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README.md

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+---
+tags:
+- mteb
+model-index:
+- name: IYun-large-zh
+  results:
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/AFQMC
+      name: MTEB AFQMC
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 54.0230470968506
+    - type: cos_sim_spearman
+      value: 58.79814040939044
+    - type: euclidean_pearson
+      value: 57.456654584077896
+    - type: euclidean_spearman
+      value: 58.797175403338585
+    - type: manhattan_pearson
+      value: 57.44746868687558
+    - type: manhattan_spearman
+      value: 58.79066161248843
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/ATEC
+      name: MTEB ATEC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 53.52082226478944
+    - type: cos_sim_spearman
+      value: 57.94121517359626
+    - type: euclidean_pearson
+      value: 61.160779395243715
+    - type: euclidean_spearman
+      value: 57.941233187487526
+    - type: manhattan_pearson
+      value: 61.15878861542791
+    - type: manhattan_spearman
+      value: 57.940620715184224
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (zh)
+      config: zh
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 48.536
+    - type: f1
+      value: 46.59904838748693
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/BQ
+      name: MTEB BQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 68.2618929828169
+    - type: cos_sim_spearman
+      value: 70.36192476428671
+    - type: euclidean_pearson
+      value: 69.41572660105302
+    - type: euclidean_spearman
+      value: 70.36195940530303
+    - type: manhattan_pearson
+      value: 69.39132691183522
+    - type: manhattan_spearman
+      value: 70.34010092400209
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/CLSClusteringP2P
+      name: MTEB CLSClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 47.08423639165573
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/CLSClusteringS2S
+      name: MTEB CLSClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 44.05176471944069
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/CMedQAv1-reranking
+      name: MTEB CMedQAv1
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 88.57151543594188
+    - type: mrr
+      value: 90.61761904761904
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/CMedQAv2-reranking
+      name: MTEB CMedQAv2
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 88.89654770110027
+    - type: mrr
+      value: 90.90099206349205
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/CmedqaRetrieval
+      name: MTEB CmedqaRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.924999999999997
+    - type: map_at_10
+      value: 40.0
+    - type: map_at_100
+      value: 41.911
+    - type: map_at_1000
+      value: 42.013
+    - type: map_at_3
+      value: 35.408
+    - type: map_at_5
+      value: 38.025999999999996
+    - type: mrr_at_1
+      value: 40.685
+    - type: mrr_at_10
+      value: 48.837
+    - type: mrr_at_100
+      value: 49.823
+    - type: mrr_at_1000
+      value: 49.863
+    - type: mrr_at_3
+      value: 46.141
+    - type: mrr_at_5
+      value: 47.707
+    - type: ndcg_at_1
+      value: 40.685
+    - type: ndcg_at_10
+      value: 46.768
+    - type: ndcg_at_100
+      value: 53.996
+    - type: ndcg_at_1000
+      value: 55.694
+    - type: ndcg_at_3
+      value: 40.993
+    - type: ndcg_at_5
+      value: 43.553999999999995
+    - type: precision_at_1
+      value: 40.685
+    - type: precision_at_10
+      value: 10.42
+    - type: precision_at_100
+      value: 1.625
+    - type: precision_at_1000
+      value: 0.184
+    - type: precision_at_3
+      value: 23.105999999999998
+    - type: precision_at_5
+      value: 16.994
+    - type: recall_at_1
+      value: 26.924999999999997
+    - type: recall_at_10
+      value: 57.818999999999996
+    - type: recall_at_100
+      value: 87.4
+    - type: recall_at_1000
+      value: 98.721
+    - type: recall_at_3
+      value: 40.732
+    - type: recall_at_5
+      value: 48.359
+  - task:
+      type: PairClassification
+    dataset:
+      type: C-MTEB/CMNLI
+      name: MTEB Cmnli
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 81.10449377368705
+    - type: cos_sim_ap
+      value: 85.15661533065932
+    - type: cos_sim_f1
+      value: 82.98479087452472
+    - type: cos_sim_precision
+      value: 75.45375972342264
+    - type: cos_sim_recall
+      value: 92.18585005279832
+    - type: dot_accuracy
+      value: 81.10449377368705
+    - type: dot_ap
+      value: 85.1383107430588
+    - type: dot_f1
+      value: 82.98479087452472
+    - type: dot_precision
+      value: 75.45375972342264
+    - type: dot_recall
+      value: 92.18585005279832
+    - type: euclidean_accuracy
+      value: 81.10449377368705
+    - type: euclidean_ap
+      value: 85.15515844935794
+    - type: euclidean_f1
+      value: 82.96860133206471
+    - type: euclidean_precision
+      value: 75.4978354978355
+    - type: euclidean_recall
+      value: 92.08025343189018
+    - type: manhattan_accuracy
+      value: 81.10449377368705
+    - type: manhattan_ap
+      value: 85.1260027067541
+    - type: manhattan_f1
+      value: 82.93384467881111
+    - type: manhattan_precision
+      value: 75.94381035996489
+    - type: manhattan_recall
+      value: 91.34107708553326
+    - type: max_accuracy
+      value: 81.10449377368705
+    - type: max_ap
+      value: 85.15661533065932
+    - type: max_f1
+      value: 82.98479087452472
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/CovidRetrieval
+      name: MTEB CovidRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 68.44
+    - type: map_at_10
+      value: 77.571
+    - type: map_at_100
+      value: 77.834
+    - type: map_at_1000
+      value: 77.838
+    - type: map_at_3
+      value: 75.913
+    - type: map_at_5
+      value: 76.942
+    - type: mrr_at_1
+      value: 68.809
+    - type: mrr_at_10
+      value: 77.656
+    - type: mrr_at_100
+      value: 77.912
+    - type: mrr_at_1000
+      value: 77.916
+    - type: mrr_at_3
+      value: 76.063
+    - type: mrr_at_5
+      value: 77.074
+    - type: ndcg_at_1
+      value: 68.704
+    - type: ndcg_at_10
+      value: 81.524
+    - type: ndcg_at_100
+      value: 82.72
+    - type: ndcg_at_1000
+      value: 82.826
+    - type: ndcg_at_3
+      value: 78.251
+    - type: ndcg_at_5
+      value: 80.075
+    - type: precision_at_1
+      value: 68.704
+    - type: precision_at_10
+      value: 9.463000000000001
+    - type: precision_at_100
+      value: 1.001
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 28.486
+    - type: precision_at_5
+      value: 18.019
+    - type: recall_at_1
+      value: 68.44
+    - type: recall_at_10
+      value: 93.625
+    - type: recall_at_100
+      value: 99.05199999999999
+    - type: recall_at_1000
+      value: 99.895
+    - type: recall_at_3
+      value: 84.879
+    - type: recall_at_5
+      value: 89.252
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/DuRetrieval
+      name: MTEB DuRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.653
+    - type: map_at_10
+      value: 79.118
+    - type: map_at_100
+      value: 81.917
+    - type: map_at_1000
+      value: 81.962
+    - type: map_at_3
+      value: 54.56999999999999
+    - type: map_at_5
+      value: 69.246
+    - type: mrr_at_1
+      value: 89.35
+    - type: mrr_at_10
+      value: 92.69
+    - type: mrr_at_100
+      value: 92.77
+    - type: mrr_at_1000
+      value: 92.77300000000001
+    - type: mrr_at_3
+      value: 92.425
+    - type: mrr_at_5
+      value: 92.575
+    - type: ndcg_at_1
+      value: 89.35
+    - type: ndcg_at_10
+      value: 86.558
+    - type: ndcg_at_100
+      value: 89.36
+    - type: ndcg_at_1000
+      value: 89.789
+    - type: ndcg_at_3
+      value: 85.419
+    - type: ndcg_at_5
+      value: 84.52
+    - type: precision_at_1
+      value: 89.35
+    - type: precision_at_10
+      value: 41.589999999999996
+    - type: precision_at_100
+      value: 4.781
+    - type: precision_at_1000
+      value: 0.488
+    - type: precision_at_3
+      value: 76.717
+    - type: precision_at_5
+      value: 65.08
+    - type: recall_at_1
+      value: 25.653
+    - type: recall_at_10
+      value: 87.651
+    - type: recall_at_100
+      value: 96.858
+    - type: recall_at_1000
+      value: 99.13300000000001
+    - type: recall_at_3
+      value: 56.901
+    - type: recall_at_5
+      value: 74.054
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/EcomRetrieval
+      name: MTEB EcomRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 52.0
+    - type: map_at_10
+      value: 62.576
+    - type: map_at_100
+      value: 63.073
+    - type: map_at_1000
+      value: 63.09
+    - type: map_at_3
+      value: 60.25
+    - type: map_at_5
+      value: 61.73
+    - type: mrr_at_1
+      value: 52.0
+    - type: mrr_at_10
+      value: 62.576
+    - type: mrr_at_100
+      value: 63.073
+    - type: mrr_at_1000
+      value: 63.09
+    - type: mrr_at_3
+      value: 60.25
+    - type: mrr_at_5
+      value: 61.73
+    - type: ndcg_at_1
+      value: 52.0
+    - type: ndcg_at_10
+      value: 67.535
+    - type: ndcg_at_100
+      value: 69.918
+    - type: ndcg_at_1000
+      value: 70.303
+    - type: ndcg_at_3
+      value: 62.839
+    - type: ndcg_at_5
+      value: 65.511
+    - type: precision_at_1
+      value: 52.0
+    - type: precision_at_10
+      value: 8.3
+    - type: precision_at_100
+      value: 0.941
+    - type: precision_at_1000
+      value: 0.097
+    - type: precision_at_3
+      value: 23.433
+    - type: precision_at_5
+      value: 15.36
+    - type: recall_at_1
+      value: 52.0
+    - type: recall_at_10
+      value: 83.0
+    - type: recall_at_100
+      value: 94.1
+    - type: recall_at_1000
+      value: 97.0
+    - type: recall_at_3
+      value: 70.3
+    - type: recall_at_5
+      value: 76.8
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/IFlyTek-classification
+      name: MTEB IFlyTek
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 51.76606387071951
+    - type: f1
+      value: 40.31516560726137
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/JDReview-classification
+      name: MTEB JDReview
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 86.69793621013133
+    - type: ap
+      value: 55.46718958939327
+    - type: f1
+      value: 81.48228915952436
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/LCQMC
+      name: MTEB LCQMC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 71.13474501946303
+    - type: cos_sim_spearman
+      value: 78.1761029193962
+    - type: euclidean_pearson
+      value: 77.48482435905522
+    - type: euclidean_spearman
+      value: 78.17607188104564
+    - type: manhattan_pearson
+      value: 77.47331798992634
+    - type: manhattan_spearman
+      value: 78.1667116013234
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/Mmarco-reranking
+      name: MTEB MMarcoReranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 28.23811014679616
+    - type: mrr
+      value: 27.34960317460317
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/MMarcoRetrieval
+      name: MTEB MMarcoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 65.697
+    - type: map_at_10
+      value: 74.778
+    - type: map_at_100
+      value: 75.117
+    - type: map_at_1000
+      value: 75.129
+    - type: map_at_3
+      value: 73.029
+    - type: map_at_5
+      value: 74.148
+    - type: mrr_at_1
+      value: 67.96600000000001
+    - type: mrr_at_10
+      value: 75.405
+    - type: mrr_at_100
+      value: 75.703
+    - type: mrr_at_1000
+      value: 75.714
+    - type: mrr_at_3
+      value: 73.892
+    - type: mrr_at_5
+      value: 74.86
+    - type: ndcg_at_1
+      value: 67.96600000000001
+    - type: ndcg_at_10
+      value: 78.444
+    - type: ndcg_at_100
+      value: 79.971
+    - type: ndcg_at_1000
+      value: 80.284
+    - type: ndcg_at_3
+      value: 75.13300000000001
+    - type: ndcg_at_5
+      value: 77.018
+    - type: precision_at_1
+      value: 67.96600000000001
+    - type: precision_at_10
+      value: 9.474
+    - type: precision_at_100
+      value: 1.023
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_3
+      value: 28.328999999999997
+    - type: precision_at_5
+      value: 17.989
+    - type: recall_at_1
+      value: 65.697
+    - type: recall_at_10
+      value: 89.09899999999999
+    - type: recall_at_100
+      value: 96.023
+    - type: recall_at_1000
+      value: 98.441
+    - type: recall_at_3
+      value: 80.343
+    - type: recall_at_5
+      value: 84.824
+  - 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: 75.86751849361129
+    - type: f1
+      value: 73.04392353740805
+  - 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: 78.43308675184936
+    - type: f1
+      value: 78.10822258565513
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/MedicalRetrieval
+      name: MTEB MedicalRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 54.900000000000006
+    - type: map_at_10
+      value: 60.99
+    - type: map_at_100
+      value: 61.556
+    - type: map_at_1000
+      value: 61.598
+    - type: map_at_3
+      value: 59.516999999999996
+    - type: map_at_5
+      value: 60.327
+    - type: mrr_at_1
+      value: 55.00000000000001
+    - type: mrr_at_10
+      value: 61.040000000000006
+    - type: mrr_at_100
+      value: 61.60600000000001
+    - type: mrr_at_1000
+      value: 61.648
+    - type: mrr_at_3
+      value: 59.567
+    - type: mrr_at_5
+      value: 60.377
+    - type: ndcg_at_1
+      value: 54.900000000000006
+    - type: ndcg_at_10
+      value: 64.021
+    - type: ndcg_at_100
+      value: 67.002
+    - type: ndcg_at_1000
+      value: 68.21300000000001
+    - type: ndcg_at_3
+      value: 60.955999999999996
+    - type: ndcg_at_5
+      value: 62.427
+    - type: precision_at_1
+      value: 54.900000000000006
+    - type: precision_at_10
+      value: 7.359999999999999
+    - type: precision_at_100
+      value: 0.881
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 21.7
+    - type: precision_at_5
+      value: 13.74
+    - type: recall_at_1
+      value: 54.900000000000006
+    - type: recall_at_10
+      value: 73.6
+    - type: recall_at_100
+      value: 88.1
+    - type: recall_at_1000
+      value: 97.8
+    - type: recall_at_3
+      value: 65.10000000000001
+    - type: recall_at_5
+      value: 68.7
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/MultilingualSentiment-classification
+      name: MTEB MultilingualSentiment
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 77.52333333333333
+    - type: f1
+      value: 77.49510023279737
+  - task:
+      type: PairClassification
+    dataset:
+      type: C-MTEB/OCNLI
+      name: MTEB Ocnli
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 81.10449377368705
+    - type: cos_sim_ap
+      value: 85.15661533065932
+    - type: cos_sim_f1
+      value: 82.98479087452472
+    - type: cos_sim_precision
+      value: 75.45375972342264
+    - type: cos_sim_recall
+      value: 92.18585005279832
+    - type: dot_accuracy
+      value: 81.10449377368705
+    - type: dot_ap
+      value: 85.1383107430588
+    - type: dot_f1
+      value: 82.98479087452472
+    - type: dot_precision
+      value: 75.45375972342264
+    - type: dot_recall
+      value: 92.18585005279832
+    - type: euclidean_accuracy
+      value: 81.10449377368705
+    - type: euclidean_ap
+      value: 85.15515844935794
+    - type: euclidean_f1
+      value: 82.96860133206471
+    - type: euclidean_precision
+      value: 75.4978354978355
+    - type: euclidean_recall
+      value: 92.08025343189018
+    - type: manhattan_accuracy
+      value: 81.10449377368705
+    - type: manhattan_ap
+      value: 85.1260027067541
+    - type: manhattan_f1
+      value: 82.93384467881111
+    - type: manhattan_precision
+      value: 75.94381035996489
+    - type: manhattan_recall
+      value: 91.34107708553326
+    - type: max_accuracy
+      value: 81.10449377368705
+    - type: max_ap
+      value: 85.15661533065932
+    - type: max_f1
+      value: 82.98479087452472
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/OnlineShopping-classification
+      name: MTEB OnlineShopping
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 93.71000000000001
+    - type: ap
+      value: 91.83202232349356
+    - type: f1
+      value: 93.69900560334331
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/PAWSX
+      name: MTEB PAWSX
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 39.12276072181213
+    - type: cos_sim_spearman
+      value: 45.47002950875883
+    - type: euclidean_pearson
+      value: 44.82137309399524
+    - type: euclidean_spearman
+      value: 45.46811344101213
+    - type: manhattan_pearson
+      value: 44.828762191664694
+    - type: manhattan_spearman
+      value: 45.48971275015666
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/QBQTC
+      name: MTEB QBQTC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 34.24312789444651
+    - type: cos_sim_spearman
+      value: 37.31008735675408
+    - type: euclidean_pearson
+      value: 35.12756687070336
+    - type: euclidean_spearman
+      value: 37.30862222238361
+    - type: manhattan_pearson
+      value: 35.08734520176313
+    - type: manhattan_spearman
+      value: 37.25663009244228
+  - 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: 61.30477884469
+    - type: cos_sim_spearman
+      value: 65.86475705722457
+    - type: euclidean_pearson
+      value: 64.06391333268994
+    - type: euclidean_spearman
+      value: 65.86335860593772
+    - type: manhattan_pearson
+      value: 64.01127637711839
+    - type: manhattan_spearman
+      value: 65.87720920117906
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/STSB
+      name: MTEB STSB
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.55425529217757
+    - type: cos_sim_spearman
+      value: 82.72308414906433
+    - type: euclidean_pearson
+      value: 82.4891240865874
+    - type: euclidean_spearman
+      value: 82.72120335429314
+    - type: manhattan_pearson
+      value: 82.4768946184714
+    - type: manhattan_spearman
+      value: 82.71021690525912
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/T2Reranking
+      name: MTEB T2Reranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 66.62441330068313
+    - type: mrr
+      value: 76.4081189347777
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/T2Retrieval
+      name: MTEB T2Retrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.883000000000003
+    - type: map_at_10
+      value: 77.525
+    - type: map_at_100
+      value: 81.144
+    - type: map_at_1000
+      value: 81.21000000000001
+    - type: map_at_3
+      value: 54.730000000000004
+    - type: map_at_5
+      value: 67.136
+    - type: mrr_at_1
+      value: 90.527
+    - type: mrr_at_10
+      value: 92.971
+    - type: mrr_at_100
+      value: 93.052
+    - type: mrr_at_1000
+      value: 93.05499999999999
+    - type: mrr_at_3
+      value: 92.557
+    - type: mrr_at_5
+      value: 92.81700000000001
+    - type: ndcg_at_1
+      value: 90.527
+    - type: ndcg_at_10
+      value: 85.08200000000001
+    - type: ndcg_at_100
+      value: 88.65899999999999
+    - type: ndcg_at_1000
+      value: 89.25999999999999
+    - type: ndcg_at_3
+      value: 86.586
+    - type: ndcg_at_5
+      value: 85.14699999999999
+    - type: precision_at_1
+      value: 90.527
+    - type: precision_at_10
+      value: 42.054
+    - type: precision_at_100
+      value: 5.013999999999999
+    - type: precision_at_1000
+      value: 0.516
+    - type: precision_at_3
+      value: 75.55199999999999
+    - type: precision_at_5
+      value: 63.249
+    - type: recall_at_1
+      value: 27.883000000000003
+    - type: recall_at_10
+      value: 83.949
+    - type: recall_at_100
+      value: 95.568
+    - type: recall_at_1000
+      value: 98.547
+    - type: recall_at_3
+      value: 56.374
+    - type: recall_at_5
+      value: 70.44200000000001
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/TNews-classification
+      name: MTEB TNews
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 53.689
+    - type: f1
+      value: 51.87029846425533
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/ThuNewsClusteringP2P
+      name: MTEB ThuNewsClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 75.13107992170329
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/ThuNewsClusteringS2S
+      name: MTEB ThuNewsClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 69.32221171095146
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/VideoRetrieval
+      name: MTEB VideoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 59.4
+    - type: map_at_10
+      value: 69.199
+    - type: map_at_100
+      value: 69.724
+    - type: map_at_1000
+      value: 69.73899999999999
+    - type: map_at_3
+      value: 67.717
+    - type: map_at_5
+      value: 68.777
+    - type: mrr_at_1
+      value: 59.3
+    - type: mrr_at_10
+      value: 69.149
+    - type: mrr_at_100
+      value: 69.674
+    - type: mrr_at_1000
+      value: 69.68900000000001
+    - type: mrr_at_3
+      value: 67.667
+    - type: mrr_at_5
+      value: 68.727
+    - type: ndcg_at_1
+      value: 59.4
+    - type: ndcg_at_10
+      value: 73.29
+    - type: ndcg_at_100
+      value: 75.589
+    - type: ndcg_at_1000
+      value: 75.985
+    - type: ndcg_at_3
+      value: 70.339
+    - type: ndcg_at_5
+      value: 72.241
+    - type: precision_at_1
+      value: 59.4
+    - type: precision_at_10
+      value: 8.58
+    - type: precision_at_100
+      value: 0.96
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 25.967000000000002
+    - type: precision_at_5
+      value: 16.5
+    - type: recall_at_1
+      value: 59.4
+    - type: recall_at_10
+      value: 85.8
+    - type: recall_at_100
+      value: 96.0
+    - type: recall_at_1000
+      value: 99.1
+    - type: recall_at_3
+      value: 77.9
+    - type: recall_at_5
+      value: 82.5
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/waimai-classification
+      name: MTEB Waimai
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 88.53
+    - type: ap
+      value: 73.56216166534062
+    - type: f1
+      value: 87.06093694294485
+---
+
+### 使用方法
+
+```
+from sentence_transformers import SentenceTransformer
+
+sentences = ["sentence1", "sentence2"]
+model = SentenceTransformer('IYun-large-zh')
+embeddings_1 = model.encode(sentences, normalize_embeddings=True)
+embeddings_2 = model.encode(sentences, normalize_embeddings=True)
+similarity = embeddings_1 @ embeddings_2.T
+print(similarity)
+```
+