piccolo-large-zh-v2 / README.md
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metadata
tags:
  - mteb
model-index:
  - name: piccolo-large-zh-v2
    results:
      - task:
          type: STS
        dataset:
          type: C-MTEB/AFQMC
          name: MTEB AFQMC
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 56.76055988260572
          - type: cos_sim_spearman
            value: 61.49271876861677
          - type: euclidean_pearson
            value: 59.14524585320711
          - type: euclidean_spearman
            value: 60.63579339225774
          - type: manhattan_pearson
            value: 59.14662752965445
          - type: manhattan_spearman
            value: 60.635190265737904
      - task:
          type: STS
        dataset:
          type: C-MTEB/ATEC
          name: MTEB ATEC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 56.21706298831197
          - type: cos_sim_spearman
            value: 59.19831457688953
          - type: euclidean_pearson
            value: 62.37752017633299
          - type: euclidean_spearman
            value: 58.79400967473204
          - type: manhattan_pearson
            value: 62.37015943212308
          - type: manhattan_spearman
            value: 58.79232537600814
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (zh)
          config: zh
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 49.440000000000005
          - type: f1
            value: 46.67381446305019
      - task:
          type: STS
        dataset:
          type: C-MTEB/BQ
          name: MTEB BQ
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 70.99026329599994
          - type: cos_sim_spearman
            value: 72.87565357908989
          - type: euclidean_pearson
            value: 71.17690439270028
          - type: euclidean_spearman
            value: 72.50428109969029
          - type: manhattan_pearson
            value: 71.17262321033088
          - type: manhattan_spearman
            value: 72.49845447987437
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/CLSClusteringP2P
          name: MTEB CLSClusteringP2P
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 57.92713421071616
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/CLSClusteringS2S
          name: MTEB CLSClusteringS2S
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 48.096546680932235
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/CMedQAv1-reranking
          name: MTEB CMedQAv1
          config: default
          split: test
          revision: None
        metrics:
          - type: map
            value: 89.31003741715936
          - type: mrr
            value: 91.38075396825397
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/CMedQAv2-reranking
          name: MTEB CMedQAv2
          config: default
          split: test
          revision: None
        metrics:
          - type: map
            value: 90.13769781784876
          - type: mrr
            value: 92.14329365079365
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/CmedqaRetrieval
          name: MTEB CmedqaRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 26.931
          - type: map_at_10
            value: 40.647
          - type: map_at_100
            value: 42.519
          - type: map_at_1000
            value: 42.616
          - type: map_at_3
            value: 36.144999999999996
          - type: map_at_5
            value: 38.717
          - type: mrr_at_1
            value: 40.935
          - type: mrr_at_10
            value: 49.684
          - type: mrr_at_100
            value: 50.598
          - type: mrr_at_1000
            value: 50.632999999999996
          - type: mrr_at_3
            value: 47.07
          - type: mrr_at_5
            value: 48.49
          - type: ndcg_at_1
            value: 40.935
          - type: ndcg_at_10
            value: 47.583999999999996
          - type: ndcg_at_100
            value: 54.69199999999999
          - type: ndcg_at_1000
            value: 56.314
          - type: ndcg_at_3
            value: 41.973
          - type: ndcg_at_5
            value: 44.334
          - type: precision_at_1
            value: 40.935
          - type: precision_at_10
            value: 10.585
          - type: precision_at_100
            value: 1.637
          - type: precision_at_1000
            value: 0.184
          - type: precision_at_3
            value: 23.881
          - type: precision_at_5
            value: 17.399
          - type: recall_at_1
            value: 26.931
          - type: recall_at_10
            value: 59.006
          - type: recall_at_100
            value: 88.247
          - type: recall_at_1000
            value: 99.045
          - type: recall_at_3
            value: 42.064
          - type: recall_at_5
            value: 49.266
      - task:
          type: PairClassification
        dataset:
          type: C-MTEB/CMNLI
          name: MTEB Cmnli
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 86.08538785327721
          - type: cos_sim_ap
            value: 92.64373114205229
          - type: cos_sim_f1
            value: 86.89951395953432
          - type: cos_sim_precision
            value: 84.11378555798687
          - type: cos_sim_recall
            value: 89.87608136544307
          - type: dot_accuracy
            value: 72.66386049308478
          - type: dot_ap
            value: 81.053422935767
          - type: dot_f1
            value: 75.19933726830277
          - type: dot_precision
            value: 67.4907063197026
          - type: dot_recall
            value: 84.89595510872107
          - type: euclidean_accuracy
            value: 85.52014431749849
          - type: euclidean_ap
            value: 91.90647782899615
          - type: euclidean_f1
            value: 86.26361413647477
          - type: euclidean_precision
            value: 82.2071595001059
          - type: euclidean_recall
            value: 90.74117371989713
          - type: manhattan_accuracy
            value: 85.48406494287433
          - type: manhattan_ap
            value: 91.89657919524385
          - type: manhattan_f1
            value: 86.20413761572752
          - type: manhattan_precision
            value: 84.324686940966
          - type: manhattan_recall
            value: 88.16927753097966
          - type: max_accuracy
            value: 86.08538785327721
          - type: max_ap
            value: 92.64373114205229
          - type: max_f1
            value: 86.89951395953432
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/CovidRetrieval
          name: MTEB CovidRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 75.50099999999999
          - type: map_at_10
            value: 83.43
          - type: map_at_100
            value: 83.577
          - type: map_at_1000
            value: 83.57900000000001
          - type: map_at_3
            value: 82.06400000000001
          - type: map_at_5
            value: 82.88600000000001
          - type: mrr_at_1
            value: 75.869
          - type: mrr_at_10
            value: 83.536
          - type: mrr_at_100
            value: 83.682
          - type: mrr_at_1000
            value: 83.68299999999999
          - type: mrr_at_3
            value: 82.244
          - type: mrr_at_5
            value: 82.998
          - type: ndcg_at_1
            value: 75.764
          - type: ndcg_at_10
            value: 86.777
          - type: ndcg_at_100
            value: 87.36
          - type: ndcg_at_1000
            value: 87.424
          - type: ndcg_at_3
            value: 84.10300000000001
          - type: ndcg_at_5
            value: 85.532
          - type: precision_at_1
            value: 75.764
          - type: precision_at_10
            value: 9.8
          - type: precision_at_100
            value: 1.005
          - type: precision_at_1000
            value: 0.101
          - type: precision_at_3
            value: 30.207
          - type: precision_at_5
            value: 18.82
          - type: recall_at_1
            value: 75.50099999999999
          - type: recall_at_10
            value: 96.997
          - type: recall_at_100
            value: 99.473
          - type: recall_at_1000
            value: 100
          - type: recall_at_3
            value: 89.831
          - type: recall_at_5
            value: 93.256
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/DuRetrieval
          name: MTEB DuRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 27.094
          - type: map_at_10
            value: 82.418
          - type: map_at_100
            value: 85.05
          - type: map_at_1000
            value: 85.083
          - type: map_at_3
            value: 57.68600000000001
          - type: map_at_5
            value: 72.476
          - type: mrr_at_1
            value: 92.25
          - type: mrr_at_10
            value: 94.621
          - type: mrr_at_100
            value: 94.675
          - type: mrr_at_1000
            value: 94.677
          - type: mrr_at_3
            value: 94.375
          - type: mrr_at_5
            value: 94.52199999999999
          - type: ndcg_at_1
            value: 92.25
          - type: ndcg_at_10
            value: 89.13600000000001
          - type: ndcg_at_100
            value: 91.532
          - type: ndcg_at_1000
            value: 91.836
          - type: ndcg_at_3
            value: 88.50099999999999
          - type: ndcg_at_5
            value: 87.251
          - type: precision_at_1
            value: 92.25
          - type: precision_at_10
            value: 42.295
          - type: precision_at_100
            value: 4.812
          - type: precision_at_1000
            value: 0.48900000000000005
          - type: precision_at_3
            value: 79.167
          - type: precision_at_5
            value: 66.56
          - type: recall_at_1
            value: 27.094
          - type: recall_at_10
            value: 89.816
          - type: recall_at_100
            value: 97.855
          - type: recall_at_1000
            value: 99.384
          - type: recall_at_3
            value: 59.557
          - type: recall_at_5
            value: 76.395
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/EcomRetrieval
          name: MTEB EcomRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 53.6
          - type: map_at_10
            value: 62.985
          - type: map_at_100
            value: 63.532999999999994
          - type: map_at_1000
            value: 63.546
          - type: map_at_3
            value: 60.617
          - type: map_at_5
            value: 62.017
          - type: mrr_at_1
            value: 53.6
          - type: mrr_at_10
            value: 62.985
          - type: mrr_at_100
            value: 63.532999999999994
          - type: mrr_at_1000
            value: 63.546
          - type: mrr_at_3
            value: 60.617
          - type: mrr_at_5
            value: 62.017
          - type: ndcg_at_1
            value: 53.6
          - type: ndcg_at_10
            value: 67.755
          - type: ndcg_at_100
            value: 70.366
          - type: ndcg_at_1000
            value: 70.696
          - type: ndcg_at_3
            value: 62.89900000000001
          - type: ndcg_at_5
            value: 65.437
          - type: precision_at_1
            value: 53.6
          - type: precision_at_10
            value: 8.28
          - type: precision_at_100
            value: 0.9490000000000001
          - type: precision_at_1000
            value: 0.098
          - type: precision_at_3
            value: 23.166999999999998
          - type: precision_at_5
            value: 15.14
          - type: recall_at_1
            value: 53.6
          - type: recall_at_10
            value: 82.8
          - type: recall_at_100
            value: 94.89999999999999
          - type: recall_at_1000
            value: 97.5
          - type: recall_at_3
            value: 69.5
          - type: recall_at_5
            value: 75.7
      - task:
          type: Classification
        dataset:
          type: C-MTEB/IFlyTek-classification
          name: MTEB IFlyTek
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 52.104655636783384
          - type: f1
            value: 41.025743582860514
      - task:
          type: Classification
        dataset:
          type: C-MTEB/JDReview-classification
          name: MTEB JDReview
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 88.57410881801127
          - type: ap
            value: 59.49612312498937
          - type: f1
            value: 83.70595013666741
      - task:
          type: STS
        dataset:
          type: C-MTEB/LCQMC
          name: MTEB LCQMC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 74.00327736048256
          - type: cos_sim_spearman
            value: 79.5459672237356
          - type: euclidean_pearson
            value: 79.18300205389669
          - type: euclidean_spearman
            value: 79.21872988987533
          - type: manhattan_pearson
            value: 79.1715470733081
          - type: manhattan_spearman
            value: 79.20756273498812
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/MMarcoRetrieval
          name: MTEB MMarcoRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 66.94600000000001
          - type: map_at_10
            value: 75.947
          - type: map_at_100
            value: 76.268
          - type: map_at_1000
            value: 76.28
          - type: map_at_3
            value: 74.13300000000001
          - type: map_at_5
            value: 75.28399999999999
          - type: mrr_at_1
            value: 69.241
          - type: mrr_at_10
            value: 76.532
          - type: mrr_at_100
            value: 76.816
          - type: mrr_at_1000
            value: 76.827
          - type: mrr_at_3
            value: 74.95
          - type: mrr_at_5
            value: 75.957
          - type: ndcg_at_1
            value: 69.241
          - type: ndcg_at_10
            value: 79.54299999999999
          - type: ndcg_at_100
            value: 80.95
          - type: ndcg_at_1000
            value: 81.252
          - type: ndcg_at_3
            value: 76.119
          - type: ndcg_at_5
            value: 78.069
          - type: precision_at_1
            value: 69.241
          - type: precision_at_10
            value: 9.576
          - type: precision_at_100
            value: 1.026
          - type: precision_at_1000
            value: 0.105
          - type: precision_at_3
            value: 28.571999999999996
          - type: precision_at_5
            value: 18.181
          - type: recall_at_1
            value: 66.94600000000001
          - type: recall_at_10
            value: 90.024
          - type: recall_at_100
            value: 96.3
          - type: recall_at_1000
            value: 98.656
          - type: recall_at_3
            value: 81.026
          - type: recall_at_5
            value: 85.658
      - 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: 77.71015467383997
          - type: f1
            value: 74.32345894845358
      - 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: 85.63214525891055
          - type: f1
            value: 84.65303466003252
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/MedicalRetrieval
          name: MTEB MedicalRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 55.50000000000001
          - type: map_at_10
            value: 61.66199999999999
          - type: map_at_100
            value: 62.13999999999999
          - type: map_at_1000
            value: 62.187000000000005
          - type: map_at_3
            value: 59.967000000000006
          - type: map_at_5
            value: 60.927
          - type: mrr_at_1
            value: 55.7
          - type: mrr_at_10
            value: 61.76199999999999
          - type: mrr_at_100
            value: 62.241
          - type: mrr_at_1000
            value: 62.287000000000006
          - type: mrr_at_3
            value: 60.06700000000001
          - type: mrr_at_5
            value: 61.027
          - type: ndcg_at_1
            value: 55.50000000000001
          - type: ndcg_at_10
            value: 64.878
          - type: ndcg_at_100
            value: 67.464
          - type: ndcg_at_1000
            value: 68.745
          - type: ndcg_at_3
            value: 61.367000000000004
          - type: ndcg_at_5
            value: 63.117999999999995
          - type: precision_at_1
            value: 55.50000000000001
          - type: precision_at_10
            value: 7.51
          - type: precision_at_100
            value: 0.878
          - type: precision_at_1000
            value: 0.098
          - type: precision_at_3
            value: 21.8
          - type: precision_at_5
            value: 13.94
          - type: recall_at_1
            value: 55.50000000000001
          - type: recall_at_10
            value: 75.1
          - type: recall_at_100
            value: 87.8
          - type: recall_at_1000
            value: 97.89999999999999
          - type: recall_at_3
            value: 65.4
          - type: recall_at_5
            value: 69.69999999999999
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/Mmarco-reranking
          name: MTEB MMarcoReranking
          config: default
          split: dev
          revision: None
        metrics:
          - type: map
            value: 33.386980266936106
          - type: mrr
            value: 32.11904761904762
      - task:
          type: Classification
        dataset:
          type: C-MTEB/MultilingualSentiment-classification
          name: MTEB MultilingualSentiment
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 79.08666666666666
          - type: f1
            value: 78.93142205976953
      - task:
          type: PairClassification
        dataset:
          type: C-MTEB/OCNLI
          name: MTEB Ocnli
          config: default
          split: validation
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 84.35300487276665
          - type: cos_sim_ap
            value: 87.83572265803564
          - type: cos_sim_f1
            value: 85.42713567839195
          - type: cos_sim_precision
            value: 81.49568552253116
          - type: cos_sim_recall
            value: 89.7571277719113
          - type: dot_accuracy
            value: 72.87493232268544
          - type: dot_ap
            value: 80.29032993894747
          - type: dot_f1
            value: 76.5938475256353
          - type: dot_precision
            value: 66.28086419753086
          - type: dot_recall
            value: 90.70749736008447
          - type: euclidean_accuracy
            value: 82.34975636166757
          - type: euclidean_ap
            value: 85.73873757468064
          - type: euclidean_f1
            value: 83.56713426853707
          - type: euclidean_precision
            value: 79.50428979980934
          - type: euclidean_recall
            value: 88.0675818373812
          - type: manhattan_accuracy
            value: 82.45804006497022
          - type: manhattan_ap
            value: 85.7176464290469
          - type: manhattan_f1
            value: 83.65095285857572
          - type: manhattan_precision
            value: 79.65616045845272
          - type: manhattan_recall
            value: 88.0675818373812
          - type: max_accuracy
            value: 84.35300487276665
          - type: max_ap
            value: 87.83572265803564
          - type: max_f1
            value: 85.42713567839195
      - task:
          type: Classification
        dataset:
          type: C-MTEB/OnlineShopping-classification
          name: MTEB OnlineShopping
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 94.61999999999999
          - type: ap
            value: 92.74140430219491
          - type: f1
            value: 94.60775857122515
      - task:
          type: STS
        dataset:
          type: C-MTEB/PAWSX
          name: MTEB PAWSX
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 39.75749234575995
          - type: cos_sim_spearman
            value: 46.48035295363829
          - type: euclidean_pearson
            value: 45.38711981599582
          - type: euclidean_spearman
            value: 46.13915356562481
          - type: manhattan_pearson
            value: 45.420770530489065
          - type: manhattan_spearman
            value: 46.179913441143775
      - task:
          type: STS
        dataset:
          type: C-MTEB/QBQTC
          name: MTEB QBQTC
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 44.02008249965321
          - type: cos_sim_spearman
            value: 45.906917552219156
          - type: euclidean_pearson
            value: 36.600317631983316
          - type: euclidean_spearman
            value: 41.97740958824762
          - type: manhattan_pearson
            value: 36.54329048509785
          - type: manhattan_spearman
            value: 41.91222171040451
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (zh)
          config: zh
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 60.97044608578288
          - type: cos_sim_spearman
            value: 63.76187490245927
          - type: euclidean_pearson
            value: 60.74245987426317
          - type: euclidean_spearman
            value: 63.32990713078846
          - type: manhattan_pearson
            value: 60.62422616577702
          - type: manhattan_spearman
            value: 63.256612476686826
      - task:
          type: STS
        dataset:
          type: C-MTEB/STSB
          name: MTEB STSB
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 76.28185867362305
          - type: cos_sim_spearman
            value: 78.71478656159289
          - type: euclidean_pearson
            value: 79.80734359535234
          - type: euclidean_spearman
            value: 79.85403491297063
          - type: manhattan_pearson
            value: 79.79454037962215
          - type: manhattan_spearman
            value: 79.82796402623201
      - task:
          type: Reranking
        dataset:
          type: C-MTEB/T2Reranking
          name: MTEB T2Reranking
          config: default
          split: dev
          revision: None
        metrics:
          - type: map
            value: 67.14759526113295
          - type: mrr
            value: 77.36422096484723
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/T2Retrieval
          name: MTEB T2Retrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 28.177999999999997
          - type: map_at_10
            value: 78.77199999999999
          - type: map_at_100
            value: 82.365
          - type: map_at_1000
            value: 82.422
          - type: map_at_3
            value: 55.452999999999996
          - type: map_at_5
            value: 68.12700000000001
          - type: mrr_at_1
            value: 91.097
          - type: mrr_at_10
            value: 93.52000000000001
          - type: mrr_at_100
            value: 93.587
          - type: mrr_at_1000
            value: 93.589
          - type: mrr_at_3
            value: 93.136
          - type: mrr_at_5
            value: 93.381
          - type: ndcg_at_1
            value: 91.097
          - type: ndcg_at_10
            value: 86.136
          - type: ndcg_at_100
            value: 89.515
          - type: ndcg_at_1000
            value: 90.049
          - type: ndcg_at_3
            value: 87.41600000000001
          - type: ndcg_at_5
            value: 86.115
          - type: precision_at_1
            value: 91.097
          - type: precision_at_10
            value: 42.597
          - type: precision_at_100
            value: 5.043
          - type: precision_at_1000
            value: 0.517
          - type: precision_at_3
            value: 76.239
          - type: precision_at_5
            value: 63.93
          - type: recall_at_1
            value: 28.177999999999997
          - type: recall_at_10
            value: 85.182
          - type: recall_at_100
            value: 96.174
          - type: recall_at_1000
            value: 98.848
          - type: recall_at_3
            value: 57.150999999999996
          - type: recall_at_5
            value: 71.50999999999999
      - task:
          type: Classification
        dataset:
          type: C-MTEB/TNews-classification
          name: MTEB TNews
          config: default
          split: validation
          revision: None
        metrics:
          - type: accuracy
            value: 54.521
          - type: f1
            value: 52.53528052282081
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/ThuNewsClusteringP2P
          name: MTEB ThuNewsClusteringP2P
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 74.2003249023509
      - task:
          type: Clustering
        dataset:
          type: C-MTEB/ThuNewsClusteringS2S
          name: MTEB ThuNewsClusteringS2S
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 68.4277378629746
      - task:
          type: Retrieval
        dataset:
          type: C-MTEB/VideoRetrieval
          name: MTEB VideoRetrieval
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 58.599999999999994
          - type: map_at_10
            value: 68.671
          - type: map_at_100
            value: 69.148
          - type: map_at_1000
            value: 69.157
          - type: map_at_3
            value: 66.9
          - type: map_at_5
            value: 68.045
          - type: mrr_at_1
            value: 58.599999999999994
          - type: mrr_at_10
            value: 68.671
          - type: mrr_at_100
            value: 69.148
          - type: mrr_at_1000
            value: 69.157
          - type: mrr_at_3
            value: 66.9
          - type: mrr_at_5
            value: 68.045
          - type: ndcg_at_1
            value: 58.599999999999994
          - type: ndcg_at_10
            value: 73.099
          - type: ndcg_at_100
            value: 75.33
          - type: ndcg_at_1000
            value: 75.58500000000001
          - type: ndcg_at_3
            value: 69.502
          - type: ndcg_at_5
            value: 71.542
          - type: precision_at_1
            value: 58.599999999999994
          - type: precision_at_10
            value: 8.68
          - type: precision_at_100
            value: 0.97
          - type: precision_at_1000
            value: 0.099
          - type: precision_at_3
            value: 25.667
          - type: precision_at_5
            value: 16.38
          - type: recall_at_1
            value: 58.599999999999994
          - type: recall_at_10
            value: 86.8
          - type: recall_at_100
            value: 97
          - type: recall_at_1000
            value: 99.1
          - type: recall_at_3
            value: 77
          - type: recall_at_5
            value: 81.89999999999999
      - task:
          type: Classification
        dataset:
          type: C-MTEB/waimai-classification
          name: MTEB Waimai
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 89.58999999999999
          - type: ap
            value: 75.69899834265364
          - type: f1
            value: 88.2026184757175

piccolo-large-zh-v2