metadata
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
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
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
- 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
- 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
- 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
- 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
- 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-llm-embedding-8B
- Chinese Text Embedding Model developed by Alibaba Quark-LLM Team. Details will be published later.