README.md

metadata

model-index:
  - name: jasper_en_vision_language_v1
    results:
      - dataset:
          config: en-ext
          name: MTEB AmazonCounterfactualClassification (en-ext)
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
          split: test
          type: mteb/amazon_counterfactual
        metrics:
          - type: accuracy
            value: 95.7271
          - type: f1
            value: 89.25450000000001
          - type: f1_weighted
            value: 95.8563
          - type: ap
            value: 67.1563
          - type: ap_weighted
            value: 67.1563
          - type: main_score
            value: 95.7271
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB AmazonCounterfactualClassification (en)
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
          split: test
          type: mteb/amazon_counterfactual
        metrics:
          - type: accuracy
            value: 93.7761
          - type: f1
            value: 90.7582
          - type: f1_weighted
            value: 93.974
          - type: ap
            value: 74.88759999999999
          - type: ap_weighted
            value: 74.88759999999999
          - type: main_score
            value: 93.7761
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB AmazonPolarityClassification (default)
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
          split: test
          type: mteb/amazon_polarity
        metrics:
          - type: accuracy
            value: 97.5809
          - type: f1
            value: 97.5808
          - type: f1_weighted
            value: 97.5808
          - type: ap
            value: 96.3911
          - type: ap_weighted
            value: 96.3911
          - type: main_score
            value: 97.5809
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB AmazonReviewsClassification (en)
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
          split: test
          type: mteb/amazon_reviews_multi
        metrics:
          - type: accuracy
            value: 62.918
          - type: f1
            value: 60.696099999999994
          - type: f1_weighted
            value: 60.696099999999994
          - type: main_score
            value: 62.918
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB ArguAna (default)
          revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
          split: test
          type: mteb/arguana
        metrics:
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            value: 41.323
          - type: ndcg_at_3
            value: 56.737
          - type: ndcg_at_5
            value: 61.254
          - type: ndcg_at_10
            value: 65.204
          - type: ndcg_at_20
            value: 66.75
          - type: ndcg_at_100
            value: 67.254
          - type: ndcg_at_1000
            value: 67.254
          - type: map_at_1
            value: 41.323
          - type: map_at_3
            value: 52.881
          - type: map_at_5
            value: 55.373000000000005
          - type: map_at_10
            value: 57.013999999999996
          - type: map_at_20
            value: 57.457
          - type: map_at_100
            value: 57.538
          - type: map_at_1000
            value: 57.538
          - type: recall_at_1
            value: 41.323
          - type: recall_at_3
            value: 67.923
          - type: recall_at_5
            value: 78.947
          - type: recall_at_10
            value: 91.11
          - type: recall_at_20
            value: 97.084
          - type: recall_at_100
            value: 99.644
          - type: recall_at_1000
            value: 99.644
          - type: precision_at_1
            value: 41.323
          - type: precision_at_3
            value: 22.641
          - type: precision_at_5
            value: 15.789
          - type: precision_at_10
            value: 9.110999999999999
          - type: precision_at_20
            value: 4.854
          - type: precision_at_100
            value: 0.996
          - type: precision_at_1000
            value: 0.1
          - type: mrr_at_1
            value: 41.6785
          - type: mrr_at_3
            value: 52.963499999999996
          - type: mrr_at_5
            value: 55.456399999999995
          - type: mrr_at_10
            value: 57.104299999999995
          - type: mrr_at_20
            value: 57.5402
          - type: mrr_at_100
            value: 57.6213
          - type: mrr_at_1000
            value: 57.6213
          - type: nauc_ndcg_at_1_max
            value: -12.633600000000001
          - type: nauc_ndcg_at_1_std
            value: -19.747700000000002
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            value: 25.820300000000003
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            value: -8.480799999999999
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            value: -18.928900000000002
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            value: 19.409499999999998
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            value: -7.9172
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            value: -19.2306
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            value: 18.5809
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            value: -9.7812
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            value: -19.9964
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            value: 18.0753
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            value: -8.6546
          - type: nauc_ndcg_at_20_std
            value: -19.3205
          - type: nauc_ndcg_at_20_diff1
            value: 20.1741
          - type: nauc_ndcg_at_100_max
            value: -9.376900000000001
          - type: nauc_ndcg_at_100_std
            value: -19.5093
          - type: nauc_ndcg_at_100_diff1
            value: 20.4997
          - type: nauc_ndcg_at_1000_max
            value: -9.376900000000001
          - type: nauc_ndcg_at_1000_std
            value: -19.5093
          - type: nauc_ndcg_at_1000_diff1
            value: 20.4997
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            value: -12.633600000000001
          - type: nauc_map_at_1_std
            value: -19.747700000000002
          - type: nauc_map_at_1_diff1
            value: 25.820300000000003
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            value: -19.3235
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            value: 20.9083
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            value: -19.4593
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            value: -19.6759
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            value: -9.8837
          - type: nauc_map_at_100_std
            value: -19.741400000000002
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            value: 21.067700000000002
          - type: nauc_map_at_1000_max
            value: -9.8837
          - type: nauc_map_at_1000_std
            value: -19.741400000000002
          - type: nauc_map_at_1000_diff1
            value: 21.067700000000002
          - type: nauc_recall_at_1_max
            value: -12.633600000000001
          - type: nauc_recall_at_1_std
            value: -19.747700000000002
          - type: nauc_recall_at_1_diff1
            value: 25.820300000000003
          - type: nauc_recall_at_3_max
            value: -4.7886999999999995
          - type: nauc_recall_at_3_std
            value: -17.4764
          - type: nauc_recall_at_3_diff1
            value: 14.3308
          - type: nauc_recall_at_5_max
            value: -1.4803
          - type: nauc_recall_at_5_std
            value: -18.2137
          - type: nauc_recall_at_5_diff1
            value: 9.4604
          - type: nauc_recall_at_10_max
            value: -8.8102
          - type: nauc_recall_at_10_std
            value: -21.8279
          - type: nauc_recall_at_10_diff1
            value: -5.5388
          - type: nauc_recall_at_20_max
            value: 25.202400000000004
          - type: nauc_recall_at_20_std
            value: -4.8613
          - type: nauc_recall_at_20_diff1
            value: 9.3917
          - type: nauc_recall_at_100_max
            value: 37.0551
          - type: nauc_recall_at_100_std
            value: 84.5472
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            value: 19.5116
          - type: nauc_recall_at_1000_max
            value: 37.0551
          - type: nauc_recall_at_1000_std
            value: 84.5472
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            value: 19.5116
          - type: nauc_precision_at_1_max
            value: -12.633600000000001
          - type: nauc_precision_at_1_std
            value: -19.747700000000002
          - type: nauc_precision_at_1_diff1
            value: 25.820300000000003
          - type: nauc_precision_at_3_max
            value: -4.7886999999999995
          - type: nauc_precision_at_3_std
            value: -17.4764
          - type: nauc_precision_at_3_diff1
            value: 14.3308
          - type: nauc_precision_at_5_max
            value: -1.4803
          - type: nauc_precision_at_5_std
            value: -18.2137
          - type: nauc_precision_at_5_diff1
            value: 9.4604
          - type: nauc_precision_at_10_max
            value: -8.8102
          - type: nauc_precision_at_10_std
            value: -21.8279
          - type: nauc_precision_at_10_diff1
            value: -5.5388
          - type: nauc_precision_at_20_max
            value: 25.202400000000004
          - type: nauc_precision_at_20_std
            value: -4.8613
          - type: nauc_precision_at_20_diff1
            value: 9.3917
          - type: nauc_precision_at_100_max
            value: 37.0551
          - type: nauc_precision_at_100_std
            value: 84.5472
          - type: nauc_precision_at_100_diff1
            value: 19.5116
          - type: nauc_precision_at_1000_max
            value: 37.0551
          - type: nauc_precision_at_1000_std
            value: 84.5472
          - type: nauc_precision_at_1000_diff1
            value: 19.5116
          - type: nauc_mrr_at_1_max
            value: -11.9728
          - type: nauc_mrr_at_1_std
            value: -19.4014
          - type: nauc_mrr_at_1_diff1
            value: 24.8653
          - type: nauc_mrr_at_3_max
            value: -9.6607
          - type: nauc_mrr_at_3_std
            value: -19.1819
          - type: nauc_mrr_at_3_diff1
            value: 20.0205
          - type: nauc_mrr_at_5_max
            value: -9.4261
          - type: nauc_mrr_at_5_std
            value: -19.3098
          - type: nauc_mrr_at_5_diff1
            value: 19.6347
          - type: nauc_mrr_at_10_max
            value: -10.1698
          - type: nauc_mrr_at_10_std
            value: -19.683
          - type: nauc_mrr_at_10_diff1
            value: 19.4823
          - type: nauc_mrr_at_20_max
            value: -9.913
          - type: nauc_mrr_at_20_std
            value: -19.517300000000002
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            value: 20.0066
          - type: nauc_mrr_at_100_max
            value: -10.0053
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            value: -19.5824
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            value: 20.061899999999998
          - type: nauc_mrr_at_1000_max
            value: -10.0053
          - type: nauc_mrr_at_1000_std
            value: -19.5824
          - type: nauc_mrr_at_1000_diff1
            value: 20.061899999999998
          - type: main_score
            value: 65.204
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB ArxivClusteringP2P (default)
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
          split: test
          type: mteb/arxiv-clustering-p2p
        metrics:
          - type: v_measure
            value: 55.710300000000004
          - type: v_measure_std
            value: 14.551900000000002
          - type: main_score
            value: 55.710300000000004
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB ArxivClusteringS2S (default)
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
          split: test
          type: mteb/arxiv-clustering-s2s
        metrics:
          - type: v_measure
            value: 51.004599999999996
          - type: v_measure_std
            value: 14.868899999999998
          - type: main_score
            value: 51.004599999999996
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB AskUbuntuDupQuestions (default)
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
          split: test
          type: mteb/askubuntudupquestions-reranking
        metrics:
          - type: map
            value: 67.38119999999999
          - type: mrr
            value: 79.0692
          - type: nAUC_map_max
            value: 21.9757
          - type: nAUC_map_std
            value: 14.3545
          - type: nAUC_map_diff1
            value: 11.82
          - type: nAUC_mrr_max
            value: 40.3449
          - type: nAUC_mrr_std
            value: 18.2678
          - type: nAUC_mrr_diff1
            value: 21.1596
          - type: main_score
            value: 67.38119999999999
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB BIOSSES (default)
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
          split: test
          type: mteb/biosses-sts
        metrics:
          - type: pearson
            value: 87.4332
          - type: spearman
            value: 84.65979999999999
          - type: cosine_pearson
            value: 87.4332
          - type: cosine_spearman
            value: 84.65979999999999
          - type: manhattan_pearson
            value: 86.37270000000001
          - type: manhattan_spearman
            value: 85.20309999999999
          - type: euclidean_pearson
            value: 86.1672
          - type: euclidean_spearman
            value: 84.7453
          - type: main_score
            value: 84.65979999999999
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB Banking77Classification (default)
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
          split: test
          type: mteb/banking77
        metrics:
          - type: accuracy
            value: 87.224
          - type: f1
            value: 86.7235
          - type: f1_weighted
            value: 86.7235
          - type: main_score
            value: 87.224
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB BiorxivClusteringP2P (default)
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
          split: test
          type: mteb/biorxiv-clustering-p2p
        metrics:
          - type: v_measure
            value: 52.04990000000001
          - type: v_measure_std
            value: 0.7255
          - type: main_score
            value: 52.04990000000001
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB BiorxivClusteringS2S (default)
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
          split: test
          type: mteb/biorxiv-clustering-s2s
        metrics:
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            value: 47.5811
          - type: v_measure_std
            value: 0.8049000000000001
          - type: main_score
            value: 47.5811
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB CQADupstackAndroidRetrieval (default)
          revision: f46a197baaae43b4f621051089b82a364682dfeb
          split: test
          type: mteb/cqadupstack-android
        metrics:
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            value: 54.371
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          - type: ndcg_at_1000
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            value: 46.005
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            value: 48.32
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            value: 50.181
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            value: 51.062
          - type: map_at_100
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            value: 53.94
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          - type: recall_at_100
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          - type: recall_at_1000
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          - type: precision_at_1000
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      - dataset:
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          name: MTEB MTOPDomainClassification (en)
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
          split: test
          type: mteb/mtop_domain
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        task:
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          name: MTEB MTOPIntentClassification (en)
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
          split: test
          type: mteb/mtop_intent
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        task:
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      - dataset:
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          name: MTEB MassiveIntentClassification (en)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
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        task:
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      - dataset:
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          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
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      - dataset:
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          revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
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          type: mteb/medrxiv-clustering-p2p
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        task:
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      - dataset:
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          name: MTEB MedrxivClusteringS2S (default)
          revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
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          type: mteb/medrxiv-clustering-s2s
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        task:
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      - dataset:
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          name: MTEB MindSmallReranking (default)
          revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
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          type: mteb/mind_small
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          name: MTEB NFCorpus (default)
          revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
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          type: mteb/nfcorpus
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      - dataset:
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          name: MTEB RedditClustering (default)
          revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
          split: test
          type: mteb/reddit-clustering
        metrics:
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          - type: v_measure_std
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          - type: main_score
            value: 73.0223
        task:
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      - dataset:
          config: default
          name: MTEB RedditClusteringP2P (default)
          revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
          split: test
          type: mteb/reddit-clustering-p2p
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          - type: main_score
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        task:
          type: Clustering
      - dataset:
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          name: MTEB SCIDOCS (default)
          revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
          split: test
          type: mteb/scidocs
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            value: 18.5224
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        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB SICK-R (default)
          revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
          split: test
          type: mteb/sickr-sts
        metrics:
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          - type: spearman
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          - type: cosine_pearson
            value: 86.8981
          - type: cosine_spearman
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          - type: manhattan_pearson
            value: 84.1165
          - type: manhattan_spearman
            value: 82.063
          - type: euclidean_pearson
            value: 84.0688
          - type: euclidean_spearman
            value: 82.2329
          - type: main_score
            value: 82.234
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS12 (default)
          revision: a0d554a64d88156834ff5ae9920b964011b16384
          split: test
          type: mteb/sts12-sts
        metrics:
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          - type: spearman
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          - type: cosine_pearson
            value: 87.8269
          - type: cosine_spearman
            value: 80.2578
          - type: manhattan_pearson
            value: 85.09020000000001
          - type: manhattan_spearman
            value: 80.5777
          - type: euclidean_pearson
            value: 84.71990000000001
          - type: euclidean_spearman
            value: 80.2547
          - type: main_score
            value: 80.2578
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS13 (default)
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
          split: test
          type: mteb/sts13-sts
        metrics:
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            value: 89.45769999999999
          - type: spearman
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          - type: cosine_pearson
            value: 89.45769999999999
          - type: cosine_spearman
            value: 89.69200000000001
          - type: manhattan_pearson
            value: 89.1685
          - type: manhattan_spearman
            value: 89.8889
          - type: euclidean_pearson
            value: 89.07969999999999
          - type: euclidean_spearman
            value: 89.7003
          - type: main_score
            value: 89.69200000000001
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS14 (default)
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
          split: test
          type: mteb/sts14-sts
        metrics:
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            value: 87.01989999999999
          - type: spearman
            value: 85.3155
          - type: cosine_pearson
            value: 87.01989999999999
          - type: cosine_spearman
            value: 85.3155
          - type: manhattan_pearson
            value: 86.24159999999999
          - type: manhattan_spearman
            value: 85.544
          - type: euclidean_pearson
            value: 86.1032
          - type: euclidean_spearman
            value: 85.31490000000001
          - type: main_score
            value: 85.3155
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS15 (default)
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
          split: test
          type: mteb/sts15-sts
        metrics:
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            value: 89.593
          - type: spearman
            value: 90.1574
          - type: cosine_pearson
            value: 89.593
          - type: cosine_spearman
            value: 90.1574
          - type: manhattan_pearson
            value: 89.93910000000001
          - type: manhattan_spearman
            value: 90.4357
          - type: euclidean_pearson
            value: 89.76650000000001
          - type: euclidean_spearman
            value: 90.1554
          - type: main_score
            value: 90.1574
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS16 (default)
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
          split: test
          type: mteb/sts16-sts
        metrics:
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            value: 85.03540000000001
          - type: spearman
            value: 86.4191
          - type: cosine_pearson
            value: 85.03540000000001
          - type: cosine_spearman
            value: 86.4191
          - type: manhattan_pearson
            value: 85.8992
          - type: manhattan_spearman
            value: 86.7274
          - type: euclidean_pearson
            value: 85.638
          - type: euclidean_spearman
            value: 86.42
          - type: main_score
            value: 86.4191
        task:
          type: STS
      - dataset:
          config: en-ar
          name: MTEB STS17 (en-ar)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
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          - type: spearman
            value: 52.721
          - type: cosine_pearson
            value: 54.1098
          - type: cosine_spearman
            value: 52.721
          - type: manhattan_pearson
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          - type: manhattan_spearman
            value: 52.727900000000005
          - type: euclidean_pearson
            value: 54.65410000000001
          - type: euclidean_spearman
            value: 52.8582
          - type: main_score
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        task:
          type: STS
      - dataset:
          config: fr-en
          name: MTEB STS17 (fr-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
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          - type: spearman
            value: 84.1421
          - type: cosine_pearson
            value: 84.3262
          - type: cosine_spearman
            value: 84.1421
          - type: manhattan_pearson
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          - type: manhattan_spearman
            value: 83.9987
          - type: euclidean_pearson
            value: 84.0174
          - type: euclidean_spearman
            value: 84.1711
          - type: main_score
            value: 84.1421
        task:
          type: STS
      - dataset:
          config: en-en
          name: MTEB STS17 (en-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
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            value: 91.38969999999999
          - type: spearman
            value: 91.00789999999999
          - type: cosine_pearson
            value: 91.38969999999999
          - type: cosine_spearman
            value: 91.00789999999999
          - type: manhattan_pearson
            value: 90.8917
          - type: manhattan_spearman
            value: 90.7834
          - type: euclidean_pearson
            value: 91.0361
          - type: euclidean_spearman
            value: 91.011
          - type: main_score
            value: 91.00789999999999
        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: 84.636
          - type: spearman
            value: 84.1977
          - type: cosine_pearson
            value: 84.636
          - type: cosine_spearman
            value: 84.1977
          - type: manhattan_pearson
            value: 84.6895
          - type: manhattan_spearman
            value: 84.1849
          - type: euclidean_pearson
            value: 84.753
          - type: euclidean_spearman
            value: 84.2251
          - type: main_score
            value: 84.1977
        task:
          type: STS
      - dataset:
          config: es-en
          name: MTEB STS17 (es-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: pearson
            value: 85.8595
          - type: spearman
            value: 86.9965
          - type: cosine_pearson
            value: 85.8595
          - type: cosine_spearman
            value: 86.9965
          - type: manhattan_pearson
            value: 86.92450000000001
          - type: manhattan_spearman
            value: 87.39489999999999
          - type: euclidean_pearson
            value: 86.5575
          - type: euclidean_spearman
            value: 86.997
          - type: main_score
            value: 86.9965
        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: 85.959
          - type: spearman
            value: 86.3103
          - type: cosine_pearson
            value: 85.959
          - type: cosine_spearman
            value: 86.3103
          - type: manhattan_pearson
            value: 85.7486
          - type: manhattan_spearman
            value: 86.0977
          - type: euclidean_pearson
            value: 85.8361
          - type: euclidean_spearman
            value: 86.2741
          - type: main_score
            value: 86.3103
        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: 86.2629
          - type: spearman
            value: 85.8372
          - type: cosine_pearson
            value: 86.2629
          - type: cosine_spearman
            value: 85.8372
          - type: manhattan_pearson
            value: 86.2491
          - type: manhattan_spearman
            value: 85.4973
          - type: euclidean_pearson
            value: 86.5074
          - type: euclidean_spearman
            value: 85.83370000000001
          - type: main_score
            value: 85.8372
        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: 57.5675
          - type: spearman
            value: 55.564899999999994
          - type: cosine_pearson
            value: 57.5675
          - type: cosine_spearman
            value: 55.564899999999994
          - type: manhattan_pearson
            value: 57.4686
          - type: manhattan_spearman
            value: 55.3816
          - type: euclidean_pearson
            value: 57.635099999999994
          - type: euclidean_spearman
            value: 55.501900000000006
          - type: main_score
            value: 55.564899999999994
        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: 76.1237
          - type: spearman
            value: 76.4
          - type: cosine_pearson
            value: 76.1237
          - type: cosine_spearman
            value: 76.4
          - type: manhattan_pearson
            value: 78.6794
          - type: manhattan_spearman
            value: 77.2282
          - type: euclidean_pearson
            value: 77.1688
          - type: euclidean_spearman
            value: 76.4
          - type: main_score
            value: 76.4
        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: 73.89099999999999
          - type: spearman
            value: 77.8292
          - type: cosine_pearson
            value: 73.89099999999999
          - type: cosine_spearman
            value: 77.8292
          - type: manhattan_pearson
            value: 77.53229999999999
          - type: manhattan_spearman
            value: 78.3926
          - type: euclidean_pearson
            value: 76.6734
          - type: euclidean_spearman
            value: 77.8721
          - type: main_score
            value: 77.8292
        task:
          type: STS
      - dataset:
          config: en
          name: MTEB STS22 (en)
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
          split: test
          type: mteb/sts22-crosslingual-sts
        metrics:
          - type: pearson
            value: 68.31099999999999
          - type: spearman
            value: 68.0764
          - type: cosine_pearson
            value: 68.31099999999999
          - type: cosine_spearman
            value: 68.0764
          - type: manhattan_pearson
            value: 69.7423
          - type: manhattan_spearman
            value: 68.3212
          - type: euclidean_pearson
            value: 69.5701
          - type: euclidean_spearman
            value: 68.2299
          - type: main_score
            value: 68.0764
        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: 65.0636
          - type: spearman
            value: 59.4669
          - type: cosine_pearson
            value: 65.0636
          - type: cosine_spearman
            value: 59.4669
          - type: manhattan_pearson
            value: 69.723
          - type: manhattan_spearman
            value: 60.3823
          - type: euclidean_pearson
            value: 68.6454
          - type: euclidean_spearman
            value: 59.384899999999995
          - type: main_score
            value: 59.4669
        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: 73.7603
          - type: spearman
            value: 73.0799
          - type: cosine_pearson
            value: 73.7603
          - type: cosine_spearman
            value: 73.0799
          - type: manhattan_pearson
            value: 76.2351
          - type: manhattan_spearman
            value: 73.60719999999999
          - type: euclidean_pearson
            value: 75.61529999999999
          - type: euclidean_spearman
            value: 72.9809
          - type: main_score
            value: 73.0799
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STSBenchmark (default)
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
          split: test
          type: mteb/stsbenchmark-sts
        metrics:
          - type: pearson
            value: 88.1242
          - type: spearman
            value: 88.8456
          - type: cosine_pearson
            value: 88.1242
          - type: cosine_spearman
            value: 88.8456
          - type: manhattan_pearson
            value: 88.6122
          - type: manhattan_spearman
            value: 89.0198
          - type: euclidean_pearson
            value: 88.5314
          - type: euclidean_spearman
            value: 88.8432
          - type: main_score
            value: 88.8456
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB SciDocsRR (default)
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
          split: test
          type: mteb/scidocs-reranking
        metrics:
          - type: map
            value: 89.06920000000001
          - type: mrr
            value: 96.977
          - type: nAUC_map_max
            value: 49.1778
          - type: nAUC_map_std
            value: 62.091499999999996
          - type: nAUC_map_diff1
            value: -13.373899999999999
          - type: nAUC_mrr_max
            value: 86.7325
          - type: nAUC_mrr_std
            value: 74.958
          - type: nAUC_mrr_diff1
            value: 25.6955
          - type: main_score
            value: 89.06920000000001
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB SciFact (default)
          revision: 0228b52cf27578f30900b9e5271d331663a030d7
          split: test
          type: mteb/scifact
        metrics:
          - type: ndcg_at_1
            value: 67.333
          - type: ndcg_at_3
            value: 75.142
          - type: ndcg_at_5
            value: 78.873
          - type: ndcg_at_10
            value: 80.372
          - type: ndcg_at_20
            value: 80.914
          - type: ndcg_at_100
            value: 81.563
          - type: ndcg_at_1000
            value: 81.601
          - type: map_at_1
            value: 63.99399999999999
          - type: map_at_3
            value: 72.181
          - type: map_at_5
            value: 74.665
          - type: map_at_10
            value: 75.51299999999999
          - type: map_at_20
            value: 75.693
          - type: map_at_100
            value: 75.78
          - type: map_at_1000
            value: 75.78099999999999
          - type: recall_at_1
            value: 63.99399999999999
          - type: recall_at_3
            value: 80.63900000000001
          - type: recall_at_5
            value: 90.017
          - type: recall_at_10
            value: 94.167
          - type: recall_at_20
            value: 96.167
          - type: recall_at_100
            value: 99.667
          - type: recall_at_1000
            value: 100
          - type: precision_at_1
            value: 67.333
          - type: precision_at_3
            value: 29.444
          - type: precision_at_5
            value: 20.067
          - type: precision_at_10
            value: 10.667
          - type: precision_at_20
            value: 5.45
          - type: precision_at_100
            value: 1.127
          - type: precision_at_1000
            value: 0.11299999999999999
          - type: mrr_at_1
            value: 67.3333
          - type: mrr_at_3
            value: 73.9444
          - type: mrr_at_5
            value: 76.0444
          - type: mrr_at_10
            value: 76.4517
          - type: mrr_at_20
            value: 76.5739
          - type: mrr_at_100
            value: 76.6556
          - type: mrr_at_1000
            value: 76.6563
          - type: nauc_ndcg_at_1_max
            value: 55.373099999999994
          - type: nauc_ndcg_at_1_std
            value: -11.362
          - type: nauc_ndcg_at_1_diff1
            value: 81.5232
          - type: nauc_ndcg_at_3_max
            value: 58.0376
          - type: nauc_ndcg_at_3_std
            value: -14.4854
          - type: nauc_ndcg_at_3_diff1
            value: 77.848
          - type: nauc_ndcg_at_5_max
            value: 55.789699999999996
          - type: nauc_ndcg_at_5_std
            value: -15.0412
          - type: nauc_ndcg_at_5_diff1
            value: 77.7873
          - type: nauc_ndcg_at_10_max
            value: 58.6243
          - type: nauc_ndcg_at_10_std
            value: -13.867799999999999
          - type: nauc_ndcg_at_10_diff1
            value: 78.071
          - type: nauc_ndcg_at_20_max
            value: 58.9032
          - type: nauc_ndcg_at_20_std
            value: -12.7998
          - type: nauc_ndcg_at_20_diff1
            value: 78.12010000000001
          - type: nauc_ndcg_at_100_max
            value: 58.0772
          - type: nauc_ndcg_at_100_std
            value: -12.4604
          - type: nauc_ndcg_at_100_diff1
            value: 78.7002
          - type: nauc_ndcg_at_1000_max
            value: 58.0835
          - type: nauc_ndcg_at_1000_std
            value: -12.662799999999999
          - type: nauc_ndcg_at_1000_diff1
            value: 78.7157
          - type: nauc_map_at_1_max
            value: 45.2711
          - type: nauc_map_at_1_std
            value: -21.685
          - type: nauc_map_at_1_diff1
            value: 80.8536
          - type: nauc_map_at_3_max
            value: 53.970600000000005
          - type: nauc_map_at_3_std
            value: -18.0178
          - type: nauc_map_at_3_diff1
            value: 78.95309999999999
          - type: nauc_map_at_5_max
            value: 54.7643
          - type: nauc_map_at_5_std
            value: -15.943999999999999
          - type: nauc_map_at_5_diff1
            value: 78.9665
          - type: nauc_map_at_10_max
            value: 56.737899999999996
          - type: nauc_map_at_10_std
            value: -14.355599999999999
          - type: nauc_map_at_10_diff1
            value: 79.095
          - type: nauc_map_at_20_max
            value: 56.804
          - type: nauc_map_at_20_std
            value: -14.033599999999998
          - type: nauc_map_at_20_diff1
            value: 79.0729
          - type: nauc_map_at_100_max
            value: 56.7168
          - type: nauc_map_at_100_std
            value: -14.000000000000002
          - type: nauc_map_at_100_diff1
            value: 79.1456
          - type: nauc_map_at_1000_max
            value: 56.7168
          - type: nauc_map_at_1000_std
            value: -14.003099999999998
          - type: nauc_map_at_1000_diff1
            value: 79.1458
          - type: nauc_recall_at_1_max
            value: 45.2711
          - type: nauc_recall_at_1_std
            value: -21.685
          - type: nauc_recall_at_1_diff1
            value: 80.8536
          - type: nauc_recall_at_3_max
            value: 55.911100000000005
          - type: nauc_recall_at_3_std
            value: -19.1603
          - type: nauc_recall_at_3_diff1
            value: 72.51689999999999
          - type: nauc_recall_at_5_max
            value: 50.6317
          - type: nauc_recall_at_5_std
            value: -21.4004
          - type: nauc_recall_at_5_diff1
            value: 68.3824
          - type: nauc_recall_at_10_max
            value: 67.3176
          - type: nauc_recall_at_10_std
            value: -23.6601
          - type: nauc_recall_at_10_diff1
            value: 67.20150000000001
          - type: nauc_recall_at_20_max
            value: 76.566
          - type: nauc_recall_at_20_std
            value: -12.4873
          - type: nauc_recall_at_20_diff1
            value: 63.6849
          - type: nauc_recall_at_100_max
            value: 55.415499999999994
          - type: nauc_recall_at_100_std
            value: 72.2222
          - type: nauc_recall_at_100_diff1
            value: 72.2222
          - type: nauc_recall_at_1000_max
            value: .nan
          - type: nauc_recall_at_1000_std
            value: .nan
          - type: nauc_recall_at_1000_diff1
            value: .nan
          - type: nauc_precision_at_1_max
            value: 55.373099999999994
          - type: nauc_precision_at_1_std
            value: -11.362
          - type: nauc_precision_at_1_diff1
            value: 81.5232
          - type: nauc_precision_at_3_max
            value: 59.23969999999999
          - type: nauc_precision_at_3_std
            value: 17.3868
          - type: nauc_precision_at_3_diff1
            value: 37.0438
          - type: nauc_precision_at_5_max
            value: 51.358599999999996
          - type: nauc_precision_at_5_std
            value: 39.9722
          - type: nauc_precision_at_5_diff1
            value: 9.2927
          - type: nauc_precision_at_10_max
            value: 44.6166
          - type: nauc_precision_at_10_std
            value: 46.4231
          - type: nauc_precision_at_10_diff1
            value: -7.435700000000001
          - type: nauc_precision_at_20_max
            value: 41.1852
          - type: nauc_precision_at_20_std
            value: 51.89359999999999
          - type: nauc_precision_at_20_diff1
            value: -14.6318
          - type: nauc_precision_at_100_max
            value: 33.6188
          - type: nauc_precision_at_100_std
            value: 60.621700000000004
          - type: nauc_precision_at_100_diff1
            value: -26.376500000000004
          - type: nauc_precision_at_1000_max
            value: 33.2976
          - type: nauc_precision_at_1000_std
            value: 60.4508
          - type: nauc_precision_at_1000_diff1
            value: -27.829500000000003
          - type: nauc_mrr_at_1_max
            value: 55.373099999999994
          - type: nauc_mrr_at_1_std
            value: -11.362
          - type: nauc_mrr_at_1_diff1
            value: 81.5232
          - type: nauc_mrr_at_3_max
            value: 58.7918
          - type: nauc_mrr_at_3_std
            value: -11.580300000000001
          - type: nauc_mrr_at_3_diff1
            value: 78.79310000000001
          - type: nauc_mrr_at_5_max
            value: 58.13270000000001
          - type: nauc_mrr_at_5_std
            value: -11.2346
          - type: nauc_mrr_at_5_diff1
            value: 78.8896
          - type: nauc_mrr_at_10_max
            value: 58.4249
          - type: nauc_mrr_at_10_std
            value: -11.842600000000001
          - type: nauc_mrr_at_10_diff1
            value: 79.0629
          - type: nauc_mrr_at_20_max
            value: 58.4409
          - type: nauc_mrr_at_20_std
            value: -11.7012
          - type: nauc_mrr_at_20_diff1
            value: 79.1097
          - type: nauc_mrr_at_100_max
            value: 58.3685
          - type: nauc_mrr_at_100_std
            value: -11.6333
          - type: nauc_mrr_at_100_diff1
            value: 79.1871
          - type: nauc_mrr_at_1000_max
            value: 58.3686
          - type: nauc_mrr_at_1000_std
            value: -11.6365
          - type: nauc_mrr_at_1000_diff1
            value: 79.1874
          - type: main_score
            value: 80.372
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB SprintDuplicateQuestions (default)
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
          split: test
          type: mteb/sprintduplicatequestions-pairclassification
        metrics:
          - type: similarity_accuracy
            value: 99.8317
          - type: similarity_accuracy_threshold
            value: 87.7015
          - type: similarity_f1
            value: 91.2821
          - type: similarity_f1_threshold
            value: 87.68599999999999
          - type: similarity_precision
            value: 93.68419999999999
          - type: similarity_recall
            value: 89
          - type: similarity_ap
            value: 96.249
          - type: cosine_accuracy
            value: 99.8317
          - type: cosine_accuracy_threshold
            value: 87.7015
          - type: cosine_f1
            value: 91.2821
          - type: cosine_f1_threshold
            value: 87.68599999999999
          - type: cosine_precision
            value: 93.68419999999999
          - type: cosine_recall
            value: 89
          - type: cosine_ap
            value: 96.249
          - type: manhattan_accuracy
            value: 99.83370000000001
          - type: manhattan_accuracy_threshold
            value: 4133.4675
          - type: manhattan_f1
            value: 91.52369999999999
          - type: manhattan_f1_threshold
            value: 4244.392400000001
          - type: manhattan_precision
            value: 92.3625
          - type: manhattan_recall
            value: 90.7
          - type: manhattan_ap
            value: 96.4021
          - type: euclidean_accuracy
            value: 99.83070000000001
          - type: euclidean_accuracy_threshold
            value: 49.684200000000004
          - type: euclidean_f1
            value: 91.24419999999999
          - type: euclidean_f1_threshold
            value: 49.7175
          - type: euclidean_precision
            value: 93.4942
          - type: euclidean_recall
            value: 89.1
          - type: euclidean_ap
            value: 96.24589999999999
          - type: dot_accuracy
            value: 99.8277
          - type: dot_accuracy_threshold
            value: 87.3743
          - type: dot_f1
            value: 91.1495
          - type: dot_f1_threshold
            value: 87.3743
          - type: dot_precision
            value: 92.7536
          - type: dot_recall
            value: 89.60000000000001
          - type: dot_ap
            value: 96.23509999999999
          - type: max_accuracy
            value: 99.83370000000001
          - type: max_f1
            value: 91.52369999999999
          - type: max_precision
            value: 93.68419999999999
          - type: max_recall
            value: 90.7
          - type: max_ap
            value: 96.4021
          - type: main_score
            value: 96.4021
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB StackExchangeClustering (default)
          revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
          split: test
          type: mteb/stackexchange-clustering
        metrics:
          - type: v_measure
            value: 80.19420000000001
          - type: v_measure_std
            value: 2.8956
          - type: main_score
            value: 80.19420000000001
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB StackExchangeClusteringP2P (default)
          revision: 815ca46b2622cec33ccafc3735d572c266efdb44
          split: test
          type: mteb/stackexchange-clustering-p2p
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            value: 1.5938
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            value: 49.416900000000005
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          config: default
          name: MTEB StackOverflowDupQuestions (default)
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
          split: test
          type: mteb/stackoverflowdupquestions-reranking
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            value: 39.2785
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            value: 54.579
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          name: MTEB SummEval (default)
          revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
          split: test
          type: mteb/summeval
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          revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
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      - dataset:
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          name: MTEB Touche2020 (default)
          revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
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      - dataset:
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          name: MTEB ToxicConversationsClassification (default)
          revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
          split: test
          type: mteb/toxic_conversations_50k
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        task:
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      - dataset:
          config: default
          name: MTEB TweetSentimentExtractionClassification (default)
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
          split: test
          type: mteb/tweet_sentiment_extraction
        metrics:
          - type: accuracy
            value: 77.24109999999999
          - type: f1
            value: 77.4964
          - type: f1_weighted
            value: 77.0248
          - type: main_score
            value: 77.24109999999999
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB TwentyNewsgroupsClustering (default)
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
          split: test
          type: mteb/twentynewsgroups-clustering
        metrics:
          - type: v_measure
            value: 63.132200000000005
          - type: v_measure_std
            value: 0.7163
          - type: main_score
            value: 63.132200000000005
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB TwitterSemEval2015 (default)
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
          split: test
          type: mteb/twittersemeval2015-pairclassification
        metrics:
          - type: similarity_accuracy
            value: 88.061
          - type: similarity_accuracy_threshold
            value: 85.9546
          - type: similarity_f1
            value: 73.36240000000001
          - type: similarity_f1_threshold
            value: 84.0127
          - type: similarity_precision
            value: 71.47149999999999
          - type: similarity_recall
            value: 75.3562
          - type: similarity_ap
            value: 80.2787
          - type: cosine_accuracy
            value: 88.061
          - type: cosine_accuracy_threshold
            value: 85.9546
          - type: cosine_f1
            value: 73.36240000000001
          - type: cosine_f1_threshold
            value: 84.0127
          - type: cosine_precision
            value: 71.47149999999999
          - type: cosine_recall
            value: 75.3562
          - type: cosine_ap
            value: 80.2787
          - type: manhattan_accuracy
            value: 87.8941
          - type: manhattan_accuracy_threshold
            value: 4374.3263
          - type: manhattan_f1
            value: 72.929
          - type: manhattan_f1_threshold
            value: 4637.7289
          - type: manhattan_precision
            value: 71.3636
          - type: manhattan_recall
            value: 74.5646
          - type: manhattan_ap
            value: 79.98140000000001
          - type: euclidean_accuracy
            value: 88.0789
          - type: euclidean_accuracy_threshold
            value: 52.9742
          - type: euclidean_f1
            value: 73.3591
          - type: euclidean_f1_threshold
            value: 56.4815
          - type: euclidean_precision
            value: 71.608
          - type: euclidean_recall
            value: 75.19789999999999
          - type: euclidean_ap
            value: 80.2656
          - type: dot_accuracy
            value: 88.0789
          - type: dot_accuracy_threshold
            value: 85.8034
          - type: dot_f1
            value: 73.40379999999999
          - type: dot_f1_threshold
            value: 84.3213
          - type: dot_precision
            value: 72.6544
          - type: dot_recall
            value: 74.16890000000001
          - type: dot_ap
            value: 80.32010000000001
          - type: max_accuracy
            value: 88.0789
          - type: max_f1
            value: 73.40379999999999
          - type: max_precision
            value: 72.6544
          - type: max_recall
            value: 75.3562
          - type: max_ap
            value: 80.32010000000001
          - type: main_score
            value: 80.32010000000001
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB TwitterURLCorpus (default)
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
          split: test
          type: mteb/twitterurlcorpus-pairclassification
        metrics:
          - type: similarity_accuracy
            value: 89.93090000000001
          - type: similarity_accuracy_threshold
            value: 82.1349
          - type: similarity_f1
            value: 80.1377
          - type: similarity_f1_threshold
            value: 80.5047
          - type: similarity_precision
            value: 77.1539
          - type: similarity_recall
            value: 83.3616
          - type: similarity_ap
            value: 87.6917
          - type: cosine_accuracy
            value: 89.93090000000001
          - type: cosine_accuracy_threshold
            value: 82.1349
          - type: cosine_f1
            value: 80.1377
          - type: cosine_f1_threshold
            value: 80.5047
          - type: cosine_precision
            value: 77.1539
          - type: cosine_recall
            value: 83.3616
          - type: cosine_ap
            value: 87.6917
          - type: manhattan_accuracy
            value: 89.86880000000001
          - type: manhattan_accuracy_threshold
            value: 4882.7347
          - type: manhattan_f1
            value: 80.2323
          - type: manhattan_f1_threshold
            value: 5185.1944
          - type: manhattan_precision
            value: 76.74889999999999
          - type: manhattan_recall
            value: 84.0468
          - type: manhattan_ap
            value: 87.70750000000001
          - type: euclidean_accuracy
            value: 89.94640000000001
          - type: euclidean_accuracy_threshold
            value: 59.9149
          - type: euclidean_f1
            value: 80.1527
          - type: euclidean_f1_threshold
            value: 62.3611
          - type: euclidean_precision
            value: 77.2744
          - type: euclidean_recall
            value: 83.2538
          - type: euclidean_ap
            value: 87.6922
          - type: dot_accuracy
            value: 89.9038
          - type: dot_accuracy_threshold
            value: 82.53049999999999
          - type: dot_f1
            value: 80.0969
          - type: dot_f1_threshold
            value: 80.7285
          - type: dot_precision
            value: 77.5853
          - type: dot_recall
            value: 82.77640000000001
          - type: dot_ap
            value: 87.668
          - type: max_accuracy
            value: 89.94640000000001
          - type: max_f1
            value: 80.2323
          - type: max_precision
            value: 77.5853
          - type: max_recall
            value: 84.0468
          - type: max_ap
            value: 87.70750000000001
          - type: main_score
            value: 87.70750000000001
        task:
          type: PairClassification
datasets:
  - BAAI/Infinity-MM
  - HuggingFaceFW/fineweb-edu
language:
  - en
base_model:
  - dunzhang/stella_en_1.5B_v5
  - google/siglip-so400m-patch14-384
tags:
  - mteb

Introduction

Based on dunzhang/stella_en_1.5B_v5 and google/siglip-so400m-patch14-384.

It can encode both text and image.

Details is coming soon.

License

This model should not be used for any commercial purpose!