tao-8k / README.md
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metadata
tags:
  - mteb
model-index:
  - name: tao-8k
    results:
      - task:
          type: STS
        dataset:
          type: C-MTEB/AFQMC
          name: MTEB AFQMC
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 46.6327281304144
          - type: cos_sim_spearman
            value: 48.842454434123376
          - type: euclidean_pearson
            value: 46.94481399008005
          - type: euclidean_spearman
            value: 48.842454434123376
          - type: manhattan_pearson
            value: 46.89375935801324
          - type: manhattan_spearman
            value: 48.78990181105918
      - task:
          type: STS
        dataset:
          type: C-MTEB/ATEC
          name: MTEB ATEC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 51.29442837260785
          - type: cos_sim_spearman
            value: 52.652094634834
          - type: euclidean_pearson
            value: 54.86278112546793
          - type: euclidean_spearman
            value: 52.65209238258423
          - type: manhattan_pearson
            value: 54.8164800665497
          - type: manhattan_spearman
            value: 52.626711935726014
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (zh)
          config: zh
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 41.51200000000001
          - type: f1
            value: 39.47955832883091
      - task:
          type: STS
        dataset:
          type: C-MTEB/BQ
          name: MTEB BQ
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 63.27653562193512
          - type: cos_sim_spearman
            value: 65.37293598647585
          - type: euclidean_pearson
            value: 63.91367659963474
          - type: euclidean_spearman
            value: 65.37294637878077
          - type: manhattan_pearson
            value: 63.89671277983551
          - type: manhattan_spearman
            value: 65.35510625635355
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/CLSClusteringP2P
          name: MTEB CLSClusteringP2P
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 39.92148459596857
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/CLSClusteringS2S
          name: MTEB CLSClusteringS2S
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 36.7800929733979
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/CMedQAv1-reranking
          name: MTEB CMedQAv1
          config: default
          split: test
          revision: None
        metrics:
          - type: map
            value: 84.56370955233704
          - type: mrr
            value: 87.14396825396825
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/CMedQAv2-reranking
          name: MTEB CMedQAv2
          config: default
          split: test
          revision: None
        metrics:
          - type: map
            value: 85.4719112626303
          - type: mrr
            value: 88.25107142857142
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/CmedqaRetrieval
          name: MTEB CmedqaRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 24.314
          - type: map_at_10
            value: 36.157000000000004
          - type: map_at_100
            value: 38.004
          - type: map_at_1000
            value: 38.129999999999995
          - type: map_at_3
            value: 32.141999999999996
          - type: map_at_5
            value: 34.414
          - type: mrr_at_1
            value: 37.384
          - type: mrr_at_10
            value: 45.261
          - type: mrr_at_100
            value: 46.271
          - type: mrr_at_1000
            value: 46.32
          - type: mrr_at_3
            value: 42.760999999999996
          - type: mrr_at_5
            value: 44.219
          - type: ndcg_at_1
            value: 37.384
          - type: ndcg_at_10
            value: 42.599
          - type: ndcg_at_100
            value: 50.068999999999996
          - type: ndcg_at_1000
            value: 52.221
          - type: ndcg_at_3
            value: 37.551
          - type: ndcg_at_5
            value: 39.711
          - type: precision_at_1
            value: 37.384
          - type: precision_at_10
            value: 9.532
          - type: precision_at_100
            value: 1.554
          - type: precision_at_1000
            value: 0.183
          - type: precision_at_3
            value: 21.205
          - type: precision_at_5
            value: 15.539
          - type: recall_at_1
            value: 24.314
          - type: recall_at_10
            value: 52.463
          - type: recall_at_100
            value: 83.86099999999999
          - type: recall_at_1000
            value: 98.17399999999999
          - type: recall_at_3
            value: 37.341
          - type: recall_at_5
            value: 43.952999999999996
      - task:
          type: PairClassification
        dataset:
          type: C-MTEB/CMNLI
          name: MTEB Cmnli
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 78.80938063740228
          - type: cos_sim_ap
            value: 87.42519095434638
          - type: cos_sim_f1
            value: 80.08597528210638
          - type: cos_sim_precision
            value: 74.10501193317423
          - type: cos_sim_recall
            value: 87.11713818096797
          - type: dot_accuracy
            value: 78.80938063740228
          - type: dot_ap
            value: 87.44023261310717
          - type: dot_f1
            value: 80.08597528210638
          - type: dot_precision
            value: 74.10501193317423
          - type: dot_recall
            value: 87.11713818096797
          - type: euclidean_accuracy
            value: 78.80938063740228
          - type: euclidean_ap
            value: 87.42517285949802
          - type: euclidean_f1
            value: 80.08597528210638
          - type: euclidean_precision
            value: 74.10501193317423
          - type: euclidean_recall
            value: 87.11713818096797
          - type: manhattan_accuracy
            value: 78.90559230306675
          - type: manhattan_ap
            value: 87.38730802838026
          - type: manhattan_f1
            value: 80.1043138107139
          - type: manhattan_precision
            value: 74.82744620381648
          - type: manhattan_recall
            value: 86.1819032031798
          - type: max_accuracy
            value: 78.90559230306675
          - type: max_ap
            value: 87.44023261310717
          - type: max_f1
            value: 80.1043138107139
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/CovidRetrieval
          name: MTEB CovidRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 69.863
          - type: map_at_10
            value: 77.865
          - type: map_at_100
            value: 78.21900000000001
          - type: map_at_1000
            value: 78.22200000000001
          - type: map_at_3
            value: 76.335
          - type: map_at_5
            value: 77.179
          - type: mrr_at_1
            value: 70.074
          - type: mrr_at_10
            value: 77.89
          - type: mrr_at_100
            value: 78.235
          - type: mrr_at_1000
            value: 78.238
          - type: mrr_at_3
            value: 76.466
          - type: mrr_at_5
            value: 77.241
          - type: ndcg_at_1
            value: 70.074
          - type: ndcg_at_10
            value: 81.375
          - type: ndcg_at_100
            value: 82.918
          - type: ndcg_at_1000
            value: 83.019
          - type: ndcg_at_3
            value: 78.32000000000001
          - type: ndcg_at_5
            value: 79.824
          - type: precision_at_1
            value: 70.074
          - type: precision_at_10
            value: 9.325999999999999
          - type: precision_at_100
            value: 1.001
          - type: precision_at_1000
            value: 0.101
          - type: precision_at_3
            value: 28.17
          - type: precision_at_5
            value: 17.682000000000002
          - type: recall_at_1
            value: 69.863
          - type: recall_at_10
            value: 92.202
          - type: recall_at_100
            value: 99.05199999999999
          - type: recall_at_1000
            value: 99.895
          - type: recall_at_3
            value: 83.93
          - type: recall_at_5
            value: 87.566
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/DuRetrieval
          name: MTEB DuRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 25.730999999999998
          - type: map_at_10
            value: 80.765
          - type: map_at_100
            value: 83.486
          - type: map_at_1000
            value: 83.521
          - type: map_at_3
            value: 55.745999999999995
          - type: map_at_5
            value: 70.473
          - type: mrr_at_1
            value: 89.55
          - type: mrr_at_10
            value: 93.028
          - type: mrr_at_100
            value: 93.093
          - type: mrr_at_1000
            value: 93.096
          - type: mrr_at_3
            value: 92.80000000000001
          - type: mrr_at_5
            value: 92.92200000000001
          - type: ndcg_at_1
            value: 89.55
          - type: ndcg_at_10
            value: 87.898
          - type: ndcg_at_100
            value: 90.366
          - type: ndcg_at_1000
            value: 90.715
          - type: ndcg_at_3
            value: 86.497
          - type: ndcg_at_5
            value: 85.533
          - type: precision_at_1
            value: 89.55
          - type: precision_at_10
            value: 42.305
          - type: precision_at_100
            value: 4.82
          - type: precision_at_1000
            value: 0.48900000000000005
          - type: precision_at_3
            value: 77.833
          - type: precision_at_5
            value: 65.81
          - type: recall_at_1
            value: 25.730999999999998
          - type: recall_at_10
            value: 89.409
          - type: recall_at_100
            value: 97.62100000000001
          - type: recall_at_1000
            value: 99.565
          - type: recall_at_3
            value: 58.298
          - type: recall_at_5
            value: 75.315
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/EcomRetrieval
          name: MTEB EcomRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 49.6
          - type: map_at_10
            value: 59.34
          - type: map_at_100
            value: 59.894999999999996
          - type: map_at_1000
            value: 59.913000000000004
          - type: map_at_3
            value: 56.667
          - type: map_at_5
            value: 58.196999999999996
          - type: mrr_at_1
            value: 49.6
          - type: mrr_at_10
            value: 59.34
          - type: mrr_at_100
            value: 59.894999999999996
          - type: mrr_at_1000
            value: 59.913000000000004
          - type: mrr_at_3
            value: 56.667
          - type: mrr_at_5
            value: 58.196999999999996
          - type: ndcg_at_1
            value: 49.6
          - type: ndcg_at_10
            value: 64.461
          - type: ndcg_at_100
            value: 67.08800000000001
          - type: ndcg_at_1000
            value: 67.578
          - type: ndcg_at_3
            value: 58.962
          - type: ndcg_at_5
            value: 61.741
          - type: precision_at_1
            value: 49.6
          - type: precision_at_10
            value: 8.07
          - type: precision_at_100
            value: 0.928
          - type: precision_at_1000
            value: 0.097
          - type: precision_at_3
            value: 21.867
          - type: precision_at_5
            value: 14.48
          - type: recall_at_1
            value: 49.6
          - type: recall_at_10
            value: 80.7
          - type: recall_at_100
            value: 92.80000000000001
          - type: recall_at_1000
            value: 96.7
          - type: recall_at_3
            value: 65.60000000000001
          - type: recall_at_5
            value: 72.39999999999999
      - task:
          type: Classification
        dataset:
          type: C-MTEB/IFlyTek-classification
          name: MTEB IFlyTek
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 47.44132358599462
          - type: f1
            value: 34.814352930577854
      - task:
          type: Classification
        dataset:
          type: C-MTEB/JDReview-classification
          name: MTEB JDReview
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 86.43527204502813
          - type: ap
            value: 55.197728692877554
          - type: f1
            value: 81.22331922899193
      - task:
          type: STS
        dataset:
          type: C-MTEB/LCQMC
          name: MTEB LCQMC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 72.21054197899034
          - type: cos_sim_spearman
            value: 77.10172371889475
          - type: euclidean_pearson
            value: 76.15914782847307
          - type: euclidean_spearman
            value: 77.10173036795658
          - type: manhattan_pearson
            value: 76.16257390318928
          - type: manhattan_spearman
            value: 77.10538180843567
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/Mmarco-reranking
          name: MTEB MMarcoReranking
          config: default
          split: dev
          revision: None
        metrics:
          - type: map
            value: 26.968179320629726
          - type: mrr
            value: 25.664285714285718
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/MMarcoRetrieval
          name: MTEB MMarcoRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 66.674
          - type: map_at_10
            value: 75.624
          - type: map_at_100
            value: 75.96199999999999
          - type: map_at_1000
            value: 75.973
          - type: map_at_3
            value: 73.9
          - type: map_at_5
            value: 75.007
          - type: mrr_at_1
            value: 68.89699999999999
          - type: mrr_at_10
            value: 76.212
          - type: mrr_at_100
            value: 76.506
          - type: mrr_at_1000
            value: 76.517
          - type: mrr_at_3
            value: 74.72999999999999
          - type: mrr_at_5
            value: 75.65899999999999
          - type: ndcg_at_1
            value: 68.89699999999999
          - type: ndcg_at_10
            value: 79.19
          - type: ndcg_at_100
            value: 80.681
          - type: ndcg_at_1000
            value: 80.97999999999999
          - type: ndcg_at_3
            value: 75.954
          - type: ndcg_at_5
            value: 77.792
          - type: precision_at_1
            value: 68.89699999999999
          - type: precision_at_10
            value: 9.519
          - type: precision_at_100
            value: 1.026
          - type: precision_at_1000
            value: 0.105
          - type: precision_at_3
            value: 28.548000000000002
          - type: precision_at_5
            value: 18.117
          - type: recall_at_1
            value: 66.674
          - type: recall_at_10
            value: 89.55499999999999
          - type: recall_at_100
            value: 96.26
          - type: recall_at_1000
            value: 98.598
          - type: recall_at_3
            value: 81.029
          - type: recall_at_5
            value: 85.37700000000001
      - 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: 68.13718897108271
          - type: f1
            value: 66.00508413016382
      - 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: 72.542030934768
          - type: f1
            value: 71.87970959109703
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/MedicalRetrieval
          name: MTEB MedicalRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 51.2
          - type: map_at_10
            value: 57.211999999999996
          - type: map_at_100
            value: 57.74
          - type: map_at_1000
            value: 57.791000000000004
          - type: map_at_3
            value: 55.900000000000006
          - type: map_at_5
            value: 56.665
          - type: mrr_at_1
            value: 51.300000000000004
          - type: mrr_at_10
            value: 57.252
          - type: mrr_at_100
            value: 57.789
          - type: mrr_at_1000
            value: 57.84
          - type: mrr_at_3
            value: 55.95
          - type: mrr_at_5
            value: 56.715
          - type: ndcg_at_1
            value: 51.2
          - type: ndcg_at_10
            value: 59.998
          - type: ndcg_at_100
            value: 62.971999999999994
          - type: ndcg_at_1000
            value: 64.453
          - type: ndcg_at_3
            value: 57.321
          - type: ndcg_at_5
            value: 58.711
          - type: precision_at_1
            value: 51.2
          - type: precision_at_10
            value: 6.87
          - type: precision_at_100
            value: 0.835
          - type: precision_at_1000
            value: 0.095
          - type: precision_at_3
            value: 20.467
          - type: precision_at_5
            value: 12.959999999999999
          - type: recall_at_1
            value: 51.2
          - type: recall_at_10
            value: 68.7
          - type: recall_at_100
            value: 83.5
          - type: recall_at_1000
            value: 95.39999999999999
          - type: recall_at_3
            value: 61.4
          - type: recall_at_5
            value: 64.8
      - task:
          type: Classification
        dataset:
          type: C-MTEB/MultilingualSentiment-classification
          name: MTEB MultilingualSentiment
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 73.33000000000001
          - type: f1
            value: 72.76740880461465
      - task:
          type: PairClassification
        dataset:
          type: C-MTEB/OCNLI
          name: MTEB Ocnli
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 75.09474824038982
          - type: cos_sim_ap
            value: 79.49093167837522
          - type: cos_sim_f1
            value: 77.762619372442
          - type: cos_sim_precision
            value: 68.29073482428115
          - type: cos_sim_recall
            value: 90.28511087645195
          - type: dot_accuracy
            value: 75.09474824038982
          - type: dot_ap
            value: 79.49093167837522
          - type: dot_f1
            value: 77.762619372442
          - type: dot_precision
            value: 68.29073482428115
          - type: dot_recall
            value: 90.28511087645195
          - type: euclidean_accuracy
            value: 75.09474824038982
          - type: euclidean_ap
            value: 79.49093167837522
          - type: euclidean_f1
            value: 77.762619372442
          - type: euclidean_precision
            value: 68.29073482428115
          - type: euclidean_recall
            value: 90.28511087645195
          - type: manhattan_accuracy
            value: 74.93232268543584
          - type: manhattan_ap
            value: 79.50256779527038
          - type: manhattan_f1
            value: 77.3749426342359
          - type: manhattan_precision
            value: 68.42532467532467
          - type: manhattan_recall
            value: 89.01795142555439
          - type: max_accuracy
            value: 75.09474824038982
          - type: max_ap
            value: 79.50256779527038
          - type: max_f1
            value: 77.762619372442
      - task:
          type: Classification
        dataset:
          type: C-MTEB/OnlineShopping-classification
          name: MTEB OnlineShopping
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 91.71
          - type: ap
            value: 89.30664330630684
          - type: f1
            value: 91.69380669543091
      - task:
          type: STS
        dataset:
          type: C-MTEB/PAWSX
          name: MTEB PAWSX
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 27.87844586552044
          - type: cos_sim_spearman
            value: 33.55828345961726
          - type: euclidean_pearson
            value: 34.008422591348754
          - type: euclidean_spearman
            value: 33.55828173553759
          - type: manhattan_pearson
            value: 33.97354762221951
          - type: manhattan_spearman
            value: 33.55061748217219
      - task:
          type: STS
        dataset:
          type: C-MTEB/QBQTC
          name: MTEB QBQTC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 37.16475906990342
          - type: cos_sim_spearman
            value: 39.02023124990304
          - type: euclidean_pearson
            value: 37.12905621621282
          - type: euclidean_spearman
            value: 39.02017798495793
          - type: manhattan_pearson
            value: 37.16400100601629
          - type: manhattan_spearman
            value: 39.027383935772335
      - 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: 66.7431509369159
          - type: cos_sim_spearman
            value: 69.10355047922879
          - type: euclidean_pearson
            value: 67.48723360063258
          - type: euclidean_spearman
            value: 69.10355047922879
          - type: manhattan_pearson
            value: 67.55981324291854
          - type: manhattan_spearman
            value: 69.1816947077302
      - task:
          type: STS
        dataset:
          type: C-MTEB/STSB
          name: MTEB STSB
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 78.27412453529412
          - type: cos_sim_spearman
            value: 78.74292565872022
          - type: euclidean_pearson
            value: 77.95359390335884
          - type: euclidean_spearman
            value: 78.7428438579602
          - type: manhattan_pearson
            value: 77.99252788851469
          - type: manhattan_spearman
            value: 78.80401873296358
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/T2Reranking
          name: MTEB T2Reranking
          config: default
          split: dev
          revision: None
        metrics:
          - type: map
            value: 66.42334440897298
          - type: mrr
            value: 76.24570128209263
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/T2Retrieval
          name: MTEB T2Retrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 27.323999999999998
          - type: map_at_10
            value: 76.752
          - type: map_at_100
            value: 80.39
          - type: map_at_1000
            value: 80.457
          - type: map_at_3
            value: 53.93
          - type: map_at_5
            value: 66.263
          - type: mrr_at_1
            value: 89.90899999999999
          - type: mrr_at_10
            value: 92.35
          - type: mrr_at_100
            value: 92.43599999999999
          - type: mrr_at_1000
            value: 92.44
          - type: mrr_at_3
            value: 91.92
          - type: mrr_at_5
            value: 92.192
          - type: ndcg_at_1
            value: 89.90899999999999
          - type: ndcg_at_10
            value: 84.352
          - type: ndcg_at_100
            value: 87.978
          - type: ndcg_at_1000
            value: 88.631
          - type: ndcg_at_3
            value: 85.845
          - type: ndcg_at_5
            value: 84.35000000000001
          - type: precision_at_1
            value: 89.90899999999999
          - type: precision_at_10
            value: 41.985
          - type: precision_at_100
            value: 5.007000000000001
          - type: precision_at_1000
            value: 0.516
          - type: precision_at_3
            value: 75.146
          - type: precision_at_5
            value: 62.92100000000001
          - type: recall_at_1
            value: 27.323999999999998
          - type: recall_at_10
            value: 83.221
          - type: recall_at_100
            value: 95.088
          - type: recall_at_1000
            value: 98.436
          - type: recall_at_3
            value: 55.58
          - type: recall_at_5
            value: 69.594
      - task:
          type: Classification
        dataset:
          type: C-MTEB/TNews-classification
          name: MTEB TNews
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 50.453
          - type: f1
            value: 48.736715267813835
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/ThuNewsClusteringP2P
          name: MTEB ThuNewsClusteringP2P
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 59.153574405500706
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/ThuNewsClusteringS2S
          name: MTEB ThuNewsClusteringS2S
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 52.79421409479782
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/VideoRetrieval
          name: MTEB VideoRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 56.699999999999996
          - type: map_at_10
            value: 66.834
          - type: map_at_100
            value: 67.313
          - type: map_at_1000
            value: 67.325
          - type: map_at_3
            value: 65.017
          - type: map_at_5
            value: 65.927
          - type: mrr_at_1
            value: 56.699999999999996
          - type: mrr_at_10
            value: 66.834
          - type: mrr_at_100
            value: 67.313
          - type: mrr_at_1000
            value: 67.325
          - type: mrr_at_3
            value: 65.017
          - type: mrr_at_5
            value: 65.927
          - type: ndcg_at_1
            value: 56.699999999999996
          - type: ndcg_at_10
            value: 71.576
          - type: ndcg_at_100
            value: 73.79400000000001
          - type: ndcg_at_1000
            value: 74.08200000000001
          - type: ndcg_at_3
            value: 67.73400000000001
          - type: ndcg_at_5
            value: 69.378
          - type: precision_at_1
            value: 56.699999999999996
          - type: precision_at_10
            value: 8.64
          - type: precision_at_100
            value: 0.9650000000000001
          - type: precision_at_1000
            value: 0.099
          - type: precision_at_3
            value: 25.2
          - type: precision_at_5
            value: 15.920000000000002
          - type: recall_at_1
            value: 56.699999999999996
          - type: recall_at_10
            value: 86.4
          - type: recall_at_100
            value: 96.5
          - type: recall_at_1000
            value: 98.7
          - type: recall_at_3
            value: 75.6
          - type: recall_at_5
            value: 79.60000000000001
      - task:
          type: Classification
        dataset:
          type: C-MTEB/waimai-classification
          name: MTEB Waimai
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 86.83
          - type: ap
            value: 70.2908139255317
          - type: f1
            value: 85.19267443803346

a try for emebdding model