README.md

metadata

tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:124788
  - loss:GISTEmbedLoss
base_model: Alibaba-NLP/gte-multilingual-base
widget:
  - source_sentence: 其他机械、设备和有形货物租赁服务代表
    sentences:
      - 其他机械和设备租赁服务工作人员
      - 电子和电信设备及零部件物流经理
      - 工业主厨
  - source_sentence: 公交车司机
    sentences:
      - 表演灯光设计师
      - 乙烯基地板安装工
      - 国际巴士司机
  - source_sentence: online communication manager
    sentences:
      - trades union official
      - social media manager
      - budget manager
  - source_sentence: Projektmanagerin
    sentences:
      - Projektmanager/Projektmanagerin
      - Category-Manager
      - Infanterist
  - source_sentence: Volksvertreter
    sentences:
      - Parlamentarier
      - Oberbürgermeister
      - Konsul
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
  - cosine_accuracy@1
  - cosine_accuracy@20
  - cosine_accuracy@50
  - cosine_accuracy@100
  - cosine_accuracy@150
  - cosine_accuracy@200
  - cosine_precision@1
  - cosine_precision@20
  - cosine_precision@50
  - cosine_precision@100
  - cosine_precision@150
  - cosine_precision@200
  - cosine_recall@1
  - cosine_recall@20
  - cosine_recall@50
  - cosine_recall@100
  - cosine_recall@150
  - cosine_recall@200
  - cosine_ndcg@1
  - cosine_ndcg@20
  - cosine_ndcg@50
  - cosine_ndcg@100
  - cosine_ndcg@150
  - cosine_ndcg@200
  - cosine_mrr@1
  - cosine_mrr@20
  - cosine_mrr@50
  - cosine_mrr@100
  - cosine_mrr@150
  - cosine_mrr@200
  - cosine_map@1
  - cosine_map@20
  - cosine_map@50
  - cosine_map@100
  - cosine_map@150
  - cosine_map@200
  - cosine_map@500
model-index:
  - name: SentenceTransformer based on Alibaba-NLP/gte-multilingual-base
    results:
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: full en
          type: full_en
        metrics:
          - type: cosine_accuracy@1
            value: 0.6666666666666666
            name: Cosine Accuracy@1
          - type: cosine_accuracy@20
            value: 0.9904761904761905
            name: Cosine Accuracy@20
          - type: cosine_accuracy@50
            value: 0.9904761904761905
            name: Cosine Accuracy@50
          - type: cosine_accuracy@100
            value: 0.9904761904761905
            name: Cosine Accuracy@100
          - type: cosine_accuracy@150
            value: 0.9904761904761905
            name: Cosine Accuracy@150
          - type: cosine_accuracy@200
            value: 0.9904761904761905
            name: Cosine Accuracy@200
          - type: cosine_precision@1
            value: 0.6666666666666666
            name: Cosine Precision@1
          - type: cosine_precision@20
            value: 0.5147619047619048
            name: Cosine Precision@20
          - type: cosine_precision@50
            value: 0.31999999999999995
            name: Cosine Precision@50
          - type: cosine_precision@100
            value: 0.19047619047619047
            name: Cosine Precision@100
          - type: cosine_precision@150
            value: 0.1361904761904762
            name: Cosine Precision@150
          - type: cosine_precision@200
            value: 0.10542857142857143
            name: Cosine Precision@200
          - type: cosine_recall@1
            value: 0.06854687410617222
            name: Cosine Recall@1
          - type: cosine_recall@20
            value: 0.5491240579458434
            name: Cosine Recall@20
          - type: cosine_recall@50
            value: 0.7553654907661455
            name: Cosine Recall@50
          - type: cosine_recall@100
            value: 0.8503209224897438
            name: Cosine Recall@100
          - type: cosine_recall@150
            value: 0.8994749092946579
            name: Cosine Recall@150
          - type: cosine_recall@200
            value: 0.9207884118691805
            name: Cosine Recall@200
          - type: cosine_ndcg@1
            value: 0.6666666666666666
            name: Cosine Ndcg@1
          - type: cosine_ndcg@20
            value: 0.6952098522285352
            name: Cosine Ndcg@20
          - type: cosine_ndcg@50
            value: 0.7229572913271685
            name: Cosine Ndcg@50
          - type: cosine_ndcg@100
            value: 0.7732532874348539
            name: Cosine Ndcg@100
          - type: cosine_ndcg@150
            value: 0.7947334799125039
            name: Cosine Ndcg@150
          - type: cosine_ndcg@200
            value: 0.8038564389556094
            name: Cosine Ndcg@200
          - type: cosine_mrr@1
            value: 0.6666666666666666
            name: Cosine Mrr@1
          - type: cosine_mrr@20
            value: 0.8182539682539683
            name: Cosine Mrr@20
          - type: cosine_mrr@50
            value: 0.8182539682539683
            name: Cosine Mrr@50
          - type: cosine_mrr@100
            value: 0.8182539682539683
            name: Cosine Mrr@100
          - type: cosine_mrr@150
            value: 0.8182539682539683
            name: Cosine Mrr@150
          - type: cosine_mrr@200
            value: 0.8182539682539683
            name: Cosine Mrr@200
          - type: cosine_map@1
            value: 0.6666666666666666
            name: Cosine Map@1
          - type: cosine_map@20
            value: 0.5566401101002375
            name: Cosine Map@20
          - type: cosine_map@50
            value: 0.55344017265156
            name: Cosine Map@50
          - type: cosine_map@100
            value: 0.5852249415484134
            name: Cosine Map@100
          - type: cosine_map@150
            value: 0.5943042662925763
            name: Cosine Map@150
          - type: cosine_map@200
            value: 0.5975837437975446
            name: Cosine Map@200
          - type: cosine_map@500
            value: 0.6015742986218369
            name: Cosine Map@500
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: full es
          type: full_es
        metrics:
          - type: cosine_accuracy@1
            value: 0.12432432432432433
            name: Cosine Accuracy@1
          - type: cosine_accuracy@20
            value: 1
            name: Cosine Accuracy@20
          - type: cosine_accuracy@50
            value: 1
            name: Cosine Accuracy@50
          - type: cosine_accuracy@100
            value: 1
            name: Cosine Accuracy@100
          - type: cosine_accuracy@150
            value: 1
            name: Cosine Accuracy@150
          - type: cosine_accuracy@200
            value: 1
            name: Cosine Accuracy@200
          - type: cosine_precision@1
            value: 0.12432432432432433
            name: Cosine Precision@1
          - type: cosine_precision@20
            value: 0.575945945945946
            name: Cosine Precision@20
          - type: cosine_precision@50
            value: 0.3923243243243244
            name: Cosine Precision@50
          - type: cosine_precision@100
            value: 0.2565945945945946
            name: Cosine Precision@100
          - type: cosine_precision@150
            value: 0.19282882882882882
            name: Cosine Precision@150
          - type: cosine_precision@200
            value: 0.1527837837837838
            name: Cosine Precision@200
          - type: cosine_recall@1
            value: 0.0036138931714884822
            name: Cosine Recall@1
          - type: cosine_recall@20
            value: 0.3852888120551914
            name: Cosine Recall@20
          - type: cosine_recall@50
            value: 0.5659574514538841
            name: Cosine Recall@50
          - type: cosine_recall@100
            value: 0.6898678629281393
            name: Cosine Recall@100
          - type: cosine_recall@150
            value: 0.7540209165372845
            name: Cosine Recall@150
          - type: cosine_recall@200
            value: 0.7858170054407897
            name: Cosine Recall@200
          - type: cosine_ndcg@1
            value: 0.12432432432432433
            name: Cosine Ndcg@1
          - type: cosine_ndcg@20
            value: 0.6168674053047035
            name: Cosine Ndcg@20
          - type: cosine_ndcg@50
            value: 0.5913690595071309
            name: Cosine Ndcg@50
          - type: cosine_ndcg@100
            value: 0.62350509928888
            name: Cosine Ndcg@100
          - type: cosine_ndcg@150
            value: 0.6556716735369459
            name: Cosine Ndcg@150
          - type: cosine_ndcg@200
            value: 0.6716557949894583
            name: Cosine Ndcg@200
          - type: cosine_mrr@1
            value: 0.12432432432432433
            name: Cosine Mrr@1
          - type: cosine_mrr@20
            value: 0.5581081081081081
            name: Cosine Mrr@20
          - type: cosine_mrr@50
            value: 0.5581081081081081
            name: Cosine Mrr@50
          - type: cosine_mrr@100
            value: 0.5581081081081081
            name: Cosine Mrr@100
          - type: cosine_mrr@150
            value: 0.5581081081081081
            name: Cosine Mrr@150
          - type: cosine_mrr@200
            value: 0.5581081081081081
            name: Cosine Mrr@200
          - type: cosine_map@1
            value: 0.12432432432432433
            name: Cosine Map@1
          - type: cosine_map@20
            value: 0.48407152706202555
            name: Cosine Map@20
          - type: cosine_map@50
            value: 0.43043374125481026
            name: Cosine Map@50
          - type: cosine_map@100
            value: 0.43735327570764515
            name: Cosine Map@100
          - type: cosine_map@150
            value: 0.45269435912524697
            name: Cosine Map@150
          - type: cosine_map@200
            value: 0.45930097680668164
            name: Cosine Map@200
          - type: cosine_map@500
            value: 0.47204219228541466
            name: Cosine Map@500
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: full de
          type: full_de
        metrics:
          - type: cosine_accuracy@1
            value: 0.2955665024630542
            name: Cosine Accuracy@1
          - type: cosine_accuracy@20
            value: 0.9753694581280788
            name: Cosine Accuracy@20
          - type: cosine_accuracy@50
            value: 0.9852216748768473
            name: Cosine Accuracy@50
          - type: cosine_accuracy@100
            value: 0.9901477832512315
            name: Cosine Accuracy@100
          - type: cosine_accuracy@150
            value: 0.9901477832512315
            name: Cosine Accuracy@150
          - type: cosine_accuracy@200
            value: 0.9901477832512315
            name: Cosine Accuracy@200
          - type: cosine_precision@1
            value: 0.2955665024630542
            name: Cosine Precision@1
          - type: cosine_precision@20
            value: 0.5103448275862069
            name: Cosine Precision@20
          - type: cosine_precision@50
            value: 0.36935960591133016
            name: Cosine Precision@50
          - type: cosine_precision@100
            value: 0.23965517241379314
            name: Cosine Precision@100
          - type: cosine_precision@150
            value: 0.1807881773399015
            name: Cosine Precision@150
          - type: cosine_precision@200
            value: 0.1461576354679803
            name: Cosine Precision@200
          - type: cosine_recall@1
            value: 0.01108543831680986
            name: Cosine Recall@1
          - type: cosine_recall@20
            value: 0.3207974783481294
            name: Cosine Recall@20
          - type: cosine_recall@50
            value: 0.5042046446720455
            name: Cosine Recall@50
          - type: cosine_recall@100
            value: 0.6172666777909689
            name: Cosine Recall@100
          - type: cosine_recall@150
            value: 0.6848138831682932
            name: Cosine Recall@150
          - type: cosine_recall@200
            value: 0.7253195006357535
            name: Cosine Recall@200
          - type: cosine_ndcg@1
            value: 0.2955665024630542
            name: Cosine Ndcg@1
          - type: cosine_ndcg@20
            value: 0.537849085734973
            name: Cosine Ndcg@20
          - type: cosine_ndcg@50
            value: 0.5288037060639387
            name: Cosine Ndcg@50
          - type: cosine_ndcg@100
            value: 0.5551941695921919
            name: Cosine Ndcg@100
          - type: cosine_ndcg@150
            value: 0.5887611959940118
            name: Cosine Ndcg@150
          - type: cosine_ndcg@200
            value: 0.6092219717029682
            name: Cosine Ndcg@200
          - type: cosine_mrr@1
            value: 0.2955665024630542
            name: Cosine Mrr@1
          - type: cosine_mrr@20
            value: 0.5164773875147672
            name: Cosine Mrr@20
          - type: cosine_mrr@50
            value: 0.5167647438366063
            name: Cosine Mrr@50
          - type: cosine_mrr@100
            value: 0.5168213657719442
            name: Cosine Mrr@100
          - type: cosine_mrr@150
            value: 0.5168213657719442
            name: Cosine Mrr@150
          - type: cosine_mrr@200
            value: 0.5168213657719442
            name: Cosine Mrr@200
          - type: cosine_map@1
            value: 0.2955665024630542
            name: Cosine Map@1
          - type: cosine_map@20
            value: 0.398398563122481
            name: Cosine Map@20
          - type: cosine_map@50
            value: 0.36032758502543594
            name: Cosine Map@50
          - type: cosine_map@100
            value: 0.3632259128424842
            name: Cosine Map@100
          - type: cosine_map@150
            value: 0.37822275477623696
            name: Cosine Map@150
          - type: cosine_map@200
            value: 0.3863148456840816
            name: Cosine Map@200
          - type: cosine_map@500
            value: 0.399227009561676
            name: Cosine Map@500
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: full zh
          type: full_zh
        metrics:
          - type: cosine_accuracy@1
            value: 0.6796116504854369
            name: Cosine Accuracy@1
          - type: cosine_accuracy@20
            value: 0.9805825242718447
            name: Cosine Accuracy@20
          - type: cosine_accuracy@50
            value: 0.9902912621359223
            name: Cosine Accuracy@50
          - type: cosine_accuracy@100
            value: 0.9902912621359223
            name: Cosine Accuracy@100
          - type: cosine_accuracy@150
            value: 0.9902912621359223
            name: Cosine Accuracy@150
          - type: cosine_accuracy@200
            value: 0.9902912621359223
            name: Cosine Accuracy@200
          - type: cosine_precision@1
            value: 0.6796116504854369
            name: Cosine Precision@1
          - type: cosine_precision@20
            value: 0.488349514563107
            name: Cosine Precision@20
          - type: cosine_precision@50
            value: 0.29631067961165053
            name: Cosine Precision@50
          - type: cosine_precision@100
            value: 0.17883495145631062
            name: Cosine Precision@100
          - type: cosine_precision@150
            value: 0.12776699029126212
            name: Cosine Precision@150
          - type: cosine_precision@200
            value: 0.09990291262135924
            name: Cosine Precision@200
          - type: cosine_recall@1
            value: 0.06931865009287731
            name: Cosine Recall@1
          - type: cosine_recall@20
            value: 0.5250914458143515
            name: Cosine Recall@20
          - type: cosine_recall@50
            value: 0.7082715439925011
            name: Cosine Recall@50
          - type: cosine_recall@100
            value: 0.8169166539243944
            name: Cosine Recall@100
          - type: cosine_recall@150
            value: 0.8613232254521018
            name: Cosine Recall@150
          - type: cosine_recall@200
            value: 0.8898175710074696
            name: Cosine Recall@200
          - type: cosine_ndcg@1
            value: 0.6796116504854369
            name: Cosine Ndcg@1
          - type: cosine_ndcg@20
            value: 0.6680745295820606
            name: Cosine Ndcg@20
          - type: cosine_ndcg@50
            value: 0.6856578240865067
            name: Cosine Ndcg@50
          - type: cosine_ndcg@100
            value: 0.7378907298421352
            name: Cosine Ndcg@100
          - type: cosine_ndcg@150
            value: 0.7576651805692517
            name: Cosine Ndcg@150
          - type: cosine_ndcg@200
            value: 0.7696718049970358
            name: Cosine Ndcg@200
          - type: cosine_mrr@1
            value: 0.6796116504854369
            name: Cosine Mrr@1
          - type: cosine_mrr@20
            value: 0.8158576051779936
            name: Cosine Mrr@20
          - type: cosine_mrr@50
            value: 0.816279724215562
            name: Cosine Mrr@50
          - type: cosine_mrr@100
            value: 0.816279724215562
            name: Cosine Mrr@100
          - type: cosine_mrr@150
            value: 0.816279724215562
            name: Cosine Mrr@150
          - type: cosine_mrr@200
            value: 0.816279724215562
            name: Cosine Mrr@200
          - type: cosine_map@1
            value: 0.6796116504854369
            name: Cosine Map@1
          - type: cosine_map@20
            value: 0.522177160195635
            name: Cosine Map@20
          - type: cosine_map@50
            value: 0.5082601209392789
            name: Cosine Map@50
          - type: cosine_map@100
            value: 0.5371705298206915
            name: Cosine Map@100
          - type: cosine_map@150
            value: 0.5454012672534121
            name: Cosine Map@150
          - type: cosine_map@200
            value: 0.5494570875591636
            name: Cosine Map@200
          - type: cosine_map@500
            value: 0.5542116087189223
            name: Cosine Map@500
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: mix es
          type: mix_es
        metrics:
          - type: cosine_accuracy@1
            value: 0.7087883515340614
            name: Cosine Accuracy@1
          - type: cosine_accuracy@20
            value: 0.9552782111284451
            name: Cosine Accuracy@20
          - type: cosine_accuracy@50
            value: 0.9802392095683827
            name: Cosine Accuracy@50
          - type: cosine_accuracy@100
            value: 0.9901196047841914
            name: Cosine Accuracy@100
          - type: cosine_accuracy@150
            value: 0.9937597503900156
            name: Cosine Accuracy@150
          - type: cosine_accuracy@200
            value: 0.9958398335933437
            name: Cosine Accuracy@200
          - type: cosine_precision@1
            value: 0.7087883515340614
            name: Cosine Precision@1
          - type: cosine_precision@20
            value: 0.12158086323452937
            name: Cosine Precision@20
          - type: cosine_precision@50
            value: 0.05122204888195529
            name: Cosine Precision@50
          - type: cosine_precision@100
            value: 0.026125845033801356
            name: Cosine Precision@100
          - type: cosine_precision@150
            value: 0.017548968625411682
            name: Cosine Precision@150
          - type: cosine_precision@200
            value: 0.013239729589183572
            name: Cosine Precision@200
          - type: cosine_recall@1
            value: 0.2737959042171211
            name: Cosine Recall@1
          - type: cosine_recall@20
            value: 0.8990032934650719
            name: Cosine Recall@20
          - type: cosine_recall@50
            value: 0.9459438377535101
            name: Cosine Recall@50
          - type: cosine_recall@100
            value: 0.9650979372508233
            name: Cosine Recall@100
          - type: cosine_recall@150
            value: 0.9731582596637198
            name: Cosine Recall@150
          - type: cosine_recall@200
            value: 0.979086496793205
            name: Cosine Recall@200
          - type: cosine_ndcg@1
            value: 0.7087883515340614
            name: Cosine Ndcg@1
          - type: cosine_ndcg@20
            value: 0.7814741332820433
            name: Cosine Ndcg@20
          - type: cosine_ndcg@50
            value: 0.7944033394497885
            name: Cosine Ndcg@50
          - type: cosine_ndcg@100
            value: 0.7986024294603647
            name: Cosine Ndcg@100
          - type: cosine_ndcg@150
            value: 0.8001222520801115
            name: Cosine Ndcg@150
          - type: cosine_ndcg@200
            value: 0.801183843730514
            name: Cosine Ndcg@200
          - type: cosine_mrr@1
            value: 0.7087883515340614
            name: Cosine Mrr@1
          - type: cosine_mrr@20
            value: 0.7804158804359833
            name: Cosine Mrr@20
          - type: cosine_mrr@50
            value: 0.7812547046826683
            name: Cosine Mrr@50
          - type: cosine_mrr@100
            value: 0.7813961782842836
            name: Cosine Mrr@100
          - type: cosine_mrr@150
            value: 0.7814280971923943
            name: Cosine Mrr@150
          - type: cosine_mrr@200
            value: 0.7814392363829243
            name: Cosine Mrr@200
          - type: cosine_map@1
            value: 0.7087883515340614
            name: Cosine Map@1
          - type: cosine_map@20
            value: 0.7070596364024803
            name: Cosine Map@20
          - type: cosine_map@50
            value: 0.7106867578203881
            name: Cosine Map@50
          - type: cosine_map@100
            value: 0.7112928928384499
            name: Cosine Map@100
          - type: cosine_map@150
            value: 0.7114314004578745
            name: Cosine Map@150
          - type: cosine_map@200
            value: 0.711504950521157
            name: Cosine Map@200
          - type: cosine_map@500
            value: 0.7116431478000537
            name: Cosine Map@500
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: mix de
          type: mix_de
        metrics:
          - type: cosine_accuracy@1
            value: 0.6484659386375455
            name: Cosine Accuracy@1
          - type: cosine_accuracy@20
            value: 0.9323972958918356
            name: Cosine Accuracy@20
          - type: cosine_accuracy@50
            value: 0.968278731149246
            name: Cosine Accuracy@50
          - type: cosine_accuracy@100
            value: 0.984919396775871
            name: Cosine Accuracy@100
          - type: cosine_accuracy@150
            value: 0.9885595423816953
            name: Cosine Accuracy@150
          - type: cosine_accuracy@200
            value: 0.9937597503900156
            name: Cosine Accuracy@200
          - type: cosine_precision@1
            value: 0.6484659386375455
            name: Cosine Precision@1
          - type: cosine_precision@20
            value: 0.12093083723348932
            name: Cosine Precision@20
          - type: cosine_precision@50
            value: 0.05140925637025482
            name: Cosine Precision@50
          - type: cosine_precision@100
            value: 0.02647425897035882
            name: Cosine Precision@100
          - type: cosine_precision@150
            value: 0.017892182353960822
            name: Cosine Precision@150
          - type: cosine_precision@200
            value: 0.013530941237649509
            name: Cosine Precision@200
          - type: cosine_recall@1
            value: 0.2435517420696828
            name: Cosine Recall@1
          - type: cosine_recall@20
            value: 0.87873114924597
            name: Cosine Recall@20
          - type: cosine_recall@50
            value: 0.9319899462645173
            name: Cosine Recall@50
          - type: cosine_recall@100
            value: 0.9596117178020455
            name: Cosine Recall@100
          - type: cosine_recall@150
            value: 0.9718322066215982
            name: Cosine Recall@150
          - type: cosine_recall@200
            value: 0.9799791991679667
            name: Cosine Recall@200
          - type: cosine_ndcg@1
            value: 0.6484659386375455
            name: Cosine Ndcg@1
          - type: cosine_ndcg@20
            value: 0.7448150588358
            name: Cosine Ndcg@20
          - type: cosine_ndcg@50
            value: 0.7595232400510039
            name: Cosine Ndcg@50
          - type: cosine_ndcg@100
            value: 0.7656851368194345
            name: Cosine Ndcg@100
          - type: cosine_ndcg@150
            value: 0.7681576326024331
            name: Cosine Ndcg@150
          - type: cosine_ndcg@200
            value: 0.7696474672652458
            name: Cosine Ndcg@200
          - type: cosine_mrr@1
            value: 0.6484659386375455
            name: Cosine Mrr@1
          - type: cosine_mrr@20
            value: 0.7323691045739125
            name: Cosine Mrr@20
          - type: cosine_mrr@50
            value: 0.733538875120878
            name: Cosine Mrr@50
          - type: cosine_mrr@100
            value: 0.733776247038599
            name: Cosine Mrr@100
          - type: cosine_mrr@150
            value: 0.7338087409764548
            name: Cosine Mrr@150
          - type: cosine_mrr@200
            value: 0.7338398642058079
            name: Cosine Mrr@200
          - type: cosine_map@1
            value: 0.6484659386375455
            name: Cosine Map@1
          - type: cosine_map@20
            value: 0.6646138211839377
            name: Cosine Map@20
          - type: cosine_map@50
            value: 0.6683657128313888
            name: Cosine Map@50
          - type: cosine_map@100
            value: 0.6692634410264182
            name: Cosine Map@100
          - type: cosine_map@150
            value: 0.669518875077899
            name: Cosine Map@150
          - type: cosine_map@200
            value: 0.6696171599377958
            name: Cosine Map@200
          - type: cosine_map@500
            value: 0.6697127210085475
            name: Cosine Map@500
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: mix zh
          type: mix_zh
        metrics:
          - type: cosine_accuracy@1
            value: 0.7667014613778705
            name: Cosine Accuracy@1
          - type: cosine_accuracy@20
            value: 0.9843423799582464
            name: Cosine Accuracy@20
          - type: cosine_accuracy@50
            value: 0.9932150313152401
            name: Cosine Accuracy@50
          - type: cosine_accuracy@100
            value: 0.9958246346555324
            name: Cosine Accuracy@100
          - type: cosine_accuracy@150
            value: 0.9973903966597077
            name: Cosine Accuracy@150
          - type: cosine_accuracy@200
            value: 0.9979123173277662
            name: Cosine Accuracy@200
          - type: cosine_precision@1
            value: 0.7667014613778705
            name: Cosine Precision@1
          - type: cosine_precision@20
            value: 0.13870041753653445
            name: Cosine Precision@20
          - type: cosine_precision@50
            value: 0.05810020876826725
            name: Cosine Precision@50
          - type: cosine_precision@100
            value: 0.029598121085595
            name: Cosine Precision@100
          - type: cosine_precision@150
            value: 0.01986778009742519
            name: Cosine Precision@150
          - type: cosine_precision@200
            value: 0.014945198329853866
            name: Cosine Precision@200
          - type: cosine_recall@1
            value: 0.25692041952480366
            name: Cosine Recall@1
          - type: cosine_recall@20
            value: 0.9156576200417536
            name: Cosine Recall@20
          - type: cosine_recall@50
            value: 0.9582637439109255
            name: Cosine Recall@50
          - type: cosine_recall@100
            value: 0.9765483646485734
            name: Cosine Recall@100
          - type: cosine_recall@150
            value: 0.9833768267223383
            name: Cosine Recall@150
          - type: cosine_recall@200
            value: 0.986464857341684
            name: Cosine Recall@200
          - type: cosine_ndcg@1
            value: 0.7667014613778705
            name: Cosine Ndcg@1
          - type: cosine_ndcg@20
            value: 0.8002168358295473
            name: Cosine Ndcg@20
          - type: cosine_ndcg@50
            value: 0.8125113081884888
            name: Cosine Ndcg@50
          - type: cosine_ndcg@100
            value: 0.8167350090334409
            name: Cosine Ndcg@100
          - type: cosine_ndcg@150
            value: 0.8181122471507385
            name: Cosine Ndcg@150
          - type: cosine_ndcg@200
            value: 0.8186874070081017
            name: Cosine Ndcg@200
          - type: cosine_mrr@1
            value: 0.7667014613778705
            name: Cosine Mrr@1
          - type: cosine_mrr@20
            value: 0.8421752732824312
            name: Cosine Mrr@20
          - type: cosine_mrr@50
            value: 0.8424954415974232
            name: Cosine Mrr@50
          - type: cosine_mrr@100
            value: 0.8425358910333786
            name: Cosine Mrr@100
          - type: cosine_mrr@150
            value: 0.8425483391786986
            name: Cosine Mrr@150
          - type: cosine_mrr@200
            value: 0.8425515411459873
            name: Cosine Mrr@200
          - type: cosine_map@1
            value: 0.7667014613778705
            name: Cosine Map@1
          - type: cosine_map@20
            value: 0.7007206423896271
            name: Cosine Map@20
          - type: cosine_map@50
            value: 0.7046277360194696
            name: Cosine Map@50
          - type: cosine_map@100
            value: 0.7053668771050886
            name: Cosine Map@100
          - type: cosine_map@150
            value: 0.7055166914145262
            name: Cosine Map@150
          - type: cosine_map@200
            value: 0.7055658329670217
            name: Cosine Map@200
          - type: cosine_map@500
            value: 0.7056512281794008
            name: Cosine Map@500

Job - Job matching Alibaba-NLP/gte-multilingual-base (v2)

Top performing model on TalentCLEF 2025 Task A. Use it for multilingual job title matching

Model Details

Model Description

• Model Type: Sentence Transformer
• Base model: Alibaba-NLP/gte-multilingual-base
• Maximum Sequence Length: 512 tokens
• Output Dimensionality: 768 dimensions
• Similarity Function: Cosine Similarity
• Training Datasets:
  • full_en
  • full_de
  • full_es
  • full_zh
  • mix

Model Sources

• Documentation: Sentence Transformers Documentation
• Repository: Sentence Transformers on GitHub
• Hugging Face: Sentence Transformers on Hugging Face

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: NewModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
  (2): Normalize()
)

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("pj-mathematician/JobGTE-multilingual-base-v2")
# Run inference
sentences = [
    'Volksvertreter',
    'Parlamentarier',
    'Oberbürgermeister',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]

Evaluation

Metrics

Information Retrieval

• Datasets: full_en, full_es, full_de, full_zh, mix_es, mix_de and mix_zh
• Evaluated with InformationRetrievalEvaluator

Metric	full_en	full_es	full_de	full_zh	mix_es	mix_de	mix_zh
cosine_accuracy@1	0.6667	0.1243	0.2956	0.6796	0.7088	0.6485	0.7667
cosine_accuracy@20	0.9905	1.0	0.9754	0.9806	0.9553	0.9324	0.9843
cosine_accuracy@50	0.9905	1.0	0.9852	0.9903	0.9802	0.9683	0.9932
cosine_accuracy@100	0.9905	1.0	0.9901	0.9903	0.9901	0.9849	0.9958
cosine_accuracy@150	0.9905	1.0	0.9901	0.9903	0.9938	0.9886	0.9974
cosine_accuracy@200	0.9905	1.0	0.9901	0.9903	0.9958	0.9938	0.9979
cosine_precision@1	0.6667	0.1243	0.2956	0.6796	0.7088	0.6485	0.7667
cosine_precision@20	0.5148	0.5759	0.5103	0.4883	0.1216	0.1209	0.1387
cosine_precision@50	0.32	0.3923	0.3694	0.2963	0.0512	0.0514	0.0581
cosine_precision@100	0.1905	0.2566	0.2397	0.1788	0.0261	0.0265	0.0296
cosine_precision@150	0.1362	0.1928	0.1808	0.1278	0.0175	0.0179	0.0199
cosine_precision@200	0.1054	0.1528	0.1462	0.0999	0.0132	0.0135	0.0149
cosine_recall@1	0.0685	0.0036	0.0111	0.0693	0.2738	0.2436	0.2569
cosine_recall@20	0.5491	0.3853	0.3208	0.5251	0.899	0.8787	0.9157
cosine_recall@50	0.7554	0.566	0.5042	0.7083	0.9459	0.932	0.9583
cosine_recall@100	0.8503	0.6899	0.6173	0.8169	0.9651	0.9596	0.9765
cosine_recall@150	0.8995	0.754	0.6848	0.8613	0.9732	0.9718	0.9834
cosine_recall@200	0.9208	0.7858	0.7253	0.8898	0.9791	0.98	0.9865
cosine_ndcg@1	0.6667	0.1243	0.2956	0.6796	0.7088	0.6485	0.7667
cosine_ndcg@20	0.6952	0.6169	0.5378	0.6681	0.7815	0.7448	0.8002
cosine_ndcg@50	0.723	0.5914	0.5288	0.6857	0.7944	0.7595	0.8125
cosine_ndcg@100	0.7733	0.6235	0.5552	0.7379	0.7986	0.7657	0.8167
cosine_ndcg@150	0.7947	0.6557	0.5888	0.7577	0.8001	0.7682	0.8181
cosine_ndcg@200	0.8039	0.6717	0.6092	0.7697	0.8012	0.7696	0.8187
cosine_mrr@1	0.6667	0.1243	0.2956	0.6796	0.7088	0.6485	0.7667
cosine_mrr@20	0.8183	0.5581	0.5165	0.8159	0.7804	0.7324	0.8422
cosine_mrr@50	0.8183	0.5581	0.5168	0.8163	0.7813	0.7335	0.8425
cosine_mrr@100	0.8183	0.5581	0.5168	0.8163	0.7814	0.7338	0.8425
cosine_mrr@150	0.8183	0.5581	0.5168	0.8163	0.7814	0.7338	0.8425
cosine_mrr@200	0.8183	0.5581	0.5168	0.8163	0.7814	0.7338	0.8426
cosine_map@1	0.6667	0.1243	0.2956	0.6796	0.7088	0.6485	0.7667
cosine_map@20	0.5566	0.4841	0.3984	0.5222	0.7071	0.6646	0.7007
cosine_map@50	0.5534	0.4304	0.3603	0.5083	0.7107	0.6684	0.7046
cosine_map@100	0.5852	0.4374	0.3632	0.5372	0.7113	0.6693	0.7054
cosine_map@150	0.5943	0.4527	0.3782	0.5454	0.7114	0.6695	0.7055
cosine_map@200	0.5976	0.4593	0.3863	0.5495	0.7115	0.6696	0.7056
cosine_map@500	0.6016	0.472	0.3992	0.5542	0.7116	0.6697	0.7057

Training Details

Training Datasets

full_en

full_en

• Dataset: full_en
• Size: 28,880 training samples
• Columns: anchor and positive
• Approximate statistics based on the first 1000 samples:

  	anchor	positive
  type	string	string
  details	min: 3 tokens mean: 5.68 tokens max: 11 tokens	min: 3 tokens mean: 5.76 tokens max: 12 tokens

• Samples:

  anchor	positive
  air commodore	flight lieutenant
  command and control officer	flight officer
  air commodore	command and control officer

• Loss: GISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.01, 'margin_strategy': 'absolute', 'margin': 0.0}
  

full_de

full_de

• Dataset: full_de
• Size: 23,023 training samples
• Columns: anchor and positive
• Approximate statistics based on the first 1000 samples:

  	anchor	positive
  type	string	string
  details	min: 3 tokens mean: 7.99 tokens max: 30 tokens	min: 3 tokens mean: 8.19 tokens max: 30 tokens

• Samples:

  anchor	positive
  Staffelkommandantin	Kommodore
  Luftwaffenoffizierin	Luftwaffenoffizier/Luftwaffenoffizierin
  Staffelkommandantin	Luftwaffenoffizierin

• Loss: GISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.01, 'margin_strategy': 'absolute', 'margin': 0.0}
  

full_es

full_es

• Dataset: full_es
• Size: 20,724 training samples
• Columns: anchor and positive
• Approximate statistics based on the first 1000 samples:

  	anchor	positive
  type	string	string
  details	min: 3 tokens mean: 9.13 tokens max: 32 tokens	min: 3 tokens mean: 8.84 tokens max: 32 tokens

• Samples:

  anchor	positive
  jefe de escuadrón	instructor
  comandante de aeronave	instructor de simulador
  instructor	oficial del Ejército del Aire

• Loss: GISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.01, 'margin_strategy': 'absolute', 'margin': 0.0}
  

full_zh

full_zh

• Dataset: full_zh
• Size: 30,401 training samples
• Columns: anchor and positive
• Approximate statistics based on the first 1000 samples:

  	anchor	positive
  type	string	string
  details	min: 5 tokens mean: 7.15 tokens max: 14 tokens	min: 5 tokens mean: 7.46 tokens max: 21 tokens

• Samples:

  anchor	positive
  技术总监	技术和运营总监
  技术总监	技术主管
  技术总监	技术艺术总监

• Loss: GISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.01, 'margin_strategy': 'absolute', 'margin': 0.0}
  

mix

mix

• Dataset: mix
• Size: 21,760 training samples
• Columns: anchor and positive
• Approximate statistics based on the first 1000 samples:

  	anchor	positive
  type	string	string
  details	min: 2 tokens mean: 6.71 tokens max: 19 tokens	min: 2 tokens mean: 7.69 tokens max: 19 tokens

• Samples:

  anchor	positive
  technical manager	Technischer Direktor für Bühne, Film und Fernsehen
  head of technical	directora técnica
  head of technical department	技术艺术总监

• Loss: GISTEmbedLoss with these parameters:

  {'guide': SentenceTransformer(
    (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: BertModel 
    (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
    (2): Normalize()
  ), 'temperature': 0.01, 'margin_strategy': 'absolute', 'margin': 0.0}
  

Training Hyperparameters

Non-Default Hyperparameters

• eval_strategy: steps
• per_device_train_batch_size: 128
• per_device_eval_batch_size: 128
• gradient_accumulation_steps: 2
• num_train_epochs: 5
• warmup_ratio: 0.05
• log_on_each_node: False
• fp16: True
• dataloader_num_workers: 4
• ddp_find_unused_parameters: True
• batch_sampler: no_duplicates

All Hyperparameters

Click to expand

• overwrite_output_dir: False
• do_predict: False
• eval_strategy: steps
• prediction_loss_only: True
• per_device_train_batch_size: 128
• per_device_eval_batch_size: 128
• per_gpu_train_batch_size: None
• per_gpu_eval_batch_size: None
• gradient_accumulation_steps: 2
• eval_accumulation_steps: None
• torch_empty_cache_steps: None
• learning_rate: 5e-05
• weight_decay: 0.0
• adam_beta1: 0.9
• adam_beta2: 0.999
• adam_epsilon: 1e-08
• max_grad_norm: 1.0
• num_train_epochs: 5
• max_steps: -1
• lr_scheduler_type: linear
• lr_scheduler_kwargs: {}
• warmup_ratio: 0.05
• warmup_steps: 0
• log_level: passive
• log_level_replica: warning
• log_on_each_node: False
• logging_nan_inf_filter: True
• save_safetensors: True
• save_on_each_node: False
• save_only_model: False
• restore_callback_states_from_checkpoint: False
• no_cuda: False
• use_cpu: False
• use_mps_device: False
• seed: 42
• data_seed: None
• jit_mode_eval: False
• use_ipex: False
• bf16: False
• fp16: True
• fp16_opt_level: O1
• half_precision_backend: auto
• bf16_full_eval: False
• fp16_full_eval: False
• tf32: None
• local_rank: 0
• ddp_backend: None
• tpu_num_cores: None
• tpu_metrics_debug: False
• debug: []
• dataloader_drop_last: True
• dataloader_num_workers: 4
• dataloader_prefetch_factor: None
• past_index: -1
• disable_tqdm: False
• remove_unused_columns: True
• label_names: None
• load_best_model_at_end: False
• ignore_data_skip: False
• fsdp: []
• fsdp_min_num_params: 0
• fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
• tp_size: 0
• fsdp_transformer_layer_cls_to_wrap: None
• accelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
• deepspeed: None
• label_smoothing_factor: 0.0
• optim: adamw_torch
• optim_args: None
• adafactor: False
• group_by_length: False
• length_column_name: length
• ddp_find_unused_parameters: True
• ddp_bucket_cap_mb: None
• ddp_broadcast_buffers: False
• dataloader_pin_memory: True
• dataloader_persistent_workers: False
• skip_memory_metrics: True
• use_legacy_prediction_loop: False
• push_to_hub: False
• resume_from_checkpoint: None
• hub_model_id: None
• hub_strategy: every_save
• hub_private_repo: None
• hub_always_push: False
• gradient_checkpointing: False
• gradient_checkpointing_kwargs: None
• include_inputs_for_metrics: False
• include_for_metrics: []
• eval_do_concat_batches: True
• fp16_backend: auto
• push_to_hub_model_id: None
• push_to_hub_organization: None
• mp_parameters:
• auto_find_batch_size: False
• full_determinism: False
• torchdynamo: None
• ray_scope: last
• ddp_timeout: 1800
• torch_compile: False
• torch_compile_backend: None
• torch_compile_mode: None
• include_tokens_per_second: False
• include_num_input_tokens_seen: False
• neftune_noise_alpha: None
• optim_target_modules: None
• batch_eval_metrics: False
• eval_on_start: False
• use_liger_kernel: False
• eval_use_gather_object: False
• average_tokens_across_devices: False
• prompts: None
• batch_sampler: no_duplicates
• multi_dataset_batch_sampler: proportional

Training Logs

Epoch	Step	Training Loss	full_en_cosine_ndcg@200	full_es_cosine_ndcg@200	full_de_cosine_ndcg@200	full_zh_cosine_ndcg@200	mix_es_cosine_ndcg@200	mix_de_cosine_ndcg@200	mix_zh_cosine_ndcg@200
-1	-1	-	0.7447	0.6125	0.5378	0.7240	0.7029	0.6345	0.7437
0.0082	1	4.3088	-	-	-	-	-	-	-
0.8230	100	1.9026	-	-	-	-	-	-	-
1.6502	200	0.9336	0.8024	0.6703	0.6109	0.7695	0.7914	0.7594	0.8136
2.4774	300	0.161	-	-	-	-	-	-	-
3.3045	400	0.1398	0.8039	0.6717	0.6092	0.7697	0.8012	0.7696	0.8187

Framework Versions

• Python: 3.11.11
• Sentence Transformers: 4.1.0
• Transformers: 4.51.2
• PyTorch: 2.6.0+cu124
• Accelerate: 1.6.0
• Datasets: 3.5.0
• Tokenizers: 0.21.1

Citation

BibTeX

Sentence Transformers

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

GISTEmbedLoss

@misc{solatorio2024gistembed,
    title={GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning},
    author={Aivin V. Solatorio},
    year={2024},
    eprint={2402.16829},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}