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---
tags:
- mteb
model-index:
- name: piccolo-base-zh
  results:
  - task:
      type: STS
    dataset:
      type: C-MTEB/AFQMC
      name: MTEB AFQMC
      config: default
      split: validation
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 49.16558217326158
    - type: cos_sim_spearman
      value: 51.4049475858823
    - type: euclidean_pearson
      value: 49.85853741070363
    - type: euclidean_spearman
      value: 51.501428092542234
    - type: manhattan_pearson
      value: 49.746099634926296
    - type: manhattan_spearman
      value: 51.41081804320127
  - task:
      type: STS
    dataset:
      type: C-MTEB/ATEC
      name: MTEB ATEC
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 52.385361699031854
    - type: cos_sim_spearman
      value: 52.59114913702212
    - type: euclidean_pearson
      value: 54.994530439418355
    - type: euclidean_spearman
      value: 52.54102886188004
    - type: manhattan_pearson
      value: 54.9503071669608
    - type: manhattan_spearman
      value: 52.51465652540901
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (zh)
      config: zh
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 40.236
    - type: f1
      value: 39.43040092463147
  - task:
      type: STS
    dataset:
      type: C-MTEB/BQ
      name: MTEB BQ
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 60.98952187211432
    - type: cos_sim_spearman
      value: 62.68189713123115
    - type: euclidean_pearson
      value: 61.089426749761344
    - type: euclidean_spearman
      value: 62.41743375544581
    - type: manhattan_pearson
      value: 61.14747216341409
    - type: manhattan_spearman
      value: 62.488918956547046
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/CLSClusteringP2P
      name: MTEB CLSClusteringP2P
      config: default
      split: test
      revision: None
    metrics:
    - type: v_measure
      value: 38.36392300667918
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/CLSClusteringS2S
      name: MTEB CLSClusteringS2S
      config: default
      split: test
      revision: None
    metrics:
    - type: v_measure
      value: 35.645927581489175
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/CMedQAv1-reranking
      name: MTEB CMedQAv1
      config: default
      split: test
      revision: None
    metrics:
    - type: map
      value: 85.25085782849087
    - type: mrr
      value: 87.77154761904762
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/CMedQAv2-reranking
      name: MTEB CMedQAv2
      config: default
      split: test
      revision: None
    metrics:
    - type: map
      value: 86.15357754080844
    - type: mrr
      value: 88.53547619047617
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/CmedqaRetrieval
      name: MTEB CmedqaRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 23.683
    - type: map_at_10
      value: 35.522999999999996
    - type: map_at_100
      value: 37.456
    - type: map_at_1000
      value: 37.576
    - type: map_at_3
      value: 31.584
    - type: map_at_5
      value: 33.684999999999995
    - type: mrr_at_1
      value: 36.459
    - type: mrr_at_10
      value: 44.534
    - type: mrr_at_100
      value: 45.6
    - type: mrr_at_1000
      value: 45.647
    - type: mrr_at_3
      value: 42.186
    - type: mrr_at_5
      value: 43.482
    - type: ndcg_at_1
      value: 36.459
    - type: ndcg_at_10
      value: 42.025
    - type: ndcg_at_100
      value: 49.754
    - type: ndcg_at_1000
      value: 51.815999999999995
    - type: ndcg_at_3
      value: 37.056
    - type: ndcg_at_5
      value: 38.962
    - type: precision_at_1
      value: 36.459
    - type: precision_at_10
      value: 9.485000000000001
    - type: precision_at_100
      value: 1.567
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 21.13
    - type: precision_at_5
      value: 15.209
    - type: recall_at_1
      value: 23.683
    - type: recall_at_10
      value: 52.190999999999995
    - type: recall_at_100
      value: 84.491
    - type: recall_at_1000
      value: 98.19600000000001
    - type: recall_at_3
      value: 37.09
    - type: recall_at_5
      value: 43.262
  - task:
      type: PairClassification
    dataset:
      type: C-MTEB/CMNLI
      name: MTEB Cmnli
      config: default
      split: validation
      revision: None
    metrics:
    - type: cos_sim_accuracy
      value: 74.20324714371618
    - type: cos_sim_ap
      value: 82.32631646194994
    - type: cos_sim_f1
      value: 76.64052827073876
    - type: cos_sim_precision
      value: 68.58725761772854
    - type: cos_sim_recall
      value: 86.83656768763151
    - type: dot_accuracy
      value: 70.33072760072159
    - type: dot_ap
      value: 77.46972172609794
    - type: dot_f1
      value: 73.6668924804026
    - type: dot_precision
      value: 62.84676354029062
    - type: dot_recall
      value: 88.98760813654431
    - type: euclidean_accuracy
      value: 74.78051713770296
    - type: euclidean_ap
      value: 82.65778389584023
    - type: euclidean_f1
      value: 77.1843623157445
    - type: euclidean_precision
      value: 71.05211406096362
    - type: euclidean_recall
      value: 84.47509936871639
    - type: manhattan_accuracy
      value: 74.76849067949489
    - type: manhattan_ap
      value: 82.55694030572194
    - type: manhattan_f1
      value: 77.1776459569154
    - type: manhattan_precision
      value: 69.5423855963991
    - type: manhattan_recall
      value: 86.69628244096329
    - type: max_accuracy
      value: 74.78051713770296
    - type: max_ap
      value: 82.65778389584023
    - type: max_f1
      value: 77.1843623157445
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/CovidRetrieval
      name: MTEB CovidRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 72.99799999999999
    - type: map_at_10
      value: 81.271
    - type: map_at_100
      value: 81.53399999999999
    - type: map_at_1000
      value: 81.535
    - type: map_at_3
      value: 80.049
    - type: map_at_5
      value: 80.793
    - type: mrr_at_1
      value: 73.13
    - type: mrr_at_10
      value: 81.193
    - type: mrr_at_100
      value: 81.463
    - type: mrr_at_1000
      value: 81.464
    - type: mrr_at_3
      value: 80.067
    - type: mrr_at_5
      value: 80.741
    - type: ndcg_at_1
      value: 73.34
    - type: ndcg_at_10
      value: 84.503
    - type: ndcg_at_100
      value: 85.643
    - type: ndcg_at_1000
      value: 85.693
    - type: ndcg_at_3
      value: 82.135
    - type: ndcg_at_5
      value: 83.401
    - type: precision_at_1
      value: 73.34
    - type: precision_at_10
      value: 9.536
    - type: precision_at_100
      value: 1.004
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 29.54
    - type: precision_at_5
      value: 18.398
    - type: recall_at_1
      value: 72.99799999999999
    - type: recall_at_10
      value: 94.31
    - type: recall_at_100
      value: 99.368
    - type: recall_at_1000
      value: 99.789
    - type: recall_at_3
      value: 87.935
    - type: recall_at_5
      value: 90.991
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/DuRetrieval
      name: MTEB DuRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 26.537
    - type: map_at_10
      value: 81.292
    - type: map_at_100
      value: 84.031
    - type: map_at_1000
      value: 84.066
    - type: map_at_3
      value: 56.571000000000005
    - type: map_at_5
      value: 71.082
    - type: mrr_at_1
      value: 91.2
    - type: mrr_at_10
      value: 93.893
    - type: mrr_at_100
      value: 93.955
    - type: mrr_at_1000
      value: 93.95700000000001
    - type: mrr_at_3
      value: 93.61699999999999
    - type: mrr_at_5
      value: 93.767
    - type: ndcg_at_1
      value: 91.2
    - type: ndcg_at_10
      value: 88.255
    - type: ndcg_at_100
      value: 90.813
    - type: ndcg_at_1000
      value: 91.144
    - type: ndcg_at_3
      value: 87.435
    - type: ndcg_at_5
      value: 85.961
    - type: precision_at_1
      value: 91.2
    - type: precision_at_10
      value: 42.14
    - type: precision_at_100
      value: 4.817
    - type: precision_at_1000
      value: 0.48900000000000005
    - type: precision_at_3
      value: 78.467
    - type: precision_at_5
      value: 65.75999999999999
    - type: recall_at_1
      value: 26.537
    - type: recall_at_10
      value: 89.262
    - type: recall_at_100
      value: 97.783
    - type: recall_at_1000
      value: 99.49799999999999
    - type: recall_at_3
      value: 58.573
    - type: recall_at_5
      value: 75.154
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/EcomRetrieval
      name: MTEB EcomRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 48.5
    - type: map_at_10
      value: 57.898
    - type: map_at_100
      value: 58.599000000000004
    - type: map_at_1000
      value: 58.616
    - type: map_at_3
      value: 55.1
    - type: map_at_5
      value: 56.80500000000001
    - type: mrr_at_1
      value: 48.5
    - type: mrr_at_10
      value: 57.898
    - type: mrr_at_100
      value: 58.599000000000004
    - type: mrr_at_1000
      value: 58.616
    - type: mrr_at_3
      value: 55.1
    - type: mrr_at_5
      value: 56.80500000000001
    - type: ndcg_at_1
      value: 48.5
    - type: ndcg_at_10
      value: 62.876
    - type: ndcg_at_100
      value: 66.00200000000001
    - type: ndcg_at_1000
      value: 66.467
    - type: ndcg_at_3
      value: 57.162
    - type: ndcg_at_5
      value: 60.263999999999996
    - type: precision_at_1
      value: 48.5
    - type: precision_at_10
      value: 7.870000000000001
    - type: precision_at_100
      value: 0.927
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 21.032999999999998
    - type: precision_at_5
      value: 14.14
    - type: recall_at_1
      value: 48.5
    - type: recall_at_10
      value: 78.7
    - type: recall_at_100
      value: 92.7
    - type: recall_at_1000
      value: 96.39999999999999
    - type: recall_at_3
      value: 63.1
    - type: recall_at_5
      value: 70.7
  - task:
      type: Classification
    dataset:
      type: C-MTEB/IFlyTek-classification
      name: MTEB IFlyTek
      config: default
      split: validation
      revision: None
    metrics:
    - type: accuracy
      value: 44.34782608695652
    - type: f1
      value: 36.401426200836205
  - task:
      type: Classification
    dataset:
      type: C-MTEB/JDReview-classification
      name: MTEB JDReview
      config: default
      split: test
      revision: None
    metrics:
    - type: accuracy
      value: 84.25891181988743
    - type: ap
      value: 50.54636280166089
    - type: f1
      value: 78.55080202541332
  - task:
      type: STS
    dataset:
      type: C-MTEB/LCQMC
      name: MTEB LCQMC
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 70.02878561337955
    - type: cos_sim_spearman
      value: 75.39509553139982
    - type: euclidean_pearson
      value: 73.92598696939956
    - type: euclidean_spearman
      value: 75.5471147196853
    - type: manhattan_pearson
      value: 73.88049486090739
    - type: manhattan_spearman
      value: 75.51361990583285
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/MMarcoRetrieval
      name: MTEB MMarcoRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 64.739
    - type: map_at_10
      value: 74.039
    - type: map_at_100
      value: 74.38
    - type: map_at_1000
      value: 74.39099999999999
    - type: map_at_3
      value: 72.074
    - type: map_at_5
      value: 73.29299999999999
    - type: mrr_at_1
      value: 66.92
    - type: mrr_at_10
      value: 74.636
    - type: mrr_at_100
      value: 74.94
    - type: mrr_at_1000
      value: 74.95
    - type: mrr_at_3
      value: 72.911
    - type: mrr_at_5
      value: 73.981
    - type: ndcg_at_1
      value: 66.92
    - type: ndcg_at_10
      value: 77.924
    - type: ndcg_at_100
      value: 79.471
    - type: ndcg_at_1000
      value: 79.73400000000001
    - type: ndcg_at_3
      value: 74.17200000000001
    - type: ndcg_at_5
      value: 76.236
    - type: precision_at_1
      value: 66.92
    - type: precision_at_10
      value: 9.5
    - type: precision_at_100
      value: 1.027
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 27.989000000000004
    - type: precision_at_5
      value: 17.874000000000002
    - type: recall_at_1
      value: 64.739
    - type: recall_at_10
      value: 89.324
    - type: recall_at_100
      value: 96.342
    - type: recall_at_1000
      value: 98.38900000000001
    - type: recall_at_3
      value: 79.378
    - type: recall_at_5
      value: 84.28099999999999
  - 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: 68.97108271687962
    - type: f1
      value: 66.8625981386677
  - 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: 73.32212508406187
    - type: f1
      value: 73.33875034670166
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/MedicalRetrieval
      name: MTEB MedicalRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 49.0
    - type: map_at_10
      value: 55.022999999999996
    - type: map_at_100
      value: 55.550999999999995
    - type: map_at_1000
      value: 55.608000000000004
    - type: map_at_3
      value: 53.417
    - type: map_at_5
      value: 54.372
    - type: mrr_at_1
      value: 49.3
    - type: mrr_at_10
      value: 55.176
    - type: mrr_at_100
      value: 55.703
    - type: mrr_at_1000
      value: 55.76
    - type: mrr_at_3
      value: 53.567
    - type: mrr_at_5
      value: 54.522000000000006
    - type: ndcg_at_1
      value: 49.0
    - type: ndcg_at_10
      value: 58.089999999999996
    - type: ndcg_at_100
      value: 60.988
    - type: ndcg_at_1000
      value: 62.580999999999996
    - type: ndcg_at_3
      value: 54.803000000000004
    - type: ndcg_at_5
      value: 56.508
    - type: precision_at_1
      value: 49.0
    - type: precision_at_10
      value: 6.78
    - type: precision_at_100
      value: 0.8210000000000001
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 19.6
    - type: precision_at_5
      value: 12.58
    - type: recall_at_1
      value: 49.0
    - type: recall_at_10
      value: 67.80000000000001
    - type: recall_at_100
      value: 82.1
    - type: recall_at_1000
      value: 94.8
    - type: recall_at_3
      value: 58.8
    - type: recall_at_5
      value: 62.9
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/Mmarco-reranking
      name: MTEB MMarcoReranking
      config: default
      split: dev
      revision: None
    metrics:
    - type: map
      value: 28.87237408060796
    - type: mrr
      value: 27.83015873015873
  - task:
      type: Classification
    dataset:
      type: C-MTEB/MultilingualSentiment-classification
      name: MTEB MultilingualSentiment
      config: default
      split: validation
      revision: None
    metrics:
    - type: accuracy
      value: 70.25
    - type: f1
      value: 70.29055400149645
  - task:
      type: PairClassification
    dataset:
      type: C-MTEB/OCNLI
      name: MTEB Ocnli
      config: default
      split: validation
      revision: None
    metrics:
    - type: cos_sim_accuracy
      value: 65.56578234975636
    - type: cos_sim_ap
      value: 70.89354058570412
    - type: cos_sim_f1
      value: 71.21024370095002
    - type: cos_sim_precision
      value: 58.48032564450475
    - type: cos_sim_recall
      value: 91.02428722280888
    - type: dot_accuracy
      value: 64.86193827828912
    - type: dot_ap
      value: 70.17697803463875
    - type: dot_f1
      value: 70.68676716917922
    - type: dot_precision
      value: 58.57043719639139
    - type: dot_recall
      value: 89.1235480464625
    - type: euclidean_accuracy
      value: 64.86193827828912
    - type: euclidean_ap
      value: 70.26847152773904
    - type: euclidean_f1
      value: 70.9984152139461
    - type: euclidean_precision
      value: 56.81674064679771
    - type: euclidean_recall
      value: 94.61457233368532
    - type: manhattan_accuracy
      value: 65.40335679480238
    - type: manhattan_ap
      value: 70.22941558736018
    - type: manhattan_f1
      value: 71.09712937475423
    - type: manhattan_precision
      value: 56.64160401002506
    - type: manhattan_recall
      value: 95.45934530095037
    - type: max_accuracy
      value: 65.56578234975636
    - type: max_ap
      value: 70.89354058570412
    - type: max_f1
      value: 71.21024370095002
  - task:
      type: Classification
    dataset:
      type: C-MTEB/OnlineShopping-classification
      name: MTEB OnlineShopping
      config: default
      split: test
      revision: None
    metrics:
    - type: accuracy
      value: 89.92999999999999
    - type: ap
      value: 87.16059195012956
    - type: f1
      value: 89.90917477839415
  - task:
      type: STS
    dataset:
      type: C-MTEB/PAWSX
      name: MTEB PAWSX
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 27.74161502387672
    - type: cos_sim_spearman
      value: 31.58353529723325
    - type: euclidean_pearson
      value: 32.43729673844635
    - type: euclidean_spearman
      value: 31.59527486602242
    - type: manhattan_pearson
      value: 32.37467059678786
    - type: manhattan_spearman
      value: 31.44408004951894
  - task:
      type: STS
    dataset:
      type: C-MTEB/QBQTC
      name: MTEB QBQTC
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 36.233749845501194
    - type: cos_sim_spearman
      value: 36.47808586229587
    - type: euclidean_pearson
      value: 32.663447466546806
    - type: euclidean_spearman
      value: 34.45830454037139
    - type: manhattan_pearson
      value: 32.80239212096335
    - type: manhattan_spearman
      value: 34.581060433895125
  - 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: 63.05131937664673
    - type: cos_sim_spearman
      value: 66.51353746725948
    - type: euclidean_pearson
      value: 61.24016998745561
    - type: euclidean_spearman
      value: 66.07115266049276
    - type: manhattan_pearson
      value: 64.55660243659054
    - type: manhattan_spearman
      value: 66.80282149562386
  - task:
      type: STS
    dataset:
      type: C-MTEB/STSB
      name: MTEB STSB
      config: default
      split: test
      revision: None
    metrics:
    - type: cos_sim_pearson
      value: 70.45533692882996
    - type: cos_sim_spearman
      value: 70.6045637565602
    - type: euclidean_pearson
      value: 72.75588977483554
    - type: euclidean_spearman
      value: 73.36630581886473
    - type: manhattan_pearson
      value: 72.72517409326954
    - type: manhattan_spearman
      value: 73.35358940437355
  - task:
      type: Reranking
    dataset:
      type: C-MTEB/T2Reranking
      name: MTEB T2Reranking
      config: default
      split: dev
      revision: None
    metrics:
    - type: map
      value: 66.45779474032288
    - type: mrr
      value: 76.0782192023729
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/T2Retrieval
      name: MTEB T2Retrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 26.458
    - type: map_at_10
      value: 74.355
    - type: map_at_100
      value: 78.158
    - type: map_at_1000
      value: 78.233
    - type: map_at_3
      value: 52.2
    - type: map_at_5
      value: 64.14
    - type: mrr_at_1
      value: 88.37
    - type: mrr_at_10
      value: 91.117
    - type: mrr_at_100
      value: 91.231
    - type: mrr_at_1000
      value: 91.23599999999999
    - type: mrr_at_3
      value: 90.645
    - type: mrr_at_5
      value: 90.948
    - type: ndcg_at_1
      value: 88.37
    - type: ndcg_at_10
      value: 82.384
    - type: ndcg_at_100
      value: 86.431
    - type: ndcg_at_1000
      value: 87.163
    - type: ndcg_at_3
      value: 83.993
    - type: ndcg_at_5
      value: 82.411
    - type: precision_at_1
      value: 88.37
    - type: precision_at_10
      value: 41.131
    - type: precision_at_100
      value: 4.9799999999999995
    - type: precision_at_1000
      value: 0.515
    - type: precision_at_3
      value: 73.651
    - type: precision_at_5
      value: 61.634
    - type: recall_at_1
      value: 26.458
    - type: recall_at_10
      value: 81.3
    - type: recall_at_100
      value: 94.342
    - type: recall_at_1000
      value: 98.103
    - type: recall_at_3
      value: 54.020999999999994
    - type: recall_at_5
      value: 67.781
  - task:
      type: Classification
    dataset:
      type: C-MTEB/TNews-classification
      name: MTEB TNews
      config: default
      split: validation
      revision: None
    metrics:
    - type: accuracy
      value: 46.814
    - type: f1
      value: 45.580027683507666
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/ThuNewsClusteringP2P
      name: MTEB ThuNewsClusteringP2P
      config: default
      split: test
      revision: None
    metrics:
    - type: v_measure
      value: 61.43613064816144
  - task:
      type: Clustering
    dataset:
      type: C-MTEB/ThuNewsClusteringS2S
      name: MTEB ThuNewsClusteringS2S
      config: default
      split: test
      revision: None
    metrics:
    - type: v_measure
      value: 53.01838461793776
  - task:
      type: Retrieval
    dataset:
      type: C-MTEB/VideoRetrieval
      name: MTEB VideoRetrieval
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 59.3
    - type: map_at_10
      value: 69.158
    - type: map_at_100
      value: 69.60300000000001
    - type: map_at_1000
      value: 69.611
    - type: map_at_3
      value: 67.467
    - type: map_at_5
      value: 68.432
    - type: mrr_at_1
      value: 59.199999999999996
    - type: mrr_at_10
      value: 69.108
    - type: mrr_at_100
      value: 69.553
    - type: mrr_at_1000
      value: 69.56099999999999
    - type: mrr_at_3
      value: 67.417
    - type: mrr_at_5
      value: 68.382
    - type: ndcg_at_1
      value: 59.3
    - type: ndcg_at_10
      value: 73.54
    - type: ndcg_at_100
      value: 75.652
    - type: ndcg_at_1000
      value: 75.868
    - type: ndcg_at_3
      value: 70.074
    - type: ndcg_at_5
      value: 71.808
    - type: precision_at_1
      value: 59.3
    - type: precision_at_10
      value: 8.709999999999999
    - type: precision_at_100
      value: 0.9690000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 25.867
    - type: precision_at_5
      value: 16.36
    - type: recall_at_1
      value: 59.3
    - type: recall_at_10
      value: 87.1
    - type: recall_at_100
      value: 96.89999999999999
    - type: recall_at_1000
      value: 98.6
    - type: recall_at_3
      value: 77.60000000000001
    - type: recall_at_5
      value: 81.8
  - task:
      type: Classification
    dataset:
      type: C-MTEB/waimai-classification
      name: MTEB Waimai
      config: default
      split: test
      revision: None
    metrics:
    - type: accuracy
      value: 84.69999999999999
    - type: ap
      value: 66.65020528563207
    - type: f1
      value: 83.00542769081453
---

## piccolo-base-zh

piccolo是一个通用embedding模型, 由来自商汤科技的通用模型组完成训练。piccolo借鉴了E5以及GTE的训练流程,采用了两阶段的训练方式。
在第一阶段中,我们搜集和爬取了4亿的中文文本对(可视为弱监督文本对数据),并采用二元组的softmax对比学习损失来优化模型。
在第二阶段中,我们从互联网搜集了2000万人工标注的中文文本对(精标数据),并采用带有难负样本的三元组的softmax对比学习损失来帮助模型更好地优化。
目前,我们提供了piccolo-base-zh和piccolo-large-zh两个模型。

piccolo is a general text embedding model, powered by General Model Group from SenseTime Research. 
Based on BERT framework, piccolo is trained using a two stage pipeline. On the first stage, we collect and crawl 400 million weakly supervised Chinese text pairs from the Internet, 
and train the model with the pair(text and text pos) softmax contrastive loss. 
On the second stage, we collect 20 million human labeled chinese text pairs from the open-source dataset, and finetune the model with tiplet (text, text_pos, text_neg) contrastive loss. 
Currently here we offer two different sizes of models, including piccolo-base-zh, piccolo-large-zh. 

## Metric
我们将piccolo与其他的开源embedding模型在CMTEB榜单上进行了比较,请参考CMTEB榜单。我们在eval文件夹中提供了复现结果的脚本。
We compared the performance of the piccolo with other embedding models on the C-MTEB benchmark. please refer to the C-MTEB leaderboard. wo provide scripts in "eval" folder for results reproducing.


| Model Name | Model Size (GB) | Dimension | Sequence Length | Average (35) | Classification (9) | Clustering (4) | Pair Classification (2) | Reranking (4) | Retrieval (8) | STS (8) |
|:----:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
| [**piccolo-large-zh**] | 0.65 | 1024 | 512 | **64.11** | 67.03 | 47.04 | 78.38 | 65.98 | 70.93 | 58.02 |
| [bge-large-zh]| 1.3 | 1024| 512 | 63.96 | 68.32 | 48.39 | 78.94 | 65.11 | 71.52 | 54.98 |
| [**piccolo-base-zh**]| 0.2 | 768 | 512 | **63.66** | 66.98 | 47.12 | 76.61 | 66.68 | 71.2 | 55.9 |
| [bge-large-zh-no-instruct]| 1.3 | 1024 | 512 | 63.4 | 68.58 | 50.01 | 76.77 | 64.9 | 70.54 | 53 |
| [bge-base-zh]| 0.41 | 768 | 512 | 62.8 | 67.07 | 47.64 | 77.5 | 64.91 | 69.53 | 54.12 |