Update README.md

README.md

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 ---
 pipeline_tag: sentence-similarity
 tags:
-  - sentence-transformers
-  - feature-extraction
-  - sentence-similarity
-  - mteb
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+- mteb
 model-index:
-  - name: stella-mrl-large-zh-v3.5-1792d
-    results:
-      - task:
-          type: STS
-        dataset:
-          type: C-MTEB/AFQMC
-          name: MTEB AFQMC
-          config: default
-          split: validation
-          revision: None
-        metrics:
-          - type: cos_sim_pearson
-            value: 54.33822814973567
-          - type: cos_sim_spearman
-            value: 58.85457316132848
-          - type: euclidean_pearson
-            value: 57.57048145477383
-          - type: euclidean_spearman
-            value: 58.854593263425095
-          - type: manhattan_pearson
-            value: 57.55884028558309
-          - type: manhattan_spearman
-            value: 58.84474216217465
-      - task:
-          type: STS
-        dataset:
-          type: C-MTEB/ATEC
-          name: MTEB ATEC
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: cos_sim_pearson
-            value: 54.219652875381875
-          - type: cos_sim_spearman
-            value: 58.079506691583546
-          - type: euclidean_pearson
-            value: 61.646366330471736
-          - type: euclidean_spearman
-            value: 58.07951006894859
-          - type: manhattan_pearson
-            value: 61.64460832085762
-          - type: manhattan_spearman
-            value: 58.08054699349972
-      - task:
-          type: Classification
-        dataset:
-          type: mteb/amazon_reviews_multi
-          name: MTEB AmazonReviewsClassification (zh)
-          config: zh
-          split: test
-          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-        metrics:
-          - type: accuracy
-            value: 46.593999999999994
-          - type: f1
-            value: 44.73150848183217
-      - task:
-          type: STS
-        dataset:
-          type: C-MTEB/BQ
-          name: MTEB BQ
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: cos_sim_pearson
-            value: 69.16841007040091
-          - type: cos_sim_spearman
-            value: 71.04760904227217
-          - type: euclidean_pearson
-            value: 69.95126084376611
-          - type: euclidean_spearman
-            value: 71.04760904184589
-          - type: manhattan_pearson
-            value: 69.92512024129407
-          - type: manhattan_spearman
-            value: 71.02613161257672
-      - task:
-          type: Clustering
-        dataset:
-          type: C-MTEB/CLSClusteringP2P
-          name: MTEB CLSClusteringP2P
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: v_measure
-            value: 43.032332399653306
-      - task:
-          type: Clustering
-        dataset:
-          type: C-MTEB/CLSClusteringS2S
-          name: MTEB CLSClusteringS2S
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: v_measure
-            value: 40.41603958793544
-      - task:
-          type: Reranking
-        dataset:
-          type: C-MTEB/CMedQAv1-reranking
-          name: MTEB CMedQAv1
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: map
-            value: 89.33487924447584
-          - type: mrr
-            value: 91.34623015873017
-      - task:
-          type: Reranking
-        dataset:
-          type: C-MTEB/CMedQAv2-reranking
-          name: MTEB CMedQAv2
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: map
-            value: 89.17795270698021
-          - type: mrr
-            value: 91.0956746031746
-      - task:
-          type: Retrieval
-        dataset:
-          type: C-MTEB/CmedqaRetrieval
-          name: MTEB CmedqaRetrieval
-          config: default
-          split: dev
-          revision: None
-        metrics:
-          - type: map_at_1
-            value: 26.809
-          - type: map_at_10
-            value: 39.906000000000006
-          - type: map_at_100
-            value: 41.858000000000004
-          - type: map_at_1000
-            value: 41.954
-          - type: map_at_3
-            value: 35.435
-          - type: map_at_5
-            value: 37.978
-          - type: mrr_at_1
-            value: 40.660000000000004
-          - type: mrr_at_10
-            value: 48.787000000000006
-          - type: mrr_at_100
-            value: 49.796
-          - type: mrr_at_1000
-            value: 49.832
-          - type: mrr_at_3
-            value: 46.166000000000004
-          - type: mrr_at_5
-            value: 47.675
-          - type: ndcg_at_1
-            value: 40.660000000000004
-          - type: ndcg_at_10
-            value: 46.614
-          - type: ndcg_at_100
-            value: 54.037
-          - type: ndcg_at_1000
-            value: 55.654
-          - type: ndcg_at_3
-            value: 41.032000000000004
-          - type: ndcg_at_5
-            value: 43.464999999999996
-          - type: precision_at_1
-            value: 40.660000000000004
-          - type: precision_at_10
-            value: 10.35
-          - type: precision_at_100
-            value: 1.6340000000000001
-          - type: precision_at_1000
-            value: 0.184
-          - type: precision_at_3
-            value: 23.122
-          - type: precision_at_5
-            value: 16.944
-          - type: recall_at_1
-            value: 26.809
-          - type: recall_at_10
-            value: 57.474000000000004
-          - type: recall_at_100
-            value: 87.976
-          - type: recall_at_1000
-            value: 98.74199999999999
-          - type: recall_at_3
-            value: 40.819
-          - type: recall_at_5
-            value: 48.175000000000004
-      - task:
-          type: PairClassification
-        dataset:
-          type: C-MTEB/CMNLI
-          name: MTEB Cmnli
-          config: default
-          split: validation
-          revision: None
-        metrics:
-          - type: cos_sim_accuracy
-            value: 83.4996993385448
-          - type: cos_sim_ap
-            value: 90.66238348446467
-          - type: cos_sim_f1
-            value: 84.39077936333699
-          - type: cos_sim_precision
-            value: 79.53651975998345
-          - type: cos_sim_recall
-            value: 89.87608136544307
-          - type: dot_accuracy
-            value: 83.4996993385448
-          - type: dot_ap
-            value: 90.64660919236363
-          - type: dot_f1
-            value: 84.39077936333699
-          - type: dot_precision
-            value: 79.53651975998345
-          - type: dot_recall
-            value: 89.87608136544307
-          - type: euclidean_accuracy
-            value: 83.4996993385448
-          - type: euclidean_ap
-            value: 90.66238269557765
-          - type: euclidean_f1
-            value: 84.39077936333699
-          - type: euclidean_precision
-            value: 79.53651975998345
-          - type: euclidean_recall
-            value: 89.87608136544307
-          - type: manhattan_accuracy
-            value: 83.35538184004811
-          - type: manhattan_ap
-            value: 90.6446013420276
-          - type: manhattan_f1
-            value: 84.37465196569775
-          - type: manhattan_precision
-            value: 80.5614632071459
-          - type: manhattan_recall
-            value: 88.56675239653963
-          - type: max_accuracy
-            value: 83.4996993385448
-          - type: max_ap
-            value: 90.66238348446467
-          - type: max_f1
-            value: 84.39077936333699
-      - task:
-          type: Retrieval
-        dataset:
-          type: C-MTEB/CovidRetrieval
-          name: MTEB CovidRetrieval
-          config: default
-          split: dev
-          revision: None
-        metrics:
-          - type: map_at_1
-            value: 68.967
-          - type: map_at_10
-            value: 77.95299999999999
-          - type: map_at_100
-            value: 78.213
-          - type: map_at_1000
-            value: 78.21900000000001
-          - type: map_at_3
-            value: 76.30799999999999
-          - type: map_at_5
-            value: 77.316
-          - type: mrr_at_1
-            value: 69.125
-          - type: mrr_at_10
-            value: 77.886
-          - type: mrr_at_100
-            value: 78.141
-          - type: mrr_at_1000
-            value: 78.147
-          - type: mrr_at_3
-            value: 76.291
-          - type: mrr_at_5
-            value: 77.29700000000001
-          - type: ndcg_at_1
-            value: 69.231
-          - type: ndcg_at_10
-            value: 81.867
-          - type: ndcg_at_100
-            value: 82.982
-          - type: ndcg_at_1000
-            value: 83.12
-          - type: ndcg_at_3
-            value: 78.592
-          - type: ndcg_at_5
-            value: 80.39
-          - type: precision_at_1
-            value: 69.231
-          - type: precision_at_10
-            value: 9.494
-          - type: precision_at_100
-            value: 0.9990000000000001
-          - type: precision_at_1000
-            value: 0.101
-          - type: precision_at_3
-            value: 28.591
-          - type: precision_at_5
-            value: 18.061
-          - type: recall_at_1
-            value: 68.967
-          - type: recall_at_10
-            value: 93.941
-          - type: recall_at_100
-            value: 98.84100000000001
-          - type: recall_at_1000
-            value: 99.895
-          - type: recall_at_3
-            value: 85.142
-          - type: recall_at_5
-            value: 89.46300000000001
-      - task:
-          type: Retrieval
-        dataset:
-          type: C-MTEB/DuRetrieval
-          name: MTEB DuRetrieval
-          config: default
-          split: dev
-          revision: None
-        metrics:
-          - type: map_at_1
-            value: 25.824
-          - type: map_at_10
-            value: 79.396
-          - type: map_at_100
-            value: 82.253
-          - type: map_at_1000
-            value: 82.295
-          - type: map_at_3
-            value: 54.83
-          - type: map_at_5
-            value: 69.536
-          - type: mrr_at_1
-            value: 89.7
-          - type: mrr_at_10
-            value: 92.929
-          - type: mrr_at_100
-            value: 93.013
-          - type: mrr_at_1000
-            value: 93.015
-          - type: mrr_at_3
-            value: 92.658
-          - type: mrr_at_5
-            value: 92.841
-          - type: ndcg_at_1
-            value: 89.7
-          - type: ndcg_at_10
-            value: 86.797
-          - type: ndcg_at_100
-            value: 89.652
-          - type: ndcg_at_1000
-            value: 90.047
-          - type: ndcg_at_3
-            value: 85.651
-          - type: ndcg_at_5
-            value: 84.747
-          - type: precision_at_1
-            value: 89.7
-          - type: precision_at_10
-            value: 41.61
-          - type: precision_at_100
-            value: 4.788
-          - type: precision_at_1000
-            value: 0.488
-          - type: precision_at_3
-            value: 76.833
-          - type: precision_at_5
-            value: 65.14
-          - type: recall_at_1
-            value: 25.824
-          - type: recall_at_10
-            value: 87.896
-          - type: recall_at_100
-            value: 97.221
-          - type: recall_at_1000
-            value: 99.29599999999999
-          - type: recall_at_3
-            value: 57.178
-          - type: recall_at_5
-            value: 74.348
-      - task:
-          type: Retrieval
-        dataset:
-          type: C-MTEB/EcomRetrieval
-          name: MTEB EcomRetrieval
-          config: default
-          split: dev
-          revision: None
-        metrics:
-          - type: map_at_1
-            value: 52.5
-          - type: map_at_10
-            value: 63.04
-          - type: map_at_100
-            value: 63.548
-          - type: map_at_1000
-            value: 63.56
-          - type: map_at_3
-            value: 60.483
-          - type: map_at_5
-            value: 62.22800000000001
-          - type: mrr_at_1
-            value: 52.5
-          - type: mrr_at_10
-            value: 63.04
-          - type: mrr_at_100
-            value: 63.548
-          - type: mrr_at_1000
-            value: 63.56
-          - type: mrr_at_3
-            value: 60.483
-          - type: mrr_at_5
-            value: 62.22800000000001
-          - type: ndcg_at_1
-            value: 52.5
-          - type: ndcg_at_10
-            value: 68.099
-          - type: ndcg_at_100
-            value: 70.48400000000001
-          - type: ndcg_at_1000
-            value: 70.769
-          - type: ndcg_at_3
-            value: 63.01
-          - type: ndcg_at_5
-            value: 66.148
-          - type: precision_at_1
-            value: 52.5
-          - type: precision_at_10
-            value: 8.39
-          - type: precision_at_100
-            value: 0.9490000000000001
-          - type: precision_at_1000
-            value: 0.097
-          - type: precision_at_3
-            value: 23.433
-          - type: precision_at_5
-            value: 15.58
-          - type: recall_at_1
-            value: 52.5
-          - type: recall_at_10
-            value: 83.89999999999999
-          - type: recall_at_100
-            value: 94.89999999999999
-          - type: recall_at_1000
-            value: 97.1
-          - type: recall_at_3
-            value: 70.3
-          - type: recall_at_5
-            value: 77.9
-      - task:
-          type: Classification
-        dataset:
-          type: C-MTEB/IFlyTek-classification
-          name: MTEB IFlyTek
-          config: default
-          split: validation
-          revision: None
-        metrics:
-          - type: accuracy
-            value: 50.742593305117346
-          - type: f1
-            value: 38.7451988564002
-      - task:
-          type: Classification
-        dataset:
-          type: C-MTEB/JDReview-classification
-          name: MTEB JDReview
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: accuracy
-            value: 86.09756097560977
-          - type: ap
-            value: 54.39255221143281
-          - type: f1
-            value: 80.8326851537251
-      - task:
-          type: STS
-        dataset:
-          type: C-MTEB/LCQMC
-          name: MTEB LCQMC
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: cos_sim_pearson
-            value: 72.32408066246728
-          - type: cos_sim_spearman
-            value: 78.25773378380241
-          - type: euclidean_pearson
-            value: 77.87824677060661
-          - type: euclidean_spearman
-            value: 78.25773599854358
-          - type: manhattan_pearson
-            value: 77.86648277798515
-          - type: manhattan_spearman
-            value: 78.24642917155661
-      - task:
-          type: Reranking
-        dataset:
-          type: C-MTEB/Mmarco-reranking
-          name: MTEB MMarcoReranking
-          config: default
-          split: dev
-          revision: None
-        metrics:
-          - type: map
-            value: 28.846601097874608
-          - type: mrr
-            value: 27.902777777777775
-      - task:
-          type: Retrieval
-        dataset:
-          type: C-MTEB/MMarcoRetrieval
-          name: MTEB MMarcoRetrieval
-          config: default
-          split: dev
-          revision: None
-        metrics:
-          - type: map_at_1
-            value: 66.533
-          - type: map_at_10
-            value: 75.58399999999999
-          - type: map_at_100
-            value: 75.91
-          - type: map_at_1000
-            value: 75.921
-          - type: map_at_3
-            value: 73.847
-          - type: map_at_5
-            value: 74.929
-          - type: mrr_at_1
-            value: 68.854
-          - type: mrr_at_10
-            value: 76.20700000000001
-          - type: mrr_at_100
-            value: 76.498
-          - type: mrr_at_1000
-            value: 76.508
-          - type: mrr_at_3
-            value: 74.71600000000001
-          - type: mrr_at_5
-            value: 75.653
-          - type: ndcg_at_1
-            value: 68.854
-          - type: ndcg_at_10
-            value: 79.209
-          - type: ndcg_at_100
-            value: 80.67
-          - type: ndcg_at_1000
-            value: 80.95
-          - type: ndcg_at_3
-            value: 75.923
-          - type: ndcg_at_5
-            value: 77.74799999999999
-          - type: precision_at_1
-            value: 68.854
-          - type: precision_at_10
-            value: 9.547
-          - type: precision_at_100
-            value: 1.027
-          - type: precision_at_1000
-            value: 0.105
-          - type: precision_at_3
-            value: 28.582
-          - type: precision_at_5
-            value: 18.112000000000002
-          - type: recall_at_1
-            value: 66.533
-          - type: recall_at_10
-            value: 89.736
-          - type: recall_at_100
-            value: 96.34
-          - type: recall_at_1000
-            value: 98.52
-          - type: recall_at_3
-            value: 81.047
-          - type: recall_at_5
-            value: 85.38900000000001
-      - 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: 73.27841291190316
-          - type: f1
-            value: 70.82287701665152
-      - 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: 76.20040349697376
-          - type: f1
-            value: 75.92782428878164
-      - task:
-          type: Retrieval
-        dataset:
-          type: C-MTEB/MedicalRetrieval
-          name: MTEB MedicalRetrieval
-          config: default
-          split: dev
-          revision: None
-        metrics:
-          - type: map_at_1
-            value: 56.39999999999999
-          - type: map_at_10
-            value: 62.122
-          - type: map_at_100
-            value: 62.692
-          - type: map_at_1000
-            value: 62.739
-          - type: map_at_3
-            value: 60.617
-          - type: map_at_5
-            value: 61.582
-          - type: mrr_at_1
-            value: 56.39999999999999
-          - type: mrr_at_10
-            value: 62.125
-          - type: mrr_at_100
-            value: 62.696
-          - type: mrr_at_1000
-            value: 62.742
-          - type: mrr_at_3
-            value: 60.617
-          - type: mrr_at_5
-            value: 61.602000000000004
-          - type: ndcg_at_1
-            value: 56.39999999999999
-          - type: ndcg_at_10
-            value: 64.986
-          - type: ndcg_at_100
-            value: 67.889
-          - type: ndcg_at_1000
-            value: 69.16499999999999
-          - type: ndcg_at_3
-            value: 61.951
-          - type: ndcg_at_5
-            value: 63.685
-          - type: precision_at_1
-            value: 56.39999999999999
-          - type: precision_at_10
-            value: 7.3999999999999995
-          - type: precision_at_100
-            value: 0.8789999999999999
-          - type: precision_at_1000
-            value: 0.098
-          - type: precision_at_3
-            value: 21.933
-          - type: precision_at_5
-            value: 14.000000000000002
-          - type: recall_at_1
-            value: 56.39999999999999
-          - type: recall_at_10
-            value: 74.0
-          - type: recall_at_100
-            value: 87.9
-          - type: recall_at_1000
-            value: 98.0
-          - type: recall_at_3
-            value: 65.8
-          - type: recall_at_5
-            value: 70.0
-      - task:
-          type: Classification
-        dataset:
-          type: C-MTEB/MultilingualSentiment-classification
-          name: MTEB MultilingualSentiment
-          config: default
-          split: validation
-          revision: None
-        metrics:
-          - type: accuracy
-            value: 76.64
-          - type: f1
-            value: 76.5446299028248
-      - task:
-          type: PairClassification
-        dataset:
-          type: C-MTEB/OCNLI
-          name: MTEB Ocnli
-          config: default
-          split: validation
-          revision: None
-        metrics:
-          - type: cos_sim_accuracy
-            value: 82.34975636166757
-          - type: cos_sim_ap
-            value: 85.51352392694149
-          - type: cos_sim_f1
-            value: 83.53057199211045
-          - type: cos_sim_precision
-            value: 78.35337650323775
-          - type: cos_sim_recall
-            value: 89.44033790918691
-          - type: dot_accuracy
-            value: 82.34975636166757
-          - type: dot_ap
-            value: 85.51347115601486
-          - type: dot_f1
-            value: 83.53057199211045
-          - type: dot_precision
-            value: 78.35337650323775
-          - type: dot_recall
-            value: 89.44033790918691
-          - type: euclidean_accuracy
-            value: 82.34975636166757
-          - type: euclidean_ap
-            value: 85.51352392694149
-          - type: euclidean_f1
-            value: 83.53057199211045
-          - type: euclidean_precision
-            value: 78.35337650323775
-          - type: euclidean_recall
-            value: 89.44033790918691
-          - type: manhattan_accuracy
-            value: 82.34975636166757
-          - type: manhattan_ap
-            value: 85.48313896880585
-          - type: manhattan_f1
-            value: 83.52414136386261
-          - type: manhattan_precision
-            value: 79.00188323917138
-          - type: manhattan_recall
-            value: 88.59556494192185
-          - type: max_accuracy
-            value: 82.34975636166757
-          - type: max_ap
-            value: 85.51352392694149
-          - type: max_f1
-            value: 83.53057199211045
-      - task:
-          type: Classification
-        dataset:
-          type: C-MTEB/OnlineShopping-classification
-          name: MTEB OnlineShopping
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: accuracy
-            value: 93.39
-          - type: ap
-            value: 91.62127505252761
-          - type: f1
-            value: 93.38126146765326
-      - task:
-          type: STS
-        dataset:
-          type: C-MTEB/PAWSX
-          name: MTEB PAWSX
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: cos_sim_pearson
-            value: 39.69424895486595
-          - type: cos_sim_spearman
-            value: 45.357868735202885
-          - type: euclidean_pearson
-            value: 44.85027304963503
-          - type: euclidean_spearman
-            value: 45.356945176162064
-          - type: manhattan_pearson
-            value: 44.866080721344744
-          - type: manhattan_spearman
-            value: 45.37053172312661
-      - task:
-          type: STS
-        dataset:
-          type: C-MTEB/QBQTC
-          name: MTEB QBQTC
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: cos_sim_pearson
-            value: 37.03908089465844
-          - type: cos_sim_spearman
-            value: 38.98314179826781
-          - type: euclidean_pearson
-            value: 37.189386019789545
-          - type: euclidean_spearman
-            value: 38.98311189555396
-          - type: manhattan_pearson
-            value: 37.14695118899785
-          - type: manhattan_spearman
-            value: 38.94957261261034
-      - 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: 65.08396305098712
-          - type: cos_sim_spearman
-            value: 66.26346934994216
-          - type: euclidean_pearson
-            value: 65.56501615370941
-          - type: euclidean_spearman
-            value: 66.26346934994216
-          - type: manhattan_pearson
-            value: 65.47984748172154
-          - type: manhattan_spearman
-            value: 66.25326746119808
-      - task:
-          type: STS
-        dataset:
-          type: C-MTEB/STSB
-          name: MTEB STSB
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: cos_sim_pearson
-            value: 80.95965207330296
-          - type: cos_sim_spearman
-            value: 82.96149593569953
-          - type: euclidean_pearson
-            value: 82.67125448003975
-          - type: euclidean_spearman
-            value: 82.96141174550262
-          - type: manhattan_pearson
-            value: 82.64660468206361
-          - type: manhattan_spearman
-            value: 82.91756025324656
-      - task:
-          type: Reranking
-        dataset:
-          type: C-MTEB/T2Reranking
-          name: MTEB T2Reranking
-          config: default
-          split: dev
-          revision: None
-        metrics:
-          - type: map
-            value: 66.43391960680063
-          - type: mrr
-            value: 76.078440855015
-      - task:
-          type: Retrieval
-        dataset:
-          type: C-MTEB/T2Retrieval
-          name: MTEB T2Retrieval
-          config: default
-          split: dev
-          revision: None
-        metrics:
-          - type: map_at_1
-            value: 28.29
-          - type: map_at_10
-            value: 78.441
-          - type: map_at_100
-            value: 82.043
-          - type: map_at_1000
-            value: 82.10499999999999
-          - type: map_at_3
-            value: 55.448
-          - type: map_at_5
-            value: 67.982
-          - type: mrr_at_1
-            value: 91.18
-          - type: mrr_at_10
-            value: 93.498
-          - type: mrr_at_100
-            value: 93.57
-          - type: mrr_at_1000
-            value: 93.572
-          - type: mrr_at_3
-            value: 93.112
-          - type: mrr_at_5
-            value: 93.351
-          - type: ndcg_at_1
-            value: 91.18
-          - type: ndcg_at_10
-            value: 85.849
-          - type: ndcg_at_100
-            value: 89.32600000000001
-          - type: ndcg_at_1000
-            value: 89.9
-          - type: ndcg_at_3
-            value: 87.333
-          - type: ndcg_at_5
-            value: 85.91499999999999
-          - type: precision_at_1
-            value: 91.18
-          - type: precision_at_10
-            value: 42.315000000000005
-          - type: precision_at_100
-            value: 5.029
-          - type: precision_at_1000
-            value: 0.517
-          - type: precision_at_3
-            value: 76.12400000000001
-          - type: precision_at_5
-            value: 63.690000000000005
-          - type: recall_at_1
-            value: 28.29
-          - type: recall_at_10
-            value: 84.679
-          - type: recall_at_100
-            value: 95.952
-          - type: recall_at_1000
-            value: 98.821
-          - type: recall_at_3
-            value: 56.987
-          - type: recall_at_5
-            value: 71.15599999999999
-      - task:
-          type: Classification
-        dataset:
-          type: C-MTEB/TNews-classification
-          name: MTEB TNews
-          config: default
-          split: validation
-          revision: None
-        metrics:
-          - type: accuracy
-            value: 53.09799999999999
-          - type: f1
-            value: 51.397192036892314
-      - task:
-          type: Clustering
-        dataset:
-          type: C-MTEB/ThuNewsClusteringP2P
-          name: MTEB ThuNewsClusteringP2P
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: v_measure
-            value: 70.59693805158501
-      - task:
-          type: Clustering
-        dataset:
-          type: C-MTEB/ThuNewsClusteringS2S
-          name: MTEB ThuNewsClusteringS2S
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: v_measure
-            value: 63.21127290121542
-      - task:
-          type: Retrieval
-        dataset:
-          type: C-MTEB/VideoRetrieval
-          name: MTEB VideoRetrieval
-          config: default
-          split: dev
-          revision: None
-        metrics:
-          - type: map_at_1
-            value: 61.3
-          - type: map_at_10
-            value: 70.658
-          - type: map_at_100
-            value: 71.096
-          - type: map_at_1000
-            value: 71.108
-          - type: map_at_3
-            value: 69.15
-          - type: map_at_5
-            value: 70.125
-          - type: mrr_at_1
-            value: 61.3
-          - type: mrr_at_10
-            value: 70.658
-          - type: mrr_at_100
-            value: 71.096
-          - type: mrr_at_1000
-            value: 71.108
-          - type: mrr_at_3
-            value: 69.15
-          - type: mrr_at_5
-            value: 70.125
-          - type: ndcg_at_1
-            value: 61.3
-          - type: ndcg_at_10
-            value: 74.71
-          - type: ndcg_at_100
-            value: 76.783
-          - type: ndcg_at_1000
-            value: 77.09899999999999
-          - type: ndcg_at_3
-            value: 71.634
-          - type: ndcg_at_5
-            value: 73.399
-          - type: precision_at_1
-            value: 61.3
-          - type: precision_at_10
-            value: 8.72
-          - type: precision_at_100
-            value: 0.967
-          - type: precision_at_1000
-            value: 0.099
-          - type: precision_at_3
-            value: 26.267000000000003
-          - type: precision_at_5
-            value: 16.619999999999997
-          - type: recall_at_1
-            value: 61.3
-          - type: recall_at_10
-            value: 87.2
-          - type: recall_at_100
-            value: 96.7
-          - type: recall_at_1000
-            value: 99.2
-          - type: recall_at_3
-            value: 78.8
-          - type: recall_at_5
-            value: 83.1
-      - task:
-          type: Classification
-        dataset:
-          type: C-MTEB/waimai-classification
-          name: MTEB Waimai
-          config: default
-          split: test
-          revision: None
-        metrics:
-          - type: accuracy
-            value: 88.01
-          - type: ap
-            value: 72.51537272974005
-          - type: f1
-            value: 86.49546025793478
+- name: stella-mrl-large-zh-v3.5-1792d
+  results:
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/AFQMC
+      name: MTEB AFQMC
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 54.33822814973567
+    - type: cos_sim_spearman
+      value: 58.85457316132848
+    - type: euclidean_pearson
+      value: 57.57048145477383
+    - type: euclidean_spearman
+      value: 58.854593263425095
+    - type: manhattan_pearson
+      value: 57.55884028558309
+    - type: manhattan_spearman
+      value: 58.84474216217465
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/ATEC
+      name: MTEB ATEC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 54.219652875381875
+    - type: cos_sim_spearman
+      value: 58.079506691583546
+    - type: euclidean_pearson
+      value: 61.646366330471736
+    - type: euclidean_spearman
+      value: 58.07951006894859
+    - type: manhattan_pearson
+      value: 61.64460832085762
+    - type: manhattan_spearman
+      value: 58.08054699349972
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (zh)
+      config: zh
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 46.593999999999994
+    - type: f1
+      value: 44.73150848183217
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/BQ
+      name: MTEB BQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 69.16841007040091
+    - type: cos_sim_spearman
+      value: 71.04760904227217
+    - type: euclidean_pearson
+      value: 69.95126084376611
+    - type: euclidean_spearman
+      value: 71.04760904184589
+    - type: manhattan_pearson
+      value: 69.92512024129407
+    - type: manhattan_spearman
+      value: 71.02613161257672
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/CLSClusteringP2P
+      name: MTEB CLSClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 43.032332399653306
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/CLSClusteringS2S
+      name: MTEB CLSClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 40.41603958793544
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/CMedQAv1-reranking
+      name: MTEB CMedQAv1
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 89.33487924447584
+    - type: mrr
+      value: 91.34623015873017
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/CMedQAv2-reranking
+      name: MTEB CMedQAv2
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 89.17795270698021
+    - type: mrr
+      value: 91.0956746031746
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/CmedqaRetrieval
+      name: MTEB CmedqaRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.809
+    - type: map_at_10
+      value: 39.906000000000006
+    - type: map_at_100
+      value: 41.858000000000004
+    - type: map_at_1000
+      value: 41.954
+    - type: map_at_3
+      value: 35.435
+    - type: map_at_5
+      value: 37.978
+    - type: mrr_at_1
+      value: 40.660000000000004
+    - type: mrr_at_10
+      value: 48.787000000000006
+    - type: mrr_at_100
+      value: 49.796
+    - type: mrr_at_1000
+      value: 49.832
+    - type: mrr_at_3
+      value: 46.166000000000004
+    - type: mrr_at_5
+      value: 47.675
+    - type: ndcg_at_1
+      value: 40.660000000000004
+    - type: ndcg_at_10
+      value: 46.614
+    - type: ndcg_at_100
+      value: 54.037
+    - type: ndcg_at_1000
+      value: 55.654
+    - type: ndcg_at_3
+      value: 41.032000000000004
+    - type: ndcg_at_5
+      value: 43.464999999999996
+    - type: precision_at_1
+      value: 40.660000000000004
+    - type: precision_at_10
+      value: 10.35
+    - type: precision_at_100
+      value: 1.6340000000000001
+    - type: precision_at_1000
+      value: 0.184
+    - type: precision_at_3
+      value: 23.122
+    - type: precision_at_5
+      value: 16.944
+    - type: recall_at_1
+      value: 26.809
+    - type: recall_at_10
+      value: 57.474000000000004
+    - type: recall_at_100
+      value: 87.976
+    - type: recall_at_1000
+      value: 98.74199999999999
+    - type: recall_at_3
+      value: 40.819
+    - type: recall_at_5
+      value: 48.175000000000004
+  - task:
+      type: PairClassification
+    dataset:
+      type: C-MTEB/CMNLI
+      name: MTEB Cmnli
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 83.4996993385448
+    - type: cos_sim_ap
+      value: 90.66238348446467
+    - type: cos_sim_f1
+      value: 84.39077936333699
+    - type: cos_sim_precision
+      value: 79.53651975998345
+    - type: cos_sim_recall
+      value: 89.87608136544307
+    - type: dot_accuracy
+      value: 83.4996993385448
+    - type: dot_ap
+      value: 90.64660919236363
+    - type: dot_f1
+      value: 84.39077936333699
+    - type: dot_precision
+      value: 79.53651975998345
+    - type: dot_recall
+      value: 89.87608136544307
+    - type: euclidean_accuracy
+      value: 83.4996993385448
+    - type: euclidean_ap
+      value: 90.66238269557765
+    - type: euclidean_f1
+      value: 84.39077936333699
+    - type: euclidean_precision
+      value: 79.53651975998345
+    - type: euclidean_recall
+      value: 89.87608136544307
+    - type: manhattan_accuracy
+      value: 83.35538184004811
+    - type: manhattan_ap
+      value: 90.6446013420276
+    - type: manhattan_f1
+      value: 84.37465196569775
+    - type: manhattan_precision
+      value: 80.5614632071459
+    - type: manhattan_recall
+      value: 88.56675239653963
+    - type: max_accuracy
+      value: 83.4996993385448
+    - type: max_ap
+      value: 90.66238348446467
+    - type: max_f1
+      value: 84.39077936333699
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/CovidRetrieval
+      name: MTEB CovidRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 68.967
+    - type: map_at_10
+      value: 77.95299999999999
+    - type: map_at_100
+      value: 78.213
+    - type: map_at_1000
+      value: 78.21900000000001
+    - type: map_at_3
+      value: 76.30799999999999
+    - type: map_at_5
+      value: 77.316
+    - type: mrr_at_1
+      value: 69.125
+    - type: mrr_at_10
+      value: 77.886
+    - type: mrr_at_100
+      value: 78.141
+    - type: mrr_at_1000
+      value: 78.147
+    - type: mrr_at_3
+      value: 76.291
+    - type: mrr_at_5
+      value: 77.29700000000001
+    - type: ndcg_at_1
+      value: 69.231
+    - type: ndcg_at_10
+      value: 81.867
+    - type: ndcg_at_100
+      value: 82.982
+    - type: ndcg_at_1000
+      value: 83.12
+    - type: ndcg_at_3
+      value: 78.592
+    - type: ndcg_at_5
+      value: 80.39
+    - type: precision_at_1
+      value: 69.231
+    - type: precision_at_10
+      value: 9.494
+    - type: precision_at_100
+      value: 0.9990000000000001
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 28.591
+    - type: precision_at_5
+      value: 18.061
+    - type: recall_at_1
+      value: 68.967
+    - type: recall_at_10
+      value: 93.941
+    - type: recall_at_100
+      value: 98.84100000000001
+    - type: recall_at_1000
+      value: 99.895
+    - type: recall_at_3
+      value: 85.142
+    - type: recall_at_5
+      value: 89.46300000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/DuRetrieval
+      name: MTEB DuRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.824
+    - type: map_at_10
+      value: 79.396
+    - type: map_at_100
+      value: 82.253
+    - type: map_at_1000
+      value: 82.295
+    - type: map_at_3
+      value: 54.83
+    - type: map_at_5
+      value: 69.536
+    - type: mrr_at_1
+      value: 89.7
+    - type: mrr_at_10
+      value: 92.929
+    - type: mrr_at_100
+      value: 93.013
+    - type: mrr_at_1000
+      value: 93.015
+    - type: mrr_at_3
+      value: 92.658
+    - type: mrr_at_5
+      value: 92.841
+    - type: ndcg_at_1
+      value: 89.7
+    - type: ndcg_at_10
+      value: 86.797
+    - type: ndcg_at_100
+      value: 89.652
+    - type: ndcg_at_1000
+      value: 90.047
+    - type: ndcg_at_3
+      value: 85.651
+    - type: ndcg_at_5
+      value: 84.747
+    - type: precision_at_1
+      value: 89.7
+    - type: precision_at_10
+      value: 41.61
+    - type: precision_at_100
+      value: 4.788
+    - type: precision_at_1000
+      value: 0.488
+    - type: precision_at_3
+      value: 76.833
+    - type: precision_at_5
+      value: 65.14
+    - type: recall_at_1
+      value: 25.824
+    - type: recall_at_10
+      value: 87.896
+    - type: recall_at_100
+      value: 97.221
+    - type: recall_at_1000
+      value: 99.29599999999999
+    - type: recall_at_3
+      value: 57.178
+    - type: recall_at_5
+      value: 74.348
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/EcomRetrieval
+      name: MTEB EcomRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 52.5
+    - type: map_at_10
+      value: 63.04
+    - type: map_at_100
+      value: 63.548
+    - type: map_at_1000
+      value: 63.56
+    - type: map_at_3
+      value: 60.483
+    - type: map_at_5
+      value: 62.22800000000001
+    - type: mrr_at_1
+      value: 52.5
+    - type: mrr_at_10
+      value: 63.04
+    - type: mrr_at_100
+      value: 63.548
+    - type: mrr_at_1000
+      value: 63.56
+    - type: mrr_at_3
+      value: 60.483
+    - type: mrr_at_5
+      value: 62.22800000000001
+    - type: ndcg_at_1
+      value: 52.5
+    - type: ndcg_at_10
+      value: 68.099
+    - type: ndcg_at_100
+      value: 70.48400000000001
+    - type: ndcg_at_1000
+      value: 70.769
+    - type: ndcg_at_3
+      value: 63.01
+    - type: ndcg_at_5
+      value: 66.148
+    - type: precision_at_1
+      value: 52.5
+    - type: precision_at_10
+      value: 8.39
+    - type: precision_at_100
+      value: 0.9490000000000001
+    - type: precision_at_1000
+      value: 0.097
+    - type: precision_at_3
+      value: 23.433
+    - type: precision_at_5
+      value: 15.58
+    - type: recall_at_1
+      value: 52.5
+    - type: recall_at_10
+      value: 83.89999999999999
+    - type: recall_at_100
+      value: 94.89999999999999
+    - type: recall_at_1000
+      value: 97.1
+    - type: recall_at_3
+      value: 70.3
+    - type: recall_at_5
+      value: 77.9
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/IFlyTek-classification
+      name: MTEB IFlyTek
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 50.742593305117346
+    - type: f1
+      value: 38.7451988564002
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/JDReview-classification
+      name: MTEB JDReview
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 86.09756097560977
+    - type: ap
+      value: 54.39255221143281
+    - type: f1
+      value: 80.8326851537251
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/LCQMC
+      name: MTEB LCQMC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 72.32408066246728
+    - type: cos_sim_spearman
+      value: 78.25773378380241
+    - type: euclidean_pearson
+      value: 77.87824677060661
+    - type: euclidean_spearman
+      value: 78.25773599854358
+    - type: manhattan_pearson
+      value: 77.86648277798515
+    - type: manhattan_spearman
+      value: 78.24642917155661
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/Mmarco-reranking
+      name: MTEB MMarcoReranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 28.846601097874608
+    - type: mrr
+      value: 27.902777777777775
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/MMarcoRetrieval
+      name: MTEB MMarcoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 66.533
+    - type: map_at_10
+      value: 75.58399999999999
+    - type: map_at_100
+      value: 75.91
+    - type: map_at_1000
+      value: 75.921
+    - type: map_at_3
+      value: 73.847
+    - type: map_at_5
+      value: 74.929
+    - type: mrr_at_1
+      value: 68.854
+    - type: mrr_at_10
+      value: 76.20700000000001
+    - type: mrr_at_100
+      value: 76.498
+    - type: mrr_at_1000
+      value: 76.508
+    - type: mrr_at_3
+      value: 74.71600000000001
+    - type: mrr_at_5
+      value: 75.653
+    - type: ndcg_at_1
+      value: 68.854
+    - type: ndcg_at_10
+      value: 79.209
+    - type: ndcg_at_100
+      value: 80.67
+    - type: ndcg_at_1000
+      value: 80.95
+    - type: ndcg_at_3
+      value: 75.923
+    - type: ndcg_at_5
+      value: 77.74799999999999
+    - type: precision_at_1
+      value: 68.854
+    - type: precision_at_10
+      value: 9.547
+    - type: precision_at_100
+      value: 1.027
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_3
+      value: 28.582
+    - type: precision_at_5
+      value: 18.112000000000002
+    - type: recall_at_1
+      value: 66.533
+    - type: recall_at_10
+      value: 89.736
+    - type: recall_at_100
+      value: 96.34
+    - type: recall_at_1000
+      value: 98.52
+    - type: recall_at_3
+      value: 81.047
+    - type: recall_at_5
+      value: 85.38900000000001
+  - 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: 73.27841291190316
+    - type: f1
+      value: 70.82287701665152
+  - 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: 76.20040349697376
+    - type: f1
+      value: 75.92782428878164
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/MedicalRetrieval
+      name: MTEB MedicalRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 56.39999999999999
+    - type: map_at_10
+      value: 62.122
+    - type: map_at_100
+      value: 62.692
+    - type: map_at_1000
+      value: 62.739
+    - type: map_at_3
+      value: 60.617
+    - type: map_at_5
+      value: 61.582
+    - type: mrr_at_1
+      value: 56.39999999999999
+    - type: mrr_at_10
+      value: 62.125
+    - type: mrr_at_100
+      value: 62.696
+    - type: mrr_at_1000
+      value: 62.742
+    - type: mrr_at_3
+      value: 60.617
+    - type: mrr_at_5
+      value: 61.602000000000004
+    - type: ndcg_at_1
+      value: 56.39999999999999
+    - type: ndcg_at_10
+      value: 64.986
+    - type: ndcg_at_100
+      value: 67.889
+    - type: ndcg_at_1000
+      value: 69.16499999999999
+    - type: ndcg_at_3
+      value: 61.951
+    - type: ndcg_at_5
+      value: 63.685
+    - type: precision_at_1
+      value: 56.39999999999999
+    - type: precision_at_10
+      value: 7.3999999999999995
+    - type: precision_at_100
+      value: 0.8789999999999999
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 21.933
+    - type: precision_at_5
+      value: 14.000000000000002
+    - type: recall_at_1
+      value: 56.39999999999999
+    - type: recall_at_10
+      value: 74
+    - type: recall_at_100
+      value: 87.9
+    - type: recall_at_1000
+      value: 98
+    - type: recall_at_3
+      value: 65.8
+    - type: recall_at_5
+      value: 70
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/MultilingualSentiment-classification
+      name: MTEB MultilingualSentiment
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 76.64
+    - type: f1
+      value: 76.5446299028248
+  - task:
+      type: PairClassification
+    dataset:
+      type: C-MTEB/OCNLI
+      name: MTEB Ocnli
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 82.34975636166757
+    - type: cos_sim_ap
+      value: 85.51352392694149
+    - type: cos_sim_f1
+      value: 83.53057199211045
+    - type: cos_sim_precision
+      value: 78.35337650323775
+    - type: cos_sim_recall
+      value: 89.44033790918691
+    - type: dot_accuracy
+      value: 82.34975636166757
+    - type: dot_ap
+      value: 85.51347115601486
+    - type: dot_f1
+      value: 83.53057199211045
+    - type: dot_precision
+      value: 78.35337650323775
+    - type: dot_recall
+      value: 89.44033790918691
+    - type: euclidean_accuracy
+      value: 82.34975636166757
+    - type: euclidean_ap
+      value: 85.51352392694149
+    - type: euclidean_f1
+      value: 83.53057199211045
+    - type: euclidean_precision
+      value: 78.35337650323775
+    - type: euclidean_recall
+      value: 89.44033790918691
+    - type: manhattan_accuracy
+      value: 82.34975636166757
+    - type: manhattan_ap
+      value: 85.48313896880585
+    - type: manhattan_f1
+      value: 83.52414136386261
+    - type: manhattan_precision
+      value: 79.00188323917138
+    - type: manhattan_recall
+      value: 88.59556494192185
+    - type: max_accuracy
+      value: 82.34975636166757
+    - type: max_ap
+      value: 85.51352392694149
+    - type: max_f1
+      value: 83.53057199211045
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/OnlineShopping-classification
+      name: MTEB OnlineShopping
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 93.39
+    - type: ap
+      value: 91.62127505252761
+    - type: f1
+      value: 93.38126146765326
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/PAWSX
+      name: MTEB PAWSX
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 39.69424895486595
+    - type: cos_sim_spearman
+      value: 45.357868735202885
+    - type: euclidean_pearson
+      value: 44.85027304963503
+    - type: euclidean_spearman
+      value: 45.356945176162064
+    - type: manhattan_pearson
+      value: 44.866080721344744
+    - type: manhattan_spearman
+      value: 45.37053172312661
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/QBQTC
+      name: MTEB QBQTC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 37.03908089465844
+    - type: cos_sim_spearman
+      value: 38.98314179826781
+    - type: euclidean_pearson
+      value: 37.189386019789545
+    - type: euclidean_spearman
+      value: 38.98311189555396
+    - type: manhattan_pearson
+      value: 37.14695118899785
+    - type: manhattan_spearman
+      value: 38.94957261261034
+  - 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: 65.08396305098712
+    - type: cos_sim_spearman
+      value: 66.26346934994216
+    - type: euclidean_pearson
+      value: 65.56501615370941
+    - type: euclidean_spearman
+      value: 66.26346934994216
+    - type: manhattan_pearson
+      value: 65.47984748172154
+    - type: manhattan_spearman
+      value: 66.25326746119808
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/STSB
+      name: MTEB STSB
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 80.95965207330296
+    - type: cos_sim_spearman
+      value: 82.96149593569953
+    - type: euclidean_pearson
+      value: 82.67125448003975
+    - type: euclidean_spearman
+      value: 82.96141174550262
+    - type: manhattan_pearson
+      value: 82.64660468206361
+    - type: manhattan_spearman
+      value: 82.91756025324656
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/T2Reranking
+      name: MTEB T2Reranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 66.43391960680063
+    - type: mrr
+      value: 76.078440855015
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/T2Retrieval
+      name: MTEB T2Retrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.29
+    - type: map_at_10
+      value: 78.441
+    - type: map_at_100
+      value: 82.043
+    - type: map_at_1000
+      value: 82.10499999999999
+    - type: map_at_3
+      value: 55.448
+    - type: map_at_5
+      value: 67.982
+    - type: mrr_at_1
+      value: 91.18
+    - type: mrr_at_10
+      value: 93.498
+    - type: mrr_at_100
+      value: 93.57
+    - type: mrr_at_1000
+      value: 93.572
+    - type: mrr_at_3
+      value: 93.112
+    - type: mrr_at_5
+      value: 93.351
+    - type: ndcg_at_1
+      value: 91.18
+    - type: ndcg_at_10
+      value: 85.849
+    - type: ndcg_at_100
+      value: 89.32600000000001
+    - type: ndcg_at_1000
+      value: 89.9
+    - type: ndcg_at_3
+      value: 87.333
+    - type: ndcg_at_5
+      value: 85.91499999999999
+    - type: precision_at_1
+      value: 91.18
+    - type: precision_at_10
+      value: 42.315000000000005
+    - type: precision_at_100
+      value: 5.029
+    - type: precision_at_1000
+      value: 0.517
+    - type: precision_at_3
+      value: 76.12400000000001
+    - type: precision_at_5
+      value: 63.690000000000005
+    - type: recall_at_1
+      value: 28.29
+    - type: recall_at_10
+      value: 84.679
+    - type: recall_at_100
+      value: 95.952
+    - type: recall_at_1000
+      value: 98.821
+    - type: recall_at_3
+      value: 56.987
+    - type: recall_at_5
+      value: 71.15599999999999
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/TNews-classification
+      name: MTEB TNews
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 53.09799999999999
+    - type: f1
+      value: 51.397192036892314
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/ThuNewsClusteringP2P
+      name: MTEB ThuNewsClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 70.59693805158501
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/ThuNewsClusteringS2S
+      name: MTEB ThuNewsClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 63.21127290121542
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/VideoRetrieval
+      name: MTEB VideoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 61.3
+    - type: map_at_10
+      value: 70.658
+    - type: map_at_100
+      value: 71.096
+    - type: map_at_1000
+      value: 71.108
+    - type: map_at_3
+      value: 69.15
+    - type: map_at_5
+      value: 70.125
+    - type: mrr_at_1
+      value: 61.3
+    - type: mrr_at_10
+      value: 70.658
+    - type: mrr_at_100
+      value: 71.096
+    - type: mrr_at_1000
+      value: 71.108
+    - type: mrr_at_3
+      value: 69.15
+    - type: mrr_at_5
+      value: 70.125
+    - type: ndcg_at_1
+      value: 61.3
+    - type: ndcg_at_10
+      value: 74.71
+    - type: ndcg_at_100
+      value: 76.783
+    - type: ndcg_at_1000
+      value: 77.09899999999999
+    - type: ndcg_at_3
+      value: 71.634
+    - type: ndcg_at_5
+      value: 73.399
+    - type: precision_at_1
+      value: 61.3
+    - type: precision_at_10
+      value: 8.72
+    - type: precision_at_100
+      value: 0.967
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 26.267000000000003
+    - type: precision_at_5
+      value: 16.619999999999997
+    - type: recall_at_1
+      value: 61.3
+    - type: recall_at_10
+      value: 87.2
+    - type: recall_at_100
+      value: 96.7
+    - type: recall_at_1000
+      value: 99.2
+    - type: recall_at_3
+      value: 78.8
+    - type: recall_at_5
+      value: 83.1
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/waimai-classification
+      name: MTEB Waimai
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 88.01
+    - type: ap
+      value: 72.51537272974005
+    - type: f1
+      value: 86.49546025793478
+license: mit
 ---