windberta-large / README.md
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metadata
tags:
  - mteb
model-index:
  - name: windberta
    results:
      - task:
          type: STS
        dataset:
          type: C-MTEB/AFQMC
          name: MTEB AFQMC
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 42.33337754104733
          - type: cos_sim_spearman
            value: 46.77492896615997
          - type: euclidean_pearson
            value: 45.485443713440205
          - type: euclidean_spearman
            value: 46.77492896615997
          - type: manhattan_pearson
            value: 45.47908853063357
          - type: manhattan_spearman
            value: 46.78349339487035
      - task:
          type: STS
        dataset:
          type: C-MTEB/ATEC
          name: MTEB ATEC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 42.4857636418899
          - type: cos_sim_spearman
            value: 50.1796711684779
          - type: euclidean_pearson
            value: 50.19857844860528
          - type: euclidean_spearman
            value: 50.17966891674149
          - type: manhattan_pearson
            value: 50.189134647291425
          - type: manhattan_spearman
            value: 50.186194448855524
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (zh)
          config: zh
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 43.32
          - type: f1
            value: 41.656310147227025
      - task:
          type: STS
        dataset:
          type: C-MTEB/BQ
          name: MTEB BQ
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 53.71954834756843
          - type: cos_sim_spearman
            value: 55.24915785430301
          - type: euclidean_pearson
            value: 54.51293350057512
          - type: euclidean_spearman
            value: 55.249150926099745
          - type: manhattan_pearson
            value: 54.47449996486367
          - type: manhattan_spearman
            value: 55.2105677621172
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/CLSClusteringP2P
          name: MTEB CLSClusteringP2P
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 42.45793696381908
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/CLSClusteringS2S
          name: MTEB CLSClusteringS2S
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 40.378561138339656
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/CMedQAv1-reranking
          name: MTEB CMedQAv1
          config: default
          split: test
          revision: None
        metrics:
          - type: map
            value: 77.41779986882574
          - type: mrr
            value: 81.09345238095239
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/CMedQAv2-reranking
          name: MTEB CMedQAv2
          config: default
          split: test
          revision: None
        metrics:
          - type: map
            value: 77.84113571204598
          - type: mrr
            value: 81.18206349206349
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/CmedqaRetrieval
          name: MTEB CmedqaRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 18.706
          - type: map_at_10
            value: 27.782
          - type: map_at_100
            value: 29.482000000000003
          - type: map_at_1000
            value: 29.64
          - type: map_at_3
            value: 24.606
          - type: map_at_5
            value: 26.32
          - type: mrr_at_1
            value: 29.307
          - type: mrr_at_10
            value: 36.226
          - type: mrr_at_100
            value: 37.262
          - type: mrr_at_1000
            value: 37.335
          - type: mrr_at_3
            value: 33.928999999999995
          - type: mrr_at_5
            value: 35.181000000000004
          - type: ndcg_at_1
            value: 29.307
          - type: ndcg_at_10
            value: 33.452
          - type: ndcg_at_100
            value: 40.747
          - type: ndcg_at_1000
            value: 43.881
          - type: ndcg_at_3
            value: 29.186
          - type: ndcg_at_5
            value: 30.866
          - type: precision_at_1
            value: 29.307
          - type: precision_at_10
            value: 7.632
          - type: precision_at_100
            value: 1.357
          - type: precision_at_1000
            value: 0.17600000000000002
          - type: precision_at_3
            value: 16.688
          - type: precision_at_5
            value: 12.173
          - type: recall_at_1
            value: 18.706
          - type: recall_at_10
            value: 41.925000000000004
          - type: recall_at_100
            value: 72.817
          - type: recall_at_1000
            value: 94.33500000000001
          - type: recall_at_3
            value: 28.968
          - type: recall_at_5
            value: 34.29
      - task:
          type: PairClassification
        dataset:
          type: C-MTEB/CMNLI
          name: MTEB Cmnli
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 79.84365604329525
          - type: cos_sim_ap
            value: 87.54800685674849
          - type: cos_sim_f1
            value: 81.0654184776552
          - type: cos_sim_precision
            value: 77.4488926746167
          - type: cos_sim_recall
            value: 85.0362403553893
          - type: dot_accuracy
            value: 79.84365604329525
          - type: dot_ap
            value: 87.55923139984687
          - type: dot_f1
            value: 81.0654184776552
          - type: dot_precision
            value: 77.4488926746167
          - type: dot_recall
            value: 85.0362403553893
          - type: euclidean_accuracy
            value: 79.84365604329525
          - type: euclidean_ap
            value: 87.54800685674849
          - type: euclidean_f1
            value: 81.0654184776552
          - type: euclidean_precision
            value: 77.4488926746167
          - type: euclidean_recall
            value: 85.0362403553893
          - type: manhattan_accuracy
            value: 79.7714972940469
          - type: manhattan_ap
            value: 87.55523320840679
          - type: manhattan_f1
            value: 80.99598034836983
          - type: manhattan_precision
            value: 77.51656336824108
          - type: manhattan_recall
            value: 84.80243161094225
          - type: max_accuracy
            value: 79.84365604329525
          - type: max_ap
            value: 87.55923139984687
          - type: max_f1
            value: 81.0654184776552
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/CovidRetrieval
          name: MTEB CovidRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 60.589999999999996
          - type: map_at_10
            value: 69.27600000000001
          - type: map_at_100
            value: 69.812
          - type: map_at_1000
            value: 69.82300000000001
          - type: map_at_3
            value: 67.448
          - type: map_at_5
            value: 68.537
          - type: mrr_at_1
            value: 60.695
          - type: mrr_at_10
            value: 69.32300000000001
          - type: mrr_at_100
            value: 69.854
          - type: mrr_at_1000
            value: 69.865
          - type: mrr_at_3
            value: 67.545
          - type: mrr_at_5
            value: 68.625
          - type: ndcg_at_1
            value: 60.695
          - type: ndcg_at_10
            value: 73.36
          - type: ndcg_at_100
            value: 75.78200000000001
          - type: ndcg_at_1000
            value: 76.077
          - type: ndcg_at_3
            value: 69.639
          - type: ndcg_at_5
            value: 71.59400000000001
          - type: precision_at_1
            value: 60.695
          - type: precision_at_10
            value: 8.704
          - type: precision_at_100
            value: 0.98
          - type: precision_at_1000
            value: 0.1
          - type: precision_at_3
            value: 25.430000000000003
          - type: precision_at_5
            value: 16.27
          - type: recall_at_1
            value: 60.589999999999996
          - type: recall_at_10
            value: 86.038
          - type: recall_at_100
            value: 96.944
          - type: recall_at_1000
            value: 99.262
          - type: recall_at_3
            value: 75.869
          - type: recall_at_5
            value: 80.55799999999999
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/DuRetrieval
          name: MTEB DuRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 23.294999999999998
          - type: map_at_10
            value: 70.99499999999999
          - type: map_at_100
            value: 74.126
          - type: map_at_1000
            value: 74.205
          - type: map_at_3
            value: 48.845
          - type: map_at_5
            value: 61.551
          - type: mrr_at_1
            value: 83.3
          - type: mrr_at_10
            value: 88.446
          - type: mrr_at_100
            value: 88.564
          - type: mrr_at_1000
            value: 88.57000000000001
          - type: mrr_at_3
            value: 88
          - type: mrr_at_5
            value: 88.25
          - type: ndcg_at_1
            value: 83.3
          - type: ndcg_at_10
            value: 80.128
          - type: ndcg_at_100
            value: 84.009
          - type: ndcg_at_1000
            value: 84.798
          - type: ndcg_at_3
            value: 78.79
          - type: ndcg_at_5
            value: 77.405
          - type: precision_at_1
            value: 83.3
          - type: precision_at_10
            value: 38.82
          - type: precision_at_100
            value: 4.657
          - type: precision_at_1000
            value: 0.484
          - type: precision_at_3
            value: 70.89999999999999
          - type: precision_at_5
            value: 59.550000000000004
          - type: recall_at_1
            value: 23.294999999999998
          - type: recall_at_10
            value: 82.12
          - type: recall_at_100
            value: 94.223
          - type: recall_at_1000
            value: 98.264
          - type: recall_at_3
            value: 51.946000000000005
          - type: recall_at_5
            value: 67.54299999999999
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/EcomRetrieval
          name: MTEB EcomRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 42
          - type: map_at_10
            value: 51.207
          - type: map_at_100
            value: 51.964
          - type: map_at_1000
            value: 51.993
          - type: map_at_3
            value: 48.9
          - type: map_at_5
            value: 50.239999999999995
          - type: mrr_at_1
            value: 42
          - type: mrr_at_10
            value: 51.207
          - type: mrr_at_100
            value: 51.964
          - type: mrr_at_1000
            value: 51.993
          - type: mrr_at_3
            value: 48.9
          - type: mrr_at_5
            value: 50.239999999999995
          - type: ndcg_at_1
            value: 42
          - type: ndcg_at_10
            value: 55.886
          - type: ndcg_at_100
            value: 59.622
          - type: ndcg_at_1000
            value: 60.480999999999995
          - type: ndcg_at_3
            value: 51.112
          - type: ndcg_at_5
            value: 53.513
          - type: precision_at_1
            value: 42
          - type: precision_at_10
            value: 7.07
          - type: precision_at_100
            value: 0.8829999999999999
          - type: precision_at_1000
            value: 0.095
          - type: precision_at_3
            value: 19.167
          - type: precision_at_5
            value: 12.659999999999998
          - type: recall_at_1
            value: 42
          - type: recall_at_10
            value: 70.7
          - type: recall_at_100
            value: 88.3
          - type: recall_at_1000
            value: 95.19999999999999
          - type: recall_at_3
            value: 57.49999999999999
          - type: recall_at_5
            value: 63.3
      - task:
          type: Classification
        dataset:
          type: C-MTEB/IFlyTek-classification
          name: MTEB IFlyTek
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 47.07964601769912
          - type: f1
            value: 35.71948030119852
      - task:
          type: Classification
        dataset:
          type: C-MTEB/JDReview-classification
          name: MTEB JDReview
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 84.48405253283303
          - type: ap
            value: 51.641044322555516
          - type: f1
            value: 79.09258868144057
      - task:
          type: STS
        dataset:
          type: C-MTEB/LCQMC
          name: MTEB LCQMC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 68.02458550340191
          - type: cos_sim_spearman
            value: 74.28734803466209
          - type: euclidean_pearson
            value: 73.34335009219284
          - type: euclidean_spearman
            value: 74.28734803466209
          - type: manhattan_pearson
            value: 73.34314353425192
          - type: manhattan_spearman
            value: 74.28417768884727
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/Mmarco-reranking
          name: MTEB MMarcoReranking
          config: default
          split: dev
          revision: None
        metrics:
          - type: map
            value: 30.17193800028175
          - type: mrr
            value: 29.161904761904765
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/MMarcoRetrieval
          name: MTEB MMarcoRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 61.039
          - type: map_at_10
            value: 70.19999999999999
          - type: map_at_100
            value: 70.602
          - type: map_at_1000
            value: 70.62
          - type: map_at_3
            value: 68.133
          - type: map_at_5
            value: 69.503
          - type: mrr_at_1
            value: 63.066
          - type: mrr_at_10
            value: 70.831
          - type: mrr_at_100
            value: 71.186
          - type: mrr_at_1000
            value: 71.202
          - type: mrr_at_3
            value: 69.00699999999999
          - type: mrr_at_5
            value: 70.22699999999999
          - type: ndcg_at_1
            value: 63.066
          - type: ndcg_at_10
            value: 74.141
          - type: ndcg_at_100
            value: 75.976
          - type: ndcg_at_1000
            value: 76.462
          - type: ndcg_at_3
            value: 70.242
          - type: ndcg_at_5
            value: 72.58099999999999
          - type: precision_at_1
            value: 63.066
          - type: precision_at_10
            value: 9.097
          - type: precision_at_100
            value: 1.001
          - type: precision_at_1000
            value: 0.104
          - type: precision_at_3
            value: 26.571
          - type: precision_at_5
            value: 17.166
          - type: recall_at_1
            value: 61.039
          - type: recall_at_10
            value: 85.666
          - type: recall_at_100
            value: 94.017
          - type: recall_at_1000
            value: 97.819
          - type: recall_at_3
            value: 75.45100000000001
          - type: recall_at_5
            value: 81.02000000000001
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (af)
          config: af
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 28.813046402151986
          - type: f1
            value: 26.66771458648628
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (am)
          config: am
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 3.0363147276395432
          - type: f1
            value: 2.1282632958878023
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ar)
          config: ar
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 6.745124411566914
          - type: f1
            value: 4.64897627862169
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (az)
          config: az
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 27.004034969737727
          - type: f1
            value: 24.50373453583708
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (bn)
          config: bn
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 3.24142568930733
          - type: f1
            value: 1.4440829714459096
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (cy)
          config: cy
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 31.176866173503697
          - type: f1
            value: 27.449943893371536
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (da)
          config: da
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 35.52790854068594
          - type: f1
            value: 32.284095877219734
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (de)
          config: de
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 30.64895763281775
          - type: f1
            value: 27.273098137670022
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (el)
          config: el
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 18.167451244115668
          - type: f1
            value: 14.717271932824833
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (en)
          config: en
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 54.76126429051782
          - type: f1
            value: 50.43678929170829
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (es)
          config: es
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 32.53194351042367
          - type: f1
            value: 30.922864615091562
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fa)
          config: fa
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 8.715534633490249
          - type: f1
            value: 5.943557212598054
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fi)
          config: fi
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 31.785474108944182
          - type: f1
            value: 28.416607289904295
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fr)
          config: fr
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 33.16072629455279
          - type: f1
            value: 31.78249030156056
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (he)
          config: he
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 3.026227303295226
          - type: f1
            value: 1.0249360076972784
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (hi)
          config: hi
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 3.611297915265635
          - type: f1
            value: 1.8805751299306375
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (hu)
          config: hu
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 30.470746469401476
          - type: f1
            value: 27.326274554457026
      - task:
          type: Classification
        dataset:
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          config: kn
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 10.309347679892403
          - type: f1
            value: 6.303469804836742
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ko)
          config: ko
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 14.515803631472762
          - type: f1
            value: 11.448228509062176
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (lv)
          config: lv
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 33.076664425016816
          - type: f1
            value: 29.62119483929902
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ml)
          config: ml
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 7.4411566913248155
          - type: f1
            value: 3.9500853520943777
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (mn)
          config: mn
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 17.982515131136516
          - type: f1
            value: 16.21370873212602
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ms)
          config: ms
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 37.92871553463349
          - type: f1
            value: 33.45105376049966
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (my)
          config: my
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 11.72831203765972
          - type: f1
            value: 8.44884960923806
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (nb)
          config: nb
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 38.02286482851379
          - type: f1
            value: 34.67204151455546
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (nl)
          config: nl
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 40.373234700739744
          - type: f1
            value: 35.65457711900268
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (pl)
          config: pl
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 36.344989912575656
          - type: f1
            value: 32.79620374350878
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (pt)
          config: pt
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 41.82918628110289
          - type: f1
            value: 38.67744252721392
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ro)
          config: ro
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 40.62542030934767
          - type: f1
            value: 36.98261635854706
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ru)
          config: ru
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 18.95763281775387
          - type: f1
            value: 16.30423107207311
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sl)
          config: sl
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 35.299260255548084
          - type: f1
            value: 31.765574086767216
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sq)
          config: sq
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 41.956960322797585
          - type: f1
            value: 38.574130779247525
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sv)
          config: sv
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 37.19233355749832
          - type: f1
            value: 33.81282301018017
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sw)
          config: sw
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 38.87693342299933
          - type: f1
            value: 36.374284150293924
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ta)
          config: ta
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 8.5137861466039
          - type: f1
            value: 3.77604514028691
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (te)
          config: te
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 7.347007397444519
          - type: f1
            value: 4.316679614648472
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (th)
          config: th
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 10.104236718224612
          - type: f1
            value: 7.587154404252399
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (tl)
          config: tl
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 35.907868190988566
          - type: f1
            value: 32.42532534803655
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (tr)
          config: tr
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 32.07800941492939
          - type: f1
            value: 31.072741162550983
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ur)
          config: ur
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 10.373234700739745
          - type: f1
            value: 7.124408430261137
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (vi)
          config: vi
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 33.91055817081373
          - type: f1
            value: 31.82496122405504
      - 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: 74.94283792871552
          - type: f1
            value: 74.29520816825985
      - 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: 70.99529253530599
          - type: f1
            value: 70.48943927686703
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/MedicalRetrieval
          name: MTEB MedicalRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 42.199999999999996
          - type: map_at_10
            value: 47.774
          - type: map_at_100
            value: 48.324
          - type: map_at_1000
            value: 48.392
          - type: map_at_3
            value: 46.317
          - type: map_at_5
            value: 47.072
          - type: mrr_at_1
            value: 42.3
          - type: mrr_at_10
            value: 47.827
          - type: mrr_at_100
            value: 48.378
          - type: mrr_at_1000
            value: 48.446
          - type: mrr_at_3
            value: 46.367000000000004
          - type: mrr_at_5
            value: 47.142
          - type: ndcg_at_1
            value: 42.199999999999996
          - type: ndcg_at_10
            value: 50.671
          - type: ndcg_at_100
            value: 53.724000000000004
          - type: ndcg_at_1000
            value: 55.694
          - type: ndcg_at_3
            value: 47.625
          - type: ndcg_at_5
            value: 48.964
          - type: precision_at_1
            value: 42.199999999999996
          - type: precision_at_10
            value: 5.99
          - type: precision_at_100
            value: 0.751
          - type: precision_at_1000
            value: 0.091
          - type: precision_at_3
            value: 17.133000000000003
          - type: precision_at_5
            value: 10.92
          - type: recall_at_1
            value: 42.199999999999996
          - type: recall_at_10
            value: 59.9
          - type: recall_at_100
            value: 75.1
          - type: recall_at_1000
            value: 91
          - type: recall_at_3
            value: 51.4
          - type: recall_at_5
            value: 54.6
      - task:
          type: Classification
        dataset:
          type: C-MTEB/MultilingualSentiment-classification
          name: MTEB MultilingualSentiment
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 72.68333333333334
          - type: f1
            value: 72.53084383657173
      - task:
          type: PairClassification
        dataset:
          type: C-MTEB/OCNLI
          name: MTEB Ocnli
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 72.92907417433676
          - type: cos_sim_ap
            value: 77.2067217322648
          - type: cos_sim_f1
            value: 76.53631284916202
          - type: cos_sim_precision
            value: 68.44296419650291
          - type: cos_sim_recall
            value: 86.80042238648363
          - type: dot_accuracy
            value: 72.92907417433676
          - type: dot_ap
            value: 77.2067217322648
          - type: dot_f1
            value: 76.53631284916202
          - type: dot_precision
            value: 68.44296419650291
          - type: dot_recall
            value: 86.80042238648363
          - type: euclidean_accuracy
            value: 72.92907417433676
          - type: euclidean_ap
            value: 77.2067217322648
          - type: euclidean_f1
            value: 76.53631284916202
          - type: euclidean_precision
            value: 68.44296419650291
          - type: euclidean_recall
            value: 86.80042238648363
          - type: manhattan_accuracy
            value: 72.98321602598809
          - type: manhattan_ap
            value: 77.10385348859928
          - type: manhattan_f1
            value: 76.67134174848059
          - type: manhattan_precision
            value: 68.79194630872483
          - type: manhattan_recall
            value: 86.58922914466737
          - type: max_accuracy
            value: 72.98321602598809
          - type: max_ap
            value: 77.2067217322648
          - type: max_f1
            value: 76.67134174848059
      - task:
          type: Classification
        dataset:
          type: C-MTEB/OnlineShopping-classification
          name: MTEB OnlineShopping
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 92.11000000000003
          - type: ap
            value: 90.49414877664759
          - type: f1
            value: 92.10539417755511
      - task:
          type: STS
        dataset:
          type: C-MTEB/PAWSX
          name: MTEB PAWSX
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 29.106919865870793
          - type: cos_sim_spearman
            value: 33.23892524348652
          - type: euclidean_pearson
            value: 33.62483348491917
          - type: euclidean_spearman
            value: 33.23892524348652
          - type: manhattan_pearson
            value: 33.63464275000747
          - type: manhattan_spearman
            value: 33.250596030941196
      - task:
          type: STS
        dataset:
          type: C-MTEB/QBQTC
          name: MTEB QBQTC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 28.83792748309052
          - type: cos_sim_spearman
            value: 30.92395949947476
          - type: euclidean_pearson
            value: 29.296076928835973
          - type: euclidean_spearman
            value: 30.92395949947476
          - type: manhattan_pearson
            value: 29.220578930008596
          - type: manhattan_spearman
            value: 30.848850181684227
      - 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: 62.485183619582465
          - type: cos_sim_spearman
            value: 64.41414883218417
          - type: euclidean_pearson
            value: 63.53854165422046
          - type: euclidean_spearman
            value: 64.41414883218417
          - type: manhattan_pearson
            value: 63.57621522539751
          - type: manhattan_spearman
            value: 64.49062238421523
      - task:
          type: STS
        dataset:
          type: C-MTEB/STSB
          name: MTEB STSB
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 78.96466421469466
          - type: cos_sim_spearman
            value: 79.74344126074892
          - type: euclidean_pearson
            value: 79.57588420768205
          - type: euclidean_spearman
            value: 79.74344126074892
          - type: manhattan_pearson
            value: 79.50301779470537
          - type: manhattan_spearman
            value: 79.67817007436709
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/T2Reranking
          name: MTEB T2Reranking
          config: default
          split: dev
          revision: None
        metrics:
          - type: map
            value: 65.85321176285859
          - type: mrr
            value: 75.72496534158688
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/T2Retrieval
          name: MTEB T2Retrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 24.437
          - type: map_at_10
            value: 67.85799999999999
          - type: map_at_100
            value: 71.65599999999999
          - type: map_at_1000
            value: 71.771
          - type: map_at_3
            value: 47.752
          - type: map_at_5
            value: 58.620000000000005
          - type: mrr_at_1
            value: 83.776
          - type: mrr_at_10
            value: 87.36699999999999
          - type: mrr_at_100
            value: 87.529
          - type: mrr_at_1000
            value: 87.535
          - type: mrr_at_3
            value: 86.669
          - type: mrr_at_5
            value: 87.126
          - type: ndcg_at_1
            value: 83.776
          - type: ndcg_at_10
            value: 76.839
          - type: ndcg_at_100
            value: 81.547
          - type: ndcg_at_1000
            value: 82.723
          - type: ndcg_at_3
            value: 78.731
          - type: ndcg_at_5
            value: 76.982
          - type: precision_at_1
            value: 83.776
          - type: precision_at_10
            value: 38.507999999999996
          - type: precision_at_100
            value: 4.809
          - type: precision_at_1000
            value: 0.509
          - type: precision_at_3
            value: 69.151
          - type: precision_at_5
            value: 57.74399999999999
          - type: recall_at_1
            value: 24.437
          - type: recall_at_10
            value: 75.887
          - type: recall_at_100
            value: 91.104
          - type: recall_at_1000
            value: 97.024
          - type: recall_at_3
            value: 49.835
          - type: recall_at_5
            value: 62.854
      - task:
          type: Classification
        dataset:
          type: C-MTEB/TNews-classification
          name: MTEB TNews
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 49.851
          - type: f1
            value: 48.115308719873006
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/ThuNewsClusteringP2P
          name: MTEB ThuNewsClusteringP2P
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 58.53624772949936
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/ThuNewsClusteringS2S
          name: MTEB ThuNewsClusteringS2S
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 54.145039782849956
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/VideoRetrieval
          name: MTEB VideoRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 49
          - type: map_at_10
            value: 58.888
          - type: map_at_100
            value: 59.512
          - type: map_at_1000
            value: 59.532
          - type: map_at_3
            value: 56.65
          - type: map_at_5
            value: 57.91
          - type: mrr_at_1
            value: 49
          - type: mrr_at_10
            value: 58.888
          - type: mrr_at_100
            value: 59.512
          - type: mrr_at_1000
            value: 59.532
          - type: mrr_at_3
            value: 56.65
          - type: mrr_at_5
            value: 57.91
          - type: ndcg_at_1
            value: 49
          - type: ndcg_at_10
            value: 63.656
          - type: ndcg_at_100
            value: 66.666
          - type: ndcg_at_1000
            value: 67.269
          - type: ndcg_at_3
            value: 59.082
          - type: ndcg_at_5
            value: 61.35
          - type: precision_at_1
            value: 49
          - type: precision_at_10
            value: 7.86
          - type: precision_at_100
            value: 0.9259999999999999
          - type: precision_at_1000
            value: 0.098
          - type: precision_at_3
            value: 22.033
          - type: precision_at_5
            value: 14.32
          - type: recall_at_1
            value: 49
          - type: recall_at_10
            value: 78.60000000000001
          - type: recall_at_100
            value: 92.60000000000001
          - type: recall_at_1000
            value: 97.5
          - type: recall_at_3
            value: 66.10000000000001
          - type: recall_at_5
            value: 71.6
      - task:
          type: Classification
        dataset:
          type: C-MTEB/waimai-classification
          name: MTEB Waimai
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 86.44000000000001
          - type: ap
            value: 69.51298270778649
          - type: f1
            value: 84.72728998827236

license: mit