README.md

metadata

model-index:
  - name: iamgroot42/rover_nexus
    results:
      - dataset:
          config: en
          name: MTEB AmazonCounterfactualClassification (en)
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
          split: test
          type: mteb/amazon_counterfactual
        metrics:
          - type: accuracy
            value: 95.7761
          - type: f1
            value: 93.8227
          - type: f1_weighted
            value: 95.9368
          - type: ap
            value: 82.63589999999999
          - type: ap_weighted
            value: 82.63589999999999
          - type: main_score
            value: 95.7761
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB AmazonPolarityClassification (default)
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
          split: test
          type: mteb/amazon_polarity
        metrics:
          - type: accuracy
            value: 97.7143
          - type: f1
            value: 97.7143
          - type: f1_weighted
            value: 97.7143
          - type: ap
            value: 96.5356
          - type: ap_weighted
            value: 96.5356
          - type: main_score
            value: 97.7143
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB AmazonReviewsClassification (en)
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
          split: test
          type: mteb/amazon_reviews_multi
        metrics:
          - type: accuracy
            value: 63.617999999999995
          - type: f1
            value: 61.487199999999994
          - type: f1_weighted
            value: 61.487199999999994
          - type: main_score
            value: 63.617999999999995
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB ArguAna (default)
          revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
          split: test
          type: mteb/arguana
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            value: 75.39099999999999
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            value: 88.795
          - type: ndcg_at_5
            value: 89.634
          - type: ndcg_at_10
            value: 89.786
          - type: ndcg_at_20
            value: 89.786
          - type: ndcg_at_100
            value: 89.786
          - type: ndcg_at_1000
            value: 89.786
          - type: map_at_1
            value: 75.39099999999999
          - type: map_at_3
            value: 85.835
          - type: map_at_5
            value: 86.311
          - type: map_at_10
            value: 86.382
          - type: map_at_20
            value: 86.382
          - type: map_at_100
            value: 86.382
          - type: map_at_1000
            value: 86.382
          - type: recall_at_1
            value: 75.39099999999999
          - type: recall_at_3
            value: 97.226
          - type: recall_at_5
            value: 99.21799999999999
          - type: recall_at_10
            value: 99.644
          - type: recall_at_20
            value: 99.644
          - type: recall_at_100
            value: 99.644
          - type: recall_at_1000
            value: 99.644
          - type: precision_at_1
            value: 75.39099999999999
          - type: precision_at_3
            value: 32.409
          - type: precision_at_5
            value: 19.844
          - type: precision_at_10
            value: 9.964
          - type: precision_at_20
            value: 4.982
          - type: precision_at_100
            value: 0.996
          - type: precision_at_1000
            value: 0.1
          - type: mrr_at_1
            value: 76.2447
          - type: mrr_at_3
            value: 86.1783
          - type: mrr_at_5
            value: 86.6015
          - type: mrr_at_10
            value: 86.6844
          - type: mrr_at_20
            value: 86.6844
          - type: mrr_at_100
            value: 86.6844
          - type: mrr_at_1000
            value: 86.6844
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            value: -0.7014
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            value: -34.0713
          - type: nauc_ndcg_at_1_diff1
            value: 72.04
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            value: -0.7801
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            value: -40.4138
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            value: 69.7499
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          - type: nauc_ndcg_at_1000_diff1
            value: 69.7499
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            value: -34.0713
          - type: nauc_map_at_1_diff1
            value: 72.04
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            value: -37.9683
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            value: 70.2016
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            value: 0.0239
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            value: -35.9525
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            value: 0.1661
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            value: -35.551899999999996
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            value: 72.04
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            value: -3.8722
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            value: -72.8357
          - type: nauc_recall_at_3_diff1
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            value: 27.9653
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            value: 91.0821
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            value: 70.0735
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            value: 22.9874
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            value: 91.0821
          - type: nauc_recall_at_20_std
            value: 70.0735
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            value: 22.9874
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            value: 91.0821
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            value: 70.0735
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            value: 22.9874
          - type: nauc_recall_at_1000_max
            value: 91.0821
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            value: 70.0735
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            value: -0.7014
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            value: -34.0713
          - type: nauc_precision_at_1_diff1
            value: 72.04
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            value: -3.8722
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            value: -72.8357
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            value: 61.261500000000005
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            value: 27.9653
          - type: nauc_precision_at_5_std
            value: -25.6213
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            value: 43.013200000000005
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            value: 91.0821
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            value: 70.0735
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            value: 91.0821
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            value: 70.0735
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            value: 91.0821
          - type: nauc_precision_at_100_std
            value: 70.0735
          - type: nauc_precision_at_100_diff1
            value: 22.9874
          - type: nauc_precision_at_1000_max
            value: 91.0821
          - type: nauc_precision_at_1000_std
            value: 70.0735
          - type: nauc_precision_at_1000_diff1
            value: 22.9874
          - type: nauc_mrr_at_1_max
            value: -2.0376
          - type: nauc_mrr_at_1_std
            value: -34.260600000000004
          - type: nauc_mrr_at_1_diff1
            value: 69.606
          - type: nauc_mrr_at_3_max
            value: -2.3678999999999997
          - type: nauc_mrr_at_3_std
            value: -38.2381
          - type: nauc_mrr_at_3_diff1
            value: 67.3485
          - type: nauc_mrr_at_5_max
            value: -1.9768999999999999
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            value: -36.711
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            value: 67.2939
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            value: -1.7911
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            value: -36.1749
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          - type: nauc_mrr_at_20_max
            value: -1.7911
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            value: -36.1749
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            value: 67.3921
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            value: -1.7911
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            value: -36.1749
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            value: 67.3921
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            value: -1.7911
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            value: -36.1749
          - type: nauc_mrr_at_1000_diff1
            value: 67.3921
          - type: main_score
            value: 89.786
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB ArxivClusteringP2P (default)
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
          split: test
          type: mteb/arxiv-clustering-p2p
        metrics:
          - type: v_measure
            value: 57.1362
          - type: v_measure_std
            value: 14.7667
          - type: main_score
            value: 57.1362
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB ArxivClusteringS2S (default)
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
          split: test
          type: mteb/arxiv-clustering-s2s
        metrics:
          - type: v_measure
            value: 52.639199999999995
          - type: v_measure_std
            value: 15.049499999999998
          - type: main_score
            value: 52.639199999999995
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB AskUbuntuDupQuestions (default)
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
          split: test
          type: mteb/askubuntudupquestions-reranking
        metrics:
          - type: map
            value: 66.93430000000001
          - type: mrr
            value: 80.2153
          - type: nAUC_map_max
            value: 28.881600000000002
          - type: nAUC_map_std
            value: 27.9878
          - type: nAUC_map_diff1
            value: 15.101500000000001
          - type: nAUC_mrr_max
            value: 38.428200000000004
          - type: nAUC_mrr_std
            value: 32.2285
          - type: nAUC_mrr_diff1
            value: 18.8509
          - type: main_score
            value: 66.93430000000001
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB BIOSSES (default)
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
          split: test
          type: mteb/biosses-sts
        metrics:
          - type: pearson
            value: 89.4712
          - type: spearman
            value: 87.7044
          - type: cosine_pearson
            value: 89.4712
          - type: cosine_spearman
            value: 87.7044
          - type: manhattan_pearson
            value: 88.1497
          - type: manhattan_spearman
            value: 87.73570000000001
          - type: euclidean_pearson
            value: 87.9881
          - type: euclidean_spearman
            value: 87.7044
          - type: main_score
            value: 87.7044
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB Banking77Classification (default)
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
          split: test
          type: mteb/banking77
        metrics:
          - type: accuracy
            value: 93.8019
          - type: f1
            value: 93.7388
          - type: f1_weighted
            value: 93.7388
          - type: main_score
            value: 93.8019
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB BiorxivClusteringP2P (default)
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
          split: test
          type: mteb/biorxiv-clustering-p2p
        metrics:
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            value: 54.646300000000004
          - type: v_measure_std
            value: 1.2942
          - type: main_score
            value: 54.646300000000004
        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: 49.9505
          - type: v_measure_std
            value: 1.1009
          - type: main_score
            value: 49.9505
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB CQADupstackAndroidRetrieval (default)
          revision: f46a197baaae43b4f621051089b82a364682dfeb
          split: test
          type: mteb/cqadupstack-android
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          name: MTEB MTOPDomainClassification (en)
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
          split: test
          type: mteb/mtop_domain
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          name: MTEB MTOPIntentClassification (en)
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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          type: mteb/mtop_intent
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        task:
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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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          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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          name: MTEB MindSmallReranking (default)
          revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
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          name: MTEB NFCorpus (default)
          revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
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          type: mteb/nfcorpus
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        task:
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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
            value: 3.3381000000000003
          - type: main_score
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        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:
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      - dataset:
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          name: MTEB SCIDOCS (default)
          revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
          split: test
          type: mteb/scidocs
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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: cosine_pearson
            value: 86.1982
          - type: cosine_spearman
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          - type: manhattan_pearson
            value: 83.7364
          - type: manhattan_spearman
            value: 81.6094
          - type: euclidean_pearson
            value: 83.7609
          - type: euclidean_spearman
            value: 81.625
          - type: main_score
            value: 81.625
        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
            value: 78.5656
          - type: cosine_pearson
            value: 87.0088
          - type: cosine_spearman
            value: 78.5685
          - type: manhattan_pearson
            value: 83.6701
          - type: manhattan_spearman
            value: 78.5915
          - type: euclidean_pearson
            value: 83.65559999999999
          - type: euclidean_spearman
            value: 78.5685
          - type: main_score
            value: 78.5685
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS13 (default)
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
          split: test
          type: mteb/sts13-sts
        metrics:
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            value: 87.8312
          - type: spearman
            value: 88.1872
          - type: cosine_pearson
            value: 87.83109999999999
          - type: cosine_spearman
            value: 88.1872
          - type: manhattan_pearson
            value: 87.7746
          - type: manhattan_spearman
            value: 88.2053
          - type: euclidean_pearson
            value: 87.7815
          - type: euclidean_spearman
            value: 88.1872
          - type: main_score
            value: 88.1872
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS14 (default)
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
          split: test
          type: mteb/sts14-sts
        metrics:
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            value: 85.604
          - type: spearman
            value: 84.0718
          - type: cosine_pearson
            value: 85.604
          - type: cosine_spearman
            value: 84.0718
          - type: manhattan_pearson
            value: 84.5478
          - type: manhattan_spearman
            value: 84.0521
          - type: euclidean_pearson
            value: 84.5694
          - type: euclidean_spearman
            value: 84.0718
          - type: main_score
            value: 84.0718
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS15 (default)
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
          split: test
          type: mteb/sts15-sts
        metrics:
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            value: 89.01559999999999
          - type: spearman
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          - type: cosine_pearson
            value: 89.01559999999999
          - type: cosine_spearman
            value: 89.4459
          - type: manhattan_pearson
            value: 88.7875
          - type: manhattan_spearman
            value: 89.4203
          - type: euclidean_pearson
            value: 88.8119
          - type: euclidean_spearman
            value: 89.4459
          - type: main_score
            value: 89.4459
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS16 (default)
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
          split: test
          type: mteb/sts16-sts
        metrics:
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            value: 85.7279
          - type: spearman
            value: 86.3643
          - type: cosine_pearson
            value: 85.7279
          - type: cosine_spearman
            value: 86.3643
          - type: manhattan_pearson
            value: 85.9517
          - type: manhattan_spearman
            value: 86.355
          - type: euclidean_pearson
            value: 85.9339
          - type: euclidean_spearman
            value: 86.3643
          - type: main_score
            value: 86.3643
        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: 89.9783
          - type: spearman
            value: 89.3624
          - type: cosine_pearson
            value: 89.9783
          - type: cosine_spearman
            value: 89.3624
          - type: manhattan_pearson
            value: 89.7846
          - type: manhattan_spearman
            value: 89.3142
          - type: euclidean_pearson
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          - type: euclidean_spearman
            value: 89.3624
          - type: main_score
            value: 89.3624
        task:
          type: STS
      - dataset:
          config: en
          name: MTEB STS22 (en)
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
          split: test
          type: mteb/sts22-crosslingual-sts
        metrics:
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          - type: spearman
            value: 65.4776
          - type: cosine_pearson
            value: 64.6745
          - type: cosine_spearman
            value: 65.4776
          - type: manhattan_pearson
            value: 65.6748
          - type: manhattan_spearman
            value: 65.3413
          - type: euclidean_pearson
            value: 65.7655
          - type: euclidean_spearman
            value: 65.4776
          - type: main_score
            value: 65.4776
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STSBenchmark (default)
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
          split: test
          type: mteb/stsbenchmark-sts
        metrics:
          - type: pearson
            value: 87.724
          - type: spearman
            value: 88.3237
          - type: cosine_pearson
            value: 87.724
          - type: cosine_spearman
            value: 88.3237
          - type: manhattan_pearson
            value: 87.9269
          - type: manhattan_spearman
            value: 88.301
          - type: euclidean_pearson
            value: 87.9367
          - type: euclidean_spearman
            value: 88.3237
          - type: main_score
            value: 88.3237
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB SciDocsRR (default)
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
          split: test
          type: mteb/scidocs-reranking
        metrics:
          - type: map
            value: 86.7192
          - type: mrr
            value: 96.4221
          - type: nAUC_map_max
            value: 43.437799999999996
          - type: nAUC_map_std
            value: 67.55980000000001
          - type: nAUC_map_diff1
            value: 0.6785
          - type: nAUC_mrr_max
            value: 83.50840000000001
          - type: nAUC_mrr_std
            value: 84.7092
          - type: nAUC_mrr_diff1
            value: 45.8165
          - type: main_score
            value: 86.7192
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB SciFact (default)
          revision: 0228b52cf27578f30900b9e5271d331663a030d7
          split: test
          type: mteb/scifact
        metrics:
          - type: ndcg_at_1
            value: 72.333
          - type: ndcg_at_3
            value: 80.896
          - type: ndcg_at_5
            value: 83.758
          - type: ndcg_at_10
            value: 85.088
          - type: ndcg_at_20
            value: 85.464
          - type: ndcg_at_100
            value: 85.637
          - type: ndcg_at_1000
            value: 85.637
          - type: map_at_1
            value: 69.467
          - type: map_at_3
            value: 77.969
          - type: map_at_5
            value: 80.03
          - type: map_at_10
            value: 80.726
          - type: map_at_20
            value: 80.87299999999999
          - type: map_at_100
            value: 80.892
          - type: map_at_1000
            value: 80.892
          - type: recall_at_1
            value: 69.467
          - type: recall_at_3
            value: 86.861
          - type: recall_at_5
            value: 93.95
          - type: recall_at_10
            value: 97.667
          - type: recall_at_20
            value: 99
          - type: recall_at_100
            value: 100
          - type: recall_at_1000
            value: 100
          - type: precision_at_1
            value: 72.333
          - type: precision_at_3
            value: 31.667
          - type: precision_at_5
            value: 20.867
          - type: precision_at_10
            value: 11
          - type: precision_at_20
            value: 5.6000000000000005
          - type: precision_at_100
            value: 1.13
          - type: precision_at_1000
            value: 0.11299999999999999
          - type: mrr_at_1
            value: 72.3333
          - type: mrr_at_3
            value: 79.2222
          - type: mrr_at_5
            value: 80.7889
          - type: mrr_at_10
            value: 81.2286
          - type: mrr_at_20
            value: 81.2656
          - type: mrr_at_100
            value: 81.2847
          - type: mrr_at_1000
            value: 81.2847
          - type: nauc_ndcg_at_1_max
            value: 38.9574
          - type: nauc_ndcg_at_1_std
            value: -0.1477
          - type: nauc_ndcg_at_1_diff1
            value: 76.0676
          - type: nauc_ndcg_at_3_max
            value: 43.899100000000004
          - type: nauc_ndcg_at_3_std
            value: 1.3967
          - type: nauc_ndcg_at_3_diff1
            value: 76.5965
          - type: nauc_ndcg_at_5_max
            value: 42.2858
          - type: nauc_ndcg_at_5_std
            value: -0.0241
          - type: nauc_ndcg_at_5_diff1
            value: 76.1049
          - type: nauc_ndcg_at_10_max
            value: 42.381
          - type: nauc_ndcg_at_10_std
            value: 2.6438
          - type: nauc_ndcg_at_10_diff1
            value: 75.9975
          - type: nauc_ndcg_at_20_max
            value: 42.9424
          - type: nauc_ndcg_at_20_std
            value: 2.8966
          - type: nauc_ndcg_at_20_diff1
            value: 76.175
          - type: nauc_ndcg_at_100_max
            value: 42.854
          - type: nauc_ndcg_at_100_std
            value: 2.8745
          - type: nauc_ndcg_at_100_diff1
            value: 75.9101
          - type: nauc_ndcg_at_1000_max
            value: 42.854
          - type: nauc_ndcg_at_1000_std
            value: 2.8745
          - type: nauc_ndcg_at_1000_diff1
            value: 75.9101
          - type: nauc_map_at_1_max
            value: 33.055299999999995
          - type: nauc_map_at_1_std
            value: -7.5394000000000005
          - type: nauc_map_at_1_diff1
            value: 77.3494
          - type: nauc_map_at_3_max
            value: 40.9863
          - type: nauc_map_at_3_std
            value: -1.8884
          - type: nauc_map_at_3_diff1
            value: 77.1306
          - type: nauc_map_at_5_max
            value: 41.2322
          - type: nauc_map_at_5_std
            value: -0.3544
          - type: nauc_map_at_5_diff1
            value: 76.129
          - type: nauc_map_at_10_max
            value: 41.6711
          - type: nauc_map_at_10_std
            value: 1.4658
          - type: nauc_map_at_10_diff1
            value: 75.9733
          - type: nauc_map_at_20_max
            value: 41.856500000000004
          - type: nauc_map_at_20_std
            value: 1.6687
          - type: nauc_map_at_20_diff1
            value: 75.9273
          - type: nauc_map_at_100_max
            value: 41.8402
          - type: nauc_map_at_100_std
            value: 1.6459000000000001
          - type: nauc_map_at_100_diff1
            value: 75.9041
          - type: nauc_map_at_1000_max
            value: 41.8402
          - type: nauc_map_at_1000_std
            value: 1.6459000000000001
          - type: nauc_map_at_1000_diff1
            value: 75.9041
          - type: nauc_recall_at_1_max
            value: 33.055299999999995
          - type: nauc_recall_at_1_std
            value: -7.5394000000000005
          - type: nauc_recall_at_1_diff1
            value: 77.3494
          - type: nauc_recall_at_3_max
            value: 46.97
          - type: nauc_recall_at_3_std
            value: -0.4234
          - type: nauc_recall_at_3_diff1
            value: 77.9507
          - type: nauc_recall_at_5_max
            value: 42.5995
          - type: nauc_recall_at_5_std
            value: -9.1448
          - type: nauc_recall_at_5_diff1
            value: 75.5352
          - type: nauc_recall_at_10_max
            value: 34.3737
          - type: nauc_recall_at_10_std
            value: 1.1004
          - type: nauc_recall_at_10_diff1
            value: 77.2476
          - type: nauc_recall_at_20_max
            value: 47.3389
          - type: nauc_recall_at_20_std
            value: -0.9648
          - type: nauc_recall_at_20_diff1
            value: 95.6427
          - type: nauc_recall_at_100_max
            value: .nan
          - type: nauc_recall_at_100_std
            value: .nan
          - type: nauc_recall_at_100_diff1
            value: .nan
          - 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: 38.9574
          - type: nauc_precision_at_1_std
            value: -0.1477
          - type: nauc_precision_at_1_diff1
            value: 76.0676
          - type: nauc_precision_at_3_max
            value: 35.383199999999995
          - type: nauc_precision_at_3_std
            value: 24.918000000000003
          - type: nauc_precision_at_3_diff1
            value: 19.4821
          - type: nauc_precision_at_5_max
            value: 25.366699999999998
          - type: nauc_precision_at_5_std
            value: 36.871900000000004
          - type: nauc_precision_at_5_diff1
            value: -13.1237
          - type: nauc_precision_at_10_max
            value: 18.4563
          - type: nauc_precision_at_10_std
            value: 48.8215
          - type: nauc_precision_at_10_diff1
            value: -32.047
          - type: nauc_precision_at_20_max
            value: 15.966
          - type: nauc_precision_at_20_std
            value: 47.1139
          - type: nauc_precision_at_20_diff1
            value: -36.0122
          - type: nauc_precision_at_100_max
            value: 14.579
          - type: nauc_precision_at_100_std
            value: 49.2394
          - type: nauc_precision_at_100_diff1
            value: -41.8326
          - type: nauc_precision_at_1000_max
            value: 14.579
          - type: nauc_precision_at_1000_std
            value: 49.2394
          - type: nauc_precision_at_1000_diff1
            value: -41.8326
          - type: nauc_mrr_at_1_max
            value: 38.9574
          - type: nauc_mrr_at_1_std
            value: -0.1477
          - type: nauc_mrr_at_1_diff1
            value: 76.0676
          - type: nauc_mrr_at_3_max
            value: 43.9004
          - type: nauc_mrr_at_3_std
            value: 3.3175999999999997
          - type: nauc_mrr_at_3_diff1
            value: 76.16969999999999
          - type: nauc_mrr_at_5_max
            value: 43.113600000000005
          - type: nauc_mrr_at_5_std
            value: 2.5391
          - type: nauc_mrr_at_5_diff1
            value: 76.0292
          - type: nauc_mrr_at_10_max
            value: 42.613099999999996
          - type: nauc_mrr_at_10_std
            value: 2.5191000000000003
          - type: nauc_mrr_at_10_diff1
            value: 75.9944
          - type: nauc_mrr_at_20_max
            value: 42.5833
          - type: nauc_mrr_at_20_std
            value: 2.3678999999999997
          - type: nauc_mrr_at_20_diff1
            value: 76.0872
          - type: nauc_mrr_at_100_max
            value: 42.5675
          - type: nauc_mrr_at_100_std
            value: 2.3453999999999997
          - type: nauc_mrr_at_100_diff1
            value: 76.0638
          - type: nauc_mrr_at_1000_max
            value: 42.5675
          - type: nauc_mrr_at_1000_std
            value: 2.3453999999999997
          - type: nauc_mrr_at_1000_diff1
            value: 76.0638
          - type: main_score
            value: 85.088
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB SprintDuplicateQuestions (default)
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
          split: test
          type: mteb/sprintduplicatequestions-pairclassification
        metrics:
          - type: similarity_accuracy
            value: 99.7129
          - type: similarity_accuracy_threshold
            value: 76.1587
          - type: similarity_f1
            value: 84.6398
          - type: similarity_f1_threshold
            value: 76.1587
          - type: similarity_precision
            value: 89.97749999999999
          - type: similarity_recall
            value: 79.9
          - type: similarity_ap
            value: 92.08539999999999
          - type: cosine_accuracy
            value: 99.7129
          - type: cosine_accuracy_threshold
            value: 76.1587
          - type: cosine_f1
            value: 84.6398
          - type: cosine_f1_threshold
            value: 76.1587
          - type: cosine_precision
            value: 89.97749999999999
          - type: cosine_recall
            value: 79.9
          - type: cosine_ap
            value: 92.08539999999999
          - type: manhattan_accuracy
            value: 99.7139
          - type: manhattan_accuracy_threshold
            value: 2490.9832
          - type: manhattan_f1
            value: 84.6522
          - type: manhattan_f1_threshold
            value: 2490.9832
          - type: manhattan_precision
            value: 90.2605
          - type: manhattan_recall
            value: 79.7
          - type: manhattan_ap
            value: 92.08
          - type: euclidean_accuracy
            value: 99.7129
          - type: euclidean_accuracy_threshold
            value: 69.0526
          - type: euclidean_f1
            value: 84.6398
          - type: euclidean_f1_threshold
            value: 69.0526
          - type: euclidean_precision
            value: 89.97749999999999
          - type: euclidean_recall
            value: 79.9
          - type: euclidean_ap
            value: 92.08539999999999
          - type: dot_accuracy
            value: 99.7129
          - type: dot_accuracy_threshold
            value: 76.1587
          - type: dot_f1
            value: 84.6398
          - type: dot_f1_threshold
            value: 76.1587
          - type: dot_precision
            value: 89.97749999999999
          - type: dot_recall
            value: 79.9
          - type: dot_ap
            value: 92.08539999999999
          - type: max_accuracy
            value: 99.7139
          - type: max_f1
            value: 84.6522
          - type: max_precision
            value: 90.2605
          - type: max_recall
            value: 79.9
          - type: max_ap
            value: 92.08539999999999
          - type: main_score
            value: 92.08539999999999
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB StackExchangeClustering (default)
          revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
          split: test
          type: mteb/stackexchange-clustering
        metrics:
          - type: v_measure
            value: 82.0328
          - type: v_measure_std
            value: 3.1285
          - type: main_score
            value: 82.0328
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB StackExchangeClusteringP2P (default)
          revision: 815ca46b2622cec33ccafc3735d572c266efdb44
          split: test
          type: mteb/stackexchange-clustering-p2p
        metrics:
          - type: v_measure
            value: 48.1665
          - type: v_measure_std
            value: 1.5214
          - type: main_score
            value: 48.1665
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB StackOverflowDupQuestions (default)
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
          split: test
          type: mteb/stackoverflowdupquestions-reranking
        metrics:
          - type: map
            value: 54.68769999999999
          - type: mrr
            value: 55.675
          - type: nAUC_map_max
            value: 10.8063
          - type: nAUC_map_std
            value: 8.713600000000001
          - type: nAUC_map_diff1
            value: 39.5509
          - type: nAUC_mrr_max
            value: 11.930399999999999
          - type: nAUC_mrr_std
            value: 9.6175
          - type: nAUC_mrr_diff1
            value: 40.0268
          - type: main_score
            value: 54.68769999999999
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB SummEval (default)
          revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
          split: test
          type: mteb/summeval
        metrics:
          - type: pearson
            value: 30.859399999999997
          - type: spearman
            value: 30.4465
          - type: cosine_spearman
            value: 30.4465
          - type: cosine_pearson
            value: 30.859399999999997
          - type: dot_spearman
            value: 30.4465
          - type: dot_pearson
            value: 30.859399999999997
          - type: main_score
            value: 30.4465
        task:
          type: Summarization
      - dataset:
          config: default
          name: MTEB TRECCOVID (default)
          revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
          split: test
          type: mteb/trec-covid
        metrics:
          - type: ndcg_at_1
            value: 88
          - type: ndcg_at_3
            value: 84.358
          - type: ndcg_at_5
            value: 82.887
          - type: ndcg_at_10
            value: 82.747
          - type: ndcg_at_20
            value: 80.381
          - type: ndcg_at_100
            value: 67.338
          - type: ndcg_at_1000
            value: 53.469
          - type: map_at_1
            value: 0.242
          - type: map_at_3
            value: 0.674
          - type: map_at_5
            value: 1.082
          - type: map_at_10
            value: 2.109
          - type: map_at_20
            value: 3.955
          - type: map_at_100
            value: 14.123
          - type: map_at_1000
            value: 31.130000000000003
          - type: recall_at_1
            value: 0.242
          - type: recall_at_3
            value: 0.685
          - type: recall_at_5
            value: 1.125
          - type: recall_at_10
            value: 2.257
          - type: recall_at_20
            value: 4.352
          - type: recall_at_100
            value: 17.044
          - type: recall_at_1000
            value: 47.494
          - type: precision_at_1
            value: 92
          - type: precision_at_3
            value: 88
          - type: precision_at_5
            value: 86.4
          - type: precision_at_10
            value: 86.4
          - type: precision_at_20
            value: 84.5
          - type: precision_at_100
            value: 69.58
          - type: precision_at_1000
            value: 22.56
          - type: mrr_at_1
            value: 92
          - type: mrr_at_3
            value: 95
          - type: mrr_at_5
            value: 95.39999999999999
          - type: mrr_at_10
            value: 95.39999999999999
          - type: mrr_at_20
            value: 95.39999999999999
          - type: mrr_at_100
            value: 95.39999999999999
          - type: mrr_at_1000
            value: 95.39999999999999
          - type: nauc_ndcg_at_1_max
            value: -34.918
          - type: nauc_ndcg_at_1_std
            value: 64.9171
          - type: nauc_ndcg_at_1_diff1
            value: -25.7963
          - type: nauc_ndcg_at_3_max
            value: -16.3991
          - type: nauc_ndcg_at_3_std
            value: 54.9104
          - type: nauc_ndcg_at_3_diff1
            value: -26.3455
          - type: nauc_ndcg_at_5_max
            value: -0.9459000000000001
          - type: nauc_ndcg_at_5_std
            value: 53.632999999999996
          - type: nauc_ndcg_at_5_diff1
            value: -27.479
          - type: nauc_ndcg_at_10_max
            value: 10.2555
          - type: nauc_ndcg_at_10_std
            value: 50.5127
          - type: nauc_ndcg_at_10_diff1
            value: -29.7344
          - type: nauc_ndcg_at_20_max
            value: 16.7577
          - type: nauc_ndcg_at_20_std
            value: 49.2737
          - type: nauc_ndcg_at_20_diff1
            value: -30.2252
          - type: nauc_ndcg_at_100_max
            value: 17.642
          - type: nauc_ndcg_at_100_std
            value: 62.1844
          - type: nauc_ndcg_at_100_diff1
            value: -24.3677
          - type: nauc_ndcg_at_1000_max
            value: 3.9043
          - type: nauc_ndcg_at_1000_std
            value: 74.6529
          - type: nauc_ndcg_at_1000_diff1
            value: -19.9165
          - type: nauc_map_at_1_max
            value: 8.2594
          - type: nauc_map_at_1_std
            value: 15.198300000000001
          - type: nauc_map_at_1_diff1
            value: 9.5579
          - type: nauc_map_at_3_max
            value: 12.1452
          - type: nauc_map_at_3_std
            value: 26.5818
          - type: nauc_map_at_3_diff1
            value: -5.2755
          - type: nauc_map_at_5_max
            value: 14.930499999999999
          - type: nauc_map_at_5_std
            value: 29.0041
          - type: nauc_map_at_5_diff1
            value: -7.671500000000001
          - type: nauc_map_at_10_max
            value: 18.997
          - type: nauc_map_at_10_std
            value: 28.7638
          - type: nauc_map_at_10_diff1
            value: -9.5023
          - type: nauc_map_at_20_max
            value: 20.1326
          - type: nauc_map_at_20_std
            value: 25.7159
          - type: nauc_map_at_20_diff1
            value: -6.8202
          - type: nauc_map_at_100_max
            value: 19.9081
          - type: nauc_map_at_100_std
            value: 44.6124
          - type: nauc_map_at_100_diff1
            value: -4.2406
          - type: nauc_map_at_1000_max
            value: 9.8118
          - type: nauc_map_at_1000_std
            value: 76.6769
          - type: nauc_map_at_1000_diff1
            value: -18.8289
          - type: nauc_recall_at_1_max
            value: 8.2594
          - type: nauc_recall_at_1_std
            value: 15.198300000000001
          - type: nauc_recall_at_1_diff1
            value: 9.5579
          - type: nauc_recall_at_3_max
            value: 12.8061
          - type: nauc_recall_at_3_std
            value: 24.857000000000003
          - type: nauc_recall_at_3_diff1
            value: -2.7226
          - type: nauc_recall_at_5_max
            value: 15.4786
          - type: nauc_recall_at_5_std
            value: 24.0416
          - type: nauc_recall_at_5_diff1
            value: -1.3981999999999999
          - type: nauc_recall_at_10_max
            value: 19.867099999999997
          - type: nauc_recall_at_10_std
            value: 21.4911
          - type: nauc_recall_at_10_diff1
            value: -0.906
          - type: nauc_recall_at_20_max
            value: 18.826999999999998
          - type: nauc_recall_at_20_std
            value: 16.9991
          - type: nauc_recall_at_20_diff1
            value: 3.3348999999999998
          - type: nauc_recall_at_100_max
            value: 17.843
          - type: nauc_recall_at_100_std
            value: 34.0944
          - type: nauc_recall_at_100_diff1
            value: 2.2885
          - type: nauc_recall_at_1000_max
            value: -0.7106
          - type: nauc_recall_at_1000_std
            value: 69.6537
          - type: nauc_recall_at_1000_diff1
            value: -19.310299999999998
          - type: nauc_precision_at_1_max
            value: -7.0495
          - type: nauc_precision_at_1_std
            value: 75.3735
          - type: nauc_precision_at_1_diff1
            value: -52.91780000000001
          - type: nauc_precision_at_3_max
            value: 7.803
          - type: nauc_precision_at_3_std
            value: 72.3574
          - type: nauc_precision_at_3_diff1
            value: -56.178200000000004
          - type: nauc_precision_at_5_max
            value: 10.770100000000001
          - type: nauc_precision_at_5_std
            value: 69.3859
          - type: nauc_precision_at_5_diff1
            value: -51.3122
          - type: nauc_precision_at_10_max
            value: 22.3857
          - type: nauc_precision_at_10_std
            value: 60.5115
          - type: nauc_precision_at_10_diff1
            value: -45.9797
          - type: nauc_precision_at_20_max
            value: 22.3038
          - type: nauc_precision_at_20_std
            value: 49.4557
          - type: nauc_precision_at_20_diff1
            value: -36.5443
          - type: nauc_precision_at_100_max
            value: 16.0115
          - type: nauc_precision_at_100_std
            value: 61.7637
          - type: nauc_precision_at_100_diff1
            value: -26.223800000000004
          - type: nauc_precision_at_1000_max
            value: -3.9560999999999997
          - type: nauc_precision_at_1000_std
            value: 38.3159
          - type: nauc_precision_at_1000_diff1
            value: -24.9664
          - type: nauc_mrr_at_1_max
            value: -7.0495
          - type: nauc_mrr_at_1_std
            value: 75.3735
          - type: nauc_mrr_at_1_diff1
            value: -52.91780000000001
          - type: nauc_mrr_at_3_max
            value: -16.909399999999998
          - type: nauc_mrr_at_3_std
            value: 77.6844
          - type: nauc_mrr_at_3_diff1
            value: -35.1727
          - type: nauc_mrr_at_5_max
            value: -13.4799
          - type: nauc_mrr_at_5_std
            value: 76.8806
          - type: nauc_mrr_at_5_diff1
            value: -41.3449
          - type: nauc_mrr_at_10_max
            value: -13.4799
          - type: nauc_mrr_at_10_std
            value: 76.8806
          - type: nauc_mrr_at_10_diff1
            value: -41.3449
          - type: nauc_mrr_at_20_max
            value: -13.4799
          - type: nauc_mrr_at_20_std
            value: 76.8806
          - type: nauc_mrr_at_20_diff1
            value: -41.3449
          - type: nauc_mrr_at_100_max
            value: -13.4799
          - type: nauc_mrr_at_100_std
            value: 76.8806
          - type: nauc_mrr_at_100_diff1
            value: -41.3449
          - type: nauc_mrr_at_1000_max
            value: -13.4799
          - type: nauc_mrr_at_1000_std
            value: 76.8806
          - type: nauc_mrr_at_1000_diff1
            value: -41.3449
          - type: main_score
            value: 82.747
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB Touche2020 (default)
          revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
          split: test
          type: mteb/touche2020
        metrics:
          - type: ndcg_at_1
            value: 54.081999999999994
          - type: ndcg_at_3
            value: 47.305
          - type: ndcg_at_5
            value: 42.753
          - type: ndcg_at_10
            value: 39.385999999999996
          - type: ndcg_at_20
            value: 38.999
          - type: ndcg_at_100
            value: 47.315000000000005
          - type: ndcg_at_1000
            value: 56.769999999999996
          - type: map_at_1
            value: 4.228
          - type: map_at_3
            value: 9.459
          - type: map_at_5
            value: 13.135
          - type: map_at_10
            value: 18.221
          - type: map_at_20
            value: 21.956
          - type: map_at_100
            value: 25.232
          - type: map_at_1000
            value: 26.582
          - type: recall_at_1
            value: 4.228
          - type: recall_at_3
            value: 10.658
          - type: recall_at_5
            value: 15.754000000000001
          - type: recall_at_10
            value: 24.826
          - type: recall_at_20
            value: 34.111999999999995
          - type: recall_at_100
            value: 52.797000000000004
          - type: recall_at_1000
            value: 82.733
          - type: precision_at_1
            value: 59.184000000000005
          - type: precision_at_3
            value: 48.980000000000004
          - type: precision_at_5
            value: 42.041000000000004
          - type: precision_at_10
            value: 34.489999999999995
          - type: precision_at_20
            value: 25.306
          - type: precision_at_100
            value: 8.735
          - type: precision_at_1000
            value: 1.52
          - type: mrr_at_1
            value: 59.183699999999995
          - type: mrr_at_3
            value: 68.0272
          - type: mrr_at_5
            value: 68.9456
          - type: mrr_at_10
            value: 70.5491
          - type: mrr_at_20
            value: 70.8804
          - type: mrr_at_100
            value: 70.9484
          - type: mrr_at_1000
            value: 70.9484
          - type: nauc_ndcg_at_1_max
            value: 14.2895
          - type: nauc_ndcg_at_1_std
            value: 15.140500000000001
          - type: nauc_ndcg_at_1_diff1
            value: 14.7508
          - type: nauc_ndcg_at_3_max
            value: -3.0176000000000003
          - type: nauc_ndcg_at_3_std
            value: 13.8234
          - type: nauc_ndcg_at_3_diff1
            value: 18.348
          - type: nauc_ndcg_at_5_max
            value: -3.2785
          - type: nauc_ndcg_at_5_std
            value: 6.0827
          - type: nauc_ndcg_at_5_diff1
            value: 19.9722
          - type: nauc_ndcg_at_10_max
            value: 0.1953
          - type: nauc_ndcg_at_10_std
            value: 4.0055
          - type: nauc_ndcg_at_10_diff1
            value: 19.0452
          - type: nauc_ndcg_at_20_max
            value: -4.6253
          - type: nauc_ndcg_at_20_std
            value: 12.3256
          - type: nauc_ndcg_at_20_diff1
            value: 16.514899999999997
          - type: nauc_ndcg_at_100_max
            value: -1.4607
          - type: nauc_ndcg_at_100_std
            value: 27.7821
          - type: nauc_ndcg_at_100_diff1
            value: 14.4344
          - type: nauc_ndcg_at_1000_max
            value: 8.2149
          - type: nauc_ndcg_at_1000_std
            value: 33.6054
          - type: nauc_ndcg_at_1000_diff1
            value: 15.9317
          - type: nauc_map_at_1_max
            value: -3.3970000000000002
          - type: nauc_map_at_1_std
            value: 2.5947999999999998
          - type: nauc_map_at_1_diff1
            value: 32.8068
          - type: nauc_map_at_3_max
            value: -5.5302999999999995
          - type: nauc_map_at_3_std
            value: 2.9596999999999998
          - type: nauc_map_at_3_diff1
            value: 35.8593
          - type: nauc_map_at_5_max
            value: -9.0474
          - type: nauc_map_at_5_std
            value: -3.2526
          - type: nauc_map_at_5_diff1
            value: 39.263
          - type: nauc_map_at_10_max
            value: -4.7221
          - type: nauc_map_at_10_std
            value: -1.3847
          - type: nauc_map_at_10_diff1
            value: 32.1957
          - type: nauc_map_at_20_max
            value: -2.9691
          - type: nauc_map_at_20_std
            value: 4.922
          - type: nauc_map_at_20_diff1
            value: 24.6601
          - type: nauc_map_at_100_max
            value: -2.7695999999999996
          - type: nauc_map_at_100_std
            value: 14.2812
          - type: nauc_map_at_100_diff1
            value: 22.034599999999998
          - type: nauc_map_at_1000_max
            value: -1.4055
          - type: nauc_map_at_1000_std
            value: 15.9695
          - type: nauc_map_at_1000_diff1
            value: 22.348000000000003
          - type: nauc_recall_at_1_max
            value: -3.3970000000000002
          - type: nauc_recall_at_1_std
            value: 2.5947999999999998
          - type: nauc_recall_at_1_diff1
            value: 32.8068
          - type: nauc_recall_at_3_max
            value: -9.774
          - type: nauc_recall_at_3_std
            value: 4.5374
          - type: nauc_recall_at_3_diff1
            value: 36.1682
          - type: nauc_recall_at_5_max
            value: -12.770999999999999
          - type: nauc_recall_at_5_std
            value: -3.5658000000000003
          - type: nauc_recall_at_5_diff1
            value: 38.3296
          - type: nauc_recall_at_10_max
            value: -8.0558
          - type: nauc_recall_at_10_std
            value: 0.024800000000000003
          - type: nauc_recall_at_10_diff1
            value: 26.5627
          - type: nauc_recall_at_20_max
            value: -9.7074
          - type: nauc_recall_at_20_std
            value: 15.120700000000001
          - type: nauc_recall_at_20_diff1
            value: 14.4759
          - type: nauc_recall_at_100_max
            value: -5.7863999999999995
          - type: nauc_recall_at_100_std
            value: 40.9887
          - type: nauc_recall_at_100_diff1
            value: 6.2395
          - type: nauc_recall_at_1000_max
            value: 27.007599999999996
          - type: nauc_recall_at_1000_std
            value: 63.81250000000001
          - type: nauc_recall_at_1000_diff1
            value: 4.8708
          - type: nauc_precision_at_1_max
            value: 12.7638
          - type: nauc_precision_at_1_std
            value: 22.0685
          - type: nauc_precision_at_1_diff1
            value: 11.7399
          - type: nauc_precision_at_3_max
            value: -8.608699999999999
          - type: nauc_precision_at_3_std
            value: 15.267900000000001
          - type: nauc_precision_at_3_diff1
            value: 16.5462
          - type: nauc_precision_at_5_max
            value: -7.2258000000000004
          - type: nauc_precision_at_5_std
            value: 1.7056000000000002
          - type: nauc_precision_at_5_diff1
            value: 17.8119
          - type: nauc_precision_at_10_max
            value: -0.0044
          - type: nauc_precision_at_10_std
            value: 4.0112000000000005
          - type: nauc_precision_at_10_diff1
            value: 3.5520000000000005
          - type: nauc_precision_at_20_max
            value: -2.7077
          - type: nauc_precision_at_20_std
            value: 34.144000000000005
          - type: nauc_precision_at_20_diff1
            value: -14.833499999999999
          - type: nauc_precision_at_100_max
            value: 12.6555
          - type: nauc_precision_at_100_std
            value: 59.5965
          - type: nauc_precision_at_100_diff1
            value: -24.3212
          - type: nauc_precision_at_1000_max
            value: 38.3951
          - type: nauc_precision_at_1000_std
            value: 32.5441
          - type: nauc_precision_at_1000_diff1
            value: -31.4919
          - type: nauc_mrr_at_1_max
            value: 12.7638
          - type: nauc_mrr_at_1_std
            value: 22.0685
          - type: nauc_mrr_at_1_diff1
            value: 11.7399
          - type: nauc_mrr_at_3_max
            value: 2.6993
          - type: nauc_mrr_at_3_std
            value: 24.444499999999998
          - type: nauc_mrr_at_3_diff1
            value: 8.2343
          - type: nauc_mrr_at_5_max
            value: 5.6594999999999995
          - type: nauc_mrr_at_5_std
            value: 22.1027
          - type: nauc_mrr_at_5_diff1
            value: 5.3648
          - type: nauc_mrr_at_10_max
            value: 5.6309
          - type: nauc_mrr_at_10_std
            value: 23.0288
          - type: nauc_mrr_at_10_diff1
            value: 5.2199
          - type: nauc_mrr_at_20_max
            value: 4.8424000000000005
          - type: nauc_mrr_at_20_std
            value: 23.6116
          - type: nauc_mrr_at_20_diff1
            value: 6.7553
          - type: nauc_mrr_at_100_max
            value: 5.3414
          - type: nauc_mrr_at_100_std
            value: 23.394000000000002
          - type: nauc_mrr_at_100_diff1
            value: 6.7397
          - type: nauc_mrr_at_1000_max
            value: 5.3414
          - type: nauc_mrr_at_1000_std
            value: 23.394000000000002
          - type: nauc_mrr_at_1000_diff1
            value: 6.7397
          - type: main_score
            value: 39.385999999999996
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB ToxicConversationsClassification (default)
          revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
          split: test
          type: mteb/toxic_conversations_50k
        metrics:
          - type: accuracy
            value: 97.5928
          - type: f1
            value: 92.9042
          - type: f1_weighted
            value: 97.7586
          - type: ap
            value: 77.5261
          - type: ap_weighted
            value: 77.5261
          - type: main_score
            value: 97.5928
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB TweetSentimentExtractionClassification (default)
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
          split: test
          type: mteb/tweet_sentiment_extraction
        metrics:
          - type: accuracy
            value: 88.2343
          - type: f1
            value: 88.4321
          - type: f1_weighted
            value: 88.13069999999999
          - type: main_score
            value: 88.2343
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB TwentyNewsgroupsClustering (default)
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
          split: test
          type: mteb/twentynewsgroups-clustering
        metrics:
          - type: v_measure
            value: 83.486
          - type: v_measure_std
            value: 2.0008000000000004
          - type: main_score
            value: 83.486
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB TwitterSemEval2015 (default)
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
          split: test
          type: mteb/twittersemeval2015-pairclassification
        metrics:
          - type: similarity_accuracy
            value: 87.7988
          - type: similarity_accuracy_threshold
            value: 74.7442
          - type: similarity_f1
            value: 72.9982
          - type: similarity_f1_threshold
            value: 71.073
          - type: similarity_precision
            value: 67.4804
          - type: similarity_recall
            value: 79.4987
          - type: similarity_ap
            value: 79.1752
          - type: cosine_accuracy
            value: 87.7988
          - type: cosine_accuracy_threshold
            value: 74.7442
          - type: cosine_f1
            value: 72.9982
          - type: cosine_f1_threshold
            value: 71.073
          - type: cosine_precision
            value: 67.4804
          - type: cosine_recall
            value: 79.4987
          - type: cosine_ap
            value: 79.1752
          - type: manhattan_accuracy
            value: 87.8107
          - type: manhattan_accuracy_threshold
            value: 2587.3787
          - type: manhattan_f1
            value: 72.8159
          - type: manhattan_f1_threshold
            value: 2713.7127
          - type: manhattan_precision
            value: 69.176
          - type: manhattan_recall
            value: 76.8602
          - type: manhattan_ap
            value: 79.1243
          - type: euclidean_accuracy
            value: 87.7988
          - type: euclidean_accuracy_threshold
            value: 71.0715
          - type: euclidean_f1
            value: 72.9982
          - type: euclidean_f1_threshold
            value: 76.0618
          - type: euclidean_precision
            value: 67.4804
          - type: euclidean_recall
            value: 79.4987
          - type: euclidean_ap
            value: 79.1752
          - type: dot_accuracy
            value: 87.7988
          - type: dot_accuracy_threshold
            value: 74.7442
          - type: dot_f1
            value: 72.9982
          - type: dot_f1_threshold
            value: 71.073
          - type: dot_precision
            value: 67.4804
          - type: dot_recall
            value: 79.4987
          - type: dot_ap
            value: 79.1752
          - type: max_accuracy
            value: 87.8107
          - type: max_f1
            value: 72.9982
          - type: max_precision
            value: 69.176
          - type: max_recall
            value: 79.4987
          - type: max_ap
            value: 79.1752
          - type: main_score
            value: 79.1752
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB TwitterURLCorpus (default)
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
          split: test
          type: mteb/twitterurlcorpus-pairclassification
        metrics:
          - type: similarity_accuracy
            value: 89.4749
          - type: similarity_accuracy_threshold
            value: 73.03659999999999
          - type: similarity_f1
            value: 79.4416
          - type: similarity_f1_threshold
            value: 70.7413
          - type: similarity_precision
            value: 75.9696
          - type: similarity_recall
            value: 83.2461
          - type: similarity_ap
            value: 87.1156
          - type: cosine_accuracy
            value: 89.4749
          - type: cosine_accuracy_threshold
            value: 73.03659999999999
          - type: cosine_f1
            value: 79.4416
          - type: cosine_f1_threshold
            value: 70.7413
          - type: cosine_precision
            value: 75.9696
          - type: cosine_recall
            value: 83.2461
          - type: cosine_ap
            value: 87.1156
          - type: manhattan_accuracy
            value: 89.471
          - type: manhattan_accuracy_threshold
            value: 2630.4434
          - type: manhattan_f1
            value: 79.4078
          - type: manhattan_f1_threshold
            value: 2764.4342
          - type: manhattan_precision
            value: 75.7675
          - type: manhattan_recall
            value: 83.4155
          - type: manhattan_ap
            value: 87.0938
          - type: euclidean_accuracy
            value: 89.4749
          - type: euclidean_accuracy_threshold
            value: 73.4349
          - type: euclidean_f1
            value: 79.4416
          - type: euclidean_f1_threshold
            value: 76.4966
          - type: euclidean_precision
            value: 75.9696
          - type: euclidean_recall
            value: 83.2461
          - type: euclidean_ap
            value: 87.1156
          - type: dot_accuracy
            value: 89.4749
          - type: dot_accuracy_threshold
            value: 73.03659999999999
          - type: dot_f1
            value: 79.4416
          - type: dot_f1_threshold
            value: 70.7413
          - type: dot_precision
            value: 75.9696
          - type: dot_recall
            value: 83.2461
          - type: dot_ap
            value: 87.1156
          - type: max_accuracy
            value: 89.4749
          - type: max_f1
            value: 79.4416
          - type: max_precision
            value: 75.9696
          - type: max_recall
            value: 83.4155
          - type: max_ap
            value: 87.1156
          - type: main_score
            value: 87.1156
        task:
          type: PairClassification
tags:
  - mteb
  - sentence-similarity
  - sentence-transformers
  - Sentence Transformers
language:
  - en

license: mit

Usage

Code example

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

def average_pool(last_hidden_states: Tensor,
                 attention_mask: Tensor) -> Tensor:
    last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0)
    return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None]

input_texts = [
    "what is the capital of Japan?",
    "Kyoto",
    "Tokyo",
    "Beijing"
]

tokenizer = AutoTokenizer.from_pretrained("iamgroot42/rover_nexus")
model = AutoModel.from_pretrained("iamgroot42/rover_nexus")

# Tokenize the input texts
batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt')

outputs = model(**batch_dict)
embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask'])

# (Optionally) normalize embeddings
embeddings = F.normalize(embeddings, p=2, dim=1)
scores = (embeddings[:1] @ embeddings[1:].T) * 100
print(scores.tolist())

Use with sentence-transformers:

from sentence_transformers import SentenceTransformer
from sentence_transformers.util import cos_sim

sentences = ['That is a happy person', 'That is a sad person']

model = SentenceTransformer('iamgroot42/rover_nexus')
embeddings = model.encode(sentences)
print(cos_sim(embeddings[0], embeddings[1]))

Model training details and data will be uploaded soon!