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metadata
tags:
  - mteb
model-index:
  - name: tao
    results:
      - task:
          type: STS
        dataset:
          type: C-MTEB/AFQMC
          name: MTEB AFQMC
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 47.33752515292192
          - type: cos_sim_spearman
            value: 49.940772056837176
          - type: euclidean_pearson
            value: 48.12147487857213
          - type: euclidean_spearman
            value: 49.9407519488174
          - type: manhattan_pearson
            value: 48.07550286372865
          - type: manhattan_spearman
            value: 49.89535645392862
      - task:
          type: STS
        dataset:
          type: C-MTEB/ATEC
          name: MTEB ATEC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 50.976865711125626
          - type: cos_sim_spearman
            value: 53.113084748593465
          - type: euclidean_pearson
            value: 55.1209592747571
          - type: euclidean_spearman
            value: 53.11308362230699
          - type: manhattan_pearson
            value: 55.09799309322416
          - type: manhattan_spearman
            value: 53.108059998577076
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (zh)
          config: zh
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 40.812
          - type: f1
            value: 39.02060856097395
      - task:
          type: STS
        dataset:
          type: C-MTEB/BQ
          name: MTEB BQ
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 62.84336868097746
          - type: cos_sim_spearman
            value: 65.540605433497
          - type: euclidean_pearson
            value: 64.08759819387913
          - type: euclidean_spearman
            value: 65.54060543369363
          - type: manhattan_pearson
            value: 64.09334283385029
          - type: manhattan_spearman
            value: 65.55376209169398
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/CLSClusteringP2P
          name: MTEB CLSClusteringP2P
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 39.964020691388505
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/CLSClusteringS2S
          name: MTEB CLSClusteringS2S
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 38.18628830038994
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/CMedQAv1-reranking
          name: MTEB CMedQAv1
          config: default
          split: test
          revision: None
        metrics:
          - type: map
            value: 85.34294439514511
          - type: mrr
            value: 88.03849206349206
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/CMedQAv2-reranking
          name: MTEB CMedQAv2
          config: default
          split: test
          revision: None
        metrics:
          - type: map
            value: 85.87127698007234
          - type: mrr
            value: 88.57980158730159
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/CmedqaRetrieval
          name: MTEB CmedqaRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 24.484
          - type: map_at_10
            value: 36.3
          - type: map_at_100
            value: 38.181
          - type: map_at_1000
            value: 38.305
          - type: map_at_3
            value: 32.39
          - type: map_at_5
            value: 34.504000000000005
          - type: mrr_at_1
            value: 37.608999999999995
          - type: mrr_at_10
            value: 45.348
          - type: mrr_at_100
            value: 46.375
          - type: mrr_at_1000
            value: 46.425
          - type: mrr_at_3
            value: 42.969
          - type: mrr_at_5
            value: 44.285999999999994
          - type: ndcg_at_1
            value: 37.608999999999995
          - type: ndcg_at_10
            value: 42.675999999999995
          - type: ndcg_at_100
            value: 50.12799999999999
          - type: ndcg_at_1000
            value: 52.321
          - type: ndcg_at_3
            value: 37.864
          - type: ndcg_at_5
            value: 39.701
          - type: precision_at_1
            value: 37.608999999999995
          - type: precision_at_10
            value: 9.527
          - type: precision_at_100
            value: 1.555
          - type: precision_at_1000
            value: 0.183
          - type: precision_at_3
            value: 21.547
          - type: precision_at_5
            value: 15.504000000000001
          - type: recall_at_1
            value: 24.484
          - type: recall_at_10
            value: 52.43299999999999
          - type: recall_at_100
            value: 83.446
          - type: recall_at_1000
            value: 98.24199999999999
          - type: recall_at_3
            value: 37.653
          - type: recall_at_5
            value: 43.643
      - task:
          type: PairClassification
        dataset:
          type: C-MTEB/CMNLI
          name: MTEB Cmnli
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 77.71497294046902
          - type: cos_sim_ap
            value: 86.84542027578229
          - type: cos_sim_f1
            value: 79.31987247608926
          - type: cos_sim_precision
            value: 72.70601987142022
          - type: cos_sim_recall
            value: 87.2574234276362
          - type: dot_accuracy
            value: 77.71497294046902
          - type: dot_ap
            value: 86.86514752961159
          - type: dot_f1
            value: 79.31987247608926
          - type: dot_precision
            value: 72.70601987142022
          - type: dot_recall
            value: 87.2574234276362
          - type: euclidean_accuracy
            value: 77.71497294046902
          - type: euclidean_ap
            value: 86.84541456571337
          - type: euclidean_f1
            value: 79.31987247608926
          - type: euclidean_precision
            value: 72.70601987142022
          - type: euclidean_recall
            value: 87.2574234276362
          - type: manhattan_accuracy
            value: 77.8111846061335
          - type: manhattan_ap
            value: 86.81148050422539
          - type: manhattan_f1
            value: 79.41176470588236
          - type: manhattan_precision
            value: 72.52173913043478
          - type: manhattan_recall
            value: 87.74842179097499
          - type: max_accuracy
            value: 77.8111846061335
          - type: max_ap
            value: 86.86514752961159
          - type: max_f1
            value: 79.41176470588236
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/CovidRetrieval
          name: MTEB CovidRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 68.862
          - type: map_at_10
            value: 77.079
          - type: map_at_100
            value: 77.428
          - type: map_at_1000
            value: 77.432
          - type: map_at_3
            value: 75.40400000000001
          - type: map_at_5
            value: 76.227
          - type: mrr_at_1
            value: 69.02000000000001
          - type: mrr_at_10
            value: 77.04299999999999
          - type: mrr_at_100
            value: 77.391
          - type: mrr_at_1000
            value: 77.395
          - type: mrr_at_3
            value: 75.44800000000001
          - type: mrr_at_5
            value: 76.23299999999999
          - type: ndcg_at_1
            value: 69.02000000000001
          - type: ndcg_at_10
            value: 80.789
          - type: ndcg_at_100
            value: 82.27499999999999
          - type: ndcg_at_1000
            value: 82.381
          - type: ndcg_at_3
            value: 77.40599999999999
          - type: ndcg_at_5
            value: 78.87100000000001
          - type: precision_at_1
            value: 69.02000000000001
          - type: precision_at_10
            value: 9.336
          - type: precision_at_100
            value: 0.9990000000000001
          - type: precision_at_1000
            value: 0.101
          - type: precision_at_3
            value: 27.889000000000003
          - type: precision_at_5
            value: 17.492
          - type: recall_at_1
            value: 68.862
          - type: recall_at_10
            value: 92.308
          - type: recall_at_100
            value: 98.84100000000001
          - type: recall_at_1000
            value: 99.684
          - type: recall_at_3
            value: 83.087
          - type: recall_at_5
            value: 86.617
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/DuRetrieval
          name: MTEB DuRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 25.063999999999997
          - type: map_at_10
            value: 78.014
          - type: map_at_100
            value: 81.021
          - type: map_at_1000
            value: 81.059
          - type: map_at_3
            value: 53.616
          - type: map_at_5
            value: 68.00399999999999
          - type: mrr_at_1
            value: 87.8
          - type: mrr_at_10
            value: 91.824
          - type: mrr_at_100
            value: 91.915
          - type: mrr_at_1000
            value: 91.917
          - type: mrr_at_3
            value: 91.525
          - type: mrr_at_5
            value: 91.752
          - type: ndcg_at_1
            value: 87.8
          - type: ndcg_at_10
            value: 85.74199999999999
          - type: ndcg_at_100
            value: 88.82900000000001
          - type: ndcg_at_1000
            value: 89.208
          - type: ndcg_at_3
            value: 84.206
          - type: ndcg_at_5
            value: 83.421
          - type: precision_at_1
            value: 87.8
          - type: precision_at_10
            value: 41.325
          - type: precision_at_100
            value: 4.8
          - type: precision_at_1000
            value: 0.48900000000000005
          - type: precision_at_3
            value: 75.783
          - type: precision_at_5
            value: 64.25999999999999
          - type: recall_at_1
            value: 25.063999999999997
          - type: recall_at_10
            value: 87.324
          - type: recall_at_100
            value: 97.261
          - type: recall_at_1000
            value: 99.309
          - type: recall_at_3
            value: 56.281000000000006
          - type: recall_at_5
            value: 73.467
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/EcomRetrieval
          name: MTEB EcomRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 46.800000000000004
          - type: map_at_10
            value: 56.887
          - type: map_at_100
            value: 57.556
          - type: map_at_1000
            value: 57.582
          - type: map_at_3
            value: 54.15
          - type: map_at_5
            value: 55.825
          - type: mrr_at_1
            value: 46.800000000000004
          - type: mrr_at_10
            value: 56.887
          - type: mrr_at_100
            value: 57.556
          - type: mrr_at_1000
            value: 57.582
          - type: mrr_at_3
            value: 54.15
          - type: mrr_at_5
            value: 55.825
          - type: ndcg_at_1
            value: 46.800000000000004
          - type: ndcg_at_10
            value: 62.061
          - type: ndcg_at_100
            value: 65.042
          - type: ndcg_at_1000
            value: 65.658
          - type: ndcg_at_3
            value: 56.52700000000001
          - type: ndcg_at_5
            value: 59.518
          - type: precision_at_1
            value: 46.800000000000004
          - type: precision_at_10
            value: 7.84
          - type: precision_at_100
            value: 0.9169999999999999
          - type: precision_at_1000
            value: 0.096
          - type: precision_at_3
            value: 21.133
          - type: precision_at_5
            value: 14.12
          - type: recall_at_1
            value: 46.800000000000004
          - type: recall_at_10
            value: 78.4
          - type: recall_at_100
            value: 91.7
          - type: recall_at_1000
            value: 96.39999999999999
          - type: recall_at_3
            value: 63.4
          - type: recall_at_5
            value: 70.6
      - task:
          type: Classification
        dataset:
          type: C-MTEB/IFlyTek-classification
          name: MTEB IFlyTek
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 48.010773374374764
          - type: f1
            value: 35.25314495210735
      - task:
          type: Classification
        dataset:
          type: C-MTEB/JDReview-classification
          name: MTEB JDReview
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 87.01688555347093
          - type: ap
            value: 56.39167630414159
          - type: f1
            value: 81.91756262306008
      - task:
          type: STS
        dataset:
          type: C-MTEB/LCQMC
          name: MTEB LCQMC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 71.17867432738112
          - type: cos_sim_spearman
            value: 77.47954247528372
          - type: euclidean_pearson
            value: 76.32408876437825
          - type: euclidean_spearman
            value: 77.47954025694959
          - type: manhattan_pearson
            value: 76.33345801575938
          - type: manhattan_spearman
            value: 77.48901582125997
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/Mmarco-reranking
          name: MTEB MMarcoReranking
          config: default
          split: dev
          revision: None
        metrics:
          - type: map
            value: 27.96333052746654
          - type: mrr
            value: 26.92023809523809
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/MMarcoRetrieval
          name: MTEB MMarcoRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 66.144
          - type: map_at_10
            value: 75.036
          - type: map_at_100
            value: 75.36
          - type: map_at_1000
            value: 75.371
          - type: map_at_3
            value: 73.258
          - type: map_at_5
            value: 74.369
          - type: mrr_at_1
            value: 68.381
          - type: mrr_at_10
            value: 75.633
          - type: mrr_at_100
            value: 75.91799999999999
          - type: mrr_at_1000
            value: 75.928
          - type: mrr_at_3
            value: 74.093
          - type: mrr_at_5
            value: 75.036
          - type: ndcg_at_1
            value: 68.381
          - type: ndcg_at_10
            value: 78.661
          - type: ndcg_at_100
            value: 80.15
          - type: ndcg_at_1000
            value: 80.456
          - type: ndcg_at_3
            value: 75.295
          - type: ndcg_at_5
            value: 77.14999999999999
          - type: precision_at_1
            value: 68.381
          - type: precision_at_10
            value: 9.481
          - type: precision_at_100
            value: 1.023
          - type: precision_at_1000
            value: 0.105
          - type: precision_at_3
            value: 28.309
          - type: precision_at_5
            value: 17.974
          - type: recall_at_1
            value: 66.144
          - type: recall_at_10
            value: 89.24499999999999
          - type: recall_at_100
            value: 96.032
          - type: recall_at_1000
            value: 98.437
          - type: recall_at_3
            value: 80.327
          - type: recall_at_5
            value: 84.733
      - 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: 68.26832548755884
          - type: f1
            value: 65.97422207086723
      - 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: 73.13046402151984
          - type: f1
            value: 72.69199129694121
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/MedicalRetrieval
          name: MTEB MedicalRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 50.4
          - type: map_at_10
            value: 56.645
          - type: map_at_100
            value: 57.160999999999994
          - type: map_at_1000
            value: 57.218
          - type: map_at_3
            value: 55.383
          - type: map_at_5
            value: 56.08800000000001
          - type: mrr_at_1
            value: 50.6
          - type: mrr_at_10
            value: 56.745999999999995
          - type: mrr_at_100
            value: 57.262
          - type: mrr_at_1000
            value: 57.318999999999996
          - type: mrr_at_3
            value: 55.483000000000004
          - type: mrr_at_5
            value: 56.188
          - type: ndcg_at_1
            value: 50.4
          - type: ndcg_at_10
            value: 59.534
          - type: ndcg_at_100
            value: 62.400999999999996
          - type: ndcg_at_1000
            value: 64.01299999999999
          - type: ndcg_at_3
            value: 56.887
          - type: ndcg_at_5
            value: 58.160000000000004
          - type: precision_at_1
            value: 50.4
          - type: precision_at_10
            value: 6.859999999999999
          - type: precision_at_100
            value: 0.828
          - type: precision_at_1000
            value: 0.096
          - type: precision_at_3
            value: 20.4
          - type: precision_at_5
            value: 12.86
          - type: recall_at_1
            value: 50.4
          - type: recall_at_10
            value: 68.60000000000001
          - type: recall_at_100
            value: 82.8
          - type: recall_at_1000
            value: 95.7
          - type: recall_at_3
            value: 61.199999999999996
          - type: recall_at_5
            value: 64.3
      - task:
          type: Classification
        dataset:
          type: C-MTEB/MultilingualSentiment-classification
          name: MTEB MultilingualSentiment
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 73.39666666666666
          - type: f1
            value: 72.86349039489504
      - task:
          type: PairClassification
        dataset:
          type: C-MTEB/OCNLI
          name: MTEB Ocnli
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 73.36220898754738
          - type: cos_sim_ap
            value: 78.50300066088354
          - type: cos_sim_f1
            value: 75.39370078740157
          - type: cos_sim_precision
            value: 70.59907834101382
          - type: cos_sim_recall
            value: 80.8870116156283
          - type: dot_accuracy
            value: 73.36220898754738
          - type: dot_ap
            value: 78.50300066088354
          - type: dot_f1
            value: 75.39370078740157
          - type: dot_precision
            value: 70.59907834101382
          - type: dot_recall
            value: 80.8870116156283
          - type: euclidean_accuracy
            value: 73.36220898754738
          - type: euclidean_ap
            value: 78.50300066088354
          - type: euclidean_f1
            value: 75.39370078740157
          - type: euclidean_precision
            value: 70.59907834101382
          - type: euclidean_recall
            value: 80.8870116156283
          - type: manhattan_accuracy
            value: 73.09149972929075
          - type: manhattan_ap
            value: 78.41160715817406
          - type: manhattan_f1
            value: 75.3623188405797
          - type: manhattan_precision
            value: 69.45681211041853
          - type: manhattan_recall
            value: 82.36536430834214
          - type: max_accuracy
            value: 73.36220898754738
          - type: max_ap
            value: 78.50300066088354
          - type: max_f1
            value: 75.39370078740157
      - task:
          type: Classification
        dataset:
          type: C-MTEB/OnlineShopping-classification
          name: MTEB OnlineShopping
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 91.82000000000001
          - type: ap
            value: 89.3671278896903
          - type: f1
            value: 91.8021970144045
      - task:
          type: STS
        dataset:
          type: C-MTEB/PAWSX
          name: MTEB PAWSX
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 30.07022294131062
          - type: cos_sim_spearman
            value: 36.21542804954441
          - type: euclidean_pearson
            value: 36.37841945307606
          - type: euclidean_spearman
            value: 36.215513214835546
          - type: manhattan_pearson
            value: 36.31755715017088
          - type: manhattan_spearman
            value: 36.16848256918425
      - task:
          type: STS
        dataset:
          type: C-MTEB/QBQTC
          name: MTEB QBQTC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 36.779755871073505
          - type: cos_sim_spearman
            value: 38.736220679196606
          - type: euclidean_pearson
            value: 37.13356686891227
          - type: euclidean_spearman
            value: 38.73619198602118
          - type: manhattan_pearson
            value: 37.175466658530816
          - type: manhattan_spearman
            value: 38.74523158724344
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (zh)
          config: zh
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 65.9737863254904
          - type: cos_sim_spearman
            value: 68.88293545840186
          - type: euclidean_pearson
            value: 67.23730973929247
          - type: euclidean_spearman
            value: 68.88293545840186
          - type: manhattan_pearson
            value: 67.30647960940956
          - type: manhattan_spearman
            value: 68.90553460682702
      - task:
          type: STS
        dataset:
          type: C-MTEB/STSB
          name: MTEB STSB
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 78.99371432933002
          - type: cos_sim_spearman
            value: 79.36496709214312
          - type: euclidean_pearson
            value: 78.77721120706431
          - type: euclidean_spearman
            value: 79.36500761622595
          - type: manhattan_pearson
            value: 78.82503201285202
          - type: manhattan_spearman
            value: 79.43915548337401
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/T2Reranking
          name: MTEB T2Reranking
          config: default
          split: dev
          revision: None
        metrics:
          - type: map
            value: 66.38418982516941
          - type: mrr
            value: 76.09996131153883
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/T2Retrieval
          name: MTEB T2Retrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 27.426000000000002
          - type: map_at_10
            value: 77.209
          - type: map_at_100
            value: 80.838
          - type: map_at_1000
            value: 80.903
          - type: map_at_3
            value: 54.196
          - type: map_at_5
            value: 66.664
          - type: mrr_at_1
            value: 90.049
          - type: mrr_at_10
            value: 92.482
          - type: mrr_at_100
            value: 92.568
          - type: mrr_at_1000
            value: 92.572
          - type: mrr_at_3
            value: 92.072
          - type: mrr_at_5
            value: 92.33
          - type: ndcg_at_1
            value: 90.049
          - type: ndcg_at_10
            value: 84.69200000000001
          - type: ndcg_at_100
            value: 88.25699999999999
          - type: ndcg_at_1000
            value: 88.896
          - type: ndcg_at_3
            value: 86.09700000000001
          - type: ndcg_at_5
            value: 84.68599999999999
          - type: precision_at_1
            value: 90.049
          - type: precision_at_10
            value: 42.142
          - type: precision_at_100
            value: 5.017
          - type: precision_at_1000
            value: 0.516
          - type: precision_at_3
            value: 75.358
          - type: precision_at_5
            value: 63.173
          - type: recall_at_1
            value: 27.426000000000002
          - type: recall_at_10
            value: 83.59400000000001
          - type: recall_at_100
            value: 95.21
          - type: recall_at_1000
            value: 98.503
          - type: recall_at_3
            value: 55.849000000000004
          - type: recall_at_5
            value: 69.986
      - task:
          type: Classification
        dataset:
          type: C-MTEB/TNews-classification
          name: MTEB TNews
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 51.925999999999995
          - type: f1
            value: 50.16867723626971
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/ThuNewsClusteringP2P
          name: MTEB ThuNewsClusteringP2P
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 60.738901671970005
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/ThuNewsClusteringS2S
          name: MTEB ThuNewsClusteringS2S
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 57.08563183138733
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/VideoRetrieval
          name: MTEB VideoRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 52
          - type: map_at_10
            value: 62.956
          - type: map_at_100
            value: 63.491
          - type: map_at_1000
            value: 63.50599999999999
          - type: map_at_3
            value: 60.733000000000004
          - type: map_at_5
            value: 62.217999999999996
          - type: mrr_at_1
            value: 52
          - type: mrr_at_10
            value: 62.956
          - type: mrr_at_100
            value: 63.491
          - type: mrr_at_1000
            value: 63.50599999999999
          - type: mrr_at_3
            value: 60.733000000000004
          - type: mrr_at_5
            value: 62.217999999999996
          - type: ndcg_at_1
            value: 52
          - type: ndcg_at_10
            value: 67.956
          - type: ndcg_at_100
            value: 70.536
          - type: ndcg_at_1000
            value: 70.908
          - type: ndcg_at_3
            value: 63.456999999999994
          - type: ndcg_at_5
            value: 66.155
          - type: precision_at_1
            value: 52
          - type: precision_at_10
            value: 8.35
          - type: precision_at_100
            value: 0.955
          - type: precision_at_1000
            value: 0.098
          - type: precision_at_3
            value: 23.767
          - type: precision_at_5
            value: 15.58
          - type: recall_at_1
            value: 52
          - type: recall_at_10
            value: 83.5
          - type: recall_at_100
            value: 95.5
          - type: recall_at_1000
            value: 98.4
          - type: recall_at_3
            value: 71.3
          - type: recall_at_5
            value: 77.9
      - task:
          type: Classification
        dataset:
          type: C-MTEB/waimai-classification
          name: MTEB Waimai
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 87.10000000000001
          - type: ap
            value: 70.81766065881429
          - type: f1
            value: 85.5323306120456

a try for emebdding model