Update README.md

README.md

@@ -1,3 +1,1072 @@
----
-license: mit
----
+---
+tags:
+- mteb
+model-index:
+- name: zpoint_large_embedding_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: 56.52479321107392
+    - type: cos_sim_spearman
+      value: 60.72175935031135
+    - type: euclidean_pearson
+      value: 59.40990657564856
+    - type: euclidean_spearman
+      value: 60.72175934804556
+    - type: manhattan_pearson
+      value: 59.4134322847349
+    - type: manhattan_spearman
+      value: 60.724413114688225
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/ATEC
+      name: MTEB ATEC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 56.492631347325464
+    - type: cos_sim_spearman
+      value: 58.765171687177656
+    - type: euclidean_pearson
+      value: 63.236364373113844
+    - type: euclidean_spearman
+      value: 58.765171686714865
+    - type: manhattan_pearson
+      value: 63.22241814845751
+    - type: manhattan_spearman
+      value: 58.762780342648234
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (zh)
+      config: zh
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 49.72
+    - type: f1
+      value: 46.588683657317084
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/BQ
+      name: MTEB BQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 73.07779128771674
+    - type: cos_sim_spearman
+      value: 75.03682691328844
+    - type: euclidean_pearson
+      value: 73.68098259699073
+    - type: euclidean_spearman
+      value: 75.03683037648963
+    - type: manhattan_pearson
+      value: 73.66963332679124
+    - type: manhattan_spearman
+      value: 75.02269337817758
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/CLSClusteringP2P
+      name: MTEB CLSClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 58.2897067752906
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/CLSClusteringS2S
+      name: MTEB CLSClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 48.79170511177673
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/CMedQAv1
+      name: MTEB CMedQAv1
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 91.10738371185181
+    - type: mrr
+      value: 92.82496031746031
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/CMedQAv2
+      name: MTEB CMedQAv2
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 90.06959035874831
+    - type: mrr
+      value: 92.00789682539683
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/CmedqaRetrieval
+      name: MTEB CmedqaRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.132
+    - type: map_at_10
+      value: 40.400999999999996
+    - type: map_at_100
+      value: 42.246
+    - type: map_at_1000
+      value: 42.351
+    - type: map_at_3
+      value: 35.94
+    - type: map_at_5
+      value: 38.527
+    - type: mrr_at_1
+      value: 41.285
+    - type: mrr_at_10
+      value: 49.474000000000004
+    - type: mrr_at_100
+      value: 50.4
+    - type: mrr_at_1000
+      value: 50.438
+    - type: mrr_at_3
+      value: 46.891
+    - type: mrr_at_5
+      value: 48.353
+    - type: ndcg_at_1
+      value: 41.285
+    - type: ndcg_at_10
+      value: 47.159
+    - type: ndcg_at_100
+      value: 54.163
+    - type: ndcg_at_1000
+      value: 55.921
+    - type: ndcg_at_3
+      value: 41.678
+    - type: ndcg_at_5
+      value: 44.069
+    - type: precision_at_1
+      value: 41.285
+    - type: precision_at_10
+      value: 10.468
+    - type: precision_at_100
+      value: 1.611
+    - type: precision_at_1000
+      value: 0.183
+    - type: precision_at_3
+      value: 23.648
+    - type: precision_at_5
+      value: 17.229
+    - type: recall_at_1
+      value: 27.132
+    - type: recall_at_10
+      value: 57.977999999999994
+    - type: recall_at_100
+      value: 86.88
+    - type: recall_at_1000
+      value: 98.586
+    - type: recall_at_3
+      value: 41.487
+    - type: recall_at_5
+      value: 48.79
+  - task:
+      type: PairClassification
+    dataset:
+      type: C-MTEB/CMNLI
+      name: MTEB Cmnli
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 86.06133493686109
+    - type: cos_sim_ap
+      value: 92.54288511740305
+    - type: cos_sim_f1
+      value: 86.85572811163628
+    - type: cos_sim_precision
+      value: 83.72748969407681
+    - type: cos_sim_recall
+      value: 90.22679448211363
+    - type: dot_accuracy
+      value: 86.06133493686109
+    - type: dot_ap
+      value: 92.53922591080917
+    - type: dot_f1
+      value: 86.85572811163628
+    - type: dot_precision
+      value: 83.72748969407681
+    - type: dot_recall
+      value: 90.22679448211363
+    - type: euclidean_accuracy
+      value: 86.06133493686109
+    - type: euclidean_ap
+      value: 92.54287994398305
+    - type: euclidean_f1
+      value: 86.85572811163628
+    - type: euclidean_precision
+      value: 83.72748969407681
+    - type: euclidean_recall
+      value: 90.22679448211363
+    - type: manhattan_accuracy
+      value: 86.01322910402887
+    - type: manhattan_ap
+      value: 92.53060255301997
+    - type: manhattan_f1
+      value: 86.81441683456458
+    - type: manhattan_precision
+      value: 83.27249302125833
+    - type: manhattan_recall
+      value: 90.67103109656301
+    - type: max_accuracy
+      value: 86.06133493686109
+    - type: max_ap
+      value: 92.54288511740305
+    - type: max_f1
+      value: 86.85572811163628
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/CovidRetrieval
+      name: MTEB CovidRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 78.899
+    - type: map_at_10
+      value: 86.232
+    - type: map_at_100
+      value: 86.331
+    - type: map_at_1000
+      value: 86.332
+    - type: map_at_3
+      value: 85.256
+    - type: map_at_5
+      value: 85.883
+    - type: mrr_at_1
+      value: 79.347
+    - type: mrr_at_10
+      value: 86.252
+    - type: mrr_at_100
+      value: 86.342
+    - type: mrr_at_1000
+      value: 86.343
+    - type: mrr_at_3
+      value: 85.283
+    - type: mrr_at_5
+      value: 85.91
+    - type: ndcg_at_1
+      value: 79.347
+    - type: ndcg_at_10
+      value: 89.143
+    - type: ndcg_at_100
+      value: 89.541
+    - type: ndcg_at_1000
+      value: 89.58
+    - type: ndcg_at_3
+      value: 87.227
+    - type: ndcg_at_5
+      value: 88.31400000000001
+    - type: precision_at_1
+      value: 79.347
+    - type: precision_at_10
+      value: 9.905
+    - type: precision_at_100
+      value: 1.0070000000000001
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 31.261
+    - type: precision_at_5
+      value: 19.305
+    - type: recall_at_1
+      value: 78.899
+    - type: recall_at_10
+      value: 97.99799999999999
+    - type: recall_at_100
+      value: 99.684
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 92.808
+    - type: recall_at_5
+      value: 95.46900000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/DuRetrieval
+      name: MTEB DuRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.107999999999997
+    - type: map_at_10
+      value: 82.525
+    - type: map_at_100
+      value: 85.168
+    - type: map_at_1000
+      value: 85.194
+    - type: map_at_3
+      value: 57.74399999999999
+    - type: map_at_5
+      value: 72.53699999999999
+    - type: mrr_at_1
+      value: 92.30000000000001
+    - type: mrr_at_10
+      value: 94.705
+    - type: mrr_at_100
+      value: 94.76599999999999
+    - type: mrr_at_1000
+      value: 94.76599999999999
+    - type: mrr_at_3
+      value: 94.55
+    - type: mrr_at_5
+      value: 94.64
+    - type: ndcg_at_1
+      value: 92.30000000000001
+    - type: ndcg_at_10
+      value: 89.23100000000001
+    - type: ndcg_at_100
+      value: 91.556
+    - type: ndcg_at_1000
+      value: 91.81700000000001
+    - type: ndcg_at_3
+      value: 88.558
+    - type: ndcg_at_5
+      value: 87.316
+    - type: precision_at_1
+      value: 92.30000000000001
+    - type: precision_at_10
+      value: 42.38
+    - type: precision_at_100
+      value: 4.818
+    - type: precision_at_1000
+      value: 0.488
+    - type: precision_at_3
+      value: 79.14999999999999
+    - type: precision_at_5
+      value: 66.63
+    - type: recall_at_1
+      value: 27.107999999999997
+    - type: recall_at_10
+      value: 89.914
+    - type: recall_at_100
+      value: 97.658
+    - type: recall_at_1000
+      value: 99.00099999999999
+    - type: recall_at_3
+      value: 59.673
+    - type: recall_at_5
+      value: 76.437
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/EcomRetrieval
+      name: MTEB EcomRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 55.00000000000001
+    - type: map_at_10
+      value: 65.57600000000001
+    - type: map_at_100
+      value: 66.096
+    - type: map_at_1000
+      value: 66.103
+    - type: map_at_3
+      value: 63.217
+    - type: map_at_5
+      value: 64.562
+    - type: mrr_at_1
+      value: 55.00000000000001
+    - type: mrr_at_10
+      value: 65.57600000000001
+    - type: mrr_at_100
+      value: 66.096
+    - type: mrr_at_1000
+      value: 66.103
+    - type: mrr_at_3
+      value: 63.217
+    - type: mrr_at_5
+      value: 64.562
+    - type: ndcg_at_1
+      value: 55.00000000000001
+    - type: ndcg_at_10
+      value: 70.74000000000001
+    - type: ndcg_at_100
+      value: 73.001
+    - type: ndcg_at_1000
+      value: 73.223
+    - type: ndcg_at_3
+      value: 65.837
+    - type: ndcg_at_5
+      value: 68.264
+    - type: precision_at_1
+      value: 55.00000000000001
+    - type: precision_at_10
+      value: 8.7
+    - type: precision_at_100
+      value: 0.97
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 24.467
+    - type: precision_at_5
+      value: 15.86
+    - type: recall_at_1
+      value: 55.00000000000001
+    - type: recall_at_10
+      value: 87.0
+    - type: recall_at_100
+      value: 97.0
+    - type: recall_at_1000
+      value: 98.8
+    - type: recall_at_3
+      value: 73.4
+    - type: recall_at_5
+      value: 79.3
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/IFlyTek-classification
+      name: MTEB IFlyTek
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 51.696806464024625
+    - type: f1
+      value: 40.02655259854763
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/JDReview-classification
+      name: MTEB JDReview
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 88.87429643527206
+    - type: ap
+      value: 59.89821610336161
+    - type: f1
+      value: 83.98100504939507
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/LCQMC
+      name: MTEB LCQMC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 72.59510783330644
+    - type: cos_sim_spearman
+      value: 79.75022839599451
+    - type: euclidean_pearson
+      value: 79.54475341768782
+    - type: euclidean_spearman
+      value: 79.75021730266204
+    - type: manhattan_pearson
+      value: 79.53741020350834
+    - type: manhattan_spearman
+      value: 79.74152434784455
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/Mmarco-reranking
+      name: MTEB MMarcoReranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 38.86925357762224
+    - type: mrr
+      value: 38.17460317460318
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/MMarcoRetrieval
+      name: MTEB MMarcoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 68.731
+    - type: map_at_10
+      value: 78.52
+    - type: map_at_100
+      value: 78.792
+    - type: map_at_1000
+      value: 78.797
+    - type: map_at_3
+      value: 76.586
+    - type: map_at_5
+      value: 77.876
+    - type: mrr_at_1
+      value: 71.003
+    - type: mrr_at_10
+      value: 79.03
+    - type: mrr_at_100
+      value: 79.27
+    - type: mrr_at_1000
+      value: 79.274
+    - type: mrr_at_3
+      value: 77.373
+    - type: mrr_at_5
+      value: 78.46600000000001
+    - type: ndcg_at_1
+      value: 71.003
+    - type: ndcg_at_10
+      value: 82.381
+    - type: ndcg_at_100
+      value: 83.504
+    - type: ndcg_at_1000
+      value: 83.627
+    - type: ndcg_at_3
+      value: 78.78699999999999
+    - type: ndcg_at_5
+      value: 80.94
+    - type: precision_at_1
+      value: 71.003
+    - type: precision_at_10
+      value: 9.961
+    - type: precision_at_100
+      value: 1.05
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 29.694
+    - type: precision_at_5
+      value: 18.963
+    - type: recall_at_1
+      value: 68.731
+    - type: recall_at_10
+      value: 93.697
+    - type: recall_at_100
+      value: 98.546
+    - type: recall_at_1000
+      value: 99.515
+    - type: recall_at_3
+      value: 84.328
+    - type: recall_at_5
+      value: 89.42
+  - 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: 76.79219905850707
+    - type: f1
+      value: 73.15228001501512
+  - 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: 84.9562878278413
+    - type: f1
+      value: 84.0910677219451
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/MedicalRetrieval
+      name: MTEB MedicalRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 57.8
+    - type: map_at_10
+      value: 64.732
+    - type: map_at_100
+      value: 65.315
+    - type: map_at_1000
+      value: 65.347
+    - type: map_at_3
+      value: 63.14999999999999
+    - type: map_at_5
+      value: 63.934999999999995
+    - type: mrr_at_1
+      value: 57.99999999999999
+    - type: mrr_at_10
+      value: 64.852
+    - type: mrr_at_100
+      value: 65.435
+    - type: mrr_at_1000
+      value: 65.467
+    - type: mrr_at_3
+      value: 63.266999999999996
+    - type: mrr_at_5
+      value: 64.072
+    - type: ndcg_at_1
+      value: 57.8
+    - type: ndcg_at_10
+      value: 68.14
+    - type: ndcg_at_100
+      value: 71.04899999999999
+    - type: ndcg_at_1000
+      value: 71.856
+    - type: ndcg_at_3
+      value: 64.813
+    - type: ndcg_at_5
+      value: 66.241
+    - type: precision_at_1
+      value: 57.8
+    - type: precision_at_10
+      value: 7.89
+    - type: precision_at_100
+      value: 0.927
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 23.200000000000003
+    - type: precision_at_5
+      value: 14.62
+    - type: recall_at_1
+      value: 57.8
+    - type: recall_at_10
+      value: 78.9
+    - type: recall_at_100
+      value: 92.7
+    - type: recall_at_1000
+      value: 99.0
+    - type: recall_at_3
+      value: 69.6
+    - type: recall_at_5
+      value: 73.1
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/MultilingualSentiment-classification
+      name: MTEB MultilingualSentiment
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 79.22333333333333
+    - type: f1
+      value: 79.01276765455862
+  - task:
+      type: PairClassification
+    dataset:
+      type: C-MTEB/OCNLI
+      name: MTEB Ocnli
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 85.32755820249052
+    - type: cos_sim_ap
+      value: 90.56118966152913
+    - type: cos_sim_f1
+      value: 86.28428927680798
+    - type: cos_sim_precision
+      value: 81.75803402646503
+    - type: cos_sim_recall
+      value: 91.34107708553326
+    - type: dot_accuracy
+      value: 85.32755820249052
+    - type: dot_ap
+      value: 90.56120405888693
+    - type: dot_f1
+      value: 86.28428927680798
+    - type: dot_precision
+      value: 81.75803402646503
+    - type: dot_recall
+      value: 91.34107708553326
+    - type: euclidean_accuracy
+      value: 85.32755820249052
+    - type: euclidean_ap
+      value: 90.56118966152913
+    - type: euclidean_f1
+      value: 86.28428927680798
+    - type: euclidean_precision
+      value: 81.75803402646503
+    - type: euclidean_recall
+      value: 91.34107708553326
+    - type: manhattan_accuracy
+      value: 85.43584190579317
+    - type: manhattan_ap
+      value: 90.52296007826511
+    - type: manhattan_f1
+      value: 86.42099949520444
+    - type: manhattan_precision
+      value: 82.7852998065764
+    - type: manhattan_recall
+      value: 90.3907074973601
+    - type: max_accuracy
+      value: 85.43584190579317
+    - type: max_ap
+      value: 90.56120405888693
+    - type: max_f1
+      value: 86.42099949520444
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/OnlineShopping-classification
+      name: MTEB OnlineShopping
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 94.87999999999998
+    - type: ap
+      value: 93.12892276945414
+    - type: f1
+      value: 94.86921245385685
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/PAWSX
+      name: MTEB PAWSX
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 38.4367277229591
+    - type: cos_sim_spearman
+      value: 45.942712312151656
+    - type: euclidean_pearson
+      value: 44.96055989566686
+    - type: euclidean_spearman
+      value: 45.94279939044163
+    - type: manhattan_pearson
+      value: 44.979762134562925
+    - type: manhattan_spearman
+      value: 45.96004430328375
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/QBQTC
+      name: MTEB QBQTC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 41.45428416733968
+    - type: cos_sim_spearman
+      value: 43.462057455255845
+    - type: euclidean_pearson
+      value: 38.20089604291246
+    - type: euclidean_spearman
+      value: 43.46288438624811
+    - type: manhattan_pearson
+      value: 38.175045608320694
+    - type: manhattan_spearman
+      value: 43.468885824666344
+  - 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: 65.61911213187778
+    - type: cos_sim_spearman
+      value: 66.70525921118497
+    - type: euclidean_pearson
+      value: 65.35554462551515
+    - type: euclidean_spearman
+      value: 66.70525921118497
+    - type: manhattan_pearson
+      value: 65.25174169329627
+    - type: manhattan_spearman
+      value: 66.6550752269368
+  - task:
+      type: STS
+    dataset:
+      type: C-MTEB/STSB
+      name: MTEB STSB
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.27160581568329
+    - type: cos_sim_spearman
+      value: 83.34482829304406
+    - type: euclidean_pearson
+      value: 82.98079434913451
+    - type: euclidean_spearman
+      value: 83.34503180775212
+    - type: manhattan_pearson
+      value: 82.95256917013506
+    - type: manhattan_spearman
+      value: 83.31034894907503
+  - task:
+      type: Reranking
+    dataset:
+      type: C-MTEB/T2Reranking
+      name: MTEB T2Reranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 69.29054152015013
+    - type: mrr
+      value: 79.73472208788729
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/T2Retrieval
+      name: MTEB T2Retrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.0
+    - type: map_at_10
+      value: 75.871
+    - type: map_at_100
+      value: 79.664
+    - type: map_at_1000
+      value: 79.725
+    - type: map_at_3
+      value: 53.14
+    - type: map_at_5
+      value: 65.365
+    - type: mrr_at_1
+      value: 88.642
+    - type: mrr_at_10
+      value: 91.732
+    - type: mrr_at_100
+      value: 91.818
+    - type: mrr_at_1000
+      value: 91.821
+    - type: mrr_at_3
+      value: 91.217
+    - type: mrr_at_5
+      value: 91.561
+    - type: ndcg_at_1
+      value: 88.642
+    - type: ndcg_at_10
+      value: 83.815
+    - type: ndcg_at_100
+      value: 87.689
+    - type: ndcg_at_1000
+      value: 88.266
+    - type: ndcg_at_3
+      value: 84.807
+    - type: ndcg_at_5
+      value: 83.53699999999999
+    - type: precision_at_1
+      value: 88.642
+    - type: precision_at_10
+      value: 41.725
+    - type: precision_at_100
+      value: 5.024
+    - type: precision_at_1000
+      value: 0.516
+    - type: precision_at_3
+      value: 74.10600000000001
+    - type: precision_at_5
+      value: 62.192
+    - type: recall_at_1
+      value: 27.0
+    - type: recall_at_10
+      value: 83.292
+    - type: recall_at_100
+      value: 95.66799999999999
+    - type: recall_at_1000
+      value: 98.56
+    - type: recall_at_3
+      value: 55.111
+    - type: recall_at_5
+      value: 69.327
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/TNews-classification
+      name: MTEB TNews
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 54.346
+    - type: f1
+      value: 52.302508458396055
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/ThuNewsClusteringP2P
+      name: MTEB ThuNewsClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 72.47709523787981
+  - task:
+      type: Clustering
+    dataset:
+      type: C-MTEB/ThuNewsClusteringS2S
+      name: MTEB ThuNewsClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 69.35293863978707
+  - task:
+      type: Retrieval
+    dataset:
+      type: C-MTEB/VideoRetrieval
+      name: MTEB VideoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 64.60000000000001
+    - type: map_at_10
+      value: 75.683
+    - type: map_at_100
+      value: 75.961
+    - type: map_at_1000
+      value: 75.96199999999999
+    - type: map_at_3
+      value: 74.083
+    - type: map_at_5
+      value: 75.03800000000001
+    - type: mrr_at_1
+      value: 64.60000000000001
+    - type: mrr_at_10
+      value: 75.683
+    - type: mrr_at_100
+      value: 75.961
+    - type: mrr_at_1000
+      value: 75.96199999999999
+    - type: mrr_at_3
+      value: 74.083
+    - type: mrr_at_5
+      value: 75.03800000000001
+    - type: ndcg_at_1
+      value: 64.60000000000001
+    - type: ndcg_at_10
+      value: 80.26299999999999
+    - type: ndcg_at_100
+      value: 81.487
+    - type: ndcg_at_1000
+      value: 81.5
+    - type: ndcg_at_3
+      value: 77.003
+    - type: ndcg_at_5
+      value: 78.708
+    - type: precision_at_1
+      value: 64.60000000000001
+    - type: precision_at_10
+      value: 9.43
+    - type: precision_at_100
+      value: 0.997
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 28.467
+    - type: precision_at_5
+      value: 17.9
+    - type: recall_at_1
+      value: 64.60000000000001
+    - type: recall_at_10
+      value: 94.3
+    - type: recall_at_100
+      value: 99.7
+    - type: recall_at_1000
+      value: 99.8
+    - type: recall_at_3
+      value: 85.39999999999999
+    - type: recall_at_5
+      value: 89.5
+  - task:
+      type: Classification
+    dataset:
+      type: C-MTEB/waimai-classification
+      name: MTEB Waimai
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 89.36
+    - type: ap
+      value: 75.26507519569006
+    - type: f1
+      value: 87.89845508858562
+language:
+  - zh
+license: mit
+---
+<h2 align="left">ZPoint Large Embedding for Chinese</h2>
+**[2024-06-04]** release zpoint_large_embedding_zh, and upload model weight to huggingface
+
+```python
+from sentence_transformers import SentenceTransformer
+sentences1 = ["这个产品真垃圾"]
+sentences2 = ["我太喜欢这个产品了"]
+model = SentenceTransformer('iampanda/zpoint_large_embedding_zh')
+embeddings_1 = model.encode(sentences1, normalize_embeddings=True)
+embeddings_2 = model.encode(sentences2, normalize_embeddings=True)
+similarity = embeddings_1 @ embeddings_2.T
+print(similarity)
+```