Upload README.md

README.md

@@ -1,14 +1,131 @@
 ---
-library_name: sentence-transformers
 model-index:
 - name: XYZ-embedding-zh-v2
   results:
+  - dataset:
+      config: default
+      name: MTEB AFQMC
+      revision: None
+      split: validation
+      type: C-MTEB/AFQMC
+    metrics:
+    - type: cos_sim_pearson
+      value: 55.51799059309076
+    - type: cos_sim_spearman
+      value: 58.407433584137806
+    - type: manhattan_pearson
+      value: 57.17473672145622
+    - type: manhattan_spearman
+      value: 58.389018054159955
+    - type: euclidean_pearson
+      value: 57.19483956761451
+    - type: euclidean_spearman
+      value: 58.407433584137806
+    - type: main_score
+      value: 58.407433584137806
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB ATEC
+      revision: None
+      split: test
+      type: C-MTEB/ATEC
+    metrics:
+    - type: cos_sim_pearson
+      value: 57.31078155367183
+    - type: cos_sim_spearman
+      value: 57.59782762324478
+    - type: manhattan_pearson
+      value: 62.525487007985035
+    - type: manhattan_spearman
+      value: 57.591139966303615
+    - type: euclidean_pearson
+      value: 62.53702437760052
+    - type: euclidean_spearman
+      value: 57.597828749091384
+    - type: main_score
+      value: 57.59782762324478
+    task:
+      type: STS
+  - dataset:
+      config: zh
+      name: MTEB AmazonReviewsClassification (zh)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: test
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 49.374
+    - type: accuracy_stderr
+      value: 1.436636349254743
+    - type: f1
+      value: 47.115240601017774
+    - type: f1_stderr
+      value: 1.5642799356594534
+    - type: main_score
+      value: 49.374
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB BQ
+      revision: None
+      split: test
+      type: C-MTEB/BQ
+    metrics:
+    - type: cos_sim_pearson
+      value: 71.49514309404829
+    - type: cos_sim_spearman
+      value: 72.66161713021279
+    - type: manhattan_pearson
+      value: 71.03443640254005
+    - type: manhattan_spearman
+      value: 72.63439621980275
+    - type: euclidean_pearson
+      value: 71.06830370642658
+    - type: euclidean_spearman
+      value: 72.66161713043078
+    - type: main_score
+      value: 72.66161713021279
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB CLSClusteringP2P
+      revision: None
+      split: test
+      type: C-MTEB/CLSClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 57.237692641281
+    - type: v_measure_std
+      value: 1.2777768354339174
+    - type: main_score
+      value: 57.237692641281
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB CLSClusteringS2S
+      revision: None
+      split: test
+      type: C-MTEB/CLSClusteringS2S
+    metrics:
+    - type: v_measure
+      value: 48.41686666939331
+    - type: v_measure_std
+      value: 1.7663118461900793
+    - type: main_score
+      value: 48.41686666939331
+    task:
+      type: Clustering
   - dataset:
       config: default
       name: MTEB CMedQAv1
       revision: None
       split: test
-      type: C-MTEB/CMedQAv1
+      type: C-MTEB/CMedQAv1-reranking
     metrics:
     - type: map
       value: 89.9766367822762
@@ -23,7 +140,7 @@ model-index:
       name: MTEB CMedQAv2
       revision: None
       split: test
-      type: C-MTEB/CMedQAv2
+      type: C-MTEB/CMedQAv2-reranking
     metrics:
     - type: map
       value: 89.04628340075982
@@ -104,6 +221,77 @@ model-index:
       value: 48.294
     task:
       type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB Cmnli
+      revision: None
+      split: validation
+      type: C-MTEB/CMNLI
+    metrics:
+    - type: cos_sim_accuracy
+      value: 82.8983764281419
+    - type: cos_sim_accuracy_threshold
+      value: 56.05731010437012
+    - type: cos_sim_ap
+      value: 90.23156362696572
+    - type: cos_sim_f1
+      value: 83.83207278307574
+    - type: cos_sim_f1_threshold
+      value: 52.05453634262085
+    - type: cos_sim_precision
+      value: 78.91044160132068
+    - type: cos_sim_recall
+      value: 89.40846387654898
+    - type: dot_accuracy
+      value: 82.8983764281419
+    - type: dot_accuracy_threshold
+      value: 56.05730414390564
+    - type: dot_ap
+      value: 90.20952356258861
+    - type: dot_f1
+      value: 83.83207278307574
+    - type: dot_f1_threshold
+      value: 52.054524421691895
+    - type: dot_precision
+      value: 78.91044160132068
+    - type: dot_recall
+      value: 89.40846387654898
+    - type: euclidean_accuracy
+      value: 82.8983764281419
+    - type: euclidean_accuracy_threshold
+      value: 93.74719858169556
+    - type: euclidean_ap
+      value: 90.23156283510565
+    - type: euclidean_f1
+      value: 83.83207278307574
+    - type: euclidean_f1_threshold
+      value: 97.92392253875732
+    - type: euclidean_precision
+      value: 78.91044160132068
+    - type: euclidean_recall
+      value: 89.40846387654898
+    - type: manhattan_accuracy
+      value: 82.85027059530968
+    - type: manhattan_accuracy_threshold
+      value: 3164.584159851074
+    - type: manhattan_ap
+      value: 90.23178004516869
+    - type: manhattan_f1
+      value: 83.82157123834887
+    - type: manhattan_f1_threshold
+      value: 3273.5992431640625
+    - type: manhattan_precision
+      value: 79.76768743400211
+    - type: manhattan_recall
+      value: 88.30956277764788
+    - type: max_accuracy
+      value: 82.8983764281419
+    - type: max_ap
+      value: 90.23178004516869
+    - type: max_f1
+      value: 83.83207278307574
+    task:
+      type: PairClassification
   - dataset:
       config: default
       name: MTEB CovidRetrieval
@@ -317,6 +505,71 @@ model-index:
       value: 70.294
     task:
       type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB IFlyTek
+      revision: None
+      split: validation
+      type: C-MTEB/IFlyTek-classification
+    metrics:
+    - type: accuracy
+      value: 52.743362831858406
+    - type: accuracy_stderr
+      value: 0.23768288128480788
+    - type: f1
+      value: 41.1548855278405
+    - type: f1_stderr
+      value: 0.4088759842813554
+    - type: main_score
+      value: 52.743362831858406
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB JDReview
+      revision: None
+      split: test
+      type: C-MTEB/JDReview-classification
+    metrics:
+    - type: accuracy
+      value: 89.08067542213884
+    - type: accuracy_stderr
+      value: 0.9559278951487445
+    - type: ap
+      value: 60.875320104586564
+    - type: ap_stderr
+      value: 2.137806661565934
+    - type: f1
+      value: 84.39314192399665
+    - type: f1_stderr
+      value: 1.132407155321657
+    - type: main_score
+      value: 89.08067542213884
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB LCQMC
+      revision: None
+      split: test
+      type: C-MTEB/LCQMC
+    metrics:
+    - type: cos_sim_pearson
+      value: 73.3633875566899
+    - type: cos_sim_spearman
+      value: 79.27679599527615
+    - type: manhattan_pearson
+      value: 79.12061667088273
+    - type: manhattan_spearman
+      value: 79.26989882781706
+    - type: euclidean_pearson
+      value: 79.12871362068391
+    - type: euclidean_spearman
+      value: 79.27679377557219
+    - type: main_score
+      value: 79.27679599527615
+    task:
+      type: STS
   - dataset:
       config: default
       name: MTEB MMarcoReranking
@@ -403,6 +656,44 @@ model-index:
       value: 82.505
     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: 77.9388029589778
+    - type: accuracy_stderr
+      value: 1.416192788478398
+    - type: f1
+      value: 74.77765701086211
+    - type: f1_stderr
+      value: 1.254859698486085
+    - type: main_score
+      value: 77.9388029589778
+    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: 83.8231338264963
+    - type: accuracy_stderr
+      value: 0.6973305760755886
+    - type: f1
+      value: 83.13105322628088
+    - type: f1_stderr
+      value: 0.600506118139685
+    - type: main_score
+      value: 83.8231338264963
+    task:
+      type: Classification
   - dataset:
       config: default
       name: MTEB MedicalRetrieval
@@ -474,6 +765,211 @@ model-index:
       value: 68.041
     task:
       type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB MultilingualSentiment
+      revision: None
+      split: validation
+      type: C-MTEB/MultilingualSentiment-classification
+    metrics:
+    - type: accuracy
+      value: 78.60333333333334
+    - type: accuracy_stderr
+      value: 0.3331499495555859
+    - type: f1
+      value: 78.4814340961856
+    - type: f1_stderr
+      value: 0.45721454672060496
+    - type: main_score
+      value: 78.60333333333334
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB Ocnli
+      revision: None
+      split: validation
+      type: C-MTEB/OCNLI
+    metrics:
+    - type: cos_sim_accuracy
+      value: 80.5630752571738
+    - type: cos_sim_accuracy_threshold
+      value: 53.72971296310425
+    - type: cos_sim_ap
+      value: 85.61885910463258
+    - type: cos_sim_f1
+      value: 82.40469208211144
+    - type: cos_sim_f1_threshold
+      value: 50.07883310317993
+    - type: cos_sim_precision
+      value: 76.70609645131938
+    - type: cos_sim_recall
+      value: 89.01795142555439
+    - type: dot_accuracy
+      value: 80.5630752571738
+    - type: dot_accuracy_threshold
+      value: 53.7297248840332
+    - type: dot_ap
+      value: 85.61885910463258
+    - type: dot_f1
+      value: 82.40469208211144
+    - type: dot_f1_threshold
+      value: 50.07884502410889
+    - type: dot_precision
+      value: 76.70609645131938
+    - type: dot_recall
+      value: 89.01795142555439
+    - type: euclidean_accuracy
+      value: 80.5630752571738
+    - type: euclidean_accuracy_threshold
+      value: 96.19801044464111
+    - type: euclidean_ap
+      value: 85.61885910463258
+    - type: euclidean_f1
+      value: 82.40469208211144
+    - type: euclidean_f1_threshold
+      value: 99.92111921310425
+    - type: euclidean_precision
+      value: 76.70609645131938
+    - type: euclidean_recall
+      value: 89.01795142555439
+    - type: manhattan_accuracy
+      value: 80.67135896047645
+    - type: manhattan_accuracy_threshold
+      value: 3323.1739044189453
+    - type: manhattan_ap
+      value: 85.55348220886658
+    - type: manhattan_f1
+      value: 82.26744186046511
+    - type: manhattan_f1_threshold
+      value: 3389.273452758789
+    - type: manhattan_precision
+      value: 76.00716204118174
+    - type: manhattan_recall
+      value: 89.65153115100317
+    - type: max_accuracy
+      value: 80.67135896047645
+    - type: max_ap
+      value: 85.61885910463258
+    - type: max_f1
+      value: 82.40469208211144
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB OnlineShopping
+      revision: None
+      split: test
+      type: C-MTEB/OnlineShopping-classification
+    metrics:
+    - type: accuracy
+      value: 94.94
+    - type: accuracy_stderr
+      value: 0.49030602688525093
+    - type: ap
+      value: 93.0785841977823
+    - type: ap_stderr
+      value: 0.5447383082750599
+    - type: f1
+      value: 94.92765777406245
+    - type: f1_stderr
+      value: 0.4891510966106189
+    - type: main_score
+      value: 94.94
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB PAWSX
+      revision: None
+      split: test
+      type: C-MTEB/PAWSX
+    metrics:
+    - type: cos_sim_pearson
+      value: 36.564307811370654
+    - type: cos_sim_spearman
+      value: 42.44208208349051
+    - type: manhattan_pearson
+      value: 42.099358471578306
+    - type: manhattan_spearman
+      value: 42.50283181486304
+    - type: euclidean_pearson
+      value: 42.07954956675317
+    - type: euclidean_spearman
+      value: 42.453014115018554
+    - type: main_score
+      value: 42.44208208349051
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB QBQTC
+      revision: None
+      split: test
+      type: C-MTEB/QBQTC
+    metrics:
+    - type: cos_sim_pearson
+      value: 39.19092968089104
+    - type: cos_sim_spearman
+      value: 41.5174661348832
+    - type: manhattan_pearson
+      value: 37.91587646684523
+    - type: manhattan_spearman
+      value: 41.536668677987194
+    - type: euclidean_pearson
+      value: 37.91079973901135
+    - type: euclidean_spearman
+      value: 41.51833855501128
+    - type: main_score
+      value: 41.5174661348832
+    task:
+      type: STS
+  - dataset:
+      config: zh
+      name: MTEB STS22 (zh)
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cos_sim_pearson
+      value: 62.029449510721605
+    - type: cos_sim_spearman
+      value: 66.31935471251364
+    - type: manhattan_pearson
+      value: 63.63179975157496
+    - type: manhattan_spearman
+      value: 66.3007950466125
+    - type: euclidean_pearson
+      value: 63.59752734041086
+    - type: euclidean_spearman
+      value: 66.31935471251364
+    - type: main_score
+      value: 66.31935471251364
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB STSB
+      revision: None
+      split: test
+      type: C-MTEB/STSB
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.81459862563769
+    - type: cos_sim_spearman
+      value: 82.15323953301453
+    - type: manhattan_pearson
+      value: 81.61904305126016
+    - type: manhattan_spearman
+      value: 82.1361073852468
+    - type: euclidean_pearson
+      value: 81.60799063723992
+    - type: euclidean_spearman
+      value: 82.15405405083231
+    - type: main_score
+      value: 82.15323953301453
+    task:
+      type: STS
   - dataset:
       config: default
       name: MTEB T2Reranking
@@ -482,11 +978,11 @@ model-index:
       type: C-MTEB/T2Reranking
     metrics:
     - type: map
-      value: 69.13287570713865
+      value: 69.13560834260383
     - type: mrr
-      value: 79.95326487625066
+      value: 79.95749642669074
     - type: main_score
-      value: 69.13287570713865
+      value: 69.13560834260383
     task:
       type: Reranking
   - dataset:
@@ -560,6 +1056,55 @@ model-index:
       value: 85.875
     task:
       type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB TNews
+      revision: None
+      split: validation
+      type: C-MTEB/TNews-classification
+    metrics:
+    - type: accuracy
+      value: 54.309000000000005
+    - type: accuracy_stderr
+      value: 0.4694347665011627
+    - type: f1
+      value: 52.598803987889255
+    - type: f1_stderr
+      value: 0.5191189533227434
+    - type: main_score
+      value: 54.309000000000005
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB ThuNewsClusteringP2P
+      revision: None
+      split: test
+      type: C-MTEB/ThuNewsClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 76.64191229011249
+    - type: v_measure_std
+      value: 2.807206940615986
+    - type: main_score
+      value: 76.64191229011249
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB ThuNewsClusteringS2S
+      revision: None
+      split: test
+      type: C-MTEB/ThuNewsClusteringS2S
+    metrics:
+    - type: v_measure
+      value: 71.02529199411326
+    - type: v_measure_std
+      value: 2.0547855888165945
+    - type: main_score
+      value: 71.02529199411326
+    task:
+      type: Clustering
   - dataset:
       config: default
       name: MTEB VideoRetrieval
@@ -631,12 +1176,32 @@ model-index:
       value: 80.93599999999999
     task:
       type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB Waimai
+      revision: None
+      split: test
+      type: C-MTEB/waimai-classification
+    metrics:
+    - type: accuracy
+      value: 89.47
+    - type: accuracy_stderr
+      value: 0.26476404589747476
+    - type: ap
+      value: 75.49555223825388
+    - type: ap_stderr
+      value: 0.596040511982105
+    - type: f1
+      value: 88.01797939221065
+    - type: f1_stderr
+      value: 0.27168216797281214
+    - type: main_score
+      value: 89.47
+    task:
+      type: Classification
 tags:
 - mteb
-language:
-- zh
 ---
-
 <h2 align="left">XYZ-embedding-zh-v2</h2>
 
 ## Usage (Sentence Transformers)