metadata
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
- 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
- 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
- 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
- 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-llm-embedding-1.5B
- Chinese Text Embedding Model developed by Alibaba Quark-LLM Team. Details will be published later.