metadata
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