winberta-large / README.md
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metadata
tags:
  - mteb
model-index:
  - name: winberta-large
    results:
      - task:
          type: STS
        dataset:
          type: C-MTEB/AFQMC
          name: MTEB AFQMC
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 41.77725389846057
          - type: cos_sim_spearman
            value: 46.70255351226939
          - type: euclidean_pearson
            value: 45.22550045993912
          - type: euclidean_spearman
            value: 46.70255351226939
          - type: manhattan_pearson
            value: 45.19405644988887
          - type: manhattan_spearman
            value: 46.680519207418264
      - task:
          type: STS
        dataset:
          type: C-MTEB/ATEC
          name: MTEB ATEC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 41.90208621690777
          - type: cos_sim_spearman
            value: 49.95255202729448
          - type: euclidean_pearson
            value: 49.756907552767956
          - type: euclidean_spearman
            value: 49.95255202729448
          - type: manhattan_pearson
            value: 49.75325413164269
          - type: manhattan_spearman
            value: 49.96252496785108
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (zh)
          config: zh
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 42.038000000000004
          - type: f1
            value: 40.20953065985179
      - task:
          type: STS
        dataset:
          type: C-MTEB/BQ
          name: MTEB BQ
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 54.24089984585099
          - type: cos_sim_spearman
            value: 56.075463873104766
          - type: euclidean_pearson
            value: 55.20252472986401
          - type: euclidean_spearman
            value: 56.075463873104766
          - type: manhattan_pearson
            value: 55.13086772848814
          - type: manhattan_spearman
            value: 56.02039158535162
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/CLSClusteringP2P
          name: MTEB CLSClusteringP2P
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 42.83769092800803
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/CLSClusteringS2S
          name: MTEB CLSClusteringS2S
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 39.772368416311195
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/CMedQAv1-reranking
          name: MTEB CMedQAv1
          config: default
          split: test
          revision: None
        metrics:
          - type: map
            value: 78.3895639270477
          - type: mrr
            value: 81.64801587301588
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/CMedQAv2-reranking
          name: MTEB CMedQAv2
          config: default
          split: test
          revision: None
        metrics:
          - type: map
            value: 80.84221923370502
          - type: mrr
            value: 84.32821428571428
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/CmedqaRetrieval
          name: MTEB CmedqaRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 18.695999999999998
          - type: map_at_10
            value: 28.171000000000003
          - type: map_at_100
            value: 29.927
          - type: map_at_1000
            value: 30.09
          - type: map_at_3
            value: 24.854000000000003
          - type: map_at_5
            value: 26.573
          - type: mrr_at_1
            value: 29.256999999999998
          - type: mrr_at_10
            value: 36.584
          - type: mrr_at_100
            value: 37.643
          - type: mrr_at_1000
            value: 37.713
          - type: mrr_at_3
            value: 34.171
          - type: mrr_at_5
            value: 35.436
          - type: ndcg_at_1
            value: 29.256999999999998
          - type: ndcg_at_10
            value: 34.079
          - type: ndcg_at_100
            value: 41.538000000000004
          - type: ndcg_at_1000
            value: 44.651999999999994
          - type: ndcg_at_3
            value: 29.439999999999998
          - type: ndcg_at_5
            value: 31.172
          - type: precision_at_1
            value: 29.256999999999998
          - type: precision_at_10
            value: 7.804
          - type: precision_at_100
            value: 1.392
          - type: precision_at_1000
            value: 0.179
          - type: precision_at_3
            value: 16.804
          - type: precision_at_5
            value: 12.267999999999999
          - type: recall_at_1
            value: 18.695999999999998
          - type: recall_at_10
            value: 43.325
          - type: recall_at_100
            value: 74.765
          - type: recall_at_1000
            value: 95.999
          - type: recall_at_3
            value: 29.384
          - type: recall_at_5
            value: 34.765
      - task:
          type: PairClassification
        dataset:
          type: C-MTEB/CMNLI
          name: MTEB Cmnli
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 79.15814792543597
          - type: cos_sim_ap
            value: 87.29838623651833
          - type: cos_sim_f1
            value: 80.6512349097353
          - type: cos_sim_precision
            value: 76.62037037037037
          - type: cos_sim_recall
            value: 85.1297638531681
          - type: dot_accuracy
            value: 79.15814792543597
          - type: dot_ap
            value: 87.30641807786448
          - type: dot_f1
            value: 80.6512349097353
          - type: dot_precision
            value: 76.62037037037037
          - type: dot_recall
            value: 85.1297638531681
          - type: euclidean_accuracy
            value: 79.15814792543597
          - type: euclidean_ap
            value: 87.29838623651833
          - type: euclidean_f1
            value: 80.6512349097353
          - type: euclidean_precision
            value: 76.62037037037037
          - type: euclidean_recall
            value: 85.1297638531681
          - type: manhattan_accuracy
            value: 79.15814792543597
          - type: manhattan_ap
            value: 87.29705330875109
          - type: manhattan_f1
            value: 80.66914498141264
          - type: manhattan_precision
            value: 75.76504415691106
          - type: manhattan_recall
            value: 86.2520458265139
          - type: max_accuracy
            value: 79.15814792543597
          - type: max_ap
            value: 87.30641807786448
          - type: max_f1
            value: 80.66914498141264
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/CovidRetrieval
          name: MTEB CovidRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 58.325
          - type: map_at_10
            value: 67.572
          - type: map_at_100
            value: 68.142
          - type: map_at_1000
            value: 68.152
          - type: map_at_3
            value: 65.446
          - type: map_at_5
            value: 66.794
          - type: mrr_at_1
            value: 58.272
          - type: mrr_at_10
            value: 67.469
          - type: mrr_at_100
            value: 68.048
          - type: mrr_at_1000
            value: 68.05799999999999
          - type: mrr_at_3
            value: 65.385
          - type: mrr_at_5
            value: 66.728
          - type: ndcg_at_1
            value: 58.377
          - type: ndcg_at_10
            value: 71.922
          - type: ndcg_at_100
            value: 74.49799999999999
          - type: ndcg_at_1000
            value: 74.80799999999999
          - type: ndcg_at_3
            value: 67.711
          - type: ndcg_at_5
            value: 70.075
          - type: precision_at_1
            value: 58.377
          - type: precision_at_10
            value: 8.641
          - type: precision_at_100
            value: 0.9809999999999999
          - type: precision_at_1000
            value: 0.101
          - type: precision_at_3
            value: 24.833
          - type: precision_at_5
            value: 16.101
          - type: recall_at_1
            value: 58.325
          - type: recall_at_10
            value: 85.458
          - type: recall_at_100
            value: 97.05
          - type: recall_at_1000
            value: 99.579
          - type: recall_at_3
            value: 74.18299999999999
          - type: recall_at_5
            value: 79.768
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/DuRetrieval
          name: MTEB DuRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 23.448
          - type: map_at_10
            value: 70.368
          - type: map_at_100
            value: 73.644
          - type: map_at_1000
            value: 73.727
          - type: map_at_3
            value: 48.317
          - type: map_at_5
            value: 61.114999999999995
          - type: mrr_at_1
            value: 83.5
          - type: mrr_at_10
            value: 88.592
          - type: mrr_at_100
            value: 88.69200000000001
          - type: mrr_at_1000
            value: 88.696
          - type: mrr_at_3
            value: 88.058
          - type: mrr_at_5
            value: 88.458
          - type: ndcg_at_1
            value: 83.5
          - type: ndcg_at_10
            value: 79.696
          - type: ndcg_at_100
            value: 83.88799999999999
          - type: ndcg_at_1000
            value: 84.64699999999999
          - type: ndcg_at_3
            value: 78.39500000000001
          - type: ndcg_at_5
            value: 77.289
          - type: precision_at_1
            value: 83.5
          - type: precision_at_10
            value: 38.525
          - type: precision_at_100
            value: 4.656
          - type: precision_at_1000
            value: 0.485
          - type: precision_at_3
            value: 70.383
          - type: precision_at_5
            value: 59.56
          - type: recall_at_1
            value: 23.448
          - type: recall_at_10
            value: 81.274
          - type: recall_at_100
            value: 94.447
          - type: recall_at_1000
            value: 98.209
          - type: recall_at_3
            value: 51.122
          - type: recall_at_5
            value: 67.29899999999999
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/EcomRetrieval
          name: MTEB EcomRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 44.2
          - type: map_at_10
            value: 54.083999999999996
          - type: map_at_100
            value: 54.775
          - type: map_at_1000
            value: 54.800000000000004
          - type: map_at_3
            value: 51.5
          - type: map_at_5
            value: 52.94
          - type: mrr_at_1
            value: 44.2
          - type: mrr_at_10
            value: 54.083999999999996
          - type: mrr_at_100
            value: 54.775
          - type: mrr_at_1000
            value: 54.800000000000004
          - type: mrr_at_3
            value: 51.5
          - type: mrr_at_5
            value: 52.94
          - type: ndcg_at_1
            value: 44.2
          - type: ndcg_at_10
            value: 59.221999999999994
          - type: ndcg_at_100
            value: 62.463
          - type: ndcg_at_1000
            value: 63.159
          - type: ndcg_at_3
            value: 53.888000000000005
          - type: ndcg_at_5
            value: 56.483000000000004
          - type: precision_at_1
            value: 44.2
          - type: precision_at_10
            value: 7.55
          - type: precision_at_100
            value: 0.9039999999999999
          - type: precision_at_1000
            value: 0.096
          - type: precision_at_3
            value: 20.267
          - type: precision_at_5
            value: 13.420000000000002
          - type: recall_at_1
            value: 44.2
          - type: recall_at_10
            value: 75.5
          - type: recall_at_100
            value: 90.4
          - type: recall_at_1000
            value: 95.89999999999999
          - type: recall_at_3
            value: 60.8
          - type: recall_at_5
            value: 67.10000000000001
      - task:
          type: Classification
        dataset:
          type: C-MTEB/IFlyTek-classification
          name: MTEB IFlyTek
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 46.30242400923432
          - type: f1
            value: 34.9084495621858
      - task:
          type: Classification
        dataset:
          type: C-MTEB/JDReview-classification
          name: MTEB JDReview
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 77.2983114446529
          - type: ap
            value: 38.88426285856333
          - type: f1
            value: 70.55729261942591
      - task:
          type: STS
        dataset:
          type: C-MTEB/LCQMC
          name: MTEB LCQMC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 68.5643564120875
          - type: cos_sim_spearman
            value: 74.96268256412532
          - type: euclidean_pearson
            value: 74.05621406127399
          - type: euclidean_spearman
            value: 74.96268256412532
          - type: manhattan_pearson
            value: 74.04916252136826
          - type: manhattan_spearman
            value: 74.95628866390487
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/Mmarco-reranking
          name: MTEB MMarcoReranking
          config: default
          split: dev
          revision: None
        metrics:
          - type: map
            value: 27.289171935571773
          - type: mrr
            value: 25.7218253968254
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/MMarcoRetrieval
          name: MTEB MMarcoRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 61.632
          - type: map_at_10
            value: 70.796
          - type: map_at_100
            value: 71.21300000000001
          - type: map_at_1000
            value: 71.22800000000001
          - type: map_at_3
            value: 68.848
          - type: map_at_5
            value: 70.044
          - type: mrr_at_1
            value: 63.768
          - type: mrr_at_10
            value: 71.516
          - type: mrr_at_100
            value: 71.884
          - type: mrr_at_1000
            value: 71.897
          - type: mrr_at_3
            value: 69.814
          - type: mrr_at_5
            value: 70.843
          - type: ndcg_at_1
            value: 63.768
          - type: ndcg_at_10
            value: 74.727
          - type: ndcg_at_100
            value: 76.649
          - type: ndcg_at_1000
            value: 77.05300000000001
          - type: ndcg_at_3
            value: 71.00800000000001
          - type: ndcg_at_5
            value: 73.015
          - type: precision_at_1
            value: 63.768
          - type: precision_at_10
            value: 9.15
          - type: precision_at_100
            value: 1.012
          - type: precision_at_1000
            value: 0.105
          - type: precision_at_3
            value: 26.848
          - type: precision_at_5
            value: 17.172
          - type: recall_at_1
            value: 61.632
          - type: recall_at_10
            value: 86.162
          - type: recall_at_100
            value: 94.953
          - type: recall_at_1000
            value: 98.148
          - type: recall_at_3
            value: 76.287
          - type: recall_at_5
            value: 81.03399999999999
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (af)
          config: af
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 25.79690652320108
          - type: f1
            value: 24.093438782440067
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (am)
          config: am
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 3.338937457969066
          - type: f1
            value: 2.404152046553366
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ar)
          config: ar
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 6.489576328177541
          - type: f1
            value: 4.62270646032821
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (az)
          config: az
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 24.767989240080695
          - type: f1
            value: 23.495689794075474
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (bn)
          config: bn
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 4.29724277067922
          - type: f1
            value: 2.2466735164037934
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (cy)
          config: cy
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 26.388702084734366
          - type: f1
            value: 23.86003112409349
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (da)
          config: da
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 31.4694014794889
          - type: f1
            value: 29.017559554815392
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (de)
          config: de
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 28.09011432414256
          - type: f1
            value: 24.796051996220104
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (el)
          config: el
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 19.240080699394753
          - type: f1
            value: 16.13607169381968
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (en)
          config: en
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 53.406186953597846
          - type: f1
            value: 49.55550114595557
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (es)
          config: es
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 30.615332885003365
          - type: f1
            value: 29.13481030937436
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fa)
          config: fa
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 7.205783456624077
          - type: f1
            value: 4.601802513446058
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fi)
          config: fi
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 27.205783456624072
          - type: f1
            value: 24.177535740725418
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fr)
          config: fr
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 32.63618022864828
          - type: f1
            value: 31.190168140021303
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (he)
          config: he
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 2.6630800268997983
          - type: f1
            value: 1.913464455449111
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (hi)
          config: hi
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 4.593140551445864
          - type: f1
            value: 2.6428594688121865
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (hu)
          config: hu
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 25.648957632817755
          - type: f1
            value: 22.88249345748577
      - task:
          type: Classification
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          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (kn)
          config: kn
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 10.097511768661734
          - type: f1
            value: 7.212356186519867
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ko)
          config: ko
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 19.196368527236046
          - type: f1
            value: 16.798046606500282
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (lv)
          config: lv
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 32.49495628782785
          - type: f1
            value: 28.359188240241444
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ml)
          config: ml
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 6.36516476126429
          - type: f1
            value: 3.7192665599079913
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (mn)
          config: mn
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 13.076664425016812
          - type: f1
            value: 9.572770203976713
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ms)
          config: ms
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 39.17955615332885
          - type: f1
            value: 33.8253960820197
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (my)
          config: my
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 12.252858103564224
          - type: f1
            value: 9.096519579346872
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (nb)
          config: nb
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 35.24209818426362
          - type: f1
            value: 32.24756964062884
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (nl)
          config: nl
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 38.17081371889711
          - type: f1
            value: 34.8539465599922
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (pl)
          config: pl
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 31.60390047074647
          - type: f1
            value: 28.24199310436465
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (pt)
          config: pt
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 40.01008742434432
          - type: f1
            value: 37.21826826542489
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ro)
          config: ro
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 39.25353059852051
          - type: f1
            value: 35.457426597271784
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ru)
          config: ru
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 16.70813718897108
          - type: f1
            value: 14.338767956114001
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sl)
          config: sl
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 33.94418291862811
          - type: f1
            value: 30.577444242695694
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sq)
          config: sq
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 40.396772024209824
          - type: f1
            value: 36.028103018769436
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sv)
          config: sv
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 30.722932078009418
          - type: f1
            value: 28.49491987141746
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sw)
          config: sw
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 37.14189643577674
          - type: f1
            value: 32.52116385408168
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ta)
          config: ta
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 8.214525891055818
          - type: f1
            value: 4.448399109965533
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (te)
          config: te
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 7.96570275722932
          - type: f1
            value: 5.128691464756114
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (th)
          config: th
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 21.55682582380632
          - type: f1
            value: 17.110218757379613
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (tl)
          config: tl
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 36.70141223940821
          - type: f1
            value: 32.96113533567822
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (tr)
          config: tr
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 28.80295897780767
          - type: f1
            value: 27.77008973951413
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ur)
          config: ur
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 10.460659045057163
          - type: f1
            value: 7.90075042321315
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (vi)
          config: vi
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 27.720242098184265
          - type: f1
            value: 26.76341970948208
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (zh-CN)
          config: zh-CN
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 75.21183591123066
          - type: f1
            value: 74.55953469104787
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (zh-TW)
          config: zh-TW
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 71.52320107599192
          - type: f1
            value: 71.16094498697193
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/MedicalRetrieval
          name: MTEB MedicalRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 43.2
          - type: map_at_10
            value: 48.788
          - type: map_at_100
            value: 49.412
          - type: map_at_1000
            value: 49.480000000000004
          - type: map_at_3
            value: 47.55
          - type: map_at_5
            value: 48.27
          - type: mrr_at_1
            value: 43.2
          - type: mrr_at_10
            value: 48.788
          - type: mrr_at_100
            value: 49.412
          - type: mrr_at_1000
            value: 49.480000000000004
          - type: mrr_at_3
            value: 47.55
          - type: mrr_at_5
            value: 48.27
          - type: ndcg_at_1
            value: 43.2
          - type: ndcg_at_10
            value: 51.504000000000005
          - type: ndcg_at_100
            value: 54.718
          - type: ndcg_at_1000
            value: 56.754000000000005
          - type: ndcg_at_3
            value: 48.975
          - type: ndcg_at_5
            value: 50.283
          - type: precision_at_1
            value: 43.2
          - type: precision_at_10
            value: 6
          - type: precision_at_100
            value: 0.755
          - type: precision_at_1000
            value: 0.092
          - type: precision_at_3
            value: 17.7
          - type: precision_at_5
            value: 11.26
          - type: recall_at_1
            value: 43.2
          - type: recall_at_10
            value: 60
          - type: recall_at_100
            value: 75.5
          - type: recall_at_1000
            value: 92
          - type: recall_at_3
            value: 53.1
          - type: recall_at_5
            value: 56.3
      - task:
          type: Classification
        dataset:
          type: C-MTEB/MultilingualSentiment-classification
          name: MTEB MultilingualSentiment
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 71.66666666666669
          - type: f1
            value: 71.30679309756734
      - task:
          type: PairClassification
        dataset:
          type: C-MTEB/OCNLI
          name: MTEB Ocnli
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 73.47049269085004
          - type: cos_sim_ap
            value: 77.45627413542758
          - type: cos_sim_f1
            value: 76.38326585695006
          - type: cos_sim_precision
            value: 66.53605015673982
          - type: cos_sim_recall
            value: 89.65153115100317
          - type: dot_accuracy
            value: 73.47049269085004
          - type: dot_ap
            value: 77.45627413542758
          - type: dot_f1
            value: 76.38326585695006
          - type: dot_precision
            value: 66.53605015673982
          - type: dot_recall
            value: 89.65153115100317
          - type: euclidean_accuracy
            value: 73.47049269085004
          - type: euclidean_ap
            value: 77.45620654340667
          - type: euclidean_f1
            value: 76.38326585695006
          - type: euclidean_precision
            value: 66.53605015673982
          - type: euclidean_recall
            value: 89.65153115100317
          - type: manhattan_accuracy
            value: 73.36220898754738
          - type: manhattan_ap
            value: 77.37536169412738
          - type: manhattan_f1
            value: 76.38640429338103
          - type: manhattan_precision
            value: 66.25290923196276
          - type: manhattan_recall
            value: 90.17951425554382
          - type: max_accuracy
            value: 73.47049269085004
          - type: max_ap
            value: 77.45627413542758
          - type: max_f1
            value: 76.38640429338103
      - task:
          type: Classification
        dataset:
          type: C-MTEB/OnlineShopping-classification
          name: MTEB OnlineShopping
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 91.53
          - type: ap
            value: 89.42581459526625
          - type: f1
            value: 91.52129393166419
      - task:
          type: STS
        dataset:
          type: C-MTEB/PAWSX
          name: MTEB PAWSX
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 29.140746638094146
          - type: cos_sim_spearman
            value: 33.485405306894954
          - type: euclidean_pearson
            value: 33.519345307695055
          - type: euclidean_spearman
            value: 33.485405306894954
          - type: manhattan_pearson
            value: 33.477525315080555
          - type: manhattan_spearman
            value: 33.45108970796106
      - task:
          type: STS
        dataset:
          type: C-MTEB/QBQTC
          name: MTEB QBQTC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 29.1489803117667
          - type: cos_sim_spearman
            value: 31.064278185902484
          - type: euclidean_pearson
            value: 29.46668604738617
          - type: euclidean_spearman
            value: 31.064327209275294
          - type: manhattan_pearson
            value: 29.486028367555363
          - type: manhattan_spearman
            value: 31.08380235579532
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (zh)
          config: zh
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 62.11437173048506
          - type: cos_sim_spearman
            value: 64.51063977663124
          - type: euclidean_pearson
            value: 63.21313519423639
          - type: euclidean_spearman
            value: 64.51063977663124
          - type: manhattan_pearson
            value: 66.21953089701206
          - type: manhattan_spearman
            value: 66.39662588897919
      - task:
          type: STS
        dataset:
          type: C-MTEB/STSB
          name: MTEB STSB
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 78.98157503278959
          - type: cos_sim_spearman
            value: 79.62582795918624
          - type: euclidean_pearson
            value: 79.44521376122044
          - type: euclidean_spearman
            value: 79.62582795918624
          - type: manhattan_pearson
            value: 79.4254734731864
          - type: manhattan_spearman
            value: 79.61078135348473
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/T2Reranking
          name: MTEB T2Reranking
          config: default
          split: dev
          revision: None
        metrics:
          - type: map
            value: 66.29923663749156
          - type: mrr
            value: 76.31176720293172
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/T2Retrieval
          name: MTEB T2Retrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 24.518
          - type: map_at_10
            value: 67.938
          - type: map_at_100
            value: 71.769
          - type: map_at_1000
            value: 71.882
          - type: map_at_3
            value: 47.884
          - type: map_at_5
            value: 58.733000000000004
          - type: mrr_at_1
            value: 84.328
          - type: mrr_at_10
            value: 87.96000000000001
          - type: mrr_at_100
            value: 88.114
          - type: mrr_at_1000
            value: 88.12
          - type: mrr_at_3
            value: 87.306
          - type: mrr_at_5
            value: 87.734
          - type: ndcg_at_1
            value: 84.328
          - type: ndcg_at_10
            value: 77.077
          - type: ndcg_at_100
            value: 81.839
          - type: ndcg_at_1000
            value: 82.974
          - type: ndcg_at_3
            value: 79.209
          - type: ndcg_at_5
            value: 77.345
          - type: precision_at_1
            value: 84.328
          - type: precision_at_10
            value: 38.596000000000004
          - type: precision_at_100
            value: 4.825
          - type: precision_at_1000
            value: 0.51
          - type: precision_at_3
            value: 69.547
          - type: precision_at_5
            value: 58.033
          - type: recall_at_1
            value: 24.518
          - type: recall_at_10
            value: 75.982
          - type: recall_at_100
            value: 91.40899999999999
          - type: recall_at_1000
            value: 97.129
          - type: recall_at_3
            value: 50.014
          - type: recall_at_5
            value: 62.971
      - task:
          type: Classification
        dataset:
          type: C-MTEB/TNews-classification
          name: MTEB TNews
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 50.17400000000001
          - type: f1
            value: 48.49778139007515
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/ThuNewsClusteringP2P
          name: MTEB ThuNewsClusteringP2P
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 58.925265567508944
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/ThuNewsClusteringS2S
          name: MTEB ThuNewsClusteringS2S
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 53.70728044857883
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/VideoRetrieval
          name: MTEB VideoRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 49.5
          - type: map_at_10
            value: 59.772000000000006
          - type: map_at_100
            value: 60.312
          - type: map_at_1000
            value: 60.333000000000006
          - type: map_at_3
            value: 57.367000000000004
          - type: map_at_5
            value: 58.797
          - type: mrr_at_1
            value: 49.5
          - type: mrr_at_10
            value: 59.772000000000006
          - type: mrr_at_100
            value: 60.312
          - type: mrr_at_1000
            value: 60.333000000000006
          - type: mrr_at_3
            value: 57.367000000000004
          - type: mrr_at_5
            value: 58.797
          - type: ndcg_at_1
            value: 49.5
          - type: ndcg_at_10
            value: 64.672
          - type: ndcg_at_100
            value: 67.389
          - type: ndcg_at_1000
            value: 67.984
          - type: ndcg_at_3
            value: 59.8
          - type: ndcg_at_5
            value: 62.385999999999996
          - type: precision_at_1
            value: 49.5
          - type: precision_at_10
            value: 8
          - type: precision_at_100
            value: 0.9289999999999999
          - type: precision_at_1000
            value: 0.098
          - type: precision_at_3
            value: 22.267
          - type: precision_at_5
            value: 14.62
          - type: recall_at_1
            value: 49.5
          - type: recall_at_10
            value: 80
          - type: recall_at_100
            value: 92.9
          - type: recall_at_1000
            value: 97.7
          - type: recall_at_3
            value: 66.8
          - type: recall_at_5
            value: 73.1
      - task:
          type: Classification
        dataset:
          type: C-MTEB/waimai-classification
          name: MTEB Waimai
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 85.97999999999999
          - type: ap
            value: 68.63874013611306
          - type: f1
            value: 84.22025909308913

license: apache-2.0