Update README.md

README.md

@@ -7,6 +7,1097 @@ tags:
 - transformers
 - semantic-search
 - chinese
+- mteb
+model-index:
+- name: sbert-chinese-general-v1
+  results:
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/AFQMC
+      name: MTEB AFQMC
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 22.293919432958074
+    - type: cos_sim_spearman
+      value: 22.56718923553609
+    - type: euclidean_pearson
+      value: 22.525656322797026
+    - type: euclidean_spearman
+      value: 22.56718923553609
+    - type: manhattan_pearson
+      value: 22.501773028824065
+    - type: manhattan_spearman
+      value: 22.536992587828397
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/ATEC
+      name: MTEB ATEC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 30.33575274463879
+    - type: cos_sim_spearman
+      value: 30.298708742167772
+    - type: euclidean_pearson
+      value: 32.33094743729218
+    - type: euclidean_spearman
+      value: 30.298710993858734
+    - type: manhattan_pearson
+      value: 32.31155376195945
+    - type: manhattan_spearman
+      value: 30.267669681690744
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (zh)
+      config: zh
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 37.507999999999996
+    - type: f1
+      value: 36.436808400753286
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/BQ
+      name: MTEB BQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 41.493256724214255
+    - type: cos_sim_spearman
+      value: 40.98395961967895
+    - type: euclidean_pearson
+      value: 41.12345737966565
+    - type: euclidean_spearman
+      value: 40.983959619555996
+    - type: manhattan_pearson
+      value: 41.02584539471014
+    - type: manhattan_spearman
+      value: 40.87549513383032
+  - task:
+      type: BitextMining
+    dataset:
+      type: mteb/bucc-bitext-mining
+      name: MTEB BUCC (zh-en)
+      config: zh-en
+      split: test
+      revision: d51519689f32196a32af33b075a01d0e7c51e252
+    metrics:
+    - type: accuracy
+      value: 9.794628751974724
+    - type: f1
+      value: 9.350535369492716
+    - type: precision
+      value: 9.179392662804986
+    - type: recall
+      value: 9.794628751974724
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/CLSClusteringP2P
+      name: MTEB CLSClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 34.984726547788284
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/CLSClusteringS2S
+      name: MTEB CLSClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 27.81945732281589
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/CMedQAv1-reranking
+      name: MTEB CMedQAv1
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 53.06586280826805
+    - type: mrr
+      value: 59.58781746031746
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/CMedQAv2-reranking
+      name: MTEB CMedQAv2
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 52.83635946154306
+    - type: mrr
+      value: 59.315079365079356
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/CmedqaRetrieval
+      name: MTEB CmedqaRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.721
+    - type: map_at_10
+      value: 8.645
+    - type: map_at_100
+      value: 9.434
+    - type: map_at_1000
+      value: 9.586
+    - type: map_at_3
+      value: 7.413
+    - type: map_at_5
+      value: 8.05
+    - type: mrr_at_1
+      value: 9.626999999999999
+    - type: mrr_at_10
+      value: 13.094
+    - type: mrr_at_100
+      value: 13.854
+    - type: mrr_at_1000
+      value: 13.958
+    - type: mrr_at_3
+      value: 11.724
+    - type: mrr_at_5
+      value: 12.409
+    - type: ndcg_at_1
+      value: 9.626999999999999
+    - type: ndcg_at_10
+      value: 11.35
+    - type: ndcg_at_100
+      value: 15.593000000000002
+    - type: ndcg_at_1000
+      value: 19.619
+    - type: ndcg_at_3
+      value: 9.317
+    - type: ndcg_at_5
+      value: 10.049
+    - type: precision_at_1
+      value: 9.626999999999999
+    - type: precision_at_10
+      value: 2.796
+    - type: precision_at_100
+      value: 0.629
+    - type: precision_at_1000
+      value: 0.11800000000000001
+    - type: precision_at_3
+      value: 5.476
+    - type: precision_at_5
+      value: 4.1209999999999996
+    - type: recall_at_1
+      value: 5.721
+    - type: recall_at_10
+      value: 15.190000000000001
+    - type: recall_at_100
+      value: 33.633
+    - type: recall_at_1000
+      value: 62.019999999999996
+    - type: recall_at_3
+      value: 9.099
+    - type: recall_at_5
+      value: 11.423
+  - task:
+      type: PairClassification
+    dataset:
+      type: C-MTEB/CMNLI
+      name: MTEB Cmnli
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 77.36620565243535
+    - type: cos_sim_ap
+      value: 85.92291866877001
+    - type: cos_sim_f1
+      value: 78.19390231037029
+    - type: cos_sim_precision
+      value: 71.24183006535948
+    - type: cos_sim_recall
+      value: 86.64952069207388
+    - type: dot_accuracy
+      value: 77.36620565243535
+    - type: dot_ap
+      value: 85.94113738490068
+    - type: dot_f1
+      value: 78.19390231037029
+    - type: dot_precision
+      value: 71.24183006535948
+    - type: dot_recall
+      value: 86.64952069207388
+    - type: euclidean_accuracy
+      value: 77.36620565243535
+    - type: euclidean_ap
+      value: 85.92291893444687
+    - type: euclidean_f1
+      value: 78.19390231037029
+    - type: euclidean_precision
+      value: 71.24183006535948
+    - type: euclidean_recall
+      value: 86.64952069207388
+    - type: manhattan_accuracy
+      value: 77.29404690318701
+    - type: manhattan_ap
+      value: 85.88284362100919
+    - type: manhattan_f1
+      value: 78.17836812144213
+    - type: manhattan_precision
+      value: 71.18448838548666
+    - type: manhattan_recall
+      value: 86.69628244096329
+    - type: max_accuracy
+      value: 77.36620565243535
+    - type: max_ap
+      value: 85.94113738490068
+    - type: max_f1
+      value: 78.19390231037029
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/CovidRetrieval
+      name: MTEB CovidRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.976
+    - type: map_at_10
+      value: 35.18
+    - type: map_at_100
+      value: 35.921
+    - type: map_at_1000
+      value: 35.998999999999995
+    - type: map_at_3
+      value: 32.763
+    - type: map_at_5
+      value: 34.165
+    - type: mrr_at_1
+      value: 26.976
+    - type: mrr_at_10
+      value: 35.234
+    - type: mrr_at_100
+      value: 35.939
+    - type: mrr_at_1000
+      value: 36.016
+    - type: mrr_at_3
+      value: 32.771
+    - type: mrr_at_5
+      value: 34.172999999999995
+    - type: ndcg_at_1
+      value: 26.976
+    - type: ndcg_at_10
+      value: 39.635
+    - type: ndcg_at_100
+      value: 43.54
+    - type: ndcg_at_1000
+      value: 45.723
+    - type: ndcg_at_3
+      value: 34.652
+    - type: ndcg_at_5
+      value: 37.186
+    - type: precision_at_1
+      value: 26.976
+    - type: precision_at_10
+      value: 5.406
+    - type: precision_at_100
+      value: 0.736
+    - type: precision_at_1000
+      value: 0.091
+    - type: precision_at_3
+      value: 13.418
+    - type: precision_at_5
+      value: 9.293999999999999
+    - type: recall_at_1
+      value: 26.976
+    - type: recall_at_10
+      value: 53.766999999999996
+    - type: recall_at_100
+      value: 72.761
+    - type: recall_at_1000
+      value: 90.148
+    - type: recall_at_3
+      value: 40.095
+    - type: recall_at_5
+      value: 46.233000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/DuRetrieval
+      name: MTEB DuRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 11.285
+    - type: map_at_10
+      value: 30.259000000000004
+    - type: map_at_100
+      value: 33.772000000000006
+    - type: map_at_1000
+      value: 34.037
+    - type: map_at_3
+      value: 21.038999999999998
+    - type: map_at_5
+      value: 25.939
+    - type: mrr_at_1
+      value: 45.1
+    - type: mrr_at_10
+      value: 55.803999999999995
+    - type: mrr_at_100
+      value: 56.301
+    - type: mrr_at_1000
+      value: 56.330999999999996
+    - type: mrr_at_3
+      value: 53.333
+    - type: mrr_at_5
+      value: 54.798
+    - type: ndcg_at_1
+      value: 45.1
+    - type: ndcg_at_10
+      value: 41.156
+    - type: ndcg_at_100
+      value: 49.518
+    - type: ndcg_at_1000
+      value: 52.947
+    - type: ndcg_at_3
+      value: 39.708
+    - type: ndcg_at_5
+      value: 38.704
+    - type: precision_at_1
+      value: 45.1
+    - type: precision_at_10
+      value: 20.75
+    - type: precision_at_100
+      value: 3.424
+    - type: precision_at_1000
+      value: 0.42700000000000005
+    - type: precision_at_3
+      value: 35.632999999999996
+    - type: precision_at_5
+      value: 30.080000000000002
+    - type: recall_at_1
+      value: 11.285
+    - type: recall_at_10
+      value: 43.242000000000004
+    - type: recall_at_100
+      value: 68.604
+    - type: recall_at_1000
+      value: 85.904
+    - type: recall_at_3
+      value: 24.404
+    - type: recall_at_5
+      value: 32.757
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/EcomRetrieval
+      name: MTEB EcomRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.0
+    - type: map_at_10
+      value: 28.364
+    - type: map_at_100
+      value: 29.199
+    - type: map_at_1000
+      value: 29.265
+    - type: map_at_3
+      value: 25.717000000000002
+    - type: map_at_5
+      value: 27.311999999999998
+    - type: mrr_at_1
+      value: 21.0
+    - type: mrr_at_10
+      value: 28.364
+    - type: mrr_at_100
+      value: 29.199
+    - type: mrr_at_1000
+      value: 29.265
+    - type: mrr_at_3
+      value: 25.717000000000002
+    - type: mrr_at_5
+      value: 27.311999999999998
+    - type: ndcg_at_1
+      value: 21.0
+    - type: ndcg_at_10
+      value: 32.708
+    - type: ndcg_at_100
+      value: 37.184
+    - type: ndcg_at_1000
+      value: 39.273
+    - type: ndcg_at_3
+      value: 27.372000000000003
+    - type: ndcg_at_5
+      value: 30.23
+    - type: precision_at_1
+      value: 21.0
+    - type: precision_at_10
+      value: 4.66
+    - type: precision_at_100
+      value: 0.685
+    - type: precision_at_1000
+      value: 0.086
+    - type: precision_at_3
+      value: 10.732999999999999
+    - type: precision_at_5
+      value: 7.82
+    - type: recall_at_1
+      value: 21.0
+    - type: recall_at_10
+      value: 46.6
+    - type: recall_at_100
+      value: 68.5
+    - type: recall_at_1000
+      value: 85.6
+    - type: recall_at_3
+      value: 32.2
+    - type: recall_at_5
+      value: 39.1
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/IFlyTek-classification
+      name: MTEB IFlyTek
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 44.878799538283964
+    - type: f1
+      value: 33.84678310261366
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/JDReview-classification
+      name: MTEB JDReview
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 82.1951219512195
+    - type: ap
+      value: 46.78292030042397
+    - type: f1
+      value: 76.20482468514128
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/LCQMC
+      name: MTEB LCQMC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 62.84331627244547
+    - type: cos_sim_spearman
+      value: 68.39990265073726
+    - type: euclidean_pearson
+      value: 66.87431827169324
+    - type: euclidean_spearman
+      value: 68.39990264979167
+    - type: manhattan_pearson
+      value: 66.89702078900328
+    - type: manhattan_spearman
+      value: 68.42107302159141
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/Mmarco-reranking
+      name: MTEB MMarcoReranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 9.28600891904827
+    - type: mrr
+      value: 8.057936507936509
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/MMarcoRetrieval
+      name: MTEB MMarcoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.820999999999998
+    - type: map_at_10
+      value: 30.44
+    - type: map_at_100
+      value: 31.35
+    - type: map_at_1000
+      value: 31.419000000000004
+    - type: map_at_3
+      value: 28.134999999999998
+    - type: map_at_5
+      value: 29.482000000000003
+    - type: mrr_at_1
+      value: 23.782
+    - type: mrr_at_10
+      value: 31.141999999999996
+    - type: mrr_at_100
+      value: 32.004
+    - type: mrr_at_1000
+      value: 32.068000000000005
+    - type: mrr_at_3
+      value: 28.904000000000003
+    - type: mrr_at_5
+      value: 30.214999999999996
+    - type: ndcg_at_1
+      value: 23.782
+    - type: ndcg_at_10
+      value: 34.625
+    - type: ndcg_at_100
+      value: 39.226
+    - type: ndcg_at_1000
+      value: 41.128
+    - type: ndcg_at_3
+      value: 29.968
+    - type: ndcg_at_5
+      value: 32.35
+    - type: precision_at_1
+      value: 23.782
+    - type: precision_at_10
+      value: 4.994
+    - type: precision_at_100
+      value: 0.736
+    - type: precision_at_1000
+      value: 0.09
+    - type: precision_at_3
+      value: 12.13
+    - type: precision_at_5
+      value: 8.495999999999999
+    - type: recall_at_1
+      value: 22.820999999999998
+    - type: recall_at_10
+      value: 47.141
+    - type: recall_at_100
+      value: 68.952
+    - type: recall_at_1000
+      value: 83.985
+    - type: recall_at_3
+      value: 34.508
+    - type: recall_at_5
+      value: 40.232
+  - 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: 57.343644922663074
+    - type: f1
+      value: 56.744802953803486
+  - 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: 62.363819771351714
+    - type: f1
+      value: 62.15920863434656
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/MedicalRetrieval
+      name: MTEB MedicalRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 14.6
+    - type: map_at_10
+      value: 18.231
+    - type: map_at_100
+      value: 18.744
+    - type: map_at_1000
+      value: 18.811
+    - type: map_at_3
+      value: 17.133000000000003
+    - type: map_at_5
+      value: 17.663
+    - type: mrr_at_1
+      value: 14.6
+    - type: mrr_at_10
+      value: 18.231
+    - type: mrr_at_100
+      value: 18.744
+    - type: mrr_at_1000
+      value: 18.811
+    - type: mrr_at_3
+      value: 17.133000000000003
+    - type: mrr_at_5
+      value: 17.663
+    - type: ndcg_at_1
+      value: 14.6
+    - type: ndcg_at_10
+      value: 20.349
+    - type: ndcg_at_100
+      value: 23.204
+    - type: ndcg_at_1000
+      value: 25.44
+    - type: ndcg_at_3
+      value: 17.995
+    - type: ndcg_at_5
+      value: 18.945999999999998
+    - type: precision_at_1
+      value: 14.6
+    - type: precision_at_10
+      value: 2.7199999999999998
+    - type: precision_at_100
+      value: 0.414
+    - type: precision_at_1000
+      value: 0.06
+    - type: precision_at_3
+      value: 6.833
+    - type: precision_at_5
+      value: 4.5600000000000005
+    - type: recall_at_1
+      value: 14.6
+    - type: recall_at_10
+      value: 27.200000000000003
+    - type: recall_at_100
+      value: 41.4
+    - type: recall_at_1000
+      value: 60.0
+    - type: recall_at_3
+      value: 20.5
+    - type: recall_at_5
+      value: 22.8
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/MultilingualSentiment-classification
+      name: MTEB MultilingualSentiment
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 66.58333333333333
+    - type: f1
+      value: 66.26700927460007
+  - task:
+      type: PairClassification
+    dataset:
+      type: C-MTEB/OCNLI
+      name: MTEB Ocnli
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 72.00866269626421
+    - type: cos_sim_ap
+      value: 77.00520104243304
+    - type: cos_sim_f1
+      value: 74.39303710490151
+    - type: cos_sim_precision
+      value: 65.69579288025889
+    - type: cos_sim_recall
+      value: 85.74445617740233
+    - type: dot_accuracy
+      value: 72.00866269626421
+    - type: dot_ap
+      value: 77.00520104243304
+    - type: dot_f1
+      value: 74.39303710490151
+    - type: dot_precision
+      value: 65.69579288025889
+    - type: dot_recall
+      value: 85.74445617740233
+    - type: euclidean_accuracy
+      value: 72.00866269626421
+    - type: euclidean_ap
+      value: 77.00520104243304
+    - type: euclidean_f1
+      value: 74.39303710490151
+    - type: euclidean_precision
+      value: 65.69579288025889
+    - type: euclidean_recall
+      value: 85.74445617740233
+    - type: manhattan_accuracy
+      value: 72.1710882512182
+    - type: manhattan_ap
+      value: 77.00551017913976
+    - type: manhattan_f1
+      value: 74.23423423423424
+    - type: manhattan_precision
+      value: 64.72898664571878
+    - type: manhattan_recall
+      value: 87.0116156282999
+    - type: max_accuracy
+      value: 72.1710882512182
+    - type: max_ap
+      value: 77.00551017913976
+    - type: max_f1
+      value: 74.39303710490151
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/OnlineShopping-classification
+      name: MTEB OnlineShopping
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 88.19000000000001
+    - type: ap
+      value: 85.13415594781077
+    - type: f1
+      value: 88.17344156114062
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/PAWSX
+      name: MTEB PAWSX
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 13.70522140998517
+    - type: cos_sim_spearman
+      value: 15.07546667334743
+    - type: euclidean_pearson
+      value: 17.49511420225285
+    - type: euclidean_spearman
+      value: 15.093970931789618
+    - type: manhattan_pearson
+      value: 17.44069961390521
+    - type: manhattan_spearman
+      value: 15.076029291596962
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/QBQTC
+      name: MTEB QBQTC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 26.835294224547155
+    - type: cos_sim_spearman
+      value: 27.920204597498856
+    - type: euclidean_pearson
+      value: 26.153796707702803
+    - type: euclidean_spearman
+      value: 27.920971379720548
+    - type: manhattan_pearson
+      value: 26.21954147857523
+    - type: manhattan_spearman
+      value: 27.996860049937478
+  - 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: 55.15901259718581
+    - type: cos_sim_spearman
+      value: 61.57967880874167
+    - type: euclidean_pearson
+      value: 53.83523291596683
+    - type: euclidean_spearman
+      value: 61.57967880874167
+    - type: manhattan_pearson
+      value: 54.99971428907956
+    - type: manhattan_spearman
+      value: 61.61229543613867
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (zh-en)
+      config: zh-en
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 34.20930208460845
+    - type: cos_sim_spearman
+      value: 33.879011104224524
+    - type: euclidean_pearson
+      value: 35.08526425284862
+    - type: euclidean_spearman
+      value: 33.879011104224524
+    - type: manhattan_pearson
+      value: 35.509419089701275
+    - type: manhattan_spearman
+      value: 33.30035487147621
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/STSB
+      name: MTEB STSB
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.30068282185835
+    - type: cos_sim_spearman
+      value: 82.16763221361724
+    - type: euclidean_pearson
+      value: 80.52772752433374
+    - type: euclidean_spearman
+      value: 82.16797037220333
+    - type: manhattan_pearson
+      value: 80.51093859500105
+    - type: manhattan_spearman
+      value: 82.17643310049654
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/T2Reranking
+      name: MTEB T2Reranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 65.14113035189213
+    - type: mrr
+      value: 74.9589270937443
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/T2Retrieval
+      name: MTEB T2Retrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 12.013
+    - type: map_at_10
+      value: 30.885
+    - type: map_at_100
+      value: 34.643
+    - type: map_at_1000
+      value: 34.927
+    - type: map_at_3
+      value: 21.901
+    - type: map_at_5
+      value: 26.467000000000002
+    - type: mrr_at_1
+      value: 49.623
+    - type: mrr_at_10
+      value: 58.05200000000001
+    - type: mrr_at_100
+      value: 58.61300000000001
+    - type: mrr_at_1000
+      value: 58.643
+    - type: mrr_at_3
+      value: 55.947
+    - type: mrr_at_5
+      value: 57.229
+    - type: ndcg_at_1
+      value: 49.623
+    - type: ndcg_at_10
+      value: 41.802
+    - type: ndcg_at_100
+      value: 49.975
+    - type: ndcg_at_1000
+      value: 53.504
+    - type: ndcg_at_3
+      value: 43.515
+    - type: ndcg_at_5
+      value: 41.576
+    - type: precision_at_1
+      value: 49.623
+    - type: precision_at_10
+      value: 22.052
+    - type: precision_at_100
+      value: 3.6450000000000005
+    - type: precision_at_1000
+      value: 0.45399999999999996
+    - type: precision_at_3
+      value: 38.616
+    - type: precision_at_5
+      value: 31.966
+    - type: recall_at_1
+      value: 12.013
+    - type: recall_at_10
+      value: 41.891
+    - type: recall_at_100
+      value: 67.096
+    - type: recall_at_1000
+      value: 84.756
+    - type: recall_at_3
+      value: 24.695
+    - type: recall_at_5
+      value: 32.09
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/TNews-classification
+      name: MTEB TNews
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 39.800999999999995
+    - type: f1
+      value: 38.5345899934575
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/ThuNewsClusteringP2P
+      name: MTEB ThuNewsClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 40.16574242797479
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/ThuNewsClusteringS2S
+      name: MTEB ThuNewsClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 24.232617974671754
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/VideoRetrieval
+      name: MTEB VideoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.6
+    - type: map_at_10
+      value: 31.328
+    - type: map_at_100
+      value: 32.088
+    - type: map_at_1000
+      value: 32.164
+    - type: map_at_3
+      value: 29.133
+    - type: map_at_5
+      value: 30.358
+    - type: mrr_at_1
+      value: 24.6
+    - type: mrr_at_10
+      value: 31.328
+    - type: mrr_at_100
+      value: 32.088
+    - type: mrr_at_1000
+      value: 32.164
+    - type: mrr_at_3
+      value: 29.133
+    - type: mrr_at_5
+      value: 30.358
+    - type: ndcg_at_1
+      value: 24.6
+    - type: ndcg_at_10
+      value: 35.150999999999996
+    - type: ndcg_at_100
+      value: 39.024
+    - type: ndcg_at_1000
+      value: 41.157
+    - type: ndcg_at_3
+      value: 30.637999999999998
+    - type: ndcg_at_5
+      value: 32.833
+    - type: precision_at_1
+      value: 24.6
+    - type: precision_at_10
+      value: 4.74
+    - type: precision_at_100
+      value: 0.66
+    - type: precision_at_1000
+      value: 0.083
+    - type: precision_at_3
+      value: 11.667
+    - type: precision_at_5
+      value: 8.06
+    - type: recall_at_1
+      value: 24.6
+    - type: recall_at_10
+      value: 47.4
+    - type: recall_at_100
+      value: 66.0
+    - type: recall_at_1000
+      value: 83.0
+    - type: recall_at_3
+      value: 35.0
+    - type: recall_at_5
+      value: 40.300000000000004
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/waimai-classification
+      name: MTEB Waimai
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 83.96000000000001
+    - type: ap
+      value: 65.11027167433211
+    - type: f1
+      value: 82.03549710974653
 ---
 
 # DMetaSoul/sbert-chinese-general-v1