_1000_diff1
            value: 68.9444
          - type: nauc_recall_at_1_max
            value: 49.762299999999996
          - type: nauc_recall_at_1_std
            value: -0.2785
          - type: nauc_recall_at_1_diff1
            value: 71.9072
          - type: nauc_recall_at_3_max
            value: 58.22580000000001
          - type: nauc_recall_at_3_std
            value: 2.3135
          - type: nauc_recall_at_3_diff1
            value: 65.5868
          - type: nauc_recall_at_5_max
            value: 60.4096
          - type: nauc_recall_at_5_std
            value: 11.7662
          - type: nauc_recall_at_5_diff1
            value: 61.5815
          - type: nauc_recall_at_10_max
            value: 72.74629999999999
          - type: nauc_recall_at_10_std
            value: 22.148
          - type: nauc_recall_at_10_diff1
            value: 62.2401
          - type: nauc_recall_at_20_max
            value: 74.9625
          - type: nauc_recall_at_20_std
            value: 28.1358
          - type: nauc_recall_at_20_diff1
            value: 63.240700000000004
          - type: nauc_recall_at_100_max
            value: 79.15910000000001
          - type: nauc_recall_at_100_std
            value: 39.4162
          - type: nauc_recall_at_100_diff1
            value: 65.733
          - type: nauc_recall_at_1000_max
            value: 100
          - type: nauc_recall_at_1000_std
            value: 72.2222
          - type: nauc_recall_at_1000_diff1
            value: 72.2222
          - type: nauc_precision_at_1_max
            value: 53.481500000000004
          - type: nauc_precision_at_1_std
            value: 8.227
          - type: nauc_precision_at_1_diff1
            value: 72.0771
          - type: nauc_precision_at_3_max
            value: 55.675799999999995
          - type: nauc_precision_at_3_std
            value: 23.9615
          - type: nauc_precision_at_3_diff1
            value: 48.1199
          - type: nauc_precision_at_5_max
            value: 50.503299999999996
          - type: nauc_precision_at_5_std
            value: 36.9259
          - type: nauc_precision_at_5_diff1
            value: 31.769399999999997
          - type: nauc_precision_at_10_max
            value: 45.4878
          - type: nauc_precision_at_10_std
            value: 44.0469
          - type: nauc_precision_at_10_diff1
            value: 16.666900000000002
          - type: nauc_precision_at_20_max
            value: 40.2908
          - type: nauc_precision_at_20_std
            value: 47.330600000000004
          - type: nauc_precision_at_20_diff1
            value: 11.0043
          - type: nauc_precision_at_100_max
            value: 27.4643
          - type: nauc_precision_at_100_std
            value: 53.0014
          - type: nauc_precision_at_100_diff1
            value: -4.8238
          - type: nauc_precision_at_1000_max
            value: 15.755099999999999
          - type: nauc_precision_at_1000_std
            value: 56.634499999999996
          - type: nauc_precision_at_1000_diff1
            value: -21.124100000000002
          - type: nauc_mrr_at_1_max
            value: 53.481500000000004
          - type: nauc_mrr_at_1_std
            value: 8.227
          - type: nauc_mrr_at_1_diff1
            value: 72.0771
          - type: nauc_mrr_at_3_max
            value: 57.6662
          - type: nauc_mrr_at_3_std
            value: 9.2816
          - type: nauc_mrr_at_3_diff1
            value: 69.8276
          - type: nauc_mrr_at_5_max
            value: 57.6565
          - type: nauc_mrr_at_5_std
            value: 10.422099999999999
          - type: nauc_mrr_at_5_diff1
            value: 69.0964
          - type: nauc_mrr_at_10_max
            value: 58.000099999999996
          - type: nauc_mrr_at_10_std
            value: 10.957600000000001
          - type: nauc_mrr_at_10_diff1
            value: 69.0098
          - type: nauc_mrr_at_20_max
            value: 58.0066
          - type: nauc_mrr_at_20_std
            value: 11.0139
          - type: nauc_mrr_at_20_diff1
            value: 69.1278
          - type: nauc_mrr_at_100_max
            value: 57.9072
          - type: nauc_mrr_at_100_std
            value: 10.9621
          - type: nauc_mrr_at_100_diff1
            value: 69.1925
          - type: nauc_mrr_at_1000_max
            value: 57.87949999999999
          - type: nauc_mrr_at_1000_std
            value: 10.934199999999999
          - type: nauc_mrr_at_1000_diff1
            value: 69.2004
          - type: main_score
            value: 71.8
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB SprintDuplicateQuestions (default)
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
          split: test
          type: mteb/sprintduplicatequestions-pairclassification
        metrics:
          - type: similarity_accuracy
            value: 99.8248
          - type: similarity_accuracy_threshold
            value: 74.6155
          - type: similarity_f1
            value: 91.12780000000001
          - type: similarity_f1_threshold
            value: 74.2422
          - type: similarity_precision
            value: 91.3568
          - type: similarity_recall
            value: 90.9
          - type: similarity_ap
            value: 96.00319999999999
          - type: cosine_accuracy
            value: 99.8248
          - type: cosine_accuracy_threshold
            value: 74.6155
          - type: cosine_f1
            value: 91.12780000000001
          - type: cosine_f1_threshold
            value: 74.2422
          - type: cosine_precision
            value: 91.3568
          - type: cosine_recall
            value: 90.9
          - type: cosine_ap
            value: 96.00319999999999
          - type: manhattan_accuracy
            value: 99.8257
          - type: manhattan_accuracy_threshold
            value: 1574.1653
          - type: manhattan_f1
            value: 91.1531
          - type: manhattan_f1_threshold
            value: 1595.7924
          - type: manhattan_precision
            value: 90.6126
          - type: manhattan_recall
            value: 91.7
          - type: manhattan_ap
            value: 95.9848
          - type: euclidean_accuracy
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          revision: 815ca46b2622cec33ccafc3735d572c266efdb44
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          - type: nauc_mrr_at_10_max
            value: -31.7904
          - type: nauc_mrr_at_10_std
            value: -19.169900000000002
          - type: nauc_mrr_at_10_diff1
            value: 17.762700000000002
          - type: nauc_mrr_at_20_max
            value: -30.44
          - type: nauc_mrr_at_20_std
            value: -20.2867
          - type: nauc_mrr_at_20_diff1
            value: 18.895500000000002
          - type: nauc_mrr_at_100_max
            value: -30.5404
          - type: nauc_mrr_at_100_std
            value: -20.5699
          - type: nauc_mrr_at_100_diff1
            value: 18.7046
          - type: nauc_mrr_at_1000_max
            value: -30.5404
          - type: nauc_mrr_at_1000_std
            value: -20.5699
          - type: nauc_mrr_at_1000_diff1
            value: 18.7046
          - type: main_score
            value: 29.767
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB ToxicConversationsClassification (default)
          revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
          split: test
          type: mteb/toxic_conversations_50k
        metrics:
          - type: accuracy
            value: 64.8096
          - type: f1
            value: 49.844300000000004
          - type: f1_weighted
            value: 72.5251
          - type: ap
            value: 11.7519
          - type: ap_weighted
            value: 11.7519
          - type: main_score
            value: 64.8096
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB TweetSentimentExtractionClassification (default)
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
          split: test
          type: mteb/tweet_sentiment_extraction
        metrics:
          - type: accuracy
            value: 58.1692
          - type: f1
            value: 58.4408
          - type: f1_weighted
            value: 57.565599999999996
          - type: main_score
            value: 58.1692
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB TwentyNewsgroupsClustering (default)
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
          split: test
          type: mteb/twentynewsgroups-clustering
        metrics:
          - type: v_measure
            value: 39.293
          - type: v_measure_std
            value: 1.5684
          - type: main_score
            value: 39.293
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB TwitterSemEval2015 (default)
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
          split: test
          type: mteb/twittersemeval2015-pairclassification
        metrics:
          - type: similarity_accuracy
            value: 83.29260000000001
          - type: similarity_accuracy_threshold
            value: 78.2732
          - type: similarity_f1
            value: 60.656600000000005
          - type: similarity_f1_threshold
            value: 73.4961
          - type: similarity_precision
            value: 59.007
          - type: similarity_recall
            value: 62.4011
          - type: similarity_ap
            value: 64.7501
          - type: cosine_accuracy
            value: 83.29260000000001
          - type: cosine_accuracy_threshold
            value: 78.2732
          - type: cosine_f1
            value: 60.656600000000005
          - type: cosine_f1_threshold
            value: 73.4961
          - type: cosine_precision
            value: 59.007
          - type: cosine_recall
            value: 62.4011
          - type: cosine_ap
            value: 64.7501
          - type: manhattan_accuracy
            value: 83.2986
          - type: manhattan_accuracy_threshold
            value: 1476.7148
          - type: manhattan_f1
            value: 60.7459
          - type: manhattan_f1_threshold
            value: 1607.9180000000001
          - type: manhattan_precision
            value: 59.0581
          - type: manhattan_recall
            value: 62.53300000000001
          - type: manhattan_ap
            value: 64.76859999999999
          - type: euclidean_accuracy
            value: 83.29260000000001
          - type: euclidean_accuracy_threshold
            value: 65.9194
          - type: euclidean_f1
            value: 60.656600000000005
          - type: euclidean_f1_threshold
            value: 72.8065
          - type: euclidean_precision
            value: 59.007
          - type: euclidean_recall
            value: 62.4011
          - type: euclidean_ap
            value: 64.7501
          - type: dot_accuracy
            value: 83.29260000000001
          - type: dot_accuracy_threshold
            value: 78.2731
          - type: dot_f1
            value: 60.656600000000005
          - type: dot_f1_threshold
            value: 73.4961
          - type: dot_precision
            value: 59.007
          - type: dot_recall
            value: 62.4011
          - type: dot_ap
            value: 64.7501
          - type: max_accuracy
            value: 83.2986
          - type: max_f1
            value: 60.7459
          - type: max_precision
            value: 59.0581
          - type: max_recall
            value: 62.53300000000001
          - type: max_ap
            value: 64.76859999999999
          - type: main_score
            value: 64.76859999999999
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB TwitterURLCorpus (default)
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
          split: test
          type: mteb/twitterurlcorpus-pairclassification
        metrics:
          - type: similarity_accuracy
            value: 89.0247
          - type: similarity_accuracy_threshold
            value: 69.271
          - type: similarity_f1
            value: 78.24419999999999
          - type: similarity_f1_threshold
            value: 66.2183
          - type: similarity_precision
            value: 76.616
          - type: similarity_recall
            value: 79.943
          - type: similarity_ap
            value: 85.9494
          - type: cosine_accuracy
            value: 89.0247
          - type: cosine_accuracy_threshold
            value: 69.271
          - type: cosine_f1
            value: 78.24419999999999
          - type: cosine_f1_threshold
            value: 66.2183
          - type: cosine_precision
            value: 76.616
          - type: cosine_recall
            value: 79.943
          - type: cosine_ap
            value: 85.9494
          - type: manhattan_accuracy
            value: 89.0267
          - type: manhattan_accuracy_threshold
            value: 1750.3544000000002
          - type: manhattan_f1
            value: 78.2188
          - type: manhattan_f1_threshold
            value: 1837.7304
          - type: manhattan_precision
            value: 75.1472
          - type: manhattan_recall
            value: 81.5522
          - type: manhattan_ap
            value: 85.9496
          - type: euclidean_accuracy
            value: 89.0247
          - type: euclidean_accuracy_threshold
            value: 78.3951
          - type: euclidean_f1
            value: 78.24419999999999
          - type: euclidean_f1_threshold
            value: 82.197
          - type: euclidean_precision
            value: 76.616
          - type: euclidean_recall
            value: 79.943
          - type: euclidean_ap
            value: 85.9494
          - type: dot_accuracy
            value: 89.0247
          - type: dot_accuracy_threshold
            value: 69.271
          - type: dot_f1
            value: 78.24419999999999
          - type: dot_f1_threshold
            value: 66.2183
          - type: dot_precision
            value: 76.616
          - type: dot_recall
            value: 79.943
          - type: dot_ap
            value: 85.9494
          - type: max_accuracy
            value: 89.0267
          - type: max_f1
            value: 78.24419999999999
          - type: max_precision
            value: 76.616
          - type: max_recall
            value: 81.5522
          - type: max_ap
            value: 85.9496
          - type: main_score
            value: 85.9496
        task:
          type: PairClassification

A modified version of Snowflake/snowflake-arctic-embed-m-v2.0, without xformers, so it works on CPU.

from sentence_transformers import SentenceTransformer
import torch

device = torch.device("cpu")
model = SentenceTransformer("cnmoro/snowflake-arctic-embed-m-v2.0-cpu", device=device, trust_remote_code=True)