Create README.md

README.md

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+---
+model-index:
+- name: Quark-Emb-8B
+  results:
+  - dataset:
+      config: default
+      name: MTEB AFQMC (default)
+      revision: latest2023
+      split: validation
+      type: C-MTEB/AFQMC
+    metrics:
+    - type: cosine_pearson
+      value: 52.87704664791064
+    - type: cosine_spearman
+      value: 53.567003436521375
+    - type: manhattan_pearson
+      value: 52.07472780799189
+    - type: manhattan_spearman
+      value: 53.5368469974003
+    - type: euclidean_pearson
+      value: 52.074186684368016
+    - type: euclidean_spearman
+      value: 53.515536447088074
+    - type: main_score
+      value: 53.567003436521375
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB ATEC (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/ATEC
+    metrics:
+    - type: cosine_pearson
+      value: 59.13301114775821
+    - type: cosine_spearman
+      value: 53.42152760117668
+    - type: manhattan_pearson
+      value: 60.05185745744783
+    - type: manhattan_spearman
+      value: 53.36914545708813
+    - type: euclidean_pearson
+      value: 60.17725014927802
+    - type: euclidean_spearman
+      value: 53.431110991334485
+    - type: main_score
+      value: 53.42152760117668
+    task:
+      type: STS
+  - dataset:
+      config: zh
+      name: MTEB AmazonReviewsClassification (zh)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: test
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 54.74600000000001
+    - type: accuracy_stderr
+      value: 1.060492338491892
+    - type: f1
+      value: 53.49846112279175
+    - type: f1_stderr
+      value: 1.729174511160517
+    - type: main_score
+      value: 54.74600000000001
+    task:
+      type: Classification
+  - dataset:
+      config: zh
+      name: MTEB AmazonReviewsClassification (zh)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: validation
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 53.468
+    - type: accuracy_stderr
+      value: 1.0129639677698308
+    - type: f1
+      value: 52.21987651679265
+    - type: f1_stderr
+      value: 1.7016822177116173
+    - type: main_score
+      value: 53.468
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB BQ (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/BQ
+    metrics:
+    - type: cosine_pearson
+      value: 69.640366232364
+    - type: cosine_spearman
+      value: 70.65881213017273
+    - type: manhattan_pearson
+      value: 67.76837799100343
+    - type: manhattan_spearman
+      value: 70.5046111101055
+    - type: euclidean_pearson
+      value: 67.83004194158737
+    - type: euclidean_spearman
+      value: 70.60927547682859
+    - type: main_score
+      value: 70.65881213017273
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB CLSClusteringP2P (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/CLSClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 62.32714079793593
+    - type: v_measure_std
+      value: 1.5782386182731478
+    - type: main_score
+      value: 62.32714079793593
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB CLSClusteringS2S (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/CLSClusteringS2S
+    metrics:
+    - type: v_measure
+      value: 59.29532340833129
+    - type: v_measure_std
+      value: 1.5258658358346424
+    - type: main_score
+      value: 59.29532340833129
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB CMedQAv1-reranking (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/CMedQAv1-reranking
+    metrics:
+    - type: map
+      value: 88.02263756085355
+    - type: mrr
+      value: 90.18928571428572
+    - type: main_score
+      value: 88.02263756085355
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB CMedQAv2-reranking (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/CMedQAv2-reranking
+    metrics:
+    - type: map
+      value: 88.81199829110464
+    - type: mrr
+      value: 90.81817460317461
+    - type: main_score
+      value: 88.81199829110464
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB CmedqaRetrieval (default)
+      revision: latest2023
+      split: dev
+      type: C-MTEB/CmedqaRetrieval
+    metrics:
+    - type: map_at_1
+      value: 27.448
+    - type: map_at_10
+      value: 40.794000000000004
+    - type: map_at_100
+      value: 42.606
+    - type: map_at_1000
+      value: 42.711
+    - type: map_at_20
+      value: 41.778
+    - type: map_at_3
+      value: 36.429
+    - type: map_at_5
+      value: 38.841
+    - type: mrr_at_1
+      value: 41.510000000000005
+    - type: mrr_at_10
+      value: 49.986999999999995
+    - type: mrr_at_100
+      value: 50.908
+    - type: mrr_at_1000
+      value: 50.946000000000005
+    - type: mrr_at_20
+      value: 50.531000000000006
+    - type: mrr_at_3
+      value: 47.562
+    - type: mrr_at_5
+      value: 48.882
+    - type: ndcg_at_1
+      value: 41.510000000000005
+    - type: ndcg_at_10
+      value: 47.620000000000005
+    - type: ndcg_at_100
+      value: 54.586999999999996
+    - type: ndcg_at_1000
+      value: 56.324
+    - type: ndcg_at_20
+      value: 50.332
+    - type: ndcg_at_3
+      value: 42.27
+    - type: ndcg_at_5
+      value: 44.421
+    - type: precision_at_1
+      value: 41.510000000000005
+    - type: precision_at_10
+      value: 10.45
+    - type: precision_at_100
+      value: 1.6179999999999999
+    - type: precision_at_1000
+      value: 0.184
+    - type: precision_at_20
+      value: 6.1339999999999995
+    - type: precision_at_3
+      value: 23.823
+    - type: precision_at_5
+      value: 17.089
+    - type: recall_at_1
+      value: 27.448
+    - type: recall_at_10
+      value: 58.629
+    - type: recall_at_100
+      value: 87.26899999999999
+    - type: recall_at_1000
+      value: 98.713
+    - type: recall_at_20
+      value: 67.929
+    - type: recall_at_3
+      value: 42.331
+    - type: recall_at_5
+      value: 49.193999999999996
+    - type: main_score
+      value: 47.620000000000005
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB Cmnli (default)
+      revision: latest2023
+      split: validation
+      type: C-MTEB/CMNLI
+    metrics:
+    - type: cos_sim_accuracy
+      value: 91.040288634997
+    - type: cos_sim_accuracy_threshold
+      value: 96.31753556207411
+    - type: cos_sim_ap
+      value: 95.94857244353375
+    - type: cos_sim_f1
+      value: 91.47971901200997
+    - type: cos_sim_f1_threshold
+      value: 96.01236110428391
+    - type: cos_sim_precision
+      value: 88.74477907232358
+    - type: cos_sim_recall
+      value: 94.388590133271
+    - type: dot_accuracy
+      value: 80.7696933253157
+    - type: dot_accuracy_threshold
+      value: 58.4022485296251
+    - type: dot_ap
+      value: 89.17817373664943
+    - type: dot_f1
+      value: 81.62572172534811
+    - type: dot_f1_threshold
+      value: 58.18378730482039
+    - type: dot_precision
+      value: 79.12642669007901
+    - type: dot_recall
+      value: 84.28805237315876
+    - type: euclidean_accuracy
+      value: 90.92002405291642
+    - type: euclidean_accuracy_threshold
+      value: 21.553298629922512
+    - type: euclidean_ap
+      value: 95.90941014786691
+    - type: euclidean_f1
+      value: 91.45241317095173
+    - type: euclidean_f1_threshold
+      value: 22.109074422645463
+    - type: euclidean_precision
+      value: 88.32498366368982
+    - type: euclidean_recall
+      value: 94.80944587327565
+    - type: manhattan_accuracy
+      value: 90.94407696933253
+    - type: manhattan_accuracy_threshold
+      value: 524.1466620016906
+    - type: manhattan_ap
+      value: 95.89310684813798
+    - type: manhattan_f1
+      value: 91.50400541577343
+    - type: manhattan_f1_threshold
+      value: 525.5181014869215
+    - type: manhattan_precision
+      value: 88.4212821631051
+    - type: manhattan_recall
+      value: 94.80944587327565
+    - type: max_accuracy
+      value: 91.040288634997
+    - type: max_ap
+      value: 95.94857244353375
+    - type: max_f1
+      value: 91.50400541577343
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB CovidRetrieval (default)
+      revision: latest2023
+      split: dev
+      type: C-MTEB/CovidRetrieval
+    metrics:
+    - type: map_at_1
+      value: 78.82000000000001
+    - type: map_at_10
+      value: 85.51100000000001
+    - type: map_at_100
+      value: 85.67099999999999
+    - type: map_at_1000
+      value: 85.672
+    - type: map_at_20
+      value: 85.641
+    - type: map_at_3
+      value: 84.321
+    - type: map_at_5
+      value: 85.048
+    - type: mrr_at_1
+      value: 78.925
+    - type: mrr_at_10
+      value: 85.548
+    - type: mrr_at_100
+      value: 85.698
+    - type: mrr_at_1000
+      value: 85.699
+    - type: mrr_at_20
+      value: 85.669
+    - type: mrr_at_3
+      value: 84.45700000000001
+    - type: mrr_at_5
+      value: 85.12100000000001
+    - type: ndcg_at_1
+      value: 78.925
+    - type: ndcg_at_10
+      value: 88.359
+    - type: ndcg_at_100
+      value: 88.98899999999999
+    - type: ndcg_at_1000
+      value: 89.017
+    - type: ndcg_at_20
+      value: 88.776
+    - type: ndcg_at_3
+      value: 86.086
+    - type: ndcg_at_5
+      value: 87.336
+    - type: precision_at_1
+      value: 78.925
+    - type: precision_at_10
+      value: 9.789
+    - type: precision_at_100
+      value: 1.0070000000000001
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_20
+      value: 4.979
+    - type: precision_at_3
+      value: 30.488
+    - type: precision_at_5
+      value: 18.925
+    - type: recall_at_1
+      value: 78.82000000000001
+    - type: recall_at_10
+      value: 96.997
+    - type: recall_at_100
+      value: 99.684
+    - type: recall_at_1000
+      value: 99.895
+    - type: recall_at_20
+      value: 98.52499999999999
+    - type: recall_at_3
+      value: 91.01700000000001
+    - type: recall_at_5
+      value: 93.994
+    - type: main_score
+      value: 88.359
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB DuRetrieval (default)
+      revision: latest2023
+      split: dev
+      type: C-MTEB/DuRetrieval
+    metrics:
+    - type: map_at_1
+      value: 28.03
+    - type: map_at_10
+      value: 85.60600000000001
+    - type: map_at_100
+      value: 88.14800000000001
+    - type: map_at_1000
+      value: 88.169
+    - type: map_at_20
+      value: 87.591
+    - type: map_at_3
+      value: 60.06
+    - type: map_at_5
+      value: 75.564
+    - type: mrr_at_1
+      value: 94.05
+    - type: mrr_at_10
+      value: 96.043
+    - type: mrr_at_100
+      value: 96.075
+    - type: mrr_at_1000
+      value: 96.077
+    - type: mrr_at_20
+      value: 96.06099999999999
+    - type: mrr_at_3
+      value: 95.875
+    - type: mrr_at_5
+      value: 96.017
+    - type: ndcg_at_1
+      value: 94.05
+    - type: ndcg_at_10
+      value: 91.58800000000001
+    - type: ndcg_at_100
+      value: 93.536
+    - type: ndcg_at_1000
+      value: 93.726
+    - type: ndcg_at_20
+      value: 92.64099999999999
+    - type: ndcg_at_3
+      value: 90.865
+    - type: ndcg_at_5
+      value: 89.972
+    - type: precision_at_1
+      value: 94.05
+    - type: precision_at_10
+      value: 43.19
+    - type: precision_at_100
+      value: 4.859
+    - type: precision_at_1000
+      value: 0.49
+    - type: precision_at_20
+      value: 23.3
+    - type: precision_at_3
+      value: 81.0
+    - type: precision_at_5
+      value: 68.36
+    - type: recall_at_1
+      value: 28.03
+    - type: recall_at_10
+      value: 92.095
+    - type: recall_at_100
+      value: 98.764
+    - type: recall_at_1000
+      value: 99.71
+    - type: recall_at_20
+      value: 95.87
+    - type: recall_at_3
+      value: 61.949
+    - type: recall_at_5
+      value: 79.41
+    - type: main_score
+      value: 91.58800000000001
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB EcomRetrieval (default)
+      revision: latest2023
+      split: dev
+      type: C-MTEB/EcomRetrieval
+    metrics:
+    - type: map_at_1
+      value: 58.599999999999994
+    - type: map_at_10
+      value: 68.88499999999999
+    - type: map_at_100
+      value: 69.269
+    - type: map_at_1000
+      value: 69.274
+    - type: map_at_20
+      value: 69.17699999999999
+    - type: map_at_3
+      value: 66.167
+    - type: map_at_5
+      value: 68.082
+    - type: mrr_at_1
+      value: 58.599999999999994
+    - type: mrr_at_10
+      value: 68.88499999999999
+    - type: mrr_at_100
+      value: 69.269
+    - type: mrr_at_1000
+      value: 69.274
+    - type: mrr_at_20
+      value: 69.17699999999999
+    - type: mrr_at_3
+      value: 66.167
+    - type: mrr_at_5
+      value: 68.082
+    - type: ndcg_at_1
+      value: 58.599999999999994
+    - type: ndcg_at_10
+      value: 74.018
+    - type: ndcg_at_100
+      value: 75.72
+    - type: ndcg_at_1000
+      value: 75.851
+    - type: ndcg_at_20
+      value: 75.08
+    - type: ndcg_at_3
+      value: 68.64
+    - type: ndcg_at_5
+      value: 72.075
+    - type: precision_at_1
+      value: 58.599999999999994
+    - type: precision_at_10
+      value: 9.01
+    - type: precision_at_100
+      value: 0.9769999999999999
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_20
+      value: 4.715
+    - type: precision_at_3
+      value: 25.267
+    - type: precision_at_5
+      value: 16.82
+    - type: recall_at_1
+      value: 58.599999999999994
+    - type: recall_at_10
+      value: 90.10000000000001
+    - type: recall_at_100
+      value: 97.7
+    - type: recall_at_1000
+      value: 98.7
+    - type: recall_at_20
+      value: 94.3
+    - type: recall_at_3
+      value: 75.8
+    - type: recall_at_5
+      value: 84.1
+    - type: main_score
+      value: 74.018
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB IFlyTek (default)
+      revision: latest2023
+      split: validation
+      type: C-MTEB/IFlyTek-classification
+    metrics:
+    - type: accuracy
+      value: 55.79838399384378
+    - type: accuracy_stderr
+      value: 0.273588131352537
+    - type: f1
+      value: 42.23811666656058
+    - type: f1_stderr
+      value: 0.2317340030986553
+    - type: main_score
+      value: 55.79838399384378
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB JDReview (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/JDReview-classification
+    metrics:
+    - type: accuracy
+      value: 89.11819887429644
+    - type: accuracy_stderr
+      value: 1.5149440328845287
+    - type: ap
+      value: 60.17445086411222
+    - type: ap_stderr
+      value: 3.4864563160430384
+    - type: f1
+      value: 84.14324891240739
+    - type: f1_stderr
+      value: 1.804154595730216
+    - type: main_score
+      value: 89.11819887429644
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB LCQMC (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/LCQMC
+    metrics:
+    - type: cosine_pearson
+      value: 80.86541640109346
+    - type: cosine_spearman
+      value: 79.60409318173409
+    - type: manhattan_pearson
+      value: 81.12725142112909
+    - type: manhattan_spearman
+      value: 79.61120096401483
+    - type: euclidean_pearson
+      value: 81.1558178459699
+    - type: euclidean_spearman
+      value: 79.63206760369867
+    - type: main_score
+      value: 79.60409318173409
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB MMarcoReranking (default)
+      revision: latest2023
+      split: dev
+      type: C-MTEB/Mmarco-reranking
+    metrics:
+    - type: map
+      value: 30.290346963620866
+    - type: mrr
+      value: 29.661507936507935
+    - type: main_score
+      value: 30.290346963620866
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB MMarcoRetrieval (default)
+      revision: latest2023
+      split: dev
+      type: C-MTEB/MMarcoRetrieval
+    metrics:
+    - type: map_at_1
+      value: 67.801
+    - type: map_at_10
+      value: 76.771
+    - type: map_at_100
+      value: 77.08
+    - type: map_at_1000
+      value: 77.091
+    - type: map_at_20
+      value: 76.982
+    - type: map_at_3
+      value: 75.035
+    - type: map_at_5
+      value: 76.171
+    - type: mrr_at_1
+      value: 70.057
+    - type: mrr_at_10
+      value: 77.387
+    - type: mrr_at_100
+      value: 77.65100000000001
+    - type: mrr_at_1000
+      value: 77.661
+    - type: mrr_at_20
+      value: 77.566
+    - type: mrr_at_3
+      value: 75.90299999999999
+    - type: mrr_at_5
+      value: 76.848
+    - type: ndcg_at_1
+      value: 70.057
+    - type: ndcg_at_10
+      value: 80.37100000000001
+    - type: ndcg_at_100
+      value: 81.71300000000001
+    - type: ndcg_at_1000
+      value: 81.982
+    - type: ndcg_at_20
+      value: 81.074
+    - type: ndcg_at_3
+      value: 77.12
+    - type: ndcg_at_5
+      value: 79.00500000000001
+    - type: precision_at_1
+      value: 70.057
+    - type: precision_at_10
+      value: 9.643
+    - type: precision_at_100
+      value: 1.031
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_20
+      value: 4.973000000000001
+    - type: precision_at_3
+      value: 28.959000000000003
+    - type: precision_at_5
+      value: 18.384
+    - type: recall_at_1
+      value: 67.801
+    - type: recall_at_10
+      value: 90.821
+    - type: recall_at_100
+      value: 96.809
+    - type: recall_at_1000
+      value: 98.87899999999999
+    - type: recall_at_20
+      value: 93.49300000000001
+    - type: recall_at_3
+      value: 82.26
+    - type: recall_at_5
+      value: 86.725
+    - type: main_score
+      value: 80.37100000000001
+    task:
+      type: Retrieval
+  - dataset:
+      config: zh-CN
+      name: MTEB MassiveIntentClassification (zh-CN)
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+      split: test
+      type: mteb/amazon_massive_intent
+    metrics:
+    - type: accuracy
+      value: 81.4862138533961
+    - type: accuracy_stderr
+      value: 1.024666951162929
+    - type: f1
+      value: 78.57865898474617
+    - type: f1_stderr
+      value: 1.1662766217911715
+    - type: main_score
+      value: 81.4862138533961
+    task:
+      type: Classification
+  - dataset:
+      config: zh-CN
+      name: MTEB MassiveScenarioClassification (zh-CN)
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+      split: test
+      type: mteb/amazon_massive_scenario
+    metrics:
+    - type: accuracy
+      value: 86.43913920645595
+    - type: accuracy_stderr
+      value: 0.6198364524624383
+    - type: f1
+      value: 85.45514450914429
+    - type: f1_stderr
+      value: 0.775295463718716
+    - type: main_score
+      value: 86.43913920645595
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB MedicalRetrieval (default)
+      revision: latest2023
+      split: dev
+      type: C-MTEB/MedicalRetrieval
+    metrics:
+    - type: map_at_1
+      value: 60.0
+    - type: map_at_10
+      value: 66.673
+    - type: map_at_100
+      value: 67.239
+    - type: map_at_1000
+      value: 67.26299999999999
+    - type: map_at_20
+      value: 67.01899999999999
+    - type: map_at_3
+      value: 65.333
+    - type: map_at_5
+      value: 66.063
+    - type: mrr_at_1
+      value: 60.099999999999994
+    - type: mrr_at_10
+      value: 66.739
+    - type: mrr_at_100
+      value: 67.306
+    - type: mrr_at_1000
+      value: 67.33
+    - type: mrr_at_20
+      value: 67.086
+    - type: mrr_at_3
+      value: 65.4
+    - type: mrr_at_5
+      value: 66.13
+    - type: ndcg_at_1
+      value: 60.0
+    - type: ndcg_at_10
+      value: 69.786
+    - type: ndcg_at_100
+      value: 72.693
+    - type: ndcg_at_1000
+      value: 73.373
+    - type: ndcg_at_20
+      value: 71.032
+    - type: ndcg_at_3
+      value: 67.024
+    - type: ndcg_at_5
+      value: 68.34
+    - type: precision_at_1
+      value: 60.0
+    - type: precision_at_10
+      value: 7.95
+    - type: precision_at_100
+      value: 0.935
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_20
+      value: 4.22
+    - type: precision_at_3
+      value: 23.967
+    - type: precision_at_5
+      value: 15.02
+    - type: recall_at_1
+      value: 60.0
+    - type: recall_at_10
+      value: 79.5
+    - type: recall_at_100
+      value: 93.5
+    - type: recall_at_1000
+      value: 98.9
+    - type: recall_at_20
+      value: 84.39999999999999
+    - type: recall_at_3
+      value: 71.89999999999999
+    - type: recall_at_5
+      value: 75.1
+    - type: main_score
+      value: 69.786
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB MultilingualSentiment (default)
+      revision: latest2023
+      split: validation
+      type: C-MTEB/MultilingualSentiment-classification
+    metrics:
+    - type: accuracy
+      value: 81.19666666666667
+    - type: accuracy_stderr
+      value: 0.6507175526550155
+    - type: f1
+      value: 81.3717120301294
+    - type: f1_stderr
+      value: 0.629161893845245
+    - type: main_score
+      value: 81.19666666666667
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB Ocnli (default)
+      revision: latest2023
+      split: validation
+      type: C-MTEB/OCNLI
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.92961559285327
+    - type: cos_sim_accuracy_threshold
+      value: 95.72410743295985
+    - type: cos_sim_ap
+      value: 94.04072585697942
+    - type: cos_sim_f1
+      value: 90.6060606060606
+    - type: cos_sim_f1_threshold
+      value: 95.71085030120679
+    - type: cos_sim_precision
+      value: 86.83446272991287
+    - type: cos_sim_recall
+      value: 94.72016895459345
+    - type: dot_accuracy
+      value: 84.29886302111532
+    - type: dot_accuracy_threshold
+      value: 58.39834018444028
+    - type: dot_ap
+      value: 90.71149047430606
+    - type: dot_f1
+      value: 84.83263598326361
+    - type: dot_f1_threshold
+      value: 58.39834018444028
+    - type: dot_precision
+      value: 84.04145077720207
+    - type: dot_recall
+      value: 85.6388595564942
+    - type: euclidean_accuracy
+      value: 89.87547374120194
+    - type: euclidean_accuracy_threshold
+      value: 22.827705768877962
+    - type: euclidean_ap
+      value: 93.87312138426815
+    - type: euclidean_f1
+      value: 90.5982905982906
+    - type: euclidean_f1_threshold
+      value: 22.940558234199905
+    - type: euclidean_precision
+      value: 86.468330134357
+    - type: euclidean_recall
+      value: 95.14255543822597
+    - type: manhattan_accuracy
+      value: 89.44233892799134
+    - type: manhattan_accuracy_threshold
+      value: 544.6256417358975
+    - type: manhattan_ap
+      value: 93.8313800715528
+    - type: manhattan_f1
+      value: 90.16641452344932
+    - type: manhattan_f1_threshold
+      value: 544.6256417358975
+    - type: manhattan_precision
+      value: 86.2934362934363
+    - type: manhattan_recall
+      value: 94.40337909186906
+    - type: max_accuracy
+      value: 89.92961559285327
+    - type: max_ap
+      value: 94.04072585697942
+    - type: max_f1
+      value: 90.6060606060606
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB OnlineShopping (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/OnlineShopping-classification
+    metrics:
+    - type: accuracy
+      value: 93.83999999999999
+    - type: accuracy_stderr
+      value: 0.4521061822182879
+    - type: ap
+      value: 92.19373645628713
+    - type: ap_stderr
+      value: 0.2927396159644918
+    - type: f1
+      value: 93.83158946571204
+    - type: f1_stderr
+      value: 0.4472553159438725
+    - type: main_score
+      value: 93.83999999999999
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB PAWSX (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/PAWSX
+    metrics:
+    - type: cosine_pearson
+      value: 50.30680596662101
+    - type: cosine_spearman
+      value: 52.41534063346883
+    - type: manhattan_pearson
+      value: 51.81137421589127
+    - type: manhattan_spearman
+      value: 52.40332176267904
+    - type: euclidean_pearson
+      value: 51.842454511431235
+    - type: euclidean_spearman
+      value: 52.4062829337432
+    - type: main_score
+      value: 52.41534063346883
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB QBQTC (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/QBQTC
+    metrics:
+    - type: cosine_pearson
+      value: 58.31070289198933
+    - type: cosine_spearman
+      value: 57.966010447080684
+    - type: manhattan_pearson
+      value: 54.99874211888254
+    - type: manhattan_spearman
+      value: 57.796012247889195
+    - type: euclidean_pearson
+      value: 55.138798573277455
+    - type: euclidean_spearman
+      value: 57.95150876116391
+    - type: main_score
+      value: 57.966010447080684
+    task:
+      type: STS
+  - dataset:
+      config: zh
+      name: MTEB STS22 (zh)
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 75.26028549682404
+    - type: cosine_spearman
+      value: 73.9002967678025
+    - type: manhattan_pearson
+      value: 73.47220514464013
+    - type: manhattan_spearman
+      value: 73.74093326288234
+    - type: euclidean_pearson
+      value: 73.59040445366989
+    - type: euclidean_spearman
+      value: 73.9002967678025
+    - type: main_score
+      value: 73.9002967678025
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB STSB (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/STSB
+    metrics:
+    - type: cosine_pearson
+      value: 78.17081373176123
+    - type: cosine_spearman
+      value: 78.61566426272397
+    - type: manhattan_pearson
+      value: 77.66643088697434
+    - type: manhattan_spearman
+      value: 78.94692354474782
+    - type: euclidean_pearson
+      value: 77.69471041307843
+    - type: euclidean_spearman
+      value: 78.92513847741967
+    - type: main_score
+      value: 78.61566426272397
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB T2Reranking (default)
+      revision: latest2023
+      split: dev
+      type: C-MTEB/T2Reranking
+    metrics:
+    - type: map
+      value: 68.13018101639273
+    - type: mrr
+      value: 79.13973922902494
+    - type: main_score
+      value: 68.13018101639273
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB T2Retrieval (default)
+      revision: latest2023
+      split: dev
+      type: C-MTEB/T2Retrieval
+    metrics:
+    - type: map_at_1
+      value: 28.591
+    - type: map_at_10
+      value: 80.979
+    - type: map_at_100
+      value: 84.411
+    - type: map_at_1000
+      value: 84.458
+    - type: map_at_20
+      value: 83.68100000000001
+    - type: map_at_3
+      value: 56.967999999999996
+    - type: map_at_5
+      value: 70.098
+    - type: mrr_at_1
+      value: 92.12700000000001
+    - type: mrr_at_10
+      value: 94.094
+    - type: mrr_at_100
+      value: 94.161
+    - type: mrr_at_1000
+      value: 94.164
+    - type: mrr_at_20
+      value: 94.14
+    - type: mrr_at_3
+      value: 93.753
+    - type: mrr_at_5
+      value: 93.98100000000001
+    - type: ndcg_at_1
+      value: 92.12700000000001
+    - type: ndcg_at_10
+      value: 87.586
+    - type: ndcg_at_100
+      value: 90.58500000000001
+    - type: ndcg_at_1000
+      value: 91.05
+    - type: ndcg_at_20
+      value: 89.132
+    - type: ndcg_at_3
+      value: 88.86800000000001
+    - type: ndcg_at_5
+      value: 87.673
+    - type: precision_at_1
+      value: 92.12700000000001
+    - type: precision_at_10
+      value: 43.35
+    - type: precision_at_100
+      value: 5.06
+    - type: precision_at_1000
+      value: 0.517
+    - type: precision_at_20
+      value: 23.895
+    - type: precision_at_3
+      value: 77.664
+    - type: precision_at_5
+      value: 65.231
+    - type: recall_at_1
+      value: 28.591
+    - type: recall_at_10
+      value: 86.342
+    - type: recall_at_100
+      value: 96.274
+    - type: recall_at_1000
+      value: 98.666
+    - type: recall_at_20
+      value: 91.741
+    - type: recall_at_3
+      value: 58.386
+    - type: recall_at_5
+      value: 72.942
+    - type: main_score
+      value: 87.586
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB TNews (default)
+      revision: latest2023
+      split: validation
+      type: C-MTEB/TNews-classification
+    metrics:
+    - type: accuracy
+      value: 58.057
+    - type: accuracy_stderr
+      value: 0.4056365368159032
+    - type: f1
+      value: 56.16542257610506
+    - type: f1_stderr
+      value: 0.49560443919264746
+    - type: main_score
+      value: 58.057
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB ThuNewsClusteringP2P (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/ThuNewsClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 83.43086890900754
+    - type: v_measure_std
+      value: 1.3242733220406704
+    - type: main_score
+      value: 83.43086890900754
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB ThuNewsClusteringS2S (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/ThuNewsClusteringS2S
+    metrics:
+    - type: v_measure
+      value: 80.17922689954183
+    - type: v_measure_std
+      value: 2.1732975942130612
+    - type: main_score
+      value: 80.17922689954183
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB VideoRetrieval (default)
+      revision: latest2023
+      split: dev
+      type: C-MTEB/VideoRetrieval
+    metrics:
+    - type: map_at_1
+      value: 68.60000000000001
+    - type: map_at_10
+      value: 77.518
+    - type: map_at_100
+      value: 77.815
+    - type: map_at_1000
+      value: 77.82
+    - type: map_at_20
+      value: 77.73299999999999
+    - type: map_at_3
+      value: 76.167
+    - type: map_at_5
+      value: 76.932
+    - type: mrr_at_1
+      value: 68.60000000000001
+    - type: mrr_at_10
+      value: 77.518
+    - type: mrr_at_100
+      value: 77.815
+    - type: mrr_at_1000
+      value: 77.82
+    - type: mrr_at_20
+      value: 77.73299999999999
+    - type: mrr_at_3
+      value: 76.167
+    - type: mrr_at_5
+      value: 76.932
+    - type: ndcg_at_1
+      value: 68.60000000000001
+    - type: ndcg_at_10
+      value: 81.339
+    - type: ndcg_at_100
+      value: 82.646
+    - type: ndcg_at_1000
+      value: 82.76599999999999
+    - type: ndcg_at_20
+      value: 82.107
+    - type: ndcg_at_3
+      value: 78.569
+    - type: ndcg_at_5
+      value: 79.937
+    - type: precision_at_1
+      value: 68.60000000000001
+    - type: precision_at_10
+      value: 9.31
+    - type: precision_at_100
+      value: 0.989
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_20
+      value: 4.805000000000001
+    - type: precision_at_3
+      value: 28.499999999999996
+    - type: precision_at_5
+      value: 17.76
+    - type: recall_at_1
+      value: 68.60000000000001
+    - type: recall_at_10
+      value: 93.10000000000001
+    - type: recall_at_100
+      value: 98.9
+    - type: recall_at_1000
+      value: 99.8
+    - type: recall_at_20
+      value: 96.1
+    - type: recall_at_3
+      value: 85.5
+    - type: recall_at_5
+      value: 88.8
+    - type: main_score
+      value: 81.339
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB Waimai (default)
+      revision: latest2023
+      split: test
+      type: C-MTEB/waimai-classification
+    metrics:
+    - type: accuracy
+      value: 90.63000000000001
+    - type: accuracy_stderr
+      value: 0.49203658400570216
+    - type: ap
+      value: 77.93466200571231
+    - type: ap_stderr
+      value: 1.2006502477223735
+    - type: f1
+      value: 89.36361097500829
+    - type: f1_stderr
+      value: 0.43660966359249054
+    - type: main_score
+      value: 90.63000000000001
+    task:
+      type: Classification
+tags:
+- mteb
+---
+
+# Quark-Emb-8B 
+
+- Chinese Text Embedding Model developed by Alibaba Quark-LLM Team. Details will be published later.