Update README.md

README.md

@@ -1,3 +1,1261 @@
----
-license: apache-2.0
----
+---
+model-index:
+- name: Yuan-embedding-1.0
+  results:
+  - dataset:
+      config: default
+      name: MTEB AFQMC (default)
+      revision: None
+      split: validation
+      type: C-MTEB/AFQMC
+    metrics:
+    - type: cosine_pearson
+      value: 56.398777687800596
+    - type: cosine_spearman
+      value: 60.2976392017466
+    - type: manhattan_pearson
+      value: 58.34432755369896
+    - type: manhattan_spearman
+      value: 59.633715024557176
+    - type: euclidean_pearson
+      value: 58.33199470250656
+    - type: euclidean_spearman
+      value: 59.633393360323595
+    - type: main_score
+      value: 60.2976392017466
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB ATEC (default)
+      revision: None
+      split: test
+      type: C-MTEB/ATEC
+    metrics:
+    - type: cosine_pearson
+      value: 56.418711941754694
+    - type: cosine_spearman
+      value: 58.49782527525838
+    - type: manhattan_pearson
+      value: 62.05335398720773
+    - type: manhattan_spearman
+      value: 58.18176592298454
+    - type: euclidean_pearson
+      value: 62.06479799788818
+    - type: euclidean_spearman
+      value: 58.18182671971488
+    - type: main_score
+      value: 58.49782527525838
+    task:
+      type: STS
+  - dataset:
+      config: zh
+      name: MTEB AmazonReviewsClassification (zh)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: test
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 46.656000000000006
+    - type: accuracy_stderr
+      value: 1.1704631561907444
+    - type: f1
+      value: 45.75911645865614
+    - type: f1_stderr
+      value: 1.323301406018355
+    - type: main_score
+      value: 46.656000000000006
+    task:
+      type: Classification
+  - dataset:
+      config: zh
+      name: MTEB AmazonReviewsClassification (zh)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: validation
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 45.84599999999999
+    - type: accuracy_stderr
+      value: 1.0539468677310073
+    - type: f1
+      value: 45.03273670979488
+    - type: f1_stderr
+      value: 1.00417269917164
+    - type: main_score
+      value: 45.84599999999999
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB BQ (default)
+      revision: None
+      split: test
+      type: C-MTEB/BQ
+    metrics:
+    - type: cosine_pearson
+      value: 71.33099160181597
+    - type: cosine_spearman
+      value: 73.06963287952199
+    - type: manhattan_pearson
+      value: 70.65314181752566
+    - type: manhattan_spearman
+      value: 72.34604440078336
+    - type: euclidean_pearson
+      value: 70.67624292501411
+    - type: euclidean_spearman
+      value: 72.3597691712343
+    - type: main_score
+      value: 73.06963287952199
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB CLSClusteringP2P (default)
+      revision: None
+      split: test
+      type: C-MTEB/CLSClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 53.79921861868626
+    - type: v_measure_std
+      value: 2.073016548125077
+    - type: main_score
+      value: 53.79921861868626
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB CLSClusteringS2S (default)
+      revision: None
+      split: test
+      type: C-MTEB/CLSClusteringS2S
+    metrics:
+    - type: v_measure
+      value: 46.22496957569903
+    - type: v_measure_std
+      value: 1.4660184854965337
+    - type: main_score
+      value: 46.22496957569903
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB CMedQAv1-reranking (default)
+      revision: None
+      split: test
+      type: C-MTEB/CMedQAv1-reranking
+    metrics:
+    - type: map
+      value: 90.00883554654739
+    - type: mrr
+      value: 92.02547619047618
+    - type: main_score
+      value: 90.00883554654739
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB CMedQAv2-reranking (default)
+      revision: None
+      split: test
+      type: C-MTEB/CMedQAv2-reranking
+    metrics:
+    - type: map
+      value: 92.47561424216632
+    - type: mrr
+      value: 94.60039682539681
+    - type: main_score
+      value: 92.47561424216632
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB CmedqaRetrieval (default)
+      revision: None
+      split: dev
+      type: C-MTEB/CmedqaRetrieval
+    metrics:
+    - type: map_at_1
+      value: 29.935000000000002
+    - type: map_at_10
+      value: 44.143
+    - type: map_at_100
+      value: 45.999
+    - type: map_at_1000
+      value: 46.084
+    - type: map_at_3
+      value: 39.445
+    - type: map_at_5
+      value: 42.218
+    - type: mrr_at_1
+      value: 44.711
+    - type: mrr_at_10
+      value: 53.88699999999999
+    - type: mrr_at_100
+      value: 54.813
+    - type: mrr_at_1000
+      value: 54.834
+    - type: mrr_at_3
+      value: 51.1
+    - type: mrr_at_5
+      value: 52.827
+    - type: ndcg_at_1
+      value: 44.711
+    - type: ndcg_at_10
+      value: 51.471999999999994
+    - type: ndcg_at_100
+      value: 58.362
+    - type: ndcg_at_1000
+      value: 59.607
+    - type: ndcg_at_3
+      value: 45.558
+    - type: ndcg_at_5
+      value: 48.345
+    - type: precision_at_1
+      value: 44.711
+    - type: precision_at_10
+      value: 11.1
+    - type: precision_at_100
+      value: 1.6650000000000003
+    - type: precision_at_1000
+      value: 0.184
+    - type: precision_at_3
+      value: 25.306
+    - type: precision_at_5
+      value: 18.404999999999998
+    - type: recall_at_1
+      value: 29.935000000000002
+    - type: recall_at_10
+      value: 63.366
+    - type: recall_at_100
+      value: 91.375
+    - type: recall_at_1000
+      value: 99.167
+    - type: recall_at_3
+      value: 45.888
+    - type: recall_at_5
+      value: 54.169
+    - type: main_score
+      value: 51.471999999999994
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB Cmnli (default)
+      revision: None
+      split: validation
+      type: C-MTEB/CMNLI
+    metrics:
+    - type: cos_sim_accuracy
+      value: 80.3968731208659
+    - type: cos_sim_accuracy_threshold
+      value: 86.61384582519531
+    - type: cos_sim_ap
+      value: 88.21894124132636
+    - type: cos_sim_f1
+      value: 81.67308750687947
+    - type: cos_sim_f1_threshold
+      value: 86.04017496109009
+    - type: cos_sim_precision
+      value: 77.1630615640599
+    - type: cos_sim_recall
+      value: 86.7430441898527
+    - type: dot_accuracy
+      value: 67.7931449188214
+    - type: dot_accuracy_threshold
+      value: 92027.47802734375
+    - type: dot_ap
+      value: 75.73048600318765
+    - type: dot_f1
+      value: 71.64554512914772
+    - type: dot_f1_threshold
+      value: 83535.70556640625
+    - type: dot_precision
+      value: 61.1056105610561
+    - type: dot_recall
+      value: 86.57937806873977
+    - type: euclidean_accuracy
+      value: 78.52074564040889
+    - type: euclidean_accuracy_threshold
+      value: 1688.486671447754
+    - type: euclidean_ap
+      value: 86.40643721988414
+    - type: euclidean_f1
+      value: 79.97822536744692
+    - type: euclidean_f1_threshold
+      value: 1748.1914520263672
+    - type: euclidean_precision
+      value: 74.83700081499592
+    - type: euclidean_recall
+      value: 85.87795183539865
+    - type: manhattan_accuracy
+      value: 78.59290438965725
+    - type: manhattan_accuracy_threshold
+      value: 57066.162109375
+    - type: manhattan_ap
+      value: 86.38300352696045
+    - type: manhattan_f1
+      value: 79.84587391630097
+    - type: manhattan_f1_threshold
+      value: 59686.376953125
+    - type: manhattan_precision
+      value: 73.62810896170548
+    - type: manhattan_recall
+      value: 87.21066167874679
+    - type: max_accuracy
+      value: 80.3968731208659
+    - type: max_ap
+      value: 88.21894124132636
+    - type: max_f1
+      value: 81.67308750687947
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB CovidRetrieval (default)
+      revision: None
+      split: dev
+      type: C-MTEB/CovidRetrieval
+    metrics:
+    - type: map_at_1
+      value: 85.485
+    - type: map_at_10
+      value: 91.135
+    - type: map_at_100
+      value: 91.16199999999999
+    - type: map_at_1000
+      value: 91.16300000000001
+    - type: map_at_3
+      value: 90.499
+    - type: map_at_5
+      value: 90.91
+    - type: mrr_at_1
+      value: 85.88
+    - type: mrr_at_10
+      value: 91.133
+    - type: mrr_at_100
+      value: 91.16
+    - type: mrr_at_1000
+      value: 91.161
+    - type: mrr_at_3
+      value: 90.551
+    - type: mrr_at_5
+      value: 90.904
+    - type: ndcg_at_1
+      value: 85.88
+    - type: ndcg_at_10
+      value: 93.163
+    - type: ndcg_at_100
+      value: 93.282
+    - type: ndcg_at_1000
+      value: 93.309
+    - type: ndcg_at_3
+      value: 91.943
+    - type: ndcg_at_5
+      value: 92.637
+    - type: precision_at_1
+      value: 85.88
+    - type: precision_at_10
+      value: 10.032
+    - type: precision_at_100
+      value: 1.008
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 32.315
+    - type: precision_at_5
+      value: 19.747
+    - type: recall_at_1
+      value: 85.485
+    - type: recall_at_10
+      value: 99.262
+    - type: recall_at_100
+      value: 99.789
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 95.96900000000001
+    - type: recall_at_5
+      value: 97.682
+    - type: main_score
+      value: 93.163
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB DuRetrieval (default)
+      revision: None
+      split: dev
+      type: C-MTEB/DuRetrieval
+    metrics:
+    - type: map_at_1
+      value: 27.29
+    - type: map_at_10
+      value: 82.832
+    - type: map_at_100
+      value: 85.482
+    - type: map_at_1000
+      value: 85.52
+    - type: map_at_3
+      value: 57.964000000000006
+    - type: map_at_5
+      value: 72.962
+    - type: mrr_at_1
+      value: 92.35
+    - type: mrr_at_10
+      value: 94.77499999999999
+    - type: mrr_at_100
+      value: 94.825
+    - type: mrr_at_1000
+      value: 94.827
+    - type: mrr_at_3
+      value: 94.50800000000001
+    - type: mrr_at_5
+      value: 94.688
+    - type: ndcg_at_1
+      value: 92.35
+    - type: ndcg_at_10
+      value: 89.432
+    - type: ndcg_at_100
+      value: 91.813
+    - type: ndcg_at_1000
+      value: 92.12
+    - type: ndcg_at_3
+      value: 88.804
+    - type: ndcg_at_5
+      value: 87.681
+    - type: precision_at_1
+      value: 92.35
+    - type: precision_at_10
+      value: 42.32
+    - type: precision_at_100
+      value: 4.812
+    - type: precision_at_1000
+      value: 0.48900000000000005
+    - type: precision_at_3
+      value: 79.367
+    - type: precision_at_5
+      value: 66.86999999999999
+    - type: recall_at_1
+      value: 27.29
+    - type: recall_at_10
+      value: 90.093
+    - type: recall_at_100
+      value: 97.916
+    - type: recall_at_1000
+      value: 99.40299999999999
+    - type: recall_at_3
+      value: 59.816
+    - type: recall_at_5
+      value: 76.889
+    - type: main_score
+      value: 89.432
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB EcomRetrieval (default)
+      revision: None
+      split: dev
+      type: C-MTEB/EcomRetrieval
+    metrics:
+    - type: map_at_1
+      value: 55.2
+    - type: map_at_10
+      value: 65.767
+    - type: map_at_100
+      value: 66.208
+    - type: map_at_1000
+      value: 66.219
+    - type: map_at_3
+      value: 63.1
+    - type: map_at_5
+      value: 64.865
+    - type: mrr_at_1
+      value: 55.2
+    - type: mrr_at_10
+      value: 65.767
+    - type: mrr_at_100
+      value: 66.208
+    - type: mrr_at_1000
+      value: 66.219
+    - type: mrr_at_3
+      value: 63.1
+    - type: mrr_at_5
+      value: 64.865
+    - type: ndcg_at_1
+      value: 55.2
+    - type: ndcg_at_10
+      value: 70.875
+    - type: ndcg_at_100
+      value: 72.931
+    - type: ndcg_at_1000
+      value: 73.2
+    - type: ndcg_at_3
+      value: 65.526
+    - type: ndcg_at_5
+      value: 68.681
+    - type: precision_at_1
+      value: 55.2
+    - type: precision_at_10
+      value: 8.690000000000001
+    - type: precision_at_100
+      value: 0.963
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 24.166999999999998
+    - type: precision_at_5
+      value: 16.02
+    - type: recall_at_1
+      value: 55.2
+    - type: recall_at_10
+      value: 86.9
+    - type: recall_at_100
+      value: 96.3
+    - type: recall_at_1000
+      value: 98.4
+    - type: recall_at_3
+      value: 72.5
+    - type: recall_at_5
+      value: 80.10000000000001
+    - type: main_score
+      value: 70.875
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB IFlyTek (default)
+      revision: None
+      split: validation
+      type: C-MTEB/IFlyTek-classification
+    metrics:
+    - type: accuracy
+      value: 46.95652173913043
+    - type: accuracy_stderr
+      value: 0.8816372193041417
+    - type: f1
+      value: 38.870262239396496
+    - type: f1_stderr
+      value: 1.1248427890133785
+    - type: main_score
+      value: 46.95652173913043
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB JDReview (default)
+      revision: None
+      split: test
+      type: C-MTEB/JDReview-classification
+    metrics:
+    - type: accuracy
+      value: 87.18574108818011
+    - type: accuracy_stderr
+      value: 1.828763099528331
+    - type: ap
+      value: 56.516251295719414
+    - type: ap_stderr
+      value: 3.3789918068717895
+    - type: f1
+      value: 82.04209146803106
+    - type: f1_stderr
+      value: 2.005027201503808
+    - type: main_score
+      value: 87.18574108818011
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB LCQMC (default)
+      revision: None
+      split: test
+      type: C-MTEB/LCQMC
+    metrics:
+    - type: cosine_pearson
+      value: 72.67112275922743
+    - type: cosine_spearman
+      value: 78.44376213964316
+    - type: manhattan_pearson
+      value: 77.51766838932976
+    - type: manhattan_spearman
+      value: 78.02885255071602
+    - type: euclidean_pearson
+      value: 77.5292348074114
+    - type: euclidean_spearman
+      value: 78.04277103380235
+    - type: main_score
+      value: 78.44376213964316
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB MMarcoReranking (default)
+      revision: None
+      split: dev
+      type: C-MTEB/Mmarco-reranking
+    metrics:
+    - type: map
+      value: 37.021133625346174
+    - type: mrr
+      value: 35.81428571428572
+    - type: main_score
+      value: 37.021133625346174
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB MMarcoRetrieval (default)
+      revision: None
+      split: dev
+      type: C-MTEB/MMarcoRetrieval
+    metrics:
+    - type: map_at_1
+      value: 69.624
+    - type: map_at_10
+      value: 78.764
+    - type: map_at_100
+      value: 79.038
+    - type: map_at_1000
+      value: 79.042
+    - type: map_at_3
+      value: 76.846
+    - type: map_at_5
+      value: 78.106
+    - type: mrr_at_1
+      value: 71.905
+    - type: mrr_at_10
+      value: 79.268
+    - type: mrr_at_100
+      value: 79.508
+    - type: mrr_at_1000
+      value: 79.512
+    - type: mrr_at_3
+      value: 77.60000000000001
+    - type: mrr_at_5
+      value: 78.701
+    - type: ndcg_at_1
+      value: 71.905
+    - type: ndcg_at_10
+      value: 82.414
+    - type: ndcg_at_100
+      value: 83.59
+    - type: ndcg_at_1000
+      value: 83.708
+    - type: ndcg_at_3
+      value: 78.803
+    - type: ndcg_at_5
+      value: 80.94
+    - type: precision_at_1
+      value: 71.905
+    - type: precision_at_10
+      value: 9.901
+    - type: precision_at_100
+      value: 1.048
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 29.479
+    - type: precision_at_5
+      value: 18.828
+    - type: recall_at_1
+      value: 69.624
+    - type: recall_at_10
+      value: 93.149
+    - type: recall_at_100
+      value: 98.367
+    - type: recall_at_1000
+      value: 99.29299999999999
+    - type: recall_at_3
+      value: 83.67599999999999
+    - type: recall_at_5
+      value: 88.752
+    - type: main_score
+      value: 82.414
+    task:
+      type: Retrieval
+  - dataset:
+      config: zh-CN
+      name: MTEB MassiveIntentClassification (zh-CN)
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+      split: test
+      type: mteb/amazon_massive_intent
+    metrics:
+    - type: accuracy
+      value: 77.36045729657029
+    - type: accuracy_stderr
+      value: 0.8944498935111289
+    - type: f1
+      value: 73.73485209304225
+    - type: f1_stderr
+      value: 0.8615191738484445
+    - type: main_score
+      value: 77.36045729657029
+    task:
+      type: Classification
+  - dataset:
+      config: zh-CN
+      name: MTEB MassiveIntentClassification (zh-CN)
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+      split: validation
+      type: mteb/amazon_massive_intent
+    metrics:
+    - type: accuracy
+      value: 78.16035415641909
+    - type: accuracy_stderr
+      value: 0.7514724220154535
+    - type: f1
+      value: 75.32402452596266
+    - type: f1_stderr
+      value: 0.5969737694527888
+    - type: main_score
+      value: 78.16035415641909
+    task:
+      type: Classification
+  - dataset:
+      config: zh-CN
+      name: MTEB MassiveScenarioClassification (zh-CN)
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+      split: test
+      type: mteb/amazon_massive_scenario
+    metrics:
+    - type: accuracy
+      value: 83.31203765971755
+    - type: accuracy_stderr
+      value: 1.1063564012537301
+    - type: f1
+      value: 82.81655735858999
+    - type: f1_stderr
+      value: 0.9643568609098954
+    - type: main_score
+      value: 83.31203765971755
+    task:
+      type: Classification
+  - dataset:
+      config: zh-CN
+      name: MTEB MassiveScenarioClassification (zh-CN)
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+      split: validation
+      type: mteb/amazon_massive_scenario
+    metrics:
+    - type: accuracy
+      value: 83.11362518445647
+    - type: accuracy_stderr
+      value: 1.252141689154366
+    - type: f1
+      value: 82.56555569957769
+    - type: f1_stderr
+      value: 0.858322314243248
+    - type: main_score
+      value: 83.11362518445647
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB MedicalRetrieval (default)
+      revision: None
+      split: dev
+      type: C-MTEB/MedicalRetrieval
+    metrics:
+    - type: map_at_1
+      value: 63.1
+    - type: map_at_10
+      value: 70.816
+    - type: map_at_100
+      value: 71.368
+    - type: map_at_1000
+      value: 71.379
+    - type: map_at_3
+      value: 69.033
+    - type: map_at_5
+      value: 70.028
+    - type: mrr_at_1
+      value: 63.4
+    - type: mrr_at_10
+      value: 70.98400000000001
+    - type: mrr_at_100
+      value: 71.538
+    - type: mrr_at_1000
+      value: 71.548
+    - type: mrr_at_3
+      value: 69.19999999999999
+    - type: mrr_at_5
+      value: 70.195
+    - type: ndcg_at_1
+      value: 63.1
+    - type: ndcg_at_10
+      value: 74.665
+    - type: ndcg_at_100
+      value: 77.16199999999999
+    - type: ndcg_at_1000
+      value: 77.408
+    - type: ndcg_at_3
+      value: 70.952
+    - type: ndcg_at_5
+      value: 72.776
+    - type: precision_at_1
+      value: 63.1
+    - type: precision_at_10
+      value: 8.68
+    - type: precision_at_100
+      value: 0.9809999999999999
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 25.5
+    - type: precision_at_5
+      value: 16.2
+    - type: recall_at_1
+      value: 63.1
+    - type: recall_at_10
+      value: 86.8
+    - type: recall_at_100
+      value: 98.1
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 76.5
+    - type: recall_at_5
+      value: 81.0
+    - type: main_score
+      value: 74.665
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB MultilingualSentiment (default)
+      revision: None
+      split: validation
+      type: C-MTEB/MultilingualSentiment-classification
+    metrics:
+    - type: accuracy
+      value: 75.98
+    - type: accuracy_stderr
+      value: 0.8634813257969153
+    - type: f1
+      value: 75.98312901227456
+    - type: f1_stderr
+      value: 0.9813231777702479
+    - type: main_score
+      value: 75.98
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB Ocnli (default)
+      revision: None
+      split: validation
+      type: C-MTEB/OCNLI
+    metrics:
+    - type: cos_sim_accuracy
+      value: 80.02165674066053
+    - type: cos_sim_accuracy_threshold
+      value: 84.70024466514587
+    - type: cos_sim_ap
+      value: 84.5948682253982
+    - type: cos_sim_f1
+      value: 80.84291187739463
+    - type: cos_sim_f1_threshold
+      value: 82.62853622436523
+    - type: cos_sim_precision
+      value: 73.97020157756354
+    - type: cos_sim_recall
+      value: 89.1235480464625
+    - type: dot_accuracy
+      value: 71.52138603140227
+    - type: dot_accuracy_threshold
+      value: 84206.94580078125
+    - type: dot_ap
+      value: 77.69986172282461
+    - type: dot_f1
+      value: 74.76467951591216
+    - type: dot_f1_threshold
+      value: 78842.08984375
+    - type: dot_precision
+      value: 64.95327102803739
+    - type: dot_recall
+      value: 88.0675818373812
+    - type: euclidean_accuracy
+      value: 76.01515971846237
+    - type: euclidean_accuracy_threshold
+      value: 1818.9674377441406
+    - type: euclidean_ap
+      value: 80.84369691331835
+    - type: euclidean_f1
+      value: 78.08988764044943
+    - type: euclidean_f1_threshold
+      value: 1922.1363067626953
+    - type: euclidean_precision
+      value: 70.14297729184187
+    - type: euclidean_recall
+      value: 88.0675818373812
+    - type: manhattan_accuracy
+      value: 76.12344342176502
+    - type: manhattan_accuracy_threshold
+      value: 61934.478759765625
+    - type: manhattan_ap
+      value: 80.8051823205177
+    - type: manhattan_f1
+      value: 78.21596244131456
+    - type: manhattan_f1_threshold
+      value: 64840.447998046875
+    - type: manhattan_precision
+      value: 70.41420118343196
+    - type: manhattan_recall
+      value: 87.96198521647307
+    - type: max_accuracy
+      value: 80.02165674066053
+    - type: max_ap
+      value: 84.5948682253982
+    - type: max_f1
+      value: 80.84291187739463
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB OnlineShopping (default)
+      revision: None
+      split: test
+      type: C-MTEB/OnlineShopping-classification
+    metrics:
+    - type: accuracy
+      value: 93.63
+    - type: accuracy_stderr
+      value: 0.7253275122315392
+    - type: ap
+      value: 91.66092551327398
+    - type: ap_stderr
+      value: 0.9661774073521741
+    - type: f1
+      value: 93.61696896914624
+    - type: f1_stderr
+      value: 0.7232416235078093
+    - type: main_score
+      value: 93.63
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB PAWSX (default)
+      revision: None
+      split: test
+      type: C-MTEB/PAWSX
+    metrics:
+    - type: cosine_pearson
+      value: 27.420084312732477
+    - type: cosine_spearman
+      value: 36.615019324915316
+    - type: manhattan_pearson
+      value: 35.38814491527626
+    - type: manhattan_spearman
+      value: 35.989020517540105
+    - type: euclidean_pearson
+      value: 35.322828019800475
+    - type: euclidean_spearman
+      value: 35.93118948093057
+    - type: main_score
+      value: 36.615019324915316
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB QBQTC (default)
+      revision: None
+      split: test
+      type: C-MTEB/QBQTC
+    metrics:
+    - type: cosine_pearson
+      value: 36.51779732355864
+    - type: cosine_spearman
+      value: 38.35615142712016
+    - type: manhattan_pearson
+      value: 31.00096996824444
+    - type: manhattan_spearman
+      value: 35.22782463612116
+    - type: euclidean_pearson
+      value: 31.04604995563808
+    - type: euclidean_spearman
+      value: 35.271420992011485
+    - type: main_score
+      value: 38.35615142712016
+    task:
+      type: STS
+  - dataset:
+      config: zh
+      name: MTEB STS22 (zh)
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 60.76376961662733
+    - type: cosine_spearman
+      value: 65.93112312064913
+    - type: manhattan_pearson
+      value: 60.18998639945854
+    - type: manhattan_spearman
+      value: 64.37697612695015
+    - type: euclidean_pearson
+      value: 60.287759656277814
+    - type: euclidean_spearman
+      value: 64.37685757691955
+    - type: main_score
+      value: 65.93112312064913
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB STSB (default)
+      revision: None
+      split: test
+      type: C-MTEB/STSB
+    metrics:
+    - type: cosine_pearson
+      value: 79.6320389543562
+    - type: cosine_spearman
+      value: 81.9230633773663
+    - type: manhattan_pearson
+      value: 80.20746913195181
+    - type: manhattan_spearman
+      value: 80.43150657863002
+    - type: euclidean_pearson
+      value: 80.1796408157508
+    - type: euclidean_spearman
+      value: 80.42930201788549
+    - type: main_score
+      value: 81.9230633773663
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB T2Reranking (default)
+      revision: None
+      split: dev
+      type: C-MTEB/T2Reranking
+    metrics:
+    - type: map
+      value: 66.67836204644267
+    - type: mrr
+      value: 76.1707222383424
+    - type: main_score
+      value: 66.67836204644267
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB T2Retrieval (default)
+      revision: None
+      split: dev
+      type: C-MTEB/T2Retrieval
+    metrics:
+    - type: map_at_1
+      value: 28.015
+    - type: map_at_10
+      value: 78.281
+    - type: map_at_100
+      value: 81.89699999999999
+    - type: map_at_1000
+      value: 81.95599999999999
+    - type: map_at_3
+      value: 55.117000000000004
+    - type: map_at_5
+      value: 67.647
+    - type: mrr_at_1
+      value: 90.496
+    - type: mrr_at_10
+      value: 93.132
+    - type: mrr_at_100
+      value: 93.207
+    - type: mrr_at_1000
+      value: 93.209
+    - type: mrr_at_3
+      value: 92.714
+    - type: mrr_at_5
+      value: 93.0
+    - type: ndcg_at_1
+      value: 90.496
+    - type: ndcg_at_10
+      value: 85.71600000000001
+    - type: ndcg_at_100
+      value: 89.164
+    - type: ndcg_at_1000
+      value: 89.71000000000001
+    - type: ndcg_at_3
+      value: 86.876
+    - type: ndcg_at_5
+      value: 85.607
+    - type: precision_at_1
+      value: 90.496
+    - type: precision_at_10
+      value: 42.398
+    - type: precision_at_100
+      value: 5.031
+    - type: precision_at_1000
+      value: 0.516
+    - type: precision_at_3
+      value: 75.729
+    - type: precision_at_5
+      value: 63.522
+    - type: recall_at_1
+      value: 28.015
+    - type: recall_at_10
+      value: 84.83000000000001
+    - type: recall_at_100
+      value: 95.964
+    - type: recall_at_1000
+      value: 98.67399999999999
+    - type: recall_at_3
+      value: 56.898
+    - type: recall_at_5
+      value: 71.163
+    - type: main_score
+      value: 85.71600000000001
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB TNews (default)
+      revision: None
+      split: validation
+      type: C-MTEB/TNews-classification
+    metrics:
+    - type: accuracy
+      value: 51.702999999999996
+    - type: accuracy_stderr
+      value: 0.8183526134863877
+    - type: f1
+      value: 50.35330734766769
+    - type: f1_stderr
+      value: 0.740275098366631
+    - type: main_score
+      value: 51.702999999999996
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB ThuNewsClusteringP2P (default)
+      revision: None
+      split: test
+      type: C-MTEB/ThuNewsClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 72.78709391223538
+    - type: v_measure_std
+      value: 1.5927130767880417
+    - type: main_score
+      value: 72.78709391223538
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB ThuNewsClusteringS2S (default)
+      revision: None
+      split: test
+      type: C-MTEB/ThuNewsClusteringS2S
+    metrics:
+    - type: v_measure
+      value: 66.80392174700211
+    - type: v_measure_std
+      value: 1.845756306548485
+    - type: main_score
+      value: 66.80392174700211
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB VideoRetrieval (default)
+      revision: None
+      split: dev
+      type: C-MTEB/VideoRetrieval
+    metrics:
+    - type: map_at_1
+      value: 65.5
+    - type: map_at_10
+      value: 75.38
+    - type: map_at_100
+      value: 75.756
+    - type: map_at_1000
+      value: 75.75800000000001
+    - type: map_at_3
+      value: 73.8
+    - type: map_at_5
+      value: 74.895
+    - type: mrr_at_1
+      value: 65.5
+    - type: mrr_at_10
+      value: 75.38
+    - type: mrr_at_100
+      value: 75.756
+    - type: mrr_at_1000
+      value: 75.75800000000001
+    - type: mrr_at_3
+      value: 73.8
+    - type: mrr_at_5
+      value: 74.895
+    - type: ndcg_at_1
+      value: 65.5
+    - type: ndcg_at_10
+      value: 79.572
+    - type: ndcg_at_100
+      value: 81.17699999999999
+    - type: ndcg_at_1000
+      value: 81.227
+    - type: ndcg_at_3
+      value: 76.44999999999999
+    - type: ndcg_at_5
+      value: 78.404
+    - type: precision_at_1
+      value: 65.5
+    - type: precision_at_10
+      value: 9.24
+    - type: precision_at_100
+      value: 0.9939999999999999
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 28.033
+    - type: precision_at_5
+      value: 17.76
+    - type: recall_at_1
+      value: 65.5
+    - type: recall_at_10
+      value: 92.4
+    - type: recall_at_100
+      value: 99.4
+    - type: recall_at_1000
+      value: 99.8
+    - type: recall_at_3
+      value: 84.1
+    - type: recall_at_5
+      value: 88.8
+    - type: main_score
+      value: 79.572
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB Waimai (default)
+      revision: None
+      split: test
+      type: C-MTEB/waimai-classification
+    metrics:
+    - type: accuracy
+      value: 88.70000000000002
+    - type: accuracy_stderr
+      value: 1.1713240371477067
+    - type: ap
+      value: 73.95357766936226
+    - type: ap_stderr
+      value: 2.3258932220157638
+    - type: f1
+      value: 87.27541455081986
+    - type: f1_stderr
+      value: 1.185968184225313
+    - type: main_score
+      value: 88.70000000000002
+    task:
+      type: Classification
+tags:
+- mteb
+---