Create README.md

README.md

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+---
+model-index:
+- name: Quark-Emb-1.5b
+  results:
+  - dataset:
+      config: default
+      name: MTEB AFQMC 
+      revision: None
+      split: validation
+      type: C-MTEB/AFQMC
+    metrics:
+    - type: cosine_pearson
+      value: 47.14285927987258
+    - type: cosine_spearman
+      value: 48.161200368263025
+    - type: manhattan_pearson
+      value: 46.852921578928694
+    - type: manhattan_spearman
+      value: 48.0768829644805
+    - type: euclidean_pearson
+      value: 46.934710408297846
+    - type: euclidean_spearman
+      value: 48.161200368263025
+    - type: main_score
+      value: 48.161200368263025
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB ATEC 
+      revision: None
+      split: test
+      type: C-MTEB/ATEC
+    metrics:
+    - type: cosine_pearson
+      value: 53.31694395347832
+    - type: cosine_spearman
+      value: 50.82142054857025
+    - type: manhattan_pearson
+      value: 55.63018022546727
+    - type: manhattan_spearman
+      value: 50.808925663235286
+    - type: euclidean_pearson
+      value: 55.630897902214585
+    - type: euclidean_spearman
+      value: 50.82142054857025
+    - type: main_score
+      value: 50.82142054857025
+    task:
+      type: STS
+  - dataset:
+      config: zh
+      name: MTEB AmazonReviewsClassification (zh)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: test
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 51.93800000000001
+    - type: accuracy_stderr
+      value: 1.6225030046197138
+    - type: f1
+      value: 49.36480272612989
+    - type: f1_stderr
+      value: 2.402473535325102
+    - type: main_score
+      value: 51.93800000000001
+    task:
+      type: Classification
+  - dataset:
+      config: zh
+      name: MTEB AmazonReviewsClassification (zh)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: validation
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 50.757999999999996
+    - type: accuracy_stderr
+      value: 1.1949041802588176
+    - type: f1
+      value: 48.18542841607346
+    - type: f1_stderr
+      value: 2.025507464835368
+    - type: main_score
+      value: 50.757999999999996
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB BQ 
+      revision: None
+      split: test
+      type: C-MTEB/BQ
+    metrics:
+    - type: cosine_pearson
+      value: 66.94471481392273
+    - type: cosine_spearman
+      value: 67.86811107045457
+    - type: manhattan_pearson
+      value: 65.56778188873142
+    - type: manhattan_spearman
+      value: 67.83060870618156
+    - type: euclidean_pearson
+      value: 65.63668085779311
+    - type: euclidean_spearman
+      value: 67.86811107045457
+    - type: main_score
+      value: 67.86811107045457
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB CLSClusteringP2P 
+      revision: None
+      split: test
+      type: C-MTEB/CLSClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 58.53706905558472
+    - type: v_measure_std
+      value: 1.3628784531981595
+    - type: main_score
+      value: 58.53706905558472
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB CLSClusteringS2S 
+      revision: None
+      split: test
+      type: C-MTEB/CLSClusteringS2S
+    metrics:
+    - type: v_measure
+      value: 54.70969139354621
+    - type: v_measure_std
+      value: 1.938384688132648
+    - type: main_score
+      value: 54.70969139354621
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB CMedQAv1
+      revision: None
+      split: test
+      type: C-MTEB/CMedQAv1-reranking
+    metrics:
+    - type: map
+      value: 87.79521046311835
+    - type: mrr
+      value: 90.01547619047618
+    - type: main_score
+      value: 87.79521046311835
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB CMedQAv2
+      revision: None
+      split: test
+      type: C-MTEB/CMedQAv2-reranking
+    metrics:
+    - type: map
+      value: 87.89916670870878
+    - type: mrr
+      value: 89.92595238095238
+    - type: main_score
+      value: 87.89916670870878
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB CmedqaRetrieval 
+      revision: None
+      split: dev
+      type: C-MTEB/CmedqaRetrieval
+    metrics:
+    - type: map_at_1
+      value: 25.444
+    - type: map_at_10
+      value: 37.763999999999996
+    - type: map_at_100
+      value: 39.641999999999996
+    - type: map_at_1000
+      value: 39.756
+    - type: map_at_3
+      value: 33.742
+    - type: map_at_5
+      value: 35.906
+    - type: mrr_at_1
+      value: 38.71
+    - type: mrr_at_10
+      value: 46.744
+    - type: mrr_at_100
+      value: 47.745
+    - type: mrr_at_1000
+      value: 47.791
+    - type: mrr_at_3
+      value: 44.324000000000005
+    - type: mrr_at_5
+      value: 45.696
+    - type: ndcg_at_1
+      value: 38.71
+    - type: ndcg_at_10
+      value: 44.285000000000004
+    - type: ndcg_at_100
+      value: 51.69200000000001
+    - type: ndcg_at_1000
+      value: 53.669999999999995
+    - type: ndcg_at_3
+      value: 39.273
+    - type: ndcg_at_5
+      value: 41.254000000000005
+    - type: precision_at_1
+      value: 38.71
+    - type: precision_at_10
+      value: 9.825000000000001
+    - type: precision_at_100
+      value: 1.583
+    - type: precision_at_1000
+      value: 0.183
+    - type: precision_at_3
+      value: 22.197
+    - type: precision_at_5
+      value: 16.019
+    - type: recall_at_1
+      value: 25.444
+    - type: recall_at_10
+      value: 54.535999999999994
+    - type: recall_at_100
+      value: 85.307
+    - type: recall_at_1000
+      value: 98.473
+    - type: recall_at_3
+      value: 39.274
+    - type: recall_at_5
+      value: 45.580999999999996
+    - type: main_score
+      value: 44.285000000000004
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB Cmnli 
+      revision: None
+      split: validation
+      type: C-MTEB/CMNLI
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.58508719182201
+    - type: cos_sim_accuracy_threshold
+      value: 97.09511288861569
+    - type: cos_sim_ap
+      value: 95.12338246323735
+    - type: cos_sim_f1
+      value: 90.19211324570271
+    - type: cos_sim_f1_threshold
+      value: 97.02014138938755
+    - type: cos_sim_precision
+      value: 86.80795847750865
+    - type: cos_sim_recall
+      value: 93.85083002104278
+    - type: dot_accuracy
+      value: 89.58508719182201
+    - type: dot_accuracy_threshold
+      value: 97.0951128886157
+    - type: dot_ap
+      value: 95.13959275940286
+    - type: dot_f1
+      value: 90.19211324570271
+    - type: dot_f1_threshold
+      value: 97.02014138938755
+    - type: dot_precision
+      value: 86.80795847750865
+    - type: dot_recall
+      value: 93.85083002104278
+    - type: euclidean_accuracy
+      value: 89.58508719182201
+    - type: euclidean_accuracy_threshold
+      value: 24.103473235790947
+    - type: euclidean_ap
+      value: 95.12338246323735
+    - type: euclidean_f1
+      value: 90.19211324570271
+    - type: euclidean_f1_threshold
+      value: 24.412531977088996
+    - type: euclidean_precision
+      value: 86.80795847750865
+    - type: euclidean_recall
+      value: 93.85083002104278
+    - type: manhattan_accuracy
+      value: 89.57306073361396
+    - type: manhattan_accuracy_threshold
+      value: 729.1211254739587
+    - type: manhattan_ap
+      value: 95.12388319543341
+    - type: manhattan_f1
+      value: 90.13956654941563
+    - type: manhattan_f1_threshold
+      value: 733.155723492131
+    - type: manhattan_precision
+      value: 87.56613756613757
+    - type: manhattan_recall
+      value: 92.8688332943652
+    - type: max_accuracy
+      value: 89.58508719182201
+    - type: max_ap
+      value: 95.13959275940286
+    - type: max_f1
+      value: 90.19211324570271
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB CovidRetrieval 
+      revision: None
+      split: dev
+      type: C-MTEB/CovidRetrieval
+    metrics:
+    - type: map_at_1
+      value: 75.29
+    - type: map_at_10
+      value: 82.392
+    - type: map_at_100
+      value: 82.581
+    - type: map_at_1000
+      value: 82.585
+    - type: map_at_3
+      value: 80.88300000000001
+    - type: map_at_5
+      value: 81.71199999999999
+    - type: mrr_at_1
+      value: 75.553
+    - type: mrr_at_10
+      value: 82.422
+    - type: mrr_at_100
+      value: 82.6
+    - type: mrr_at_1000
+      value: 82.604
+    - type: mrr_at_3
+      value: 80.927
+    - type: mrr_at_5
+      value: 81.765
+    - type: ndcg_at_1
+      value: 75.44800000000001
+    - type: ndcg_at_10
+      value: 85.655
+    - type: ndcg_at_100
+      value: 86.435
+    - type: ndcg_at_1000
+      value: 86.541
+    - type: ndcg_at_3
+      value: 82.60300000000001
+    - type: ndcg_at_5
+      value: 84.062
+    - type: precision_at_1
+      value: 75.44800000000001
+    - type: precision_at_10
+      value: 9.663
+    - type: precision_at_100
+      value: 1.002
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 29.329
+    - type: precision_at_5
+      value: 18.314
+    - type: recall_at_1
+      value: 75.29
+    - type: recall_at_10
+      value: 95.838
+    - type: recall_at_100
+      value: 99.157
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 87.566
+    - type: recall_at_5
+      value: 90.991
+    - type: main_score
+      value: 85.655
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB DuRetrieval 
+      revision: None
+      split: dev
+      type: C-MTEB/DuRetrieval
+    metrics:
+    - type: map_at_1
+      value: 27.584999999999997
+    - type: map_at_10
+      value: 85.112
+    - type: map_at_100
+      value: 87.632
+    - type: map_at_1000
+      value: 87.654
+    - type: map_at_3
+      value: 59.504999999999995
+    - type: map_at_5
+      value: 75.029
+    - type: mrr_at_1
+      value: 93.30000000000001
+    - type: mrr_at_10
+      value: 95.44200000000001
+    - type: mrr_at_100
+      value: 95.498
+    - type: mrr_at_1000
+      value: 95.5
+    - type: mrr_at_3
+      value: 95.258
+    - type: mrr_at_5
+      value: 95.36099999999999
+    - type: ndcg_at_1
+      value: 93.30000000000001
+    - type: ndcg_at_10
+      value: 91.086
+    - type: ndcg_at_100
+      value: 93.089
+    - type: ndcg_at_1000
+      value: 93.297
+    - type: ndcg_at_3
+      value: 90.432
+    - type: ndcg_at_5
+      value: 89.361
+    - type: precision_at_1
+      value: 93.30000000000001
+    - type: precision_at_10
+      value: 43.21
+    - type: precision_at_100
+      value: 4.857
+    - type: precision_at_1000
+      value: 0.49
+    - type: precision_at_3
+      value: 81.0
+    - type: precision_at_5
+      value: 68.28999999999999
+    - type: recall_at_1
+      value: 27.584999999999997
+    - type: recall_at_10
+      value: 91.73599999999999
+    - type: recall_at_100
+      value: 98.648
+    - type: recall_at_1000
+      value: 99.751
+    - type: recall_at_3
+      value: 61.378
+    - type: recall_at_5
+      value: 78.672
+    - type: main_score
+      value: 91.086
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB EcomRetrieval 
+      revision: None
+      split: dev
+      type: C-MTEB/EcomRetrieval
+    metrics:
+    - type: map_at_1
+      value: 55.1
+    - type: map_at_10
+      value: 65.268
+    - type: map_at_100
+      value: 65.756
+    - type: map_at_1000
+      value: 65.765
+    - type: map_at_3
+      value: 63.132999999999996
+    - type: map_at_5
+      value: 64.25800000000001
+    - type: mrr_at_1
+      value: 55.1
+    - type: mrr_at_10
+      value: 65.268
+    - type: mrr_at_100
+      value: 65.756
+    - type: mrr_at_1000
+      value: 65.765
+    - type: mrr_at_3
+      value: 63.132999999999996
+    - type: mrr_at_5
+      value: 64.25800000000001
+    - type: ndcg_at_1
+      value: 55.1
+    - type: ndcg_at_10
+      value: 70.15599999999999
+    - type: ndcg_at_100
+      value: 72.368
+    - type: ndcg_at_1000
+      value: 72.635
+    - type: ndcg_at_3
+      value: 65.697
+    - type: ndcg_at_5
+      value: 67.741
+    - type: precision_at_1
+      value: 55.1
+    - type: precision_at_10
+      value: 8.55
+    - type: precision_at_100
+      value: 0.955
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 24.367
+    - type: precision_at_5
+      value: 15.620000000000001
+    - type: recall_at_1
+      value: 55.1
+    - type: recall_at_10
+      value: 85.5
+    - type: recall_at_100
+      value: 95.5
+    - type: recall_at_1000
+      value: 97.6
+    - type: recall_at_3
+      value: 73.1
+    - type: recall_at_5
+      value: 78.10000000000001
+    - type: main_score
+      value: 70.15599999999999
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB IFlyTek 
+      revision: None
+      split: validation
+      type: C-MTEB/IFlyTek-classification
+    metrics:
+    - type: accuracy
+      value: 52.743362831858406
+    - type: accuracy_stderr
+      value: 0.4449967616714387
+    - type: f1
+      value: 40.13427504900375
+    - type: f1_stderr
+      value: 0.17565290177989018
+    - type: main_score
+      value: 52.743362831858406
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB JDReview 
+      revision: None
+      split: test
+      type: C-MTEB/JDReview-classification
+    metrics:
+    - type: accuracy
+      value: 90.13133208255161
+    - type: accuracy_stderr
+      value: 0.9647249630155678
+    - type: ap
+      value: 62.848199712439765
+    - type: ap_stderr
+      value: 1.986859492917626
+    - type: f1
+      value: 85.48543445690254
+    - type: f1_stderr
+      value: 1.0490059319804828
+    - type: main_score
+      value: 90.13133208255161
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB LCQMC 
+      revision: None
+      split: test
+      type: C-MTEB/LCQMC
+    metrics:
+    - type: cosine_pearson
+      value: 77.75677384428634
+    - type: cosine_spearman
+      value: 78.86284859566986
+    - type: manhattan_pearson
+      value: 79.8032754323316
+    - type: manhattan_spearman
+      value: 78.85558562163624
+    - type: euclidean_pearson
+      value: 79.82552324704292
+    - type: euclidean_spearman
+      value: 78.86284859566986
+    - type: main_score
+      value: 78.86284859566986
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB MMarcoReranking 
+      revision: None
+      split: dev
+      type: C-MTEB/Mmarco-reranking
+    metrics:
+    - type: map
+      value: 30.737025407798523
+    - type: mrr
+      value: 29.26111111111111
+    - type: main_score
+      value: 30.737025407798523
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB MMarcoRetrieval 
+      revision: None
+      split: dev
+      type: C-MTEB/MMarcoRetrieval
+    metrics:
+    - type: map_at_1
+      value: 70.244
+    - type: map_at_10
+      value: 78.975
+    - type: map_at_100
+      value: 79.253
+    - type: map_at_1000
+      value: 79.26100000000001
+    - type: map_at_3
+      value: 77.363
+    - type: map_at_5
+      value: 78.364
+    - type: mrr_at_1
+      value: 72.521
+    - type: mrr_at_10
+      value: 79.514
+    - type: mrr_at_100
+      value: 79.75
+    - type: mrr_at_1000
+      value: 79.757
+    - type: mrr_at_3
+      value: 78.095
+    - type: mrr_at_5
+      value: 78.987
+    - type: ndcg_at_1
+      value: 72.521
+    - type: ndcg_at_10
+      value: 82.395
+    - type: ndcg_at_100
+      value: 83.554
+    - type: ndcg_at_1000
+      value: 83.774
+    - type: ndcg_at_3
+      value: 79.341
+    - type: ndcg_at_5
+      value: 81.036
+    - type: precision_at_1
+      value: 72.521
+    - type: precision_at_10
+      value: 9.812
+    - type: precision_at_100
+      value: 1.038
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 29.694
+    - type: precision_at_5
+      value: 18.712999999999997
+    - type: recall_at_1
+      value: 70.244
+    - type: recall_at_10
+      value: 92.35
+    - type: recall_at_100
+      value: 97.419
+    - type: recall_at_1000
+      value: 99.16199999999999
+    - type: recall_at_3
+      value: 84.303
+    - type: recall_at_5
+      value: 88.325
+    - type: main_score
+      value: 82.395
+    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: 76.3752521856086
+    - type: accuracy_stderr
+      value: 1.3911220977886072
+    - type: f1
+      value: 73.38330839246518
+    - type: f1_stderr
+      value: 0.9864886479418102
+    - type: main_score
+      value: 76.3752521856086
+    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: 81.8022864828514
+    - type: accuracy_stderr
+      value: 1.4060452754762354
+    - type: f1
+      value: 80.85164585310973
+    - type: f1_stderr
+      value: 1.2664399398388577
+    - type: main_score
+      value: 81.8022864828514
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB MedicalRetrieval 
+      revision: None
+      split: dev
+      type: C-MTEB/MedicalRetrieval
+    metrics:
+    - type: map_at_1
+      value: 57.199999999999996
+    - type: map_at_10
+      value: 63.346999999999994
+    - type: map_at_100
+      value: 63.852
+    - type: map_at_1000
+      value: 63.88700000000001
+    - type: map_at_3
+      value: 61.967000000000006
+    - type: map_at_5
+      value: 62.66199999999999
+    - type: mrr_at_1
+      value: 57.3
+    - type: mrr_at_10
+      value: 63.397000000000006
+    - type: mrr_at_100
+      value: 63.902
+    - type: mrr_at_1000
+      value: 63.937
+    - type: mrr_at_3
+      value: 62.017
+    - type: mrr_at_5
+      value: 62.712
+    - type: ndcg_at_1
+      value: 57.199999999999996
+    - type: ndcg_at_10
+      value: 66.38300000000001
+    - type: ndcg_at_100
+      value: 69.267
+    - type: ndcg_at_1000
+      value: 70.233
+    - type: ndcg_at_3
+      value: 63.44499999999999
+    - type: ndcg_at_5
+      value: 64.71000000000001
+    - type: precision_at_1
+      value: 57.199999999999996
+    - type: precision_at_10
+      value: 7.6
+    - type: precision_at_100
+      value: 0.905
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 22.567
+    - type: precision_at_5
+      value: 14.16
+    - type: recall_at_1
+      value: 57.199999999999996
+    - type: recall_at_10
+      value: 76.0
+    - type: recall_at_100
+      value: 90.5
+    - type: recall_at_1000
+      value: 98.2
+    - type: recall_at_3
+      value: 67.7
+    - type: recall_at_5
+      value: 70.8
+    - type: main_score
+      value: 66.38300000000001
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB MultilingualSentiment 
+      revision: None
+      split: validation
+      type: C-MTEB/MultilingualSentiment-classification
+    metrics:
+    - type: accuracy
+      value: 80.12333333333335
+    - type: accuracy_stderr
+      value: 0.31377628265303376
+    - type: f1
+      value: 80.26166732998303
+    - type: f1_stderr
+      value: 0.2836457609943486
+    - type: main_score
+      value: 80.12333333333335
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB Ocnli 
+      revision: None
+      split: validation
+      type: C-MTEB/OCNLI
+    metrics:
+    - type: cos_sim_accuracy
+      value: 87.54737412019492
+    - type: cos_sim_accuracy_threshold
+      value: 96.99121475650863
+    - type: cos_sim_ap
+      value: 91.71816430648396
+    - type: cos_sim_f1
+      value: 88.27655310621243
+    - type: cos_sim_f1_threshold
+      value: 96.8697507135398
+    - type: cos_sim_precision
+      value: 83.98474737845567
+    - type: cos_sim_recall
+      value: 93.03062302006336
+    - type: dot_accuracy
+      value: 87.54737412019492
+    - type: dot_accuracy_threshold
+      value: 96.99121475650863
+    - type: dot_ap
+      value: 91.71816430648396
+    - type: dot_f1
+      value: 88.27655310621243
+    - type: dot_f1_threshold
+      value: 96.86975071353979
+    - type: dot_precision
+      value: 83.98474737845567
+    - type: dot_recall
+      value: 93.03062302006336
+    - type: euclidean_accuracy
+      value: 87.54737412019492
+    - type: euclidean_accuracy_threshold
+      value: 24.530733065589622
+    - type: euclidean_ap
+      value: 91.71816430648396
+    - type: euclidean_f1
+      value: 88.27655310621243
+    - type: euclidean_f1_threshold
+      value: 25.020988098238107
+    - type: euclidean_precision
+      value: 83.98474737845567
+    - type: euclidean_recall
+      value: 93.03062302006336
+    - type: manhattan_accuracy
+      value: 87.27666486193829
+    - type: manhattan_accuracy_threshold
+      value: 752.4905438529156
+    - type: manhattan_ap
+      value: 91.70647280240597
+    - type: manhattan_f1
+      value: 88.08920425747591
+    - type: manhattan_f1_threshold
+      value: 752.4905438529156
+    - type: manhattan_precision
+      value: 84.69785575048732
+    - type: manhattan_recall
+      value: 91.76346356916578
+    - type: max_accuracy
+      value: 87.54737412019492
+    - type: max_ap
+      value: 91.71816430648396
+    - type: max_f1
+      value: 88.27655310621243
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB OnlineShopping 
+      revision: None
+      split: test
+      type: C-MTEB/OnlineShopping-classification
+    metrics:
+    - type: accuracy
+      value: 94.46999999999998
+    - type: accuracy_stderr
+      value: 0.2865309756378883
+    - type: ap
+      value: 93.00417328431348
+    - type: ap_stderr
+      value: 0.5383352662551945
+    - type: f1
+      value: 94.4618263222835
+    - type: f1_stderr
+      value: 0.2840342094212124
+    - type: main_score
+      value: 94.46999999999998
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB PAWSX 
+      revision: None
+      split: test
+      type: C-MTEB/PAWSX
+    metrics:
+    - type: cosine_pearson
+      value: 46.85211982536296
+    - type: cosine_spearman
+      value: 49.917839688145996
+    - type: manhattan_pearson
+      value: 49.66820248148123
+    - type: manhattan_spearman
+      value: 49.94013555794742
+    - type: euclidean_pearson
+      value: 49.63608491973345
+    - type: euclidean_spearman
+      value: 49.917839688145996
+    - type: main_score
+      value: 49.917839688145996
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB QBQTC 
+      revision: None
+      split: test
+      type: C-MTEB/QBQTC
+    metrics:
+    - type: cosine_pearson
+      value: 55.18355221701257
+    - type: cosine_spearman
+      value: 54.67390932826382
+    - type: manhattan_pearson
+      value: 53.32847494683504
+    - type: manhattan_spearman
+      value: 54.61660160532041
+    - type: euclidean_pearson
+      value: 53.405599174765364
+    - type: euclidean_spearman
+      value: 54.67390932826382
+    - type: main_score
+      value: 54.67390932826382
+    task:
+      type: STS
+  - dataset:
+      config: zh
+      name: MTEB STS22 (zh)
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 67.89319522460808
+    - type: cosine_spearman
+      value: 68.98524514928238
+    - type: manhattan_pearson
+      value: 67.65257700660463
+    - type: manhattan_spearman
+      value: 69.17199742136434
+    - type: euclidean_pearson
+      value: 67.52535570217756
+    - type: euclidean_spearman
+      value: 68.98524514928238
+    - type: main_score
+      value: 68.98524514928238
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB STSB 
+      revision: None
+      split: test
+      type: C-MTEB/STSB
+    metrics:
+    - type: cosine_pearson
+      value: 75.4871803618505
+    - type: cosine_spearman
+      value: 76.17471665593993
+    - type: manhattan_pearson
+      value: 75.73597640243183
+    - type: manhattan_spearman
+      value: 76.20048941210949
+    - type: euclidean_pearson
+      value: 75.66172628182565
+    - type: euclidean_spearman
+      value: 76.17471665593993
+    - type: main_score
+      value: 76.17471665593993
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB T2Reranking 
+      revision: None
+      split: dev
+      type: C-MTEB/T2Reranking
+    metrics:
+    - type: map
+      value: 67.45036855302303
+    - type: mrr
+      value: 78.15107441080697
+    - type: main_score
+      value: 67.45036855302303
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB T2Retrieval 
+      revision: None
+      split: dev
+      type: C-MTEB/T2Retrieval
+    metrics:
+    - type: map_at_1
+      value: 28.094
+    - type: map_at_10
+      value: 79.367
+    - type: map_at_100
+      value: 82.89800000000001
+    - type: map_at_1000
+      value: 82.953
+    - type: map_at_3
+      value: 55.782
+    - type: map_at_5
+      value: 68.667
+    - type: mrr_at_1
+      value: 91.237
+    - type: mrr_at_10
+      value: 93.399
+    - type: mrr_at_100
+      value: 93.479
+    - type: mrr_at_1000
+      value: 93.482
+    - type: mrr_at_3
+      value: 93.029
+    - type: mrr_at_5
+      value: 93.273
+    - type: ndcg_at_1
+      value: 91.237
+    - type: ndcg_at_10
+      value: 86.368
+    - type: ndcg_at_100
+      value: 89.637
+    - type: ndcg_at_1000
+      value: 90.16300000000001
+    - type: ndcg_at_3
+      value: 87.691
+    - type: ndcg_at_5
+      value: 86.462
+    - type: precision_at_1
+      value: 91.237
+    - type: precision_at_10
+      value: 42.841
+    - type: precision_at_100
+      value: 5.047
+    - type: precision_at_1000
+      value: 0.517
+    - type: precision_at_3
+      value: 76.708
+    - type: precision_at_5
+      value: 64.428
+    - type: recall_at_1
+      value: 28.094
+    - type: recall_at_10
+      value: 85.181
+    - type: recall_at_100
+      value: 95.953
+    - type: recall_at_1000
+      value: 98.63
+    - type: recall_at_3
+      value: 57.267999999999994
+    - type: recall_at_5
+      value: 71.75399999999999
+    - type: main_score
+      value: 86.368
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB TNews 
+      revision: None
+      split: validation
+      type: C-MTEB/TNews-classification
+    metrics:
+    - type: accuracy
+      value: 55.482
+    - type: accuracy_stderr
+      value: 0.3268577672321692
+    - type: f1
+      value: 53.57211848235611
+    - type: f1_stderr
+      value: 0.3511138517262321
+    - type: main_score
+      value: 55.482
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB ThuNewsClusteringP2P 
+      revision: None
+      split: test
+      type: C-MTEB/ThuNewsClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 79.44895384385426
+    - type: v_measure_std
+      value: 2.315777338929376
+    - type: main_score
+      value: 79.44895384385426
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB ThuNewsClusteringS2S 
+      revision: None
+      split: test
+      type: C-MTEB/ThuNewsClusteringS2S
+    metrics:
+    - type: v_measure
+      value: 76.95904984506356
+    - type: v_measure_std
+      value: 2.244801218820472
+    - type: main_score
+      value: 76.95904984506356
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB VideoRetrieval 
+      revision: None
+      split: dev
+      type: C-MTEB/VideoRetrieval
+    metrics:
+    - type: map_at_1
+      value: 65.60000000000001
+    - type: map_at_10
+      value: 75.24499999999999
+    - type: map_at_100
+      value: 75.51
+    - type: map_at_1000
+      value: 75.519
+    - type: map_at_3
+      value: 73.68299999999999
+    - type: map_at_5
+      value: 74.638
+    - type: mrr_at_1
+      value: 65.60000000000001
+    - type: mrr_at_10
+      value: 75.24499999999999
+    - type: mrr_at_100
+      value: 75.51
+    - type: mrr_at_1000
+      value: 75.519
+    - type: mrr_at_3
+      value: 73.68299999999999
+    - type: mrr_at_5
+      value: 74.638
+    - type: ndcg_at_1
+      value: 65.60000000000001
+    - type: ndcg_at_10
+      value: 79.338
+    - type: ndcg_at_100
+      value: 80.585
+    - type: ndcg_at_1000
+      value: 80.772
+    - type: ndcg_at_3
+      value: 76.189
+    - type: ndcg_at_5
+      value: 77.915
+    - type: precision_at_1
+      value: 65.60000000000001
+    - type: precision_at_10
+      value: 9.19
+    - type: precision_at_100
+      value: 0.976
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 27.800000000000004
+    - type: precision_at_5
+      value: 17.52
+    - type: recall_at_1
+      value: 65.60000000000001
+    - type: recall_at_10
+      value: 91.9
+    - type: recall_at_100
+      value: 97.6
+    - type: recall_at_1000
+      value: 99.0
+    - type: recall_at_3
+      value: 83.39999999999999
+    - type: recall_at_5
+      value: 87.6
+    - type: main_score
+      value: 79.338
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB Waimai 
+      revision: None
+      split: test
+      type: C-MTEB/waimai-classification
+    metrics:
+    - type: accuracy
+      value: 89.9
+    - type: accuracy_stderr
+      value: 0.7861297602813425
+    - type: ap
+      value: 76.33068327298966
+    - type: ap_stderr
+      value: 1.6404446239337744
+    - type: f1
+      value: 88.66175970131309
+    - type: f1_stderr
+      value: 0.7269675835542363
+    - type: main_score
+      value: 89.9
+    task:
+      type: Classification
+tags:
+- mteb
+---
+# Quark-Emb-1.5B 
+
+- Chinese Text Embedding Model developed by Alibaba Quark-LLM Team. Details will be published later.