m3e-ernie-xbase-zh / README.md
neosfeng
update model and metric
bf092ae
metadata
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
          - 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
          - 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
          - 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
          - 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
          - 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