sentence-transformers sentence-similarity mteb zh en model-index autotrain_compatible endpoints_compatible region:us
---
language:
- zh
- en
tags:
- sentence-transformers
- sentence-similarity
- mteb
model-index:
- name: zh
  results:
  - task:
      type: STS
    dataset:
      type: C-MTEB/AFQMC
      name: MTEB AFQMC
      config: default
      split: validation
      revision: b44c3b011063adb25877c13823db83bb193913c4
    metrics:
    - type: cos_sim_pearson
      value: 36.28363608508365
    - type: cos_sim_spearman
      value: 37.39698005114737
    - type: euclidean_pearson
      value: 36.407377294778186
    - type: euclidean_spearman
      value: 37.396959945459166
    - type: manhattan_pearson
      value: 36.30818480805082
    - type: manhattan_spearman
      value: 37.28435580456356
  - task:
      type: STS
    dataset:
      type: C-MTEB/ATEC
      name: MTEB ATEC
      config: default
      split: test
      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
    metrics:
    - type: cos_sim_pearson
      value: 39.918566602029536
    - type: cos_sim_spearman
      value: 42.163555979292155
    - type: euclidean_pearson
      value: 43.24429263158407
    - type: euclidean_spearman
      value: 42.16355485217486
    - type: manhattan_pearson
      value: 43.23108002349145
    - type: manhattan_spearman
      value: 42.156854810425834
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (zh)
      config: zh
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 47.788000000000004
    - type: f1
      value: 44.518439064691925
  - task:
      type: STS
    dataset:
      type: C-MTEB/BQ
      name: MTEB BQ
      config: default
      split: test
      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
    metrics:
    - type: cos_sim_pearson
      value: 67.03414409142314
    - type: cos_sim_spearman
      value: 70.95560250546684
    - type: euclidean_pearson
      value: 69.35644910492917
    - type: euclidean_spearman
      value: 70.95560250269956
    - type: manhattan_pearson
      value: 69.32201332479197
    - type: manhattan_spearman
      value: 70.92406185691
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/CLSClusteringP2P
      name: MTEB CLSClusteringP2P
      config: default
      split: test
      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
    metrics:
    - type: v_measure
      value: 39.31955168227449
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/CLSClusteringS2S
      name: MTEB CLSClusteringS2S
      config: default
      split: test
      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
    metrics:
    - type: v_measure
      value: 37.8418274237459
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/CMedQAv1-reranking
      name: MTEB CMedQAv1
      config: default
      split: test
      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
    metrics:
    - type: map
      value: 80.66118119519746
    - type: mrr
      value: 83.47972222222222
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/CMedQAv2-reranking
      name: MTEB CMedQAv2
      config: default
      split: test
      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
    metrics:
    - type: map
      value: 79.31430375371524
    - type: mrr
      value: 82.10194444444444
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/CmedqaRetrieval
      name: MTEB CmedqaRetrieval
      config: default
      split: dev
      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
    metrics:
    - type: map_at_1
      value: 16.672
    - type: map_at_10
      value: 26.273000000000003
    - type: map_at_100
      value: 28.044999999999998
    - type: map_at_1000
      value: 28.208
    - type: map_at_3
      value: 22.989
    - type: map_at_5
      value: 24.737000000000002
    - type: mrr_at_1
      value: 26.257
    - type: mrr_at_10
      value: 34.358
    - type: mrr_at_100
      value: 35.436
    - type: mrr_at_1000
      value: 35.513
    - type: mrr_at_3
      value: 31.954
    - type: mrr_at_5
      value: 33.234
    - type: ndcg_at_1
      value: 26.257
    - type: ndcg_at_10
      value: 32.326
    - type: ndcg_at_100
      value: 39.959
    - type: ndcg_at_1000
      value: 43.163000000000004
    - type: ndcg_at_3
      value: 27.700999999999997
    - type: ndcg_at_5
      value: 29.514000000000003
    - type: precision_at_1
      value: 26.257
    - type: precision_at_10
      value: 7.607
    - type: precision_at_100
      value: 1.388
    - type: precision_at_1000
      value: 0.179
    - type: precision_at_3
      value: 16.162000000000003
    - type: precision_at_5
      value: 11.933
    - type: recall_at_1
      value: 16.672
    - type: recall_at_10
      value: 42.135
    - type: recall_at_100
      value: 74.417
    - type: recall_at_1000
      value: 96.417
    - type: recall_at_3
      value: 28.416999999999998
    - type: recall_at_5
      value: 33.873999999999995
  - task:
      type: PairClassification
    dataset:
      type: C-MTEB/CMNLI
      name: MTEB Cmnli
      config: default
      split: validation
      revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
    metrics:
    - type: cos_sim_accuracy
      value: 61.11846061334937
    - type: cos_sim_ap
      value: 65.68356716139071
    - type: cos_sim_f1
      value: 68.15213842637937
    - type: cos_sim_precision
      value: 52.35109717868338
    - type: cos_sim_recall
      value: 97.61515080664017
    - type: dot_accuracy
      value: 61.11846061334937
    - type: dot_ap
      value: 65.68369552204702
    - type: dot_f1
      value: 68.15213842637937
    - type: dot_precision
      value: 52.35109717868338
    - type: dot_recall
      value: 97.61515080664017
    - type: euclidean_accuracy
      value: 61.11846061334937
    - type: euclidean_ap
      value: 65.68356789608616
    - type: euclidean_f1
      value: 68.15213842637937
    - type: euclidean_precision
      value: 52.35109717868338
    - type: euclidean_recall
      value: 97.61515080664017
    - type: manhattan_accuracy
      value: 61.17859290438966
    - type: manhattan_ap
      value: 65.68230365595265
    - type: manhattan_f1
      value: 68.14029363784665
    - type: manhattan_precision
      value: 52.32368783665289
    - type: manhattan_recall
      value: 97.66191255552957
    - type: max_accuracy
      value: 61.17859290438966
    - type: max_ap
      value: 65.68369552204702
    - type: max_f1
      value: 68.15213842637937
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/CovidRetrieval
      name: MTEB CovidRetrieval
      config: default
      split: dev
      revision: 1271c7809071a13532e05f25fb53511ffce77117
    metrics:
    - type: map_at_1
      value: 51.054
    - type: map_at_10
      value: 61.926
    - type: map_at_100
      value: 62.514
    - type: map_at_1000
      value: 62.529
    - type: map_at_3
      value: 59.272999999999996
    - type: map_at_5
      value: 60.943000000000005
    - type: mrr_at_1
      value: 51.212
    - type: mrr_at_10
      value: 61.916000000000004
    - type: mrr_at_100
      value: 62.495999999999995
    - type: mrr_at_1000
      value: 62.511
    - type: mrr_at_3
      value: 59.326
    - type: mrr_at_5
      value: 60.958999999999996
    - type: ndcg_at_1
      value: 51.212
    - type: ndcg_at_10
      value: 67.223
    - type: ndcg_at_100
      value: 69.92699999999999
    - type: ndcg_at_1000
      value: 70.307
    - type: ndcg_at_3
      value: 61.873
    - type: ndcg_at_5
      value: 64.883
    - type: precision_at_1
      value: 51.212
    - type: precision_at_10
      value: 8.472
    - type: precision_at_100
      value: 0.9730000000000001
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 23.253
    - type: precision_at_5
      value: 15.448
    - type: recall_at_1
      value: 51.054
    - type: recall_at_10
      value: 83.825
    - type: recall_at_100
      value: 96.207
    - type: recall_at_1000
      value: 99.157
    - type: recall_at_3
      value: 69.31
    - type: recall_at_5
      value: 76.66
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/DuRetrieval
      name: MTEB DuRetrieval
      config: default
      split: dev
      revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
    metrics:
    - type: map_at_1
      value: 21.247
    - type: map_at_10
      value: 64.793
    - type: map_at_100
      value: 68.62899999999999
    - type: map_at_1000
      value: 68.718
    - type: map_at_3
      value: 44.192
    - type: map_at_5
      value: 55.435
    - type: mrr_at_1
      value: 76.7
    - type: mrr_at_10
      value: 84.22
    - type: mrr_at_100
      value: 84.341
    - type: mrr_at_1000
      value: 84.346
    - type: mrr_at_3
      value: 83.42500000000001
    - type: mrr_at_5
      value: 83.902
    - type: ndcg_at_1
      value: 76.7
    - type: ndcg_at_10
      value: 75.271
    - type: ndcg_at_100
      value: 80.62
    - type: ndcg_at_1000
      value: 81.45
    - type: ndcg_at_3
      value: 72.803
    - type: ndcg_at_5
      value: 71.694
    - type: precision_at_1
      value: 76.7
    - type: precision_at_10
      value: 36.925000000000004
    - type: precision_at_100
      value: 4.675
    - type: precision_at_1000
      value: 0.48700000000000004
    - type: precision_at_3
      value: 65.383
    - type: precision_at_5
      value: 55.15
    - type: recall_at_1
      value: 21.247
    - type: recall_at_10
      value: 78.38300000000001
    - type: recall_at_100
      value: 94.759
    - type: recall_at_1000
      value: 98.907
    - type: recall_at_3
      value: 48.04
    - type: recall_at_5
      value: 62.883
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/EcomRetrieval
      name: MTEB EcomRetrieval
      config: default
      split: dev
      revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
    metrics:
    - type: map_at_1
      value: 42.0
    - type: map_at_10
      value: 52.691
    - type: map_at_100
      value: 53.456
    - type: map_at_1000
      value: 53.480000000000004
    - type: map_at_3
      value: 49.583
    - type: map_at_5
      value: 51.723
    - type: mrr_at_1
      value: 42.0
    - type: mrr_at_10
      value: 52.691
    - type: mrr_at_100
      value: 53.456
    - type: mrr_at_1000
      value: 53.480000000000004
    - type: mrr_at_3
      value: 49.583
    - type: mrr_at_5
      value: 51.723
    - type: ndcg_at_1
      value: 42.0
    - type: ndcg_at_10
      value: 58.243
    - type: ndcg_at_100
      value: 61.907999999999994
    - type: ndcg_at_1000
      value: 62.483999999999995
    - type: ndcg_at_3
      value: 52.03
    - type: ndcg_at_5
      value: 55.85099999999999
    - type: precision_at_1
      value: 42.0
    - type: precision_at_10
      value: 7.580000000000001
    - type: precision_at_100
      value: 0.928
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 19.7
    - type: precision_at_5
      value: 13.66
    - type: recall_at_1
      value: 42.0
    - type: recall_at_10
      value: 75.8
    - type: recall_at_100
      value: 92.80000000000001
    - type: recall_at_1000
      value: 97.2
    - type: recall_at_3
      value: 59.099999999999994
    - type: recall_at_5
      value: 68.30000000000001
  - task:
      type: Classification
    dataset:
      type: C-MTEB/IFlyTek-classification
      name: MTEB IFlyTek
      config: default
      split: validation
      revision: 421605374b29664c5fc098418fe20ada9bd55f8a
    metrics:
    - type: accuracy
      value: 44.86340900346287
    - type: f1
      value: 31.324006049353713
  - task:
      type: Classification
    dataset:
      type: C-MTEB/JDReview-classification
      name: MTEB JDReview
      config: default
      split: test
      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
    metrics:
    - type: accuracy
      value: 88.48030018761726
    - type: ap
      value: 59.392058006606476
    - type: f1
      value: 83.61333024672861
  - task:
      type: STS
    dataset:
      type: C-MTEB/LCQMC
      name: MTEB LCQMC
      config: default
      split: test
      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
    metrics:
    - type: cos_sim_pearson
      value: 66.36852873686233
    - type: cos_sim_spearman
      value: 73.27371960661353
    - type: euclidean_pearson
      value: 71.38209904858738
    - type: euclidean_spearman
      value: 73.27373512049904
    - type: manhattan_pearson
      value: 71.51557697058817
    - type: manhattan_spearman
      value: 73.38956581066971
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/Mmarco-reranking
      name: MTEB MMarcoReranking
      config: default
      split: dev
      revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6
    metrics:
    - type: map
      value: 19.57107231987867
    - type: mrr
      value: 18.224603174603175
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/MMarcoRetrieval
      name: MTEB MMarcoRetrieval
      config: default
      split: dev
      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
    metrics:
    - type: map_at_1
      value: 43.785000000000004
    - type: map_at_10
      value: 53.278000000000006
    - type: map_at_100
      value: 53.946000000000005
    - type: map_at_1000
      value: 53.983000000000004
    - type: map_at_3
      value: 50.846999999999994
    - type: map_at_5
      value: 52.286
    - type: mrr_at_1
      value: 45.559
    - type: mrr_at_10
      value: 54.129000000000005
    - type: mrr_at_100
      value: 54.732
    - type: mrr_at_1000
      value: 54.766999999999996
    - type: mrr_at_3
      value: 51.885999999999996
    - type: mrr_at_5
      value: 53.212
    - type: ndcg_at_1
      value: 45.559
    - type: ndcg_at_10
      value: 57.909
    - type: ndcg_at_100
      value: 61.068999999999996
    - type: ndcg_at_1000
      value: 62.09400000000001
    - type: ndcg_at_3
      value: 53.125
    - type: ndcg_at_5
      value: 55.614
    - type: precision_at_1
      value: 45.559
    - type: precision_at_10
      value: 7.617
    - type: precision_at_100
      value: 0.9199999999999999
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 20.707
    - type: precision_at_5
      value: 13.730999999999998
    - type: recall_at_1
      value: 43.785000000000004
    - type: recall_at_10
      value: 71.543
    - type: recall_at_100
      value: 86.197
    - type: recall_at_1000
      value: 94.305
    - type: recall_at_3
      value: 58.677
    - type: recall_at_5
      value: 64.62599999999999
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (zh-CN)
      config: zh-CN
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.29455279085406
    - type: f1
      value: 58.42865357114413
  - 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: 66.89979825151312
    - type: f1
      value: 66.6125514843663
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/MedicalRetrieval
      name: MTEB MedicalRetrieval
      config: default
      split: dev
      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
    metrics:
    - type: map_at_1
      value: 44.7
    - type: map_at_10
      value: 51.307
    - type: map_at_100
      value: 52.002
    - type: map_at_1000
      value: 52.06699999999999
    - type: map_at_3
      value: 49.55
    - type: map_at_5
      value: 50.544999999999995
    - type: mrr_at_1
      value: 44.9
    - type: mrr_at_10
      value: 51.415
    - type: mrr_at_100
      value: 52.111
    - type: mrr_at_1000
      value: 52.175000000000004
    - type: mrr_at_3
      value: 49.683
    - type: mrr_at_5
      value: 50.653000000000006
    - type: ndcg_at_1
      value: 44.7
    - type: ndcg_at_10
      value: 54.778000000000006
    - type: ndcg_at_100
      value: 58.526
    - type: ndcg_at_1000
      value: 60.187999999999995
    - type: ndcg_at_3
      value: 51.129999999999995
    - type: ndcg_at_5
      value: 52.933
    - type: precision_at_1
      value: 44.7
    - type: precision_at_10
      value: 6.58
    - type: precision_at_100
      value: 0.8420000000000001
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 18.567
    - type: precision_at_5
      value: 12.02
    - type: recall_at_1
      value: 44.7
    - type: recall_at_10
      value: 65.8
    - type: recall_at_100
      value: 84.2
    - type: recall_at_1000
      value: 97.2
    - type: recall_at_3
      value: 55.7
    - type: recall_at_5
      value: 60.099999999999994
  - task:
      type: Retrieval
    dataset:
      type: Shitao/MLDR
      name: MTEB MultiLongDocRetrieval (zh)
      config: zh
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 7.625
    - type: map_at_10
      value: 10.238
    - type: map_at_100
      value: 10.885
    - type: map_at_1000
      value: 10.958
    - type: map_at_3
      value: 9.292
    - type: map_at_5
      value: 9.91
    - type: mrr_at_1
      value: 7.625
    - type: mrr_at_10
      value: 10.238
    - type: mrr_at_100
      value: 10.885
    - type: mrr_at_1000
      value: 10.958
    - type: mrr_at_3
      value: 9.292
    - type: mrr_at_5
      value: 9.91
    - type: ndcg_at_1
      value: 7.625
    - type: ndcg_at_10
      value: 11.784
    - type: ndcg_at_100
      value: 15.133
    - type: ndcg_at_1000
      value: 17.511
    - type: ndcg_at_3
      value: 9.857000000000001
    - type: ndcg_at_5
      value: 10.981
    - type: precision_at_1
      value: 7.625
    - type: precision_at_10
      value: 1.675
    - type: precision_at_100
      value: 0.329
    - type: precision_at_1000
      value: 0.053
    - type: precision_at_3
      value: 3.833
    - type: precision_at_5
      value: 2.85
    - type: recall_at_1
      value: 7.625
    - type: recall_at_10
      value: 16.75
    - type: recall_at_100
      value: 32.875
    - type: recall_at_1000
      value: 52.625
    - type: recall_at_3
      value: 11.5
    - type: recall_at_5
      value: 14.249999999999998
  - task:
      type: Classification
    dataset:
      type: C-MTEB/MultilingualSentiment-classification
      name: MTEB MultilingualSentiment
      config: default
      split: validation
      revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
    metrics:
    - type: accuracy
      value: 78.45666666666666
    - type: f1
      value: 78.06393644109178
  - task:
      type: PairClassification
    dataset:
      type: C-MTEB/OCNLI
      name: MTEB Ocnli
      config: default
      split: validation
      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
    metrics:
    - type: cos_sim_accuracy
      value: 59.88088792636708
    - type: cos_sim_ap
      value: 59.993466246406854
    - type: cos_sim_f1
      value: 69.33333333333334
    - type: cos_sim_precision
      value: 54.23122765196663
    - type: cos_sim_recall
      value: 96.09292502639916
    - type: dot_accuracy
      value: 59.88088792636708
    - type: dot_ap
      value: 59.99351215786742
    - type: dot_f1
      value: 69.33333333333334
    - type: dot_precision
      value: 54.23122765196663
    - type: dot_recall
      value: 96.09292502639916
    - type: euclidean_accuracy
      value: 59.88088792636708
    - type: euclidean_ap
      value: 59.993466246406854
    - type: euclidean_f1
      value: 69.33333333333334
    - type: euclidean_precision
      value: 54.23122765196663
    - type: euclidean_recall
      value: 96.09292502639916
    - type: manhattan_accuracy
      value: 59.989171629669734
    - type: manhattan_ap
      value: 60.06745167956717
    - type: manhattan_f1
      value: 69.37381404174573
    - type: manhattan_precision
      value: 54.14691943127961
    - type: manhattan_recall
      value: 96.51531151003168
    - type: max_accuracy
      value: 59.989171629669734
    - type: max_ap
      value: 60.06745167956717
    - type: max_f1
      value: 69.37381404174573
  - task:
      type: Classification
    dataset:
      type: C-MTEB/OnlineShopping-classification
      name: MTEB OnlineShopping
      config: default
      split: test
      revision: e610f2ebd179a8fda30ae534c3878750a96db120
    metrics:
    - type: accuracy
      value: 92.58
    - type: ap
      value: 90.58624365698103
    - type: f1
      value: 92.56998002261557
  - task:
      type: STS
    dataset:
      type: C-MTEB/PAWSX
      name: MTEB PAWSX
      config: default
      split: test
      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
    metrics:
    - type: cos_sim_pearson
      value: 15.428347645738844
    - type: cos_sim_spearman
      value: 18.54916824520863
    - type: euclidean_pearson
      value: 18.525706701701317
    - type: euclidean_spearman
      value: 18.564855538117524
    - type: manhattan_pearson
      value: 18.54511262151164
    - type: manhattan_spearman
      value: 18.587848451111213
  - task:
      type: PairClassification
    dataset:
      type: paws-x
      name: MTEB PawsX (zh)
      config: zh
      split: test
      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
    metrics:
    - type: cos_sim_accuracy
      value: 60.3
    - type: cos_sim_ap
      value: 57.92869006380703
    - type: cos_sim_f1
      value: 62.31681786461968
    - type: cos_sim_precision
      value: 45.283975659229206
    - type: cos_sim_recall
      value: 99.88814317673378
    - type: dot_accuracy
      value: 60.3
    - type: dot_ap
      value: 57.7632607916169
    - type: dot_f1
      value: 62.31681786461968
    - type: dot_precision
      value: 45.283975659229206
    - type: dot_recall
      value: 99.88814317673378
    - type: euclidean_accuracy
      value: 60.3
    - type: euclidean_ap
      value: 57.92869006380703
    - type: euclidean_f1
      value: 62.31681786461968
    - type: euclidean_precision
      value: 45.283975659229206
    - type: euclidean_recall
      value: 99.88814317673378
    - type: manhattan_accuracy
      value: 60.25
    - type: manhattan_ap
      value: 57.929597845689706
    - type: manhattan_f1
      value: 62.31681786461968
    - type: manhattan_precision
      value: 45.283975659229206
    - type: manhattan_recall
      value: 99.88814317673378
    - type: max_accuracy
      value: 60.3
    - type: max_ap
      value: 57.929597845689706
    - type: max_f1
      value: 62.31681786461968
  - task:
      type: STS
    dataset:
      type: C-MTEB/QBQTC
      name: MTEB QBQTC
      config: default
      split: test
      revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
    metrics:
    - type: cos_sim_pearson
      value: 28.445664430656038
    - type: cos_sim_spearman
      value: 29.599326690902288
    - type: euclidean_pearson
      value: 27.900455284977017
    - type: euclidean_spearman
      value: 29.599947224705264
    - type: manhattan_pearson
      value: 28.101656918683116
    - type: manhattan_spearman
      value: 29.78083888978687
  - task:
      type: STS
    dataset:
      type: mteb/sts22-crosslingual-sts
      name: MTEB STS22 (zh)
      config: zh
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 61.13774633735679
    - type: cos_sim_spearman
      value: 65.43749616084263
    - type: euclidean_pearson
      value: 63.42122949030793
    - type: euclidean_spearman
      value: 65.43749616084263
    - type: manhattan_pearson
      value: 63.78466267937151
    - type: manhattan_spearman
      value: 65.4252196465631
  - task:
      type: STS
    dataset:
      type: C-MTEB/STSB
      name: MTEB STSB
      config: default
      split: test
      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
    metrics:
    - type: cos_sim_pearson
      value: 66.43725663481563
    - type: cos_sim_spearman
      value: 66.91073455354187
    - type: euclidean_pearson
      value: 67.25178758750022
    - type: euclidean_spearman
      value: 66.91129699608939
    - type: manhattan_pearson
      value: 67.33381999971951
    - type: manhattan_spearman
      value: 66.9990458174529
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/T2Reranking
      name: MTEB T2Reranking
      config: default
      split: dev
      revision: 76631901a18387f85eaa53e5450019b87ad58ef9
    metrics:
    - type: map
      value: 64.31327281684898
    - type: mrr
      value: 73.58095291829211
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/T2Retrieval
      name: MTEB T2Retrieval
      config: default
      split: dev
      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
    metrics:
    - type: map_at_1
      value: 20.961
    - type: map_at_10
      value: 59.065
    - type: map_at_100
      value: 63.544
    - type: map_at_1000
      value: 63.681
    - type: map_at_3
      value: 40.849999999999994
    - type: map_at_5
      value: 50.268
    - type: mrr_at_1
      value: 74.934
    - type: mrr_at_10
      value: 80.571
    - type: mrr_at_100
      value: 80.814
    - type: mrr_at_1000
      value: 80.82300000000001
    - type: mrr_at_3
      value: 79.449
    - type: mrr_at_5
      value: 80.13
    - type: ndcg_at_1
      value: 74.934
    - type: ndcg_at_10
      value: 69.215
    - type: ndcg_at_100
      value: 75.61099999999999
    - type: ndcg_at_1000
      value: 77.03999999999999
    - type: ndcg_at_3
      value: 70.04899999999999
    - type: ndcg_at_5
      value: 68.50699999999999
    - type: precision_at_1
      value: 74.934
    - type: precision_at_10
      value: 35.569
    - type: precision_at_100
      value: 4.757
    - type: precision_at_1000
      value: 0.509
    - type: precision_at_3
      value: 61.802
    - type: precision_at_5
      value: 51.882
    - type: recall_at_1
      value: 20.961
    - type: recall_at_10
      value: 69.626
    - type: recall_at_100
      value: 89.464
    - type: recall_at_1000
      value: 96.721
    - type: recall_at_3
      value: 43.608999999999995
    - type: recall_at_5
      value: 55.724
  - task:
      type: Classification
    dataset:
      type: C-MTEB/TNews-classification
      name: MTEB TNews
      config: default
      split: validation
      revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
    metrics:
    - type: accuracy
      value: 50.01800000000001
    - type: f1
      value: 48.262341643251936
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/ThuNewsClusteringP2P
      name: MTEB ThuNewsClusteringP2P
      config: default
      split: test
      revision: 5798586b105c0434e4f0fe5e767abe619442cf93
    metrics:
    - type: v_measure
      value: 60.68748256831344
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/ThuNewsClusteringS2S
      name: MTEB ThuNewsClusteringS2S
      config: default
      split: test
      revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
    metrics:
    - type: v_measure
      value: 56.73298697800912
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/VideoRetrieval
      name: MTEB VideoRetrieval
      config: default
      split: dev
      revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
    metrics:
    - type: map_at_1
      value: 46.9
    - type: map_at_10
      value: 57.849
    - type: map_at_100
      value: 58.532
    - type: map_at_1000
      value: 58.553
    - type: map_at_3
      value: 55.467
    - type: map_at_5
      value: 56.92700000000001
    - type: mrr_at_1
      value: 46.9
    - type: mrr_at_10
      value: 57.849
    - type: mrr_at_100
      value: 58.532
    - type: mrr_at_1000
      value: 58.553
    - type: mrr_at_3
      value: 55.467
    - type: mrr_at_5
      value: 56.92700000000001
    - type: ndcg_at_1
      value: 46.9
    - type: ndcg_at_10
      value: 63.09
    - type: ndcg_at_100
      value: 66.43
    - type: ndcg_at_1000
      value: 66.949
    - type: ndcg_at_3
      value: 58.226
    - type: ndcg_at_5
      value: 60.838
    - type: precision_at_1
      value: 46.9
    - type: precision_at_10
      value: 7.95
    - type: precision_at_100
      value: 0.951
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 22.067
    - type: precision_at_5
      value: 14.499999999999998
    - type: recall_at_1
      value: 46.9
    - type: recall_at_10
      value: 79.5
    - type: recall_at_100
      value: 95.1
    - type: recall_at_1000
      value: 99.1
    - type: recall_at_3
      value: 66.2
    - type: recall_at_5
      value: 72.5
  - task:
      type: Classification
    dataset:
      type: C-MTEB/waimai-classification
      name: MTEB Waimai
      config: default
      split: test
      revision: 339287def212450dcaa9df8c22bf93e9980c7023
    metrics:
    - type: accuracy
      value: 89.09
    - type: ap
      value: 74.68093732384233
    - type: f1
      value: 87.7768409829789
---