---
model-index:
- name: text_emb_V1
  results:
  - dataset:
      config: default
      name: MTEB AFQMC (default)
      revision: b44c3b011063adb25877c13823db83bb193913c4
      split: validation
      type: C-MTEB/AFQMC
    metrics:
    - type: pearson
      value: 55.1136
    - type: spearman
      value: 57.1755
    - type: cosine_pearson
      value: 55.1136
    - type: cosine_spearman
      value: 57.1755
    - type: manhattan_pearson
      value: 56.5728
    - type: manhattan_spearman
      value: 57.1558
    - type: euclidean_pearson
      value: 56.6013
    - type: euclidean_spearman
      value: 57.1755
    - type: main_score
      value: 57.1755
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB ATEC (default)
      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
      split: validation
      type: C-MTEB/ATEC
    metrics:
    - type: pearson
      value: 55.882799999999996
    - type: spearman
      value: 56.4007
    - type: cosine_pearson
      value: 55.882799999999996
    - type: cosine_spearman
      value: 56.4007
    - type: manhattan_pearson
      value: 60.958999999999996
    - type: manhattan_spearman
      value: 56.3925
    - type: euclidean_pearson
      value: 60.95080000000001
    - type: euclidean_spearman
      value: 56.4007
    - type: main_score
      value: 56.4007
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB ATEC (default)
      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
      split: test
      type: C-MTEB/ATEC
    metrics:
    - type: pearson
      value: 56.549099999999996
    - type: spearman
      value: 56.425599999999996
    - type: cosine_pearson
      value: 56.549099999999996
    - type: cosine_spearman
      value: 56.425599999999996
    - type: manhattan_pearson
      value: 61.853199999999994
    - type: manhattan_spearman
      value: 56.401199999999996
    - type: euclidean_pearson
      value: 61.8652
    - type: euclidean_spearman
      value: 56.425599999999996
    - type: main_score
      value: 56.425599999999996
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB BQ (default)
      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
      split: validation
      type: C-MTEB/BQ
    metrics:
    - type: pearson
      value: 74.49090000000001
    - type: spearman
      value: 74.3392
    - type: cosine_pearson
      value: 74.49090000000001
    - type: cosine_spearman
      value: 74.3392
    - type: manhattan_pearson
      value: 75.2621
    - type: manhattan_spearman
      value: 74.3669
    - type: euclidean_pearson
      value: 75.24640000000001
    - type: euclidean_spearman
      value: 74.3392
    - type: main_score
      value: 74.3392
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB BQ (default)
      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
      split: test
      type: C-MTEB/BQ
    metrics:
    - type: pearson
      value: 72.0912
    - type: spearman
      value: 72.0973
    - type: cosine_pearson
      value: 72.0912
    - type: cosine_spearman
      value: 72.0973
    - type: manhattan_pearson
      value: 72.6131
    - type: manhattan_spearman
      value: 72.1342
    - type: euclidean_pearson
      value: 72.5862
    - type: euclidean_spearman
      value: 72.0973
    - type: main_score
      value: 72.0973
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB Cmnli (default)
      revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
      split: validation
      type: C-MTEB/CMNLI
    metrics:
    - type: similarity_accuracy
      value: 84.7023
    - type: similarity_accuracy_threshold
      value: 71.7336
    - type: similarity_f1
      value: 85.5698
    - type: similarity_f1_threshold
      value: 70.102
    - type: similarity_precision
      value: 82.3848
    - type: similarity_recall
      value: 89.011
    - type: similarity_ap
      value: 91.9215
    - type: cosine_accuracy
      value: 84.7023
    - type: cosine_accuracy_threshold
      value: 71.7336
    - type: cosine_f1
      value: 85.5698
    - type: cosine_f1_threshold
      value: 70.102
    - type: cosine_precision
      value: 82.3848
    - type: cosine_recall
      value: 89.011
    - type: cosine_ap
      value: 91.9099
    - type: manhattan_accuracy
      value: 84.8467
    - type: manhattan_accuracy_threshold
      value: 1559.3493
    - type: manhattan_f1
      value: 85.589
    - type: manhattan_f1_threshold
      value: 1628.4885
    - type: manhattan_precision
      value: 82.4204
    - type: manhattan_recall
      value: 89.011
    - type: manhattan_ap
      value: 91.9403
    - type: euclidean_accuracy
      value: 84.7023
    - type: euclidean_accuracy_threshold
      value: 75.18820000000001
    - type: euclidean_f1
      value: 85.5698
    - type: euclidean_f1_threshold
      value: 77.3279
    - type: euclidean_precision
      value: 82.3848
    - type: euclidean_recall
      value: 89.011
    - type: euclidean_ap
      value: 91.9099
    - type: dot_accuracy
      value: 84.7023
    - type: dot_accuracy_threshold
      value: 71.7336
    - type: dot_f1
      value: 85.5698
    - type: dot_f1_threshold
      value: 70.102
    - type: dot_precision
      value: 82.3848
    - type: dot_recall
      value: 89.011
    - type: dot_ap
      value: 91.9201
    - type: max_accuracy
      value: 84.8467
    - type: max_f1
      value: 85.589
    - type: max_precision
      value: 82.4204
    - type: max_recall
      value: 89.011
    - type: max_ap
      value: 91.9403
    - type: main_score
      value: 84.8467
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB LCQMC (default)
      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
      split: test
      type: C-MTEB/LCQMC
    metrics:
    - type: pearson
      value: 70.8121
    - type: spearman
      value: 77.81949999999999
    - type: cosine_pearson
      value: 70.8121
    - type: cosine_spearman
      value: 77.81949999999999
    - type: manhattan_pearson
      value: 77.81620000000001
    - type: manhattan_spearman
      value: 77.8609
    - type: euclidean_pearson
      value: 77.8304
    - type: euclidean_spearman
      value: 77.81949999999999
    - type: main_score
      value: 77.81949999999999
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB Ocnli (default)
      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
      split: validation
      type: C-MTEB/OCNLI
    metrics:
    - type: similarity_accuracy
      value: 83.7574
    - type: similarity_accuracy_threshold
      value: 74.45
    - type: similarity_f1
      value: 84.7047
    - type: similarity_f1_threshold
      value: 70.1439
    - type: similarity_precision
      value: 81.1412
    - type: similarity_recall
      value: 88.59559999999999
    - type: similarity_ap
      value: 90.13210000000001
    - type: cosine_accuracy
      value: 83.7574
    - type: cosine_accuracy_threshold
      value: 74.45
    - type: cosine_f1
      value: 84.7047
    - type: cosine_f1_threshold
      value: 70.1439
    - type: cosine_precision
      value: 81.1412
    - type: cosine_recall
      value: 88.59559999999999
    - type: cosine_ap
      value: 90.1322
    - type: manhattan_accuracy
      value: 83.9199
    - type: manhattan_accuracy_threshold
      value: 1496.4575
    - type: manhattan_f1
      value: 84.9772
    - type: manhattan_f1_threshold
      value: 1605.1863
    - type: manhattan_precision
      value: 81.5534
    - type: manhattan_recall
      value: 88.7012
    - type: manhattan_ap
      value: 90.239
    - type: euclidean_accuracy
      value: 83.7574
    - type: euclidean_accuracy_threshold
      value: 71.4842
    - type: euclidean_f1
      value: 84.7047
    - type: euclidean_f1_threshold
      value: 77.2737
    - type: euclidean_precision
      value: 81.1412
    - type: euclidean_recall
      value: 88.59559999999999
    - type: euclidean_ap
      value: 90.13210000000001
    - type: dot_accuracy
      value: 83.7574
    - type: dot_accuracy_threshold
      value: 74.45
    - type: dot_f1
      value: 84.7047
    - type: dot_f1_threshold
      value: 70.1439
    - type: dot_precision
      value: 81.1412
    - type: dot_recall
      value: 88.59559999999999
    - type: dot_ap
      value: 90.1322
    - type: max_accuracy
      value: 83.9199
    - type: max_f1
      value: 84.9772
    - type: max_precision
      value: 81.5534
    - type: max_recall
      value: 88.7012
    - type: max_ap
      value: 90.239
    - type: main_score
      value: 83.9199
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB PAWSX (default)
      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
      split: test
      type: C-MTEB/PAWSX
    metrics:
    - type: pearson
      value: 33.814699999999995
    - type: spearman
      value: 35.4391
    - type: cosine_pearson
      value: 33.814699999999995
    - type: cosine_spearman
      value: 35.4223
    - type: manhattan_pearson
      value: 36.013
    - type: manhattan_spearman
      value: 35.5863
    - type: euclidean_pearson
      value: 35.876999999999995
    - type: euclidean_spearman
      value: 35.436800000000005
    - type: main_score
      value: 35.4223
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB QBQTC (default)
      revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
      split: test
      type: C-MTEB/QBQTC
    metrics:
    - type: pearson
      value: 55.0385
    - type: spearman
      value: 54.0346
    - type: cosine_pearson
      value: 55.0385
    - type: cosine_spearman
      value: 54.0353
    - type: manhattan_pearson
      value: 54.2188
    - type: manhattan_spearman
      value: 54.3934
    - type: euclidean_pearson
      value: 53.8578
    - type: euclidean_spearman
      value: 54.0357
    - type: main_score
      value: 54.0353
    task:
      type: STS
  - dataset:
      config: zh
      name: MTEB STS22 (zh)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: pearson
      value: 35.320499999999996
    - type: spearman
      value: 45.4569
    - type: cosine_pearson
      value: 35.320499999999996
    - type: cosine_spearman
      value: 45.4569
    - type: manhattan_pearson
      value: 39.5784
    - type: manhattan_spearman
      value: 45.2067
    - type: euclidean_pearson
      value: 39.8407
    - type: euclidean_spearman
      value: 45.4569
    - type: main_score
      value: 45.4569
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STSB (default)
      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
      split: validation
      type: C-MTEB/STSB
    metrics:
    - type: pearson
      value: 72.63
    - type: spearman
      value: 74.65039999999999
    - type: cosine_pearson
      value: 72.63
    - type: cosine_spearman
      value: 74.6505
    - type: manhattan_pearson
      value: 75.0128
    - type: manhattan_spearman
      value: 74.558
    - type: euclidean_pearson
      value: 75.0734
    - type: euclidean_spearman
      value: 74.6505
    - type: main_score
      value: 74.6505
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STSB (default)
      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
      split: test
      type: C-MTEB/STSB
    metrics:
    - type: pearson
      value: 72.6558
    - type: spearman
      value: 72.18860000000001
    - type: cosine_pearson
      value: 72.6558
    - type: cosine_spearman
      value: 72.1876
    - type: manhattan_pearson
      value: 73.25540000000001
    - type: manhattan_spearman
      value: 72.0847
    - type: euclidean_pearson
      value: 73.3532
    - type: euclidean_spearman
      value: 72.1878
    - type: main_score
      value: 72.1876
    task:
      type: STS
tags:
- mteb
license: apache-2.0
---