license:mit model-index region:us
---
license: mit
# tags:
# - mteb
model-index:
- name: hui-embedding
  results:
  - task:
      type: STS
    dataset:
      type: C-MTEB/AFQMC
      name: MTEB AFQMC
      config: default
      split: validation
      revision: b44c3b011063adb25877c13823db83bb193913c4
    metrics:
    - type: cos_sim_pearson
      value: 49.378812776509605
    - type: cos_sim_spearman
      value: 54.847928348721375
    - type: euclidean_pearson
      value: 53.04925208393059
    - type: euclidean_spearman
      value: 54.847928348721375
    - type: manhattan_pearson
      value: 53.06246682259037
    - type: manhattan_spearman
      value: 54.87201329143453
  - task:
      type: STS
    dataset:
      type: C-MTEB/ATEC
      name: MTEB ATEC
      config: default
      split: test
      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
    metrics:
    - type: cos_sim_pearson
      value: 48.1600594371303
    - type: cos_sim_spearman
      value: 55.1323822895328
    - type: euclidean_pearson
      value: 55.4361186282293
    - type: euclidean_spearman
      value: 55.13238454056627
    - type: manhattan_pearson
      value: 55.41462879819177
    - type: manhattan_spearman
      value: 55.13393260953372
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (zh)
      config: zh
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 46.715999999999994
    - type: f1
      value: 45.031952047233084
  - task:
      type: STS
    dataset:
      type: C-MTEB/BQ
      name: MTEB BQ
      config: default
      split: test
      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
    metrics:
    - type: cos_sim_pearson
      value: 63.51780001831422
    - type: cos_sim_spearman
      value: 65.57016807800922
    - type: euclidean_pearson
      value: 64.0519397443374
    - type: euclidean_spearman
      value: 65.57018193343218
    - type: manhattan_pearson
      value: 63.95723624728276
    - type: manhattan_spearman
      value: 65.48557125105762
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/CLSClusteringP2P
      name: MTEB CLSClusteringP2P
      config: default
      split: test
      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
    metrics:
    - type: v_measure
      value: 42.5667507726515
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/CLSClusteringS2S
      name: MTEB CLSClusteringS2S
      config: default
      split: test
      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
    metrics:
    - type: v_measure
      value: 40.510799373442566
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/CMedQAv1-reranking
      name: MTEB CMedQAv1
      config: default
      split: test
      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
    metrics:
    - type: map
      value: 87.12221041649349
    - type: mrr
      value: 89.57150793650794
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/CMedQAv2-reranking
      name: MTEB CMedQAv2
      config: default
      split: test
      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
    metrics:
    - type: map
      value: 87.59790061886422
    - type: mrr
      value: 90.19202380952382
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/CmedqaRetrieval
      name: MTEB CmedqaRetrieval
      config: default
      split: dev
      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
    metrics:
    - type: map_at_1
      value: 25.22
    - type: map_at_10
      value: 37.611
    - type: map_at_100
      value: 39.505
    - type: map_at_1000
      value: 39.617999999999995
    - type: map_at_3
      value: 33.387
    - type: map_at_5
      value: 35.776
    - type: mrr_at_1
      value: 38.385000000000005
    - type: mrr_at_10
      value: 46.487
    - type: mrr_at_100
      value: 47.508
    - type: mrr_at_1000
      value: 47.55
    - type: mrr_at_3
      value: 43.897999999999996
    - type: mrr_at_5
      value: 45.371
    - type: ndcg_at_1
      value: 38.385000000000005
    - type: ndcg_at_10
      value: 44.232
    - type: ndcg_at_100
      value: 51.639
    - type: ndcg_at_1000
      value: 53.561
    - type: ndcg_at_3
      value: 38.855000000000004
    - type: ndcg_at_5
      value: 41.159
    - type: precision_at_1
      value: 38.385000000000005
    - type: precision_at_10
      value: 9.817
    - type: precision_at_100
      value: 1.58
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 21.88
    - type: precision_at_5
      value: 15.969
    - type: recall_at_1
      value: 25.22
    - type: recall_at_10
      value: 54.909
    - type: recall_at_100
      value: 85.469
    - type: recall_at_1000
      value: 98.18599999999999
    - type: recall_at_3
      value: 38.834999999999994
    - type: recall_at_5
      value: 45.87
  - task:
      type: PairClassification
    dataset:
      type: C-MTEB/CMNLI
      name: MTEB Cmnli
      config: default
      split: validation
      revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
    metrics:
    - type: cos_sim_accuracy
      value: 83.22309079975948
    - type: cos_sim_ap
      value: 89.94908564295963
    - type: cos_sim_f1
      value: 84.3951165371809
    - type: cos_sim_precision
      value: 80.32960067610395
    - type: cos_sim_recall
      value: 88.89408463876549
    - type: dot_accuracy
      value: 83.22309079975948
    - type: dot_ap
      value: 89.95437246807009
    - type: dot_f1
      value: 84.3951165371809
    - type: dot_precision
      value: 80.32960067610395
    - type: dot_recall
      value: 88.89408463876549
    - type: euclidean_accuracy
      value: 83.22309079975948
    - type: euclidean_ap
      value: 89.94908838738027
    - type: euclidean_f1
      value: 84.3951165371809
    - type: euclidean_precision
      value: 80.32960067610395
    - type: euclidean_recall
      value: 88.89408463876549
    - type: manhattan_accuracy
      value: 83.23511725796753
    - type: manhattan_ap
      value: 89.94576222197006
    - type: manhattan_f1
      value: 84.44100409156253
    - type: manhattan_precision
      value: 80.10910616869492
    - type: manhattan_recall
      value: 89.26817862988075
    - type: max_accuracy
      value: 83.23511725796753
    - type: max_ap
      value: 89.95437246807009
    - type: max_f1
      value: 84.44100409156253
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/CovidRetrieval
      name: MTEB CovidRetrieval
      config: default
      split: dev
      revision: 1271c7809071a13532e05f25fb53511ffce77117
    metrics:
    - type: map_at_1
      value: 76.87
    - type: map_at_10
      value: 84.513
    - type: map_at_100
      value: 84.616
    - type: map_at_1000
      value: 84.61800000000001
    - type: map_at_3
      value: 83.127
    - type: map_at_5
      value: 83.99600000000001
    - type: mrr_at_1
      value: 77.239
    - type: mrr_at_10
      value: 84.583
    - type: mrr_at_100
      value: 84.68
    - type: mrr_at_1000
      value: 84.681
    - type: mrr_at_3
      value: 83.281
    - type: mrr_at_5
      value: 84.097
    - type: ndcg_at_1
      value: 77.134
    - type: ndcg_at_10
      value: 87.71600000000001
    - type: ndcg_at_100
      value: 88.172
    - type: ndcg_at_1000
      value: 88.211
    - type: ndcg_at_3
      value: 84.993
    - type: ndcg_at_5
      value: 86.519
    - type: precision_at_1
      value: 77.134
    - type: precision_at_10
      value: 9.852
    - type: precision_at_100
      value: 1.006
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 30.313000000000002
    - type: precision_at_5
      value: 18.945999999999998
    - type: recall_at_1
      value: 76.87
    - type: recall_at_10
      value: 97.524
    - type: recall_at_100
      value: 99.579
    - type: recall_at_1000
      value: 99.895
    - type: recall_at_3
      value: 90.227
    - type: recall_at_5
      value: 93.888
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/DuRetrieval
      name: MTEB DuRetrieval
      config: default
      split: dev
      revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
    metrics:
    - type: map_at_1
      value: 25.941
    - type: map_at_10
      value: 78.793
    - type: map_at_100
      value: 81.583
    - type: map_at_1000
      value: 81.63
    - type: map_at_3
      value: 54.767999999999994
    - type: map_at_5
      value: 69.16499999999999
    - type: mrr_at_1
      value: 90.45
    - type: mrr_at_10
      value: 93.401
    - type: mrr_at_100
      value: 93.452
    - type: mrr_at_1000
      value: 93.45599999999999
    - type: mrr_at_3
      value: 93.10000000000001
    - type: mrr_at_5
      value: 93.27499999999999
    - type: ndcg_at_1
      value: 90.45
    - type: ndcg_at_10
      value: 86.433
    - type: ndcg_at_100
      value: 89.287
    - type: ndcg_at_1000
      value: 89.74600000000001
    - type: ndcg_at_3
      value: 85.64500000000001
    - type: ndcg_at_5
      value: 84.444
    - type: precision_at_1
      value: 90.45
    - type: precision_at_10
      value: 41.185
    - type: precision_at_100
      value: 4.761
    - type: precision_at_1000
      value: 0.48700000000000004
    - type: precision_at_3
      value: 76.617
    - type: precision_at_5
      value: 64.68
    - type: recall_at_1
      value: 25.941
    - type: recall_at_10
      value: 87.393
    - type: recall_at_100
      value: 96.54
    - type: recall_at_1000
      value: 98.956
    - type: recall_at_3
      value: 56.976000000000006
    - type: recall_at_5
      value: 73.714
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/EcomRetrieval
      name: MTEB EcomRetrieval
      config: default
      split: dev
      revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
    metrics:
    - type: map_at_1
      value: 52.900000000000006
    - type: map_at_10
      value: 63.139
    - type: map_at_100
      value: 63.62799999999999
    - type: map_at_1000
      value: 63.639
    - type: map_at_3
      value: 60.817
    - type: map_at_5
      value: 62.197
    - type: mrr_at_1
      value: 52.900000000000006
    - type: mrr_at_10
      value: 63.139
    - type: mrr_at_100
      value: 63.62799999999999
    - type: mrr_at_1000
      value: 63.639
    - type: mrr_at_3
      value: 60.817
    - type: mrr_at_5
      value: 62.197
    - type: ndcg_at_1
      value: 52.900000000000006
    - type: ndcg_at_10
      value: 68.038
    - type: ndcg_at_100
      value: 70.41199999999999
    - type: ndcg_at_1000
      value: 70.717
    - type: ndcg_at_3
      value: 63.287000000000006
    - type: ndcg_at_5
      value: 65.766
    - type: precision_at_1
      value: 52.900000000000006
    - type: precision_at_10
      value: 8.34
    - type: precision_at_100
      value: 0.9450000000000001
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 23.467
    - type: precision_at_5
      value: 15.28
    - type: recall_at_1
      value: 52.900000000000006
    - type: recall_at_10
      value: 83.39999999999999
    - type: recall_at_100
      value: 94.5
    - type: recall_at_1000
      value: 96.89999999999999
    - type: recall_at_3
      value: 70.39999999999999
    - type: recall_at_5
      value: 76.4
  - task:
      type: Classification
    dataset:
      type: C-MTEB/IFlyTek-classification
      name: MTEB IFlyTek
      config: default
      split: validation
      revision: 421605374b29664c5fc098418fe20ada9bd55f8a
    metrics:
    - type: accuracy
      value: 49.74220854174683
    - type: f1
      value: 38.01254780588847
  - task:
      type: Classification
    dataset:
      type: C-MTEB/JDReview-classification
      name: MTEB JDReview
      config: default
      split: test
      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
    metrics:
    - type: accuracy
      value: 86.73545966228893
    - type: ap
      value: 55.72394235169542
    - type: f1
      value: 81.58550390953492
  - task:
      type: STS
    dataset:
      type: C-MTEB/LCQMC
      name: MTEB LCQMC
      config: default
      split: test
      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
    metrics:
    - type: cos_sim_pearson
      value: 69.96738688541858
    - type: cos_sim_spearman
      value: 75.54733864118711
    - type: euclidean_pearson
      value: 74.62650665031346
    - type: euclidean_spearman
      value: 75.54734085635552
    - type: manhattan_pearson
      value: 74.60961858490293
    - type: manhattan_spearman
      value: 75.5274896144882
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/Mmarco-reranking
      name: MTEB MMarcoReranking
      config: default
      split: dev
      revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6
    metrics:
    - type: map
      value: 28.07658854954957
    - type: mrr
      value: 26.98015873015873
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/MMarcoRetrieval
      name: MTEB MMarcoRetrieval
      config: default
      split: dev
      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
    metrics:
    - type: map_at_1
      value: 65.566
    - type: map_at_10
      value: 74.75699999999999
    - type: map_at_100
      value: 75.071
    - type: map_at_1000
      value: 75.08500000000001
    - type: map_at_3
      value: 72.965
    - type: map_at_5
      value: 74.146
    - type: mrr_at_1
      value: 67.808
    - type: mrr_at_10
      value: 75.42999999999999
    - type: mrr_at_100
      value: 75.696
    - type: mrr_at_1000
      value: 75.708
    - type: mrr_at_3
      value: 73.902
    - type: mrr_at_5
      value: 74.902
    - type: ndcg_at_1
      value: 67.808
    - type: ndcg_at_10
      value: 78.469
    - type: ndcg_at_100
      value: 79.886
    - type: ndcg_at_1000
      value: 80.257
    - type: ndcg_at_3
      value: 75.115
    - type: ndcg_at_5
      value: 77.086
    - type: precision_at_1
      value: 67.808
    - type: precision_at_10
      value: 9.474
    - type: precision_at_100
      value: 1.019
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 28.266000000000002
    - type: precision_at_5
      value: 18.014
    - type: recall_at_1
      value: 65.566
    - type: recall_at_10
      value: 89.193
    - type: recall_at_100
      value: 95.64399999999999
    - type: recall_at_1000
      value: 98.541
    - type: recall_at_3
      value: 80.41199999999999
    - type: recall_at_5
      value: 85.056
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (zh-CN)
      config: zh-CN
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 72.85810356422327
    - type: f1
      value: 70.24900138264265
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (zh-CN)
      config: zh-CN
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 75.47074646940149
    - type: f1
      value: 75.02944928791243
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/MedicalRetrieval
      name: MTEB MedicalRetrieval
      config: default
      split: dev
      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
    metrics:
    - type: map_at_1
      value: 53.300000000000004
    - type: map_at_10
      value: 60.086
    - type: map_at_100
      value: 60.633
    - type: map_at_1000
      value: 60.67399999999999
    - type: map_at_3
      value: 58.567
    - type: map_at_5
      value: 59.44199999999999
    - type: mrr_at_1
      value: 53.400000000000006
    - type: mrr_at_10
      value: 60.143
    - type: mrr_at_100
      value: 60.69799999999999
    - type: mrr_at_1000
      value: 60.739
    - type: mrr_at_3
      value: 58.633
    - type: mrr_at_5
      value: 59.508
    - type: ndcg_at_1
      value: 53.300000000000004
    - type: ndcg_at_10
      value: 63.388
    - type: ndcg_at_100
      value: 66.257
    - type: ndcg_at_1000
      value: 67.419
    - type: ndcg_at_3
      value: 60.224
    - type: ndcg_at_5
      value: 61.794000000000004
    - type: precision_at_1
      value: 53.300000000000004
    - type: precision_at_10
      value: 7.380000000000001
    - type: precision_at_100
      value: 0.877
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 21.667
    - type: precision_at_5
      value: 13.76
    - type: recall_at_1
      value: 53.300000000000004
    - type: recall_at_10
      value: 73.8
    - type: recall_at_100
      value: 87.7
    - type: recall_at_1000
      value: 97.0
    - type: recall_at_3
      value: 65.0
    - type: recall_at_5
      value: 68.8
  - task:
      type: Classification
    dataset:
      type: C-MTEB/MultilingualSentiment-classification
      name: MTEB MultilingualSentiment
      config: default
      split: validation
      revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
    metrics:
    - type: accuracy
      value: 76.28000000000002
    - type: f1
      value: 76.31632893766579
  - task:
      type: PairClassification
    dataset:
      type: C-MTEB/OCNLI
      name: MTEB Ocnli
      config: default
      split: validation
      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
    metrics:
    - type: cos_sim_accuracy
      value: 78.72225230102869
    - type: cos_sim_ap
      value: 80.64016185061472
    - type: cos_sim_f1
      value: 80.52190121155638
    - type: cos_sim_precision
      value: 72.06005004170142
    - type: cos_sim_recall
      value: 91.23548046462513
    - type: dot_accuracy
      value: 78.72225230102869
    - type: dot_ap
      value: 80.64030954198267
    - type: dot_f1
      value: 80.52190121155638
    - type: dot_precision
      value: 72.06005004170142
    - type: dot_recall
      value: 91.23548046462513
    - type: euclidean_accuracy
      value: 78.72225230102869
    - type: euclidean_ap
      value: 80.64016185061472
    - type: euclidean_f1
      value: 80.52190121155638
    - type: euclidean_precision
      value: 72.06005004170142
    - type: euclidean_recall
      value: 91.23548046462513
    - type: manhattan_accuracy
      value: 78.18083378451544
    - type: manhattan_ap
      value: 80.52168370151603
    - type: manhattan_f1
      value: 80.43684710351377
    - type: manhattan_precision
      value: 73.0802415875755
    - type: manhattan_recall
      value: 89.44033790918691
    - type: max_accuracy
      value: 78.72225230102869
    - type: max_ap
      value: 80.64030954198267
    - type: max_f1
      value: 80.52190121155638
  - task:
      type: Classification
    dataset:
      type: C-MTEB/OnlineShopping-classification
      name: MTEB OnlineShopping
      config: default
      split: test
      revision: e610f2ebd179a8fda30ae534c3878750a96db120
    metrics:
    - type: accuracy
      value: 92.50999999999999
    - type: ap
      value: 90.6813824215301
    - type: f1
      value: 92.50242491859119
  - task:
      type: STS
    dataset:
      type: C-MTEB/PAWSX
      name: MTEB PAWSX
      config: default
      split: test
      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
    metrics:
    - type: cos_sim_pearson
      value: 33.62875118995766
    - type: cos_sim_spearman
      value: 37.89501991717997
    - type: euclidean_pearson
      value: 38.11011221831966
    - type: euclidean_spearman
      value: 37.895526338330484
    - type: manhattan_pearson
      value: 38.116858432886445
    - type: manhattan_spearman
      value: 37.88106872717212
  - task:
      type: STS
    dataset:
      type: C-MTEB/QBQTC
      name: MTEB QBQTC
      config: default
      split: test
      revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
    metrics:
    - type: cos_sim_pearson
      value: 32.1385659529461
    - type: cos_sim_spearman
      value: 33.68856769791845
    - type: euclidean_pearson
      value: 32.15616490172132
    - type: euclidean_spearman
      value: 33.68858640049767
    - type: manhattan_pearson
      value: 32.14550781906868
    - type: manhattan_spearman
      value: 33.65866728414211
  - task:
      type: STS
    dataset:
      type: mteb/sts22-crosslingual-sts
      name: MTEB STS22 (zh)
      config: zh
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 63.64041828778335
    - type: cos_sim_spearman
      value: 64.3174530347361
    - type: euclidean_pearson
      value: 63.479188950744536
    - type: euclidean_spearman
      value: 64.3174530347361
    - type: manhattan_pearson
      value: 64.39947888986349
    - type: manhattan_spearman
      value: 64.85543965969501
  - task:
      type: STS
    dataset:
      type: C-MTEB/STSB
      name: MTEB STSB
      config: default
      split: test
      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
    metrics:
    - type: cos_sim_pearson
      value: 79.7474147570934
    - type: cos_sim_spearman
      value: 81.18400577201275
    - type: euclidean_pearson
      value: 80.94389968174902
    - type: euclidean_spearman
      value: 81.1838334524369
    - type: manhattan_pearson
      value: 80.88029725713798
    - type: manhattan_spearman
      value: 81.12169479476515
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/T2Reranking
      name: MTEB T2Reranking
      config: default
      split: dev
      revision: 76631901a18387f85eaa53e5450019b87ad58ef9
    metrics:
    - type: map
      value: 66.59735366130352
    - type: mrr
      value: 76.42600563132046
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/T2Retrieval
      name: MTEB T2Retrieval
      config: default
      split: dev
      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
    metrics:
    - type: map_at_1
      value: 28.819
    - type: map_at_10
      value: 77.486
    - type: map_at_100
      value: 81.14
    - type: map_at_1000
      value: 81.21300000000001
    - type: map_at_3
      value: 55.432
    - type: map_at_5
      value: 67.486
    - type: mrr_at_1
      value: 91.364
    - type: mrr_at_10
      value: 94.059
    - type: mrr_at_100
      value: 94.118
    - type: mrr_at_1000
      value: 94.119
    - type: mrr_at_3
      value: 93.705
    - type: mrr_at_5
      value: 93.928
    - type: ndcg_at_1
      value: 91.364
    - type: ndcg_at_10
      value: 85.446
    - type: ndcg_at_100
      value: 89.10900000000001
    - type: ndcg_at_1000
      value: 89.75
    - type: ndcg_at_3
      value: 87.259
    - type: ndcg_at_5
      value: 85.658
    - type: precision_at_1
      value: 91.364
    - type: precision_at_10
      value: 41.525
    - type: precision_at_100
      value: 4.989
    - type: precision_at_1000
      value: 0.516
    - type: precision_at_3
      value: 75.44999999999999
    - type: precision_at_5
      value: 62.773999999999994
    - type: recall_at_1
      value: 28.819
    - type: recall_at_10
      value: 84.20400000000001
    - type: recall_at_100
      value: 95.773
    - type: recall_at_1000
      value: 98.79
    - type: recall_at_3
      value: 57.281000000000006
    - type: recall_at_5
      value: 71.06099999999999
  - task:
      type: Classification
    dataset:
      type: C-MTEB/TNews-classification
      name: MTEB TNews
      config: default
      split: validation
      revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
    metrics:
    - type: accuracy
      value: 52.16399999999999
    - type: f1
      value: 50.49861014604211
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/ThuNewsClusteringP2P
      name: MTEB ThuNewsClusteringP2P
      config: default
      split: test
      revision: 5798586b105c0434e4f0fe5e767abe619442cf93
    metrics:
    - type: v_measure
      value: 70.29645586740038
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/ThuNewsClusteringS2S
      name: MTEB ThuNewsClusteringS2S
      config: default
      split: test
      revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
    metrics:
    - type: v_measure
      value: 62.99298994761416
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/VideoRetrieval
      name: MTEB VideoRetrieval
      config: default
      split: dev
      revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
    metrics:
    - type: map_at_1
      value: 60.099999999999994
    - type: map_at_10
      value: 69.404
    - type: map_at_100
      value: 69.85900000000001
    - type: map_at_1000
      value: 69.87299999999999
    - type: map_at_3
      value: 67.80000000000001
    - type: map_at_5
      value: 68.755
    - type: mrr_at_1
      value: 60.099999999999994
    - type: mrr_at_10
      value: 69.404
    - type: mrr_at_100
      value: 69.85900000000001
    - type: mrr_at_1000
      value: 69.87299999999999
    - type: mrr_at_3
      value: 67.80000000000001
    - type: mrr_at_5
      value: 68.755
    - type: ndcg_at_1
      value: 60.099999999999994
    - type: ndcg_at_10
      value: 73.624
    - type: ndcg_at_100
      value: 75.763
    - type: ndcg_at_1000
      value: 76.077
    - type: ndcg_at_3
      value: 70.316
    - type: ndcg_at_5
      value: 72.063
    - type: precision_at_1
      value: 60.099999999999994
    - type: precision_at_10
      value: 8.67
    - type: precision_at_100
      value: 0.9650000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 25.867
    - type: precision_at_5
      value: 16.38
    - type: recall_at_1
      value: 60.099999999999994
    - type: recall_at_10
      value: 86.7
    - type: recall_at_100
      value: 96.5
    - type: recall_at_1000
      value: 98.9
    - type: recall_at_3
      value: 77.60000000000001
    - type: recall_at_5
      value: 81.89999999999999
  - task:
      type: Classification
    dataset:
      type: C-MTEB/waimai-classification
      name: MTEB Waimai
      config: default
      split: test
      revision: 339287def212450dcaa9df8c22bf93e9980c7023
    metrics:
    - type: accuracy
      value: 88.36
    - type: ap
      value: 73.25144216855439
    - type: f1
      value: 86.75076261442027
---
