xyz模型

README.md

@@ -2,154 +2,6 @@
 model-index:
 - name: XYZ-embedding
   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-reranking
-    metrics:
-    - type: map
-      value: 89.9766367822762
-    - type: mrr
-      value: 91.88896825396824
-    - type: main_score
-      value: 89.9766367822762
-    task:
-      type: Reranking
-  - dataset:
-      config: default
-      name: MTEB CMedQAv2
-      revision: None
-      split: test
-      type: C-MTEB/CMedQAv2-reranking
-    metrics:
-    - type: map
-      value: 89.04628340075982
-    - type: mrr
-      value: 91.21702380952381
-    - type: main_score
-      value: 89.04628340075982
-    task:
-      type: Reranking
   - dataset:
       config: default
       name: MTEB CmedqaRetrieval
@@ -221,77 +73,6 @@ 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
@@ -505,86 +286,6 @@ 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
-      revision: None
-      split: dev
-      type: C-MTEB/Mmarco-reranking
-    metrics:
-    - type: map
-      value: 37.68251937316638
-    - type: mrr
-      value: 36.61746031746032
-    - type: main_score
-      value: 37.68251937316638
-    task:
-      type: Reranking
   - dataset:
       config: default
       name: MTEB MMarcoRetrieval
@@ -656,44 +357,6 @@ 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
@@ -765,226 +428,6 @@ 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
-      revision: None
-      split: dev
-      type: C-MTEB/T2Reranking
-    metrics:
-    - type: map
-      value: 69.13560834260383
-    - type: mrr
-      value: 79.95749642669074
-    - type: main_score
-      value: 69.13560834260383
-    task:
-      type: Reranking
   - dataset:
       config: default
       name: MTEB T2Retrieval
@@ -1056,55 +499,6 @@ 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
@@ -1176,32 +570,13 @@ 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</h2>
 
 ## Usage (Sentence Transformers)
@@ -1231,4 +606,4 @@ print(embeddings.shape)
 similarities = model.similarity(embeddings, embeddings)
 print(similarities.shape)
 # [3, 3]
-```
+```