README.md

metadata

pipeline_tag: sentence-similarity
tags:
  - sentence-transformers
  - feature-extraction
  - sentence-similarity
  - mteb
  - arctic
  - snowflake-arctic-embed
  - transformers.js
  - mlx
license: apache-2.0
language:
  - af
  - ar
  - az
  - be
  - bg
  - bn
  - ca
  - ceb
  - cs
  - cy
  - da
  - de
  - el
  - en
  - es
  - et
  - eu
  - fa
  - fi
  - fr
  - gl
  - gu
  - he
  - hi
  - hr
  - ht
  - hu
  - hy
  - id
  - is
  - it
  - ja
  - jv
  - ka
  - kk
  - km
  - kn
  - ko
  - ky
  - lo
  - lt
  - lv
  - mk
  - ml
  - mn
  - mr
  - ms
  - my
  - ne
  - nl
  - pa
  - pl
  - pt
  - qu
  - ro
  - ru
  - si
  - sk
  - sl
  - so
  - sq
  - sr
  - sv
  - sw
  - ta
  - te
  - th
  - tl
  - tr
  - uk
  - ur
  - vi
  - yo
  - zh
model-index:
  - name: snowflake-arctic-embed-l-v2.0
    results:
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonCounterfactualClassification (en-ext)
          type: mteb/amazon_counterfactual
          config: en-ext
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 67.039
          - type: f1
            value: 55.1806
          - type: f1_weighted
            value: 73.41149999999999
          - type: ap
            value: 17.9914
          - type: ap_weighted
            value: 17.9914
          - type: main_score
            value: 67.039
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonCounterfactualClassification (en)
          type: mteb/amazon_counterfactual
          config: en
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 65.59700000000001
          - type: f1
            value: 60.244299999999996
          - type: f1_weighted
            value: 68.9975
          - type: ap
            value: 29.762100000000004
          - type: ap_weighted
            value: 29.762100000000004
          - type: main_score
            value: 65.59700000000001
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonPolarityClassification (default)
          type: mteb/amazon_polarity
          config: default
          split: test
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
        metrics:
          - type: accuracy
            value: 74.2565
          - type: f1
            value: 74.0291
          - type: f1_weighted
            value: 74.0291
          - type: ap
            value: 68.7595
          - type: ap_weighted
            value: 68.7595
          - type: main_score
            value: 74.2565
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonReviewsClassification (en)
          type: mteb/amazon_reviews_multi
          config: en
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 34.946
          - type: f1
            value: 34.2853
          - type: f1_weighted
            value: 34.2853
          - type: main_score
            value: 34.946
      - task:
          type: Retrieval
        dataset:
          name: MTEB ArguAna (default)
          type: mteb/arguana
          config: default
          split: test
          revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
        metrics:
          - type: ndcg_at_1
            value: 33.286
          - type: ndcg_at_3
            value: 49.051
          - type: ndcg_at_5
            value: 54.107000000000006
          - type: ndcg_at_10
            value: 59.146
          - type: ndcg_at_20
            value: 60.897999999999996
          - type: ndcg_at_100
            value: 61.78399999999999
          - type: ndcg_at_1000
            value: 61.845000000000006
          - type: map_at_1
            value: 33.286
          - type: map_at_3
            value: 45.14
          - type: map_at_5
            value: 47.939
          - type: map_at_10
            value: 50.046
          - type: map_at_20
            value: 50.56
          - type: map_at_100
            value: 50.708
          - type: map_at_1000
            value: 50.712
          - type: recall_at_1
            value: 33.286
          - type: recall_at_3
            value: 60.38400000000001
          - type: recall_at_5
            value: 72.688
          - type: recall_at_10
            value: 88.122
          - type: recall_at_20
            value: 94.808
          - type: recall_at_100
            value: 99.21799999999999
          - type: recall_at_1000
            value: 99.644
          - type: precision_at_1
            value: 33.286
          - type: precision_at_3
            value: 20.128
          - type: precision_at_5
            value: 14.538
          - type: precision_at_10
            value: 8.812000000000001
          - type: precision_at_20
            value: 4.74
          - type: precision_at_100
            value: 0.992
          - type: precision_at_1000
            value: 0.1
          - type: mrr_at_1
            value: 33.926
          - type: mrr_at_3
            value: 45.3414
          - type: mrr_at_5
            value: 48.1828
          - type: mrr_at_10
            value: 50.270700000000005
          - type: mrr_at_20
            value: 50.7844
          - type: mrr_at_100
            value: 50.9259
          - type: mrr_at_1000
            value: 50.9294
          - type: nauc_ndcg_at_1_max
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          - type: nauc_ndcg_at_1_std
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          - type: nauc_ndcg_at_100_max
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          - type: nauc_ndcg_at_100_diff1
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          - type: nauc_ndcg_at_1000_max
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          - type: nauc_map_at_1_max
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          - type: nauc_map_at_1_std
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          - type: nauc_map_at_1_diff1
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          - type: nauc_map_at_3_max
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          - type: nauc_map_at_3_std
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          - type: nauc_map_at_3_diff1
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          - type: nauc_map_at_5_max
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          - type: nauc_map_at_5_std
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            value: -15.8624
          - type: nauc_map_at_100_diff1
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          - type: nauc_map_at_1000_max
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          - type: nauc_map_at_1000_std
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          - type: nauc_map_at_1000_diff1
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          - type: nauc_recall_at_1_max
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          - type: nauc_recall_at_1_std
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          - type: nauc_recall_at_1_diff1
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          - type: nauc_recall_at_3_max
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          - type: nauc_recall_at_3_std
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          - type: nauc_recall_at_3_diff1
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          - type: nauc_recall_at_5_max
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          - type: nauc_recall_at_5_std
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          - type: nauc_recall_at_10_max
            value: -2.8548
          - type: nauc_recall_at_10_std
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          - type: nauc_recall_at_10_diff1
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          - type: nauc_recall_at_20_max
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          - type: nauc_recall_at_20_std
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          - type: nauc_recall_at_20_diff1
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          - type: nauc_recall_at_100_max
            value: 44.0173
          - type: nauc_recall_at_100_std
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          - type: nauc_recall_at_100_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_precision_at_1_max
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          - type: nauc_precision_at_1_std
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          - type: nauc_precision_at_3_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_precision_at_10_max
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          - type: nauc_precision_at_10_std
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          - type: nauc_precision_at_10_diff1
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          - type: nauc_precision_at_20_max
            value: 14.2043
          - type: nauc_precision_at_20_std
            value: 2.1298999999999997
          - type: nauc_precision_at_20_diff1
            value: -1.9900000000000002
          - type: nauc_precision_at_100_max
            value: 44.0173
          - type: nauc_precision_at_100_std
            value: 42.131800000000005
          - type: nauc_precision_at_100_diff1
            value: 29.9983
          - type: nauc_precision_at_1000_max
            value: 25.9434
          - type: nauc_precision_at_1000_std
            value: 53.9252
          - type: nauc_precision_at_1000_diff1
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          - type: nauc_mrr_at_1_max
            value: -9.833
          - type: nauc_mrr_at_1_std
            value: -14.8351
          - type: nauc_mrr_at_1_diff1
            value: 16.7604
          - type: nauc_mrr_at_3_max
            value: -9.0116
          - type: nauc_mrr_at_3_std
            value: -16.296
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            value: 14.178199999999999
          - type: nauc_mrr_at_5_max
            value: -8.308300000000001
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            value: -15.751999999999999
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            value: 13.306299999999998
          - type: nauc_mrr_at_10_max
            value: -8.7962
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            value: -15.688099999999999
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            value: 13.2589
          - type: nauc_mrr_at_20_max
            value: -8.6773
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            value: -15.479499999999998
          - type: nauc_mrr_at_20_diff1
            value: 13.354
          - type: nauc_mrr_at_100_max
            value: -8.7533
          - type: nauc_mrr_at_100_std
            value: -15.553600000000001
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            value: 13.4796
          - type: nauc_mrr_at_1000_max
            value: -8.7608
          - type: nauc_mrr_at_1000_std
            value: -15.5582
          - type: nauc_mrr_at_1000_diff1
            value: 13.4748
          - type: main_score
            value: 59.146
      - task:
          type: Clustering
        dataset:
          name: MTEB ArxivClusteringP2P (default)
          type: mteb/arxiv-clustering-p2p
          config: default
          split: test
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
        metrics:
          - type: v_measure
            value: 43.9715
          - type: v_measure_std
            value: 13.4325
          - type: main_score
            value: 43.9715
      - task:
          type: Clustering
        dataset:
          name: MTEB ArxivClusteringS2S (default)
          type: mteb/arxiv-clustering-s2s
          config: default
          split: test
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
        metrics:
          - type: v_measure
            value: 34.775800000000004
          - type: v_measure_std
            value: 13.922799999999999
          - type: main_score
            value: 34.775800000000004
      - task:
          type: Reranking
        dataset:
          name: MTEB AskUbuntuDupQuestions (default)
          type: mteb/askubuntudupquestions-reranking
          config: default
          split: test
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
        metrics:
          - type: map
            value: 63.3521
          - type: mrr
            value: 77.5965
          - type: nAUC_map_max
            value: 21.2353
          - type: nAUC_map_std
            value: 17.002100000000002
          - type: nAUC_map_diff1
            value: 3.8135000000000003
          - type: nAUC_mrr_max
            value: 35.058299999999996
          - type: nAUC_mrr_std
            value: 20.432
          - type: nAUC_mrr_diff1
            value: 9.2584
          - type: main_score
            value: 63.3521
      - task:
          type: STS
        dataset:
          name: MTEB BIOSSES (default)
          type: mteb/biosses-sts
          config: default
          split: test
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
        metrics:
          - type: pearson
            value: 89.8072
          - type: spearman
            value: 87.2875
          - type: cosine_pearson
            value: 89.8072
          - type: cosine_spearman
            value: 87.2875
          - type: manhattan_pearson
            value: 87.9173
          - type: manhattan_spearman
            value: 86.7327
          - type: euclidean_pearson
            value: 88.21600000000001
          - type: euclidean_spearman
            value: 87.2875
          - type: main_score
            value: 87.2875
      - task:
          type: Classification
        dataset:
          name: MTEB Banking77Classification (default)
          type: mteb/banking77
          config: default
          split: test
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
        metrics:
          - type: accuracy
            value: 81.8149
          - type: f1
            value: 81.2226
          - type: f1_weighted
            value: 81.2226
          - type: main_score
            value: 81.8149
      - task:
          type: Clustering
        dataset:
          name: MTEB BiorxivClusteringP2P (default)
          type: mteb/biorxiv-clustering-p2p
          config: default
          split: test
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
        metrics:
          - type: v_measure
            value: 35.0927
          - type: v_measure_std
            value: 0.7048
          - type: main_score
            value: 35.0927
      - task:
          type: Clustering
        dataset:
          name: MTEB BiorxivClusteringS2S (default)
          type: mteb/biorxiv-clustering-s2s
          config: default
          split: test
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
        metrics:
          - type: v_measure
            value: 30.220999999999997
          - type: v_measure_std
            value: 1.107
          - type: main_score
            value: 30.220999999999997
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackAndroidRetrieval (default)
          type: mteb/cqadupstack-android
          config: default
          split: test
          revision: f46a197baaae43b4f621051089b82a364682dfeb
        metrics:
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          - type: ndcg_at_5
            value: 52.88699999999999
          - type: ndcg_at_10
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          - type: ndcg_at_20
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          - type: ndcg_at_100
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          - type: ndcg_at_1000
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          - type: map_at_1
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          - 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_5
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          - type: recall_at_10
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          - type: recall_at_1000
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          - type: precision_at_1000
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          revision: CQADupstackRetrieval_is_a_combined_dataset
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          type: mteb/msmarco
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        dataset:
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          type: mteb/mtop_domain
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          split: test
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      - task:
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          type: mteb/mtop_intent
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          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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      - task:
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          type: mteb/amazon_massive_intent
          config: en
          split: test
          revision: 4672e20407010da34463acc759c162ca9734bca6
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      - task:
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          type: mteb/amazon_massive_scenario
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          split: test
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
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      - task:
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          type: mteb/medrxiv-clustering-p2p
          config: default
          split: test
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      - task:
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          type: mteb/medrxiv-clustering-s2s
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      - task:
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          type: mteb/mind_small
          config: default
          split: test
          revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
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      - task:
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          type: mteb/nfcorpus
          config: default
          split: test
          revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
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      - task:
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          type: mteb/sickr-sts
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          type: mteb/sts12-sts
          config: default
          split: test
          revision: a0d554a64d88156834ff5ae9920b964011b16384
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      - task:
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          type: mteb/sts13-sts
          config: default
          split: test
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
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      - task:
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          type: mteb/sts14-sts
          config: default
          split: test
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
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      - task:
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          type: mteb/sts15-sts
          config: default
          split: test
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
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      - task:
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          type: mteb/sts16-sts
          config: default
          split: test
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
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      - task:
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        dataset:
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          type: mteb/sts17-crosslingual-sts
          config: en-en
          split: test
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
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          - type: euclidean_spearman
            value: 84.5436
          - type: main_score
            value: 84.5436
      - task:
          type: STS
        dataset:
          name: MTEB STS17 (en-tr)
          type: mteb/sts17-crosslingual-sts
          config: en-tr
          split: test
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
        metrics:
          - type: pearson
            value: 62.0001
          - type: spearman
            value: 63.631099999999996
          - type: cosine_pearson
            value: 62.0001
          - type: cosine_spearman
            value: 63.631099999999996
          - type: manhattan_pearson
            value: 62.239599999999996
          - type: manhattan_spearman
            value: 62.892199999999995
          - type: euclidean_pearson
            value: 62.9809
          - type: euclidean_spearman
            value: 63.631099999999996
          - type: main_score
            value: 63.631099999999996
      - task:
          type: STS
        dataset:
          name: MTEB STS17 (it-en)
          type: mteb/sts17-crosslingual-sts
          config: it-en
          split: test
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
        metrics:
          - type: pearson
            value: 75.1556
          - type: spearman
            value: 76.8807
          - type: cosine_pearson
            value: 75.1556
          - type: cosine_spearman
            value: 76.8807
          - type: manhattan_pearson
            value: 76.2428
          - type: manhattan_spearman
            value: 76.8101
          - type: euclidean_pearson
            value: 76.107
          - type: euclidean_spearman
            value: 76.8807
          - type: main_score
            value: 76.8807
      - task:
          type: STS
        dataset:
          name: MTEB STS17 (es-en)
          type: mteb/sts17-crosslingual-sts
          config: es-en
          split: test
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
        metrics:
          - type: pearson
            value: 69.85719999999999
          - type: spearman
            value: 71.0489
          - type: cosine_pearson
            value: 69.85719999999999
          - type: cosine_spearman
            value: 71.0489
          - type: manhattan_pearson
            value: 71.08449999999999
          - type: manhattan_spearman
            value: 71.0051
          - type: euclidean_pearson
            value: 71.19760000000001
          - type: euclidean_spearman
            value: 71.0489
          - type: main_score
            value: 71.0489
      - task:
          type: STS
        dataset:
          name: MTEB STS17 (nl-en)
          type: mteb/sts17-crosslingual-sts
          config: nl-en
          split: test
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
        metrics:
          - type: pearson
            value: 76.1131
          - type: spearman
            value: 78.2714
          - type: cosine_pearson
            value: 76.1131
          - type: cosine_spearman
            value: 78.2714
          - type: manhattan_pearson
            value: 76.70270000000001
          - type: manhattan_spearman
            value: 77.7803
          - type: euclidean_pearson
            value: 77.14269999999999
          - type: euclidean_spearman
            value: 78.2714
          - type: main_score
            value: 78.2714
      - task:
          type: STS
        dataset:
          name: MTEB STS17 (fr-en)
          type: mteb/sts17-crosslingual-sts
          config: fr-en
          split: test
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
        metrics:
          - type: pearson
            value: 74.49719999999999
          - type: spearman
            value: 76.2747
          - type: cosine_pearson
            value: 74.49719999999999
          - type: cosine_spearman
            value: 76.2747
          - type: manhattan_pearson
            value: 75.071
          - type: manhattan_spearman
            value: 75.8969
          - type: euclidean_pearson
            value: 75.289
          - type: euclidean_spearman
            value: 76.2747
          - type: main_score
            value: 76.2747
      - task:
          type: STS
        dataset:
          name: MTEB STS17 (en-de)
          type: mteb/sts17-crosslingual-sts
          config: en-de
          split: test
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
        metrics:
          - type: pearson
            value: 76.7073
          - type: spearman
            value: 79.3107
          - type: cosine_pearson
            value: 76.7073
          - type: cosine_spearman
            value: 79.3107
          - type: manhattan_pearson
            value: 77.9578
          - type: manhattan_spearman
            value: 79.3195
          - type: euclidean_pearson
            value: 77.7386
          - type: euclidean_spearman
            value: 79.3107
          - type: main_score
            value: 79.3107
      - task:
          type: STS
        dataset:
          name: MTEB STS17 (en-ar)
          type: mteb/sts17-crosslingual-sts
          config: en-ar
          split: test
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
        metrics:
          - type: pearson
            value: 60.5826
          - type: spearman
            value: 61.0502
          - type: cosine_pearson
            value: 60.5826
          - type: cosine_spearman
            value: 61.0502
          - type: manhattan_pearson
            value: 61.202
          - type: manhattan_spearman
            value: 61.2039
          - type: euclidean_pearson
            value: 61.1915
          - type: euclidean_spearman
            value: 61.0502
          - type: main_score
            value: 61.0502
      - task:
          type: STS
        dataset:
          name: MTEB STS22 (en)
          type: mteb/sts22-crosslingual-sts
          config: en
          split: test
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
        metrics:
          - type: pearson
            value: 69.2521
          - type: spearman
            value: 68.06219999999999
          - type: cosine_pearson
            value: 69.2521
          - type: cosine_spearman
            value: 68.06219999999999
          - type: manhattan_pearson
            value: 70.5115
          - type: manhattan_spearman
            value: 67.8705
          - type: euclidean_pearson
            value: 70.68480000000001
          - type: euclidean_spearman
            value: 68.06219999999999
          - type: main_score
            value: 68.06219999999999
      - task:
          type: STS
        dataset:
          name: MTEB STS22 (pl-en)
          type: mteb/sts22-crosslingual-sts
          config: pl-en
          split: test
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
        metrics:
          - type: pearson
            value: 77.97500000000001
          - type: spearman
            value: 76.848
          - type: cosine_pearson
            value: 77.97500000000001
          - type: cosine_spearman
            value: 76.848
          - type: manhattan_pearson
            value: 76.4098
          - type: manhattan_spearman
            value: 76.6188
          - type: euclidean_pearson
            value: 77.17500000000001
          - type: euclidean_spearman
            value: 76.848
          - type: main_score
            value: 76.848
      - task:
          type: STS
        dataset:
          name: MTEB STS22 (zh-en)
          type: mteb/sts22-crosslingual-sts
          config: zh-en
          split: test
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
        metrics:
          - type: pearson
            value: 71.3604
          - type: spearman
            value: 70.7891
          - type: cosine_pearson
            value: 71.3604
          - type: cosine_spearman
            value: 70.7891
          - type: manhattan_pearson
            value: 73.0185
          - type: manhattan_spearman
            value: 70.79299999999999
          - type: euclidean_pearson
            value: 73.17620000000001
          - type: euclidean_spearman
            value: 70.7891
          - type: main_score
            value: 70.7891
      - task:
          type: STS
        dataset:
          name: MTEB STS22 (es-en)
          type: mteb/sts22-crosslingual-sts
          config: es-en
          split: test
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
        metrics:
          - type: pearson
            value: 77.58239999999999
          - type: spearman
            value: 78.5907
          - type: cosine_pearson
            value: 77.58239999999999
          - type: cosine_spearman
            value: 78.5907
          - type: manhattan_pearson
            value: 79.25720000000001
          - type: manhattan_spearman
            value: 78.6249
          - type: euclidean_pearson
            value: 79.3724
          - type: euclidean_spearman
            value: 78.5907
          - type: main_score
            value: 78.5907
      - task:
          type: STS
        dataset:
          name: MTEB STS22 (de-en)
          type: mteb/sts22-crosslingual-sts
          config: de-en
          split: test
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
        metrics:
          - type: pearson
            value: 63.324000000000005
          - type: spearman
            value: 55.1099
          - type: cosine_pearson
            value: 63.324000000000005
          - type: cosine_spearman
            value: 55.1099
          - type: manhattan_pearson
            value: 67.3128
          - type: manhattan_spearman
            value: 56.340199999999996
          - type: euclidean_pearson
            value: 67.12089999999999
          - type: euclidean_spearman
            value: 55.1099
          - type: main_score
            value: 55.1099
      - task:
          type: STS
        dataset:
          name: MTEB STSBenchmark (default)
          type: mteb/stsbenchmark-sts
          config: default
          split: test
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
        metrics:
          - type: pearson
            value: 78.02329999999999
          - type: spearman
            value: 79.1887
          - type: cosine_pearson
            value: 78.02329999999999
          - type: cosine_spearman
            value: 79.1887
          - type: manhattan_pearson
            value: 78.8951
          - type: manhattan_spearman
            value: 78.9444
          - type: euclidean_pearson
            value: 79.1499
          - type: euclidean_spearman
            value: 79.1888
          - type: main_score
            value: 79.1887
      - task:
          type: Reranking
        dataset:
          name: MTEB SciDocsRR (default)
          type: mteb/scidocs-reranking
          config: default
          split: test
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
        metrics:
          - type: map
            value: 78.7501
          - type: mrr
            value: 93.9748
          - type: nAUC_map_max
            value: 54.495599999999996
          - type: nAUC_map_std
            value: 70.0377
          - type: nAUC_map_diff1
            value: 6.0146999999999995
          - type: nAUC_mrr_max
            value: 81.1486
          - type: nAUC_mrr_std
            value: 78.3478
          - type: nAUC_mrr_diff1
            value: 50.7613
          - type: main_score
            value: 78.7501
      - task:
          type: Retrieval
        dataset:
          name: MTEB SciFact (default)
          type: mteb/scifact
          config: default
          split: test
          revision: 0228b52cf27578f30900b9e5271d331663a030d7
        metrics:
          - type: ndcg_at_1
            value: 58.667
          - type: ndcg_at_3
            value: 66.022
          - type: ndcg_at_5
            value: 68.508
          - type: ndcg_at_10
            value: 70.586
          - type: ndcg_at_20
            value: 71.714
          - type: ndcg_at_100
            value: 72.81
          - type: ndcg_at_1000
            value: 73.482
          - type: map_at_1
            value: 55.594
          - type: map_at_3
            value: 63.2
          - type: map_at_5
            value: 64.996
          - type: map_at_10
            value: 65.988
          - type: map_at_20
            value: 66.347
          - type: map_at_100
            value: 66.526
          - type: map_at_1000
            value: 66.547
          - type: recall_at_1
            value: 55.594
          - type: recall_at_3
            value: 71.22800000000001
          - type: recall_at_5
            value: 77.078
          - type: recall_at_10
            value: 83.172
          - type: recall_at_20
            value: 87.422
          - type: recall_at_100
            value: 93.167
          - type: recall_at_1000
            value: 98.667
          - type: precision_at_1
            value: 58.667
          - type: precision_at_3
            value: 25.778000000000002
          - type: precision_at_5
            value: 17.333000000000002
          - type: precision_at_10
            value: 9.433
          - type: precision_at_20
            value: 4.967
          - type: precision_at_100
            value: 1.06
          - type: precision_at_1000
            value: 0.11199999999999999
          - type: mrr_at_1
            value: 58.666700000000006
          - type: mrr_at_3
            value: 65.3889
          - type: mrr_at_5
            value: 66.62219999999999
          - type: mrr_at_10
            value: 67.3364
          - type: mrr_at_20
            value: 67.6046
          - type: mrr_at_100
            value: 67.73320000000001
          - type: mrr_at_1000
            value: 67.7526
          - type: nauc_ndcg_at_1_max
            value: 60.2511
          - type: nauc_ndcg_at_1_std
            value: 12.422
          - type: nauc_ndcg_at_1_diff1
            value: 74.4289
          - type: nauc_ndcg_at_3_max
            value: 60.2109
          - type: nauc_ndcg_at_3_std
            value: 11.0152
          - type: nauc_ndcg_at_3_diff1
            value: 71.0436
          - type: nauc_ndcg_at_5_max
            value: 62.690999999999995
          - type: nauc_ndcg_at_5_std
            value: 13.585700000000001
          - type: nauc_ndcg_at_5_diff1
            value: 70.4007
          - type: nauc_ndcg_at_10_max
            value: 62.740899999999996
          - type: nauc_ndcg_at_10_std
            value: 13.980400000000001
          - type: nauc_ndcg_at_10_diff1
            value: 70.0506
          - type: nauc_ndcg_at_20_max
            value: 62.271699999999996
          - type: nauc_ndcg_at_20_std
            value: 15.9756
          - type: nauc_ndcg_at_20_diff1
            value: 70.3237
          - type: nauc_ndcg_at_100_max
            value: 62.125
          - type: nauc_ndcg_at_100_std
            value: 15.5809
          - type: nauc_ndcg_at_100_diff1
            value: 70.4151
          - type: nauc_ndcg_at_1000_max
            value: 61.9259
          - type: nauc_ndcg_at_1000_std
            value: 15.3462
          - type: nauc_ndcg_at_1000_diff1
            value: 70.7346
          - type: nauc_map_at_1_max
            value: 53.6767
          - type: nauc_map_at_1_std
            value: 3.7751
          - type: nauc_map_at_1_diff1
            value: 74.60329999999999
          - type: nauc_map_at_3_max
            value: 57.0403
          - type: nauc_map_at_3_std
            value: 8.2272
          - type: nauc_map_at_3_diff1
            value: 71.7906
          - type: nauc_map_at_5_max
            value: 59.6713
          - type: nauc_map_at_5_std
            value: 10.8346
          - type: nauc_map_at_5_diff1
            value: 71.3356
          - type: nauc_map_at_10_max
            value: 60.0086
          - type: nauc_map_at_10_std
            value: 11.4394
          - type: nauc_map_at_10_diff1
            value: 71.14869999999999
          - type: nauc_map_at_20_max
            value: 59.940599999999996
          - type: nauc_map_at_20_std
            value: 12.0728
          - type: nauc_map_at_20_diff1
            value: 71.31
          - type: nauc_map_at_100_max
            value: 59.95589999999999
          - type: nauc_map_at_100_std
            value: 12.148299999999999
          - type: nauc_map_at_100_diff1
            value: 71.2142
          - type: nauc_map_at_1000_max
            value: 59.9486
          - type: nauc_map_at_1000_std
            value: 12.139
          - type: nauc_map_at_1000_diff1
            value: 71.2225
          - type: nauc_recall_at_1_max
            value: 53.6767
          - type: nauc_recall_at_1_std
            value: 3.7751
          - type: nauc_recall_at_1_diff1
            value: 74.60329999999999
          - type: nauc_recall_at_3_max
            value: 60.4078
          - type: nauc_recall_at_3_std
            value: 9.038300000000001
          - type: nauc_recall_at_3_diff1
            value: 67.60119999999999
          - type: nauc_recall_at_5_max
            value: 68.0179
          - type: nauc_recall_at_5_std
            value: 16.061600000000002
          - type: nauc_recall_at_5_diff1
            value: 65.54759999999999
          - type: nauc_recall_at_10_max
            value: 68.7372
          - type: nauc_recall_at_10_std
            value: 16.8637
          - type: nauc_recall_at_10_diff1
            value: 62.7613
          - type: nauc_recall_at_20_max
            value: 67.1403
          - type: nauc_recall_at_20_std
            value: 31.3919
          - type: nauc_recall_at_20_diff1
            value: 62.66929999999999
          - type: nauc_recall_at_100_max
            value: 68.6366
          - type: nauc_recall_at_100_std
            value: 32.4577
          - type: nauc_recall_at_100_diff1
            value: 64.52029999999999
          - type: nauc_recall_at_1000_max
            value: 70.7166
          - type: nauc_recall_at_1000_std
            value: 70.47149999999999
          - type: nauc_recall_at_1000_diff1
            value: 85.58590000000001
          - type: nauc_precision_at_1_max
            value: 60.2511
          - type: nauc_precision_at_1_std
            value: 12.422
          - type: nauc_precision_at_1_diff1
            value: 74.4289
          - type: nauc_precision_at_3_max
            value: 58.75280000000001
          - type: nauc_precision_at_3_std
            value: 27.605400000000003
          - type: nauc_precision_at_3_diff1
            value: 49.1523
          - type: nauc_precision_at_5_max
            value: 56.4694
          - type: nauc_precision_at_5_std
            value: 39.080799999999996
          - type: nauc_precision_at_5_diff1
            value: 28.8162
          - type: nauc_precision_at_10_max
            value: 48.8894
          - type: nauc_precision_at_10_std
            value: 43.8149
          - type: nauc_precision_at_10_diff1
            value: 15.0093
          - type: nauc_precision_at_20_max
            value: 41.4059
          - type: nauc_precision_at_20_std
            value: 50.7143
          - type: nauc_precision_at_20_diff1
            value: 8.3552
          - type: nauc_precision_at_100_max
            value: 33.5064
          - type: nauc_precision_at_100_std
            value: 52.8775
          - type: nauc_precision_at_100_diff1
            value: -5.0870999999999995
          - type: nauc_precision_at_1000_max
            value: 23.9064
          - type: nauc_precision_at_1000_std
            value: 57.784800000000004
          - type: nauc_precision_at_1000_diff1
            value: -20.1246
          - type: nauc_mrr_at_1_max
            value: 60.2511
          - type: nauc_mrr_at_1_std
            value: 12.422
          - type: nauc_mrr_at_1_diff1
            value: 74.4289
          - type: nauc_mrr_at_3_max
            value: 62.663199999999996
          - type: nauc_mrr_at_3_std
            value: 14.7348
          - type: nauc_mrr_at_3_diff1
            value: 72.1185
          - type: nauc_mrr_at_5_max
            value: 63.3871
          - type: nauc_mrr_at_5_std
            value: 15.773000000000001
          - type: nauc_mrr_at_5_diff1
            value: 71.6722
          - type: nauc_mrr_at_10_max
            value: 62.8474
          - type: nauc_mrr_at_10_std
            value: 15.1896
          - type: nauc_mrr_at_10_diff1
            value: 71.64110000000001
          - type: nauc_mrr_at_20_max
            value: 62.699400000000004
          - type: nauc_mrr_at_20_std
            value: 15.554499999999999
          - type: nauc_mrr_at_20_diff1
            value: 71.6049
          - type: nauc_mrr_at_100_max
            value: 62.6665
          - type: nauc_mrr_at_100_std
            value: 15.4586
          - type: nauc_mrr_at_100_diff1
            value: 71.6217
          - type: nauc_mrr_at_1000_max
            value: 62.6641
          - type: nauc_mrr_at_1000_std
            value: 15.4535
          - type: nauc_mrr_at_1000_diff1
            value: 71.6307
          - type: main_score
            value: 70.586
      - task:
          type: PairClassification
        dataset:
          name: MTEB SprintDuplicateQuestions (default)
          type: mteb/sprintduplicatequestions-pairclassification
          config: default
          split: test
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
        metrics:
          - type: similarity_accuracy
            value: 99.8416
          - type: similarity_accuracy_threshold
            value: 74.52069999999999
          - type: similarity_f1
            value: 92.008
          - type: similarity_f1_threshold
            value: 74.4529
          - type: similarity_precision
            value: 91.9162
          - type: similarity_recall
            value: 92.10000000000001
          - type: similarity_ap
            value: 96.54209999999999
          - type: cosine_accuracy
            value: 99.8416
          - type: cosine_accuracy_threshold
            value: 74.52069999999999
          - type: cosine_f1
            value: 92.008
          - type: cosine_f1_threshold
            value: 74.4529
          - type: cosine_precision
            value: 91.9162
          - type: cosine_recall
            value: 92.10000000000001
          - type: cosine_ap
            value: 96.54209999999999
          - type: manhattan_accuracy
            value: 99.8446
          - type: manhattan_accuracy_threshold
            value: 1784.866
          - type: manhattan_f1
            value: 92.1539
          - type: manhattan_f1_threshold
            value: 1787.6774
          - type: manhattan_precision
            value: 92.1079
          - type: manhattan_recall
            value: 92.2
          - type: manhattan_ap
            value: 96.5207
          - type: euclidean_accuracy
            value: 99.8416
          - type: euclidean_accuracy_threshold
            value: 71.3853
          - type: euclidean_f1
            value: 92.008
          - type: euclidean_f1_threshold
            value: 71.4803
          - type: euclidean_precision
            value: 91.9162
          - type: euclidean_recall
            value: 92.10000000000001
          - type: euclidean_ap
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          - type: nauc_mrr_at_20_std
            value: -22.4697
          - type: nauc_mrr_at_20_diff1
            value: -5.7068
          - type: nauc_mrr_at_100_max
            value: -23.0016
          - type: nauc_mrr_at_100_std
            value: -22.488
          - type: nauc_mrr_at_100_diff1
            value: -5.3738
          - type: nauc_mrr_at_1000_max
            value: -23.0016
          - type: nauc_mrr_at_1000_std
            value: -22.488
          - type: nauc_mrr_at_1000_diff1
            value: -5.3738
          - type: main_score
            value: 29.499
      - task:
          type: Classification
        dataset:
          name: MTEB ToxicConversationsClassification (default)
          type: mteb/toxic_conversations_50k
          config: default
          split: test
          revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
        metrics:
          - type: accuracy
            value: 65.8643
          - type: f1
            value: 50.6764
          - type: f1_weighted
            value: 73.2472
          - type: ap
            value: 12.2658
          - type: ap_weighted
            value: 12.2658
          - type: main_score
            value: 65.8643
      - task:
          type: Classification
        dataset:
          name: MTEB TweetSentimentExtractionClassification (default)
          type: mteb/tweet_sentiment_extraction
          config: default
          split: test
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
        metrics:
          - type: accuracy
            value: 59.6633
          - type: f1
            value: 59.935700000000004
          - type: f1_weighted
            value: 59.0249
          - type: main_score
            value: 59.6633
      - task:
          type: Clustering
        dataset:
          name: MTEB TwentyNewsgroupsClustering (default)
          type: mteb/twentynewsgroups-clustering
          config: default
          split: test
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
        metrics:
          - type: v_measure
            value: 43.2311
          - type: v_measure_std
            value: 2.3994999999999997
          - type: main_score
            value: 43.2311
      - task:
          type: PairClassification
        dataset:
          name: MTEB TwitterSemEval2015 (default)
          type: mteb/twittersemeval2015-pairclassification
          config: default
          split: test
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
        metrics:
          - type: similarity_accuracy
            value: 83.8469
          - type: similarity_accuracy_threshold
            value: 77.6695
          - type: similarity_f1
            value: 62.3159
          - type: similarity_f1_threshold
            value: 71.6554
          - type: similarity_precision
            value: 59.114599999999996
          - type: similarity_recall
            value: 65.8839
          - type: similarity_ap
            value: 67.00930000000001
          - type: cosine_accuracy
            value: 83.8469
          - type: cosine_accuracy_threshold
            value: 77.6695
          - type: cosine_f1
            value: 62.3159
          - type: cosine_f1_threshold
            value: 71.6554
          - type: cosine_precision
            value: 59.114599999999996
          - type: cosine_recall
            value: 65.8839
          - type: cosine_ap
            value: 67.00930000000001
          - type: manhattan_accuracy
            value: 83.7694
          - type: manhattan_accuracy_threshold
            value: 1677.8293999999999
          - type: manhattan_f1
            value: 62.1324
          - type: manhattan_f1_threshold
            value: 1848.6641
          - type: manhattan_precision
            value: 61.839999999999996
          - type: manhattan_recall
            value: 62.4274
          - type: manhattan_ap
            value: 66.8849
          - type: euclidean_accuracy
            value: 83.8469
          - type: euclidean_accuracy_threshold
            value: 66.8288
          - type: euclidean_f1
            value: 62.3159
          - type: euclidean_f1_threshold
            value: 75.2922
          - type: euclidean_precision
            value: 59.114599999999996
          - type: euclidean_recall
            value: 65.8839
          - type: euclidean_ap
            value: 67.00930000000001
          - type: dot_accuracy
            value: 83.8469
          - type: dot_accuracy_threshold
            value: 77.6695
          - type: dot_f1
            value: 62.3159
          - type: dot_f1_threshold
            value: 71.6554
          - type: dot_precision
            value: 59.114599999999996
          - type: dot_recall
            value: 65.8839
          - type: dot_ap
            value: 67.00930000000001
          - type: max_accuracy
            value: 83.8469
          - type: max_f1
            value: 62.3159
          - type: max_precision
            value: 61.839999999999996
          - type: max_recall
            value: 65.8839
          - type: max_ap
            value: 67.00930000000001
          - type: main_score
            value: 67.00930000000001
      - task:
          type: PairClassification
        dataset:
          name: MTEB TwitterURLCorpus (default)
          type: mteb/twitterurlcorpus-pairclassification
          config: default
          split: test
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
        metrics:
          - type: similarity_accuracy
            value: 88.8811
          - type: similarity_accuracy_threshold
            value: 71.1053
          - type: similarity_f1
            value: 77.9005
          - type: similarity_f1_threshold
            value: 67.5068
          - type: similarity_precision
            value: 75.5609
          - type: similarity_recall
            value: 80.3896
          - type: similarity_ap
            value: 85.459
          - type: cosine_accuracy
            value: 88.8811
          - type: cosine_accuracy_threshold
            value: 71.1053
          - type: cosine_f1
            value: 77.9005
          - type: cosine_f1_threshold
            value: 67.5068
          - type: cosine_precision
            value: 75.5609
          - type: cosine_recall
            value: 80.3896
          - type: cosine_ap
            value: 85.459
          - type: manhattan_accuracy
            value: 88.8598
          - type: manhattan_accuracy_threshold
            value: 1928.9173
          - type: manhattan_f1
            value: 77.9172
          - type: manhattan_f1_threshold
            value: 2007.8883999999998
          - type: manhattan_precision
            value: 76.29310000000001
          - type: manhattan_recall
            value: 79.6119
          - type: manhattan_ap
            value: 85.4464
          - type: euclidean_accuracy
            value: 88.8811
          - type: euclidean_accuracy_threshold
            value: 76.0193
          - type: euclidean_f1
            value: 77.9005
          - type: euclidean_f1_threshold
            value: 80.6141
          - type: euclidean_precision
            value: 75.5609
          - type: euclidean_recall
            value: 80.3896
          - type: euclidean_ap
            value: 85.459
          - type: dot_accuracy
            value: 88.8811
          - type: dot_accuracy_threshold
            value: 71.1053
          - type: dot_f1
            value: 77.9005
          - type: dot_f1_threshold
            value: 67.5068
          - type: dot_precision
            value: 75.5609
          - type: dot_recall
            value: 80.3896
          - type: dot_ap
            value: 85.459
          - type: max_accuracy
            value: 88.8811
          - type: max_f1
            value: 77.9172
          - type: max_precision
            value: 76.29310000000001
          - type: max_recall
            value: 80.3896
          - type: max_ap
            value: 85.459
          - type: main_score
            value: 85.459

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

The Model mlx-community/snowflake-arctic-embed-l-v2.0-6bit was converted to MLX format from Snowflake/snowflake-arctic-embed-l-v2.0 using mlx-lm version 0.0.3.

Use with mlx

pip install mlx-embeddings

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

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

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

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

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