metadata

tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:18644575
  - loss:RZTKMatryoshka2dLoss
base_model: intfloat/multilingual-e5-base
widget:
  - source_sentence: 'query: кисточки для макияжа'
    sentences:
      - 'passage: Парасоля компактна складана Airton Z3510 механіка Чорна'
      - 'passage: Корпус FrimeCom LB-081 BL 400W 12cm'
      - 'passage: Кисті для макіяжу Kylie 12 шт набір кистей пензлика 12 шт Білі'
  - source_sentence: 'query: hg средство'
    sentences:
      - 'passage: Відеореєстратор Globex GE-115'
      - 'passage: Плямовивідник для тканин HG Oxi 0.5 кг (324050106)'
      - >-
        passage: Мережевий подовжувач MERLION B530, 10А 220В, 5 розеток, 3,0 м,
        перетин 3х0,75мм, чорний Q30
  - source_sentence: 'query: 471 картридж'
    sentences:
      - 'passage: Картридж Canon CLI-471 XL PIXMA MG5740/MG6840 Grey (0350C001)'
      - 'passage: Ключница Valenta кожаная Синяя (ХК41612)'
      - 'passage: Біговели  Діаметр коліс 12" (30.5 см)'
  - source_sentence: 'query: кольцо'
    sentences:
      - >-
        passage: Сумки SumWin Для кого Для женщин Вид Сумки. Цвет Черный
        Количество грузовых мест 1 Модель сумки Кросс-боди Материал
        Искусственная кожа Страна регистрации бренда Украина
        Страна-производитель товара Китай Тип гарантийного талона Гарантия по
        чеку Форма Круглая Доставка Доставка в магазины ROZETKA
      - >-
        passage: Корпуси Phanteks Форм-фактор материнської плати ATX Тип корпусу
        Fulltower Колір Чорний Кількість внутрішніх відсіків 3.5" 13 теги Круті
        Матеріал Алюміній
      - 'passage: Кольцо с бабочкой "Mini Butterfly", серебро'
  - source_sentence: 'query: сумочка женская'
    sentences:
      - >-
        passage: Сумки Без бренда Для кого Для женщин Цвет Черный Стиль
        Повседневные Модель сумки Кросс-боди Материал Экокожа Страна регистрации
        бренда Украина Страна-производитель товара Китай Количество отделений 3
        Форма Трапеция Застежка Магнит
      - >-
        passage: Пенали Kite Гарантія 14 днів Колір Бірюзовий Стать Для дівчаток
        Матеріал Поліестер Кількість відділень 1 Кількість вантажних місць 1
        Країна реєстрації бренда Німеччина Країна-виробник товару Китай Вага, г
        350 Тип гарантійного талона Гарантія по чеку Особливості З наповненням
        Форма Книжка
      - >-
        passage: Шампунь PROFIStyle Класс косметики Профессиональная Пол Для
        женщин Количество грузовых мест 1 Страна регистрации бренда Украина
        Серия Profistyle Страна-производитель товара Украина Объем 5 л Тип волос
        Все типы волос Назначение Для очищения волос Тип гарантийного талона Без
        гарантийного талона Доставка Доставка в магазины ROZETKA Доставка Готов
        к отправке
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
  - dot_accuracy@1
  - dot_accuracy@3
  - dot_accuracy@5
  - dot_accuracy@10
  - dot_precision@1
  - dot_precision@3
  - dot_precision@5
  - dot_precision@10
  - dot_recall@1
  - dot_recall@3
  - dot_recall@5
  - dot_recall@10
  - dot_ndcg@10
  - dot_mrr@10
  - dot_map@100
  - dot_ndcg@1
  - dot_mrr@1
model-index:
  - name: SentenceTransformer based on intfloat/multilingual-e5-base
    results:
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: bm full
          type: bm-full
        metrics:
          - type: dot_accuracy@1
            value: 0.47841472045293704
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.6553432413305025
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.7331917905166313
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.8283793347487615
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.47841472045293704
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.4861995753715499
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.4876150035385704
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.4910474168435951
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.011351462591853162
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.03449117733770484
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.057669566486942436
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.11452942341940178
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.48926390789530216
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.5827980543479477
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.36280520756352586
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: core uk title
          type: core-uk-title
        metrics:
          - type: dot_accuracy@1
            value: 0.6303901437371663
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.8542094455852156
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.9240246406570842
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.973305954825462
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.6303901437371663
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.6379192334017795
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.624640657084189
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.5196098562628337
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.06432071345934735
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.1941943610200646
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.3154921649259734
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.5135267830369895
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.5824689476221301
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.7525264007040191
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.5641261600874217
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: core ru title
          type: core-ru-title
        metrics:
          - type: dot_accuracy@1
            value: 0.6416837782340863
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.8562628336755647
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.9229979466119097
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.9691991786447639
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.6416837782340863
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.6471594798083503
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.633264887063655
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.5252566735112937
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.0656523606676101
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.19734738384711206
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.32075535697878377
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.518985171764795
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.5898234843670869
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.7593062481666181
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.5728620912840142
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: core uk options
          type: core-uk-options
        metrics:
          - type: dot_accuracy@1
            value: 0.4948665297741273
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.7464065708418891
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.837782340862423
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.9322381930184805
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.4948665297741273
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.4989733059548255
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.49507186858316227
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.45400410677618075
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.04964465358761168
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.15084259771646535
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.24819367614844123
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.4471062523959915
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.4895423721577878
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.6382761318079595
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.49557058138522575
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: core ru options
          type: core-ru-options
        metrics:
          - type: dot_accuracy@1
            value: 0.48767967145790553
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.7505133470225873
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.8367556468172485
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.9291581108829569
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.48767967145790553
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.4986310746064339
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.4975359342915811
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.45195071868583164
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.04851468328413007
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.14950617034051025
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.2481739767794847
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.44488472424288944
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.48827111188574646
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.6368082037743232
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.4951823868475039
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: options uk title
          type: options-uk-title
        metrics:
          - type: dot_accuracy@1
            value: 0.7572383073496659
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.9376391982182628
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.9665924276169265
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.9933184855233853
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.7572383073496659
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.7490720118782479
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.711804008908686
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.5541202672605791
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.11543915129661232
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.34200363482100676
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.5370094518201423
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.7924881972766159
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.7650169670738622
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.850054795489094
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.7380727317887708
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: options ru title
          type: options-ru-title
        metrics:
          - type: dot_accuracy@1
            value: 0.7706013363028953
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.9309576837416481
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.9665924276169265
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.9933184855233853
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.7706013363028953
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.746844840386043
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.712249443207127
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.5505567928730514
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.11822576705650203
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.3409996400530922
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.5359948514736934
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.7883290428947444
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.7637672715459831
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.8557897620815217
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.7395006608870638
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: options uk options
          type: options-uk-options
        metrics:
          - type: dot_accuracy@1
            value: 0.6325167037861915
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.844097995545657
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.910913140311804
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.9487750556792873
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.6325167037861915
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.6221232368225686
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.602672605790646
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.49643652561247215
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.09247718997162206
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.27593618334152853
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.4409379348688926
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.6951361370626404
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.6589801178305443
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.7480468059532647
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.6414571076888178
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: options ru options
          type: options-ru-options
        metrics:
          - type: dot_accuracy@1
            value: 0.6369710467706013
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.8374164810690423
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.8930957683741648
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.9465478841870824
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.6369710467706013
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.635486265775798
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.6071269487750557
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.4939866369710468
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.09363496562828412
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.2826698419126036
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.44549921743685666
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.6956133880966844
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.6610343624368801
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.7464338742178385
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.6451679716029399
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: rusisms uk title
          type: rusisms-uk-title
        metrics:
          - type: dot_accuracy@1
            value: 0.6412698412698413
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.7904761904761904
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.8285714285714286
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.8857142857142857
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.6412698412698413
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.6634920634920635
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.6552380952380952
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.6234920634920637
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.04133075530701777
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.1170592846495341
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.17830553909997546
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.31008571089134707
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.6647746031552833
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.7268543713781809
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.5853570509786064
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: rusisms ru title
          type: rusisms-ru-title
        metrics:
          - type: dot_accuracy@1
            value: 0.6698412698412698
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.7777777777777778
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.834920634920635
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.8920634920634921
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.6698412698412698
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.6645502645502644
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.6577777777777778
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.626031746031746
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.04434422970262397
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.11704562106444193
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.1773543477691105
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.30781876553915866
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.6682830160464889
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.7408213655832702
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.592275762720651
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: rusisms uk options
          type: rusisms-uk-options
        metrics:
          - type: dot_accuracy@1
            value: 0.5079365079365079
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.6285714285714286
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.7174603174603175
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.7904761904761904
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.5079365079365079
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.5058201058201058
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.5161904761904762
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.5111111111111111
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.032681042657417864
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.08490359132017175
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.14131766688622155
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.25180769140267506
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.5372281406420663
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.5902317964222725
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.4986827236995346
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: rusisms ru options
          type: rusisms-ru-options
        metrics:
          - type: dot_accuracy@1
            value: 0.4984126984126984
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.6476190476190476
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.7492063492063492
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.8063492063492064
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.4984126984126984
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.5195767195767197
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.5276190476190475
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.5177777777777778
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.03202754604702237
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.08547386088540315
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.14166544702843223
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.25453386918000204
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.5433437983757069
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.5972423784328544
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.5053350497126974
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: rusisms corrected uk title
          type: rusisms_corrected-uk-title
        metrics:
          - type: dot_accuracy@1
            value: 0.7120253164556962
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.819620253164557
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.870253164556962
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.9113924050632911
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.7120253164556962
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.7183544303797469
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.7082278481012658
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.6683544303797468
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.04969812837853694
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.12741782983341862
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.19731659021523865
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.3409923887206817
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.7194597470114055
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.7808808016877635
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.6388697195804478
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: rusisms corrected ru title
          type: rusisms_corrected-ru-title
        metrics:
          - type: dot_accuracy@1
            value: 0.7088607594936709
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.8291139240506329
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.870253164556962
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.9113924050632911
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.7088607594936709
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.7162447257383966
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.7037974683544304
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.6629746835443039
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.04888449873376417
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.12829212684740135
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.19987613332490306
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.3356192325461046
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.7127299992462074
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.7792708961221617
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.6395009156047453
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: rusisms corrected uk options
          type: rusisms_corrected-uk-options
        metrics:
          - type: dot_accuracy@1
            value: 0.5537974683544303
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.7278481012658228
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.7848101265822784
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.8544303797468354
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.5537974683544303
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.5738396624472574
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.5759493670886076
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.5645569620253166
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.0398666442289475
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.10622990404547561
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.16577310801842357
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.28425407965410443
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.5965577106105705
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.6513147980711272
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.5594863722365065
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: rusisms corrected ru options
          type: rusisms_corrected-ru-options
        metrics:
          - type: dot_accuracy@1
            value: 0.5727848101265823
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.7215189873417721
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.7848101265822784
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.8607594936708861
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.5727848101265823
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.5822784810126582
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.5810126582278481
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.5655063291139241
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.039125841492212286
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.10198185350545384
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.16299351965480724
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.28079825575547895
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.5986535833917944
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.6613936608398633
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.5634230712770681
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: core typos uk title
          type: core_typos-uk-title
        metrics:
          - type: dot_accuracy@1
            value: 0.5451745379876797
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.7874743326488707
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.8490759753593429
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.9117043121149897
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.5451745379876797
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.5492813141683778
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.5277207392197125
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.4458932238193019
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.055501817487715537
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.16799075803409055
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.26738880088922357
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.4420220810379646
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.5009599181825904
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.6744923568332187
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.4756860853091724
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: core typos ru title
          type: core_typos-ru-title
        metrics:
          - type: dot_accuracy@1
            value: 0.5677618069815195
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.7802874743326489
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.8490759753593429
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.9075975359342916
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.5677618069815195
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.553388090349076
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.535523613963039
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.4521560574948666
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.05788962617685893
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.16991013827739276
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.2724072401441347
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.4493398516770904
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.5093051901273817
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.6864704540269218
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.48302575127668773
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: core typos uk options
          type: core_typos-uk-options
        metrics:
          - type: dot_accuracy@1
            value: 0.42505133470225875
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.6478439425051334
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.7433264887063655
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.8429158110882957
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.42505133470225875
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.4182067077344285
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.41704312114989733
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.37997946611909655
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.04281943186324754
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.12630907755998344
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.20887045080712793
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.37542821461999504
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.41173177598646793
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.5581076236107032
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.40947735972105836
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: core typos ru options
          type: core_typos-ru-options
        metrics:
          - type: dot_accuracy@1
            value: 0.42299794661190965
            name: Dot Accuracy@1
          - type: dot_accuracy@3
            value: 0.6509240246406571
            name: Dot Accuracy@3
          - type: dot_accuracy@5
            value: 0.7464065708418891
            name: Dot Accuracy@5
          - type: dot_accuracy@10
            value: 0.8459958932238193
            name: Dot Accuracy@10
          - type: dot_precision@1
            value: 0.42299794661190965
            name: Dot Precision@1
          - type: dot_precision@3
            value: 0.42231348391512663
            name: Dot Precision@3
          - type: dot_precision@5
            value: 0.41581108829568786
            name: Dot Precision@5
          - type: dot_precision@10
            value: 0.376694045174538
            name: Dot Precision@10
          - type: dot_recall@1
            value: 0.04208886721644905
            name: Dot Recall@1
          - type: dot_recall@3
            value: 0.12759403691355015
            name: Dot Recall@3
          - type: dot_recall@5
            value: 0.2076836983626753
            name: Dot Recall@5
          - type: dot_recall@10
            value: 0.37292863983662994
            name: Dot Recall@10
          - type: dot_ndcg@10
            value: 0.4101083135252108
            name: Dot Ndcg@10
          - type: dot_mrr@10
            value: 0.5588503471203672
            name: Dot Mrr@10
          - type: dot_map@100
            value: 0.40851869049399947
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: 'bm full  matryoshka dim 768  '
          type: bm-full--matryoshka_dim-768--
        metrics:
          - type: dot_accuracy@1
            value: 0.47841472045293704
            name: Dot Accuracy@1
          - type: dot_precision@1
            value: 0.47841472045293704
            name: Dot Precision@1
          - type: dot_recall@1
            value: 0.011351462591853162
            name: Dot Recall@1
          - type: dot_ndcg@1
            value: 0.47841472045293704
            name: Dot Ndcg@1
          - type: dot_mrr@1
            value: 0.47841472045293704
            name: Dot Mrr@1
          - type: dot_map@100
            value: 0.36280520756352586
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: 'bm full  matryoshka dim 512  '
          type: bm-full--matryoshka_dim-512--
        metrics:
          - type: dot_accuracy@1
            value: 0.4759377211606511
            name: Dot Accuracy@1
          - type: dot_precision@1
            value: 0.4759377211606511
            name: Dot Precision@1
          - type: dot_recall@1
            value: 0.0114070381458067
            name: Dot Recall@1
          - type: dot_ndcg@1
            value: 0.4759377211606511
            name: Dot Ndcg@1
          - type: dot_mrr@1
            value: 0.4759377211606511
            name: Dot Mrr@1
          - type: dot_map@100
            value: 0.36005063767775514
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: 'bm full  matryoshka dim 256  '
          type: bm-full--matryoshka_dim-256--
        metrics:
          - type: dot_accuracy@1
            value: 0.4759377211606511
            name: Dot Accuracy@1
          - type: dot_precision@1
            value: 0.4759377211606511
            name: Dot Precision@1
          - type: dot_recall@1
            value: 0.011372889899440053
            name: Dot Recall@1
          - type: dot_ndcg@1
            value: 0.4759377211606511
            name: Dot Ndcg@1
          - type: dot_mrr@1
            value: 0.4759377211606511
            name: Dot Mrr@1
          - type: dot_map@100
            value: 0.3488370117998616
            name: Dot Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: 'bm full  matryoshka dim 128  '
          type: bm-full--matryoshka_dim-128--
        metrics:
          - type: dot_accuracy@1
            value: 0.45222929936305734
            name: Dot Accuracy@1
          - type: dot_precision@1
            value: 0.45222929936305734
            name: Dot Precision@1
          - type: dot_recall@1
            value: 0.010638577599638174
            name: Dot Recall@1
          - type: dot_ndcg@1
            value: 0.45222929936305734
            name: Dot Ndcg@1
          - type: dot_mrr@1
            value: 0.45222929936305734
            name: Dot Mrr@1
          - type: dot_map@100
            value: 0.32466551163194907
            name: Dot Map@100

SentenceTransformer based on intfloat/multilingual-e5-base

This is a sentence-transformers model finetuned from intfloat/multilingual-e5-base on the rozetka_positive_pairs dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

Model Details

Model Description

Model Type: Sentence Transformer
Base model: intfloat/multilingual-e5-base
Maximum Sequence Length: 512 tokens
Output Dimensionality: 768 dimensions
Similarity Function: Dot Product
Training Dataset:
- rozetka_positive_pairs

Model Sources

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

Full Model Architecture

RZTKSentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: XLMRobertaModel 
  (1): Pooling({'word_embedding_dimension': 768, '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()
)

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("yklymchuk-rztk/multilingual-e5-base-matryoshka2d-mnr-4-continue")
# Run inference
sentences = [
    'query: сумочка женская',
    'passage: Сумки Без бренда Для кого Для женщин Цвет Черный Стиль Повседневные Модель сумки Кросс-боди Материал Экокожа Страна регистрации бренда Украина Страна-производитель товара Китай Количество отделений 3 Форма Трапеция Застежка Магнит',
    'passage: Пенали Kite Гарантія 14 днів Колір Бірюзовий Стать Для дівчаток Матеріал Поліестер Кількість відділень 1 Кількість вантажних місць 1 Країна реєстрації бренда Німеччина Країна-виробник товару Китай Вага, г 350 Тип гарантійного талона Гарантія по чеку Особливості З наповненням Форма Книжка',
]
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: bm-full, core-uk-title, core-ru-title, core-uk-options, core-ru-options, options-uk-title, options-ru-title, options-uk-options, options-ru-options, rusisms-uk-title, rusisms-ru-title, rusisms-uk-options, rusisms-ru-options, rusisms_corrected-uk-title, rusisms_corrected-ru-title, rusisms_corrected-uk-options, rusisms_corrected-ru-options, core_typos-uk-title, core_typos-ru-title, core_typos-uk-options and core_typos-ru-options
Evaluated with InformationRetrievalEvaluator

Metric	bm-full	core-uk-title	core-ru-title	core-uk-options	core-ru-options	options-uk-title	options-ru-title	options-uk-options	options-ru-options	rusisms-uk-title	rusisms-ru-title	rusisms-uk-options	rusisms-ru-options	rusisms_corrected-uk-title	rusisms_corrected-ru-title	rusisms_corrected-uk-options	rusisms_corrected-ru-options	core_typos-uk-title	core_typos-ru-title	core_typos-uk-options	core_typos-ru-options
dot_accuracy@1	0.4784	0.6304	0.6417	0.4949	0.4877	0.7572	0.7706	0.6325	0.637	0.6413	0.6698	0.5079	0.4984	0.712	0.7089	0.5538	0.5728	0.5452	0.5678	0.4251	0.423
dot_accuracy@3	0.6553	0.8542	0.8563	0.7464	0.7505	0.9376	0.931	0.8441	0.8374	0.7905	0.7778	0.6286	0.6476	0.8196	0.8291	0.7278	0.7215	0.7875	0.7803	0.6478	0.6509
dot_accuracy@5	0.7332	0.924	0.923	0.8378	0.8368	0.9666	0.9666	0.9109	0.8931	0.8286	0.8349	0.7175	0.7492	0.8703	0.8703	0.7848	0.7848	0.8491	0.8491	0.7433	0.7464
dot_accuracy@10	0.8284	0.9733	0.9692	0.9322	0.9292	0.9933	0.9933	0.9488	0.9465	0.8857	0.8921	0.7905	0.8063	0.9114	0.9114	0.8544	0.8608	0.9117	0.9076	0.8429	0.846
dot_precision@1	0.4784	0.6304	0.6417	0.4949	0.4877	0.7572	0.7706	0.6325	0.637	0.6413	0.6698	0.5079	0.4984	0.712	0.7089	0.5538	0.5728	0.5452	0.5678	0.4251	0.423
dot_precision@3	0.4862	0.6379	0.6472	0.499	0.4986	0.7491	0.7468	0.6221	0.6355	0.6635	0.6646	0.5058	0.5196	0.7184	0.7162	0.5738	0.5823	0.5493	0.5534	0.4182	0.4223
dot_precision@5	0.4876	0.6246	0.6333	0.4951	0.4975	0.7118	0.7122	0.6027	0.6071	0.6552	0.6578	0.5162	0.5276	0.7082	0.7038	0.5759	0.581	0.5277	0.5355	0.417	0.4158
dot_precision@10	0.491	0.5196	0.5253	0.454	0.452	0.5541	0.5506	0.4964	0.494	0.6235	0.626	0.5111	0.5178	0.6684	0.663	0.5646	0.5655	0.4459	0.4522	0.38	0.3767
dot_recall@1	0.0114	0.0643	0.0657	0.0496	0.0485	0.1154	0.1182	0.0925	0.0936	0.0413	0.0443	0.0327	0.032	0.0497	0.0489	0.0399	0.0391	0.0555	0.0579	0.0428	0.0421
dot_recall@3	0.0345	0.1942	0.1973	0.1508	0.1495	0.342	0.341	0.2759	0.2827	0.1171	0.117	0.0849	0.0855	0.1274	0.1283	0.1062	0.102	0.168	0.1699	0.1263	0.1276
dot_recall@5	0.0577	0.3155	0.3208	0.2482	0.2482	0.537	0.536	0.4409	0.4455	0.1783	0.1774	0.1413	0.1417	0.1973	0.1999	0.1658	0.163	0.2674	0.2724	0.2089	0.2077
dot_recall@10	0.1145	0.5135	0.519	0.4471	0.4449	0.7925	0.7883	0.6951	0.6956	0.3101	0.3078	0.2518	0.2545	0.341	0.3356	0.2843	0.2808	0.442	0.4493	0.3754	0.3729
dot_ndcg@10	0.4893	0.5825	0.5898	0.4895	0.4883	0.765	0.7638	0.659	0.661	0.6648	0.6683	0.5372	0.5433	0.7195	0.7127	0.5966	0.5987	0.501	0.5093	0.4117	0.4101
dot_mrr@10	0.5828	0.7525	0.7593	0.6383	0.6368	0.8501	0.8558	0.748	0.7464	0.7269	0.7408	0.5902	0.5972	0.7809	0.7793	0.6513	0.6614	0.6745	0.6865	0.5581	0.5589
dot_map@100	0.3628	0.5641	0.5729	0.4956	0.4952	0.7381	0.7395	0.6415	0.6452	0.5854	0.5923	0.4987	0.5053	0.6389	0.6395	0.5595	0.5634	0.4757	0.483	0.4095	0.4085

Information Retrieval

Datasets: bm-full--matryoshka_dim-768--, bm-full--matryoshka_dim-512--, bm-full--matryoshka_dim-256-- and bm-full--matryoshka_dim-128--
Evaluated with InformationRetrievalEvaluator

Metric	bm-full--matryoshka_dim-768--	bm-full--matryoshka_dim-512--	bm-full--matryoshka_dim-256--	bm-full--matryoshka_dim-128--
dot_accuracy@1	0.4784	0.4759	0.4759	0.4522
dot_precision@1	0.4784	0.4759	0.4759	0.4522
dot_recall@1	0.0114	0.0114	0.0114	0.0106
dot_ndcg@1	0.4784	0.4759	0.4759	0.4522
dot_mrr@1	0.4784	0.4759	0.4759	0.4522
dot_map@100	0.3628	0.3601	0.3488	0.3247

Training Details

Training Dataset

rozetka_positive_pairs

Dataset: rozetka_positive_pairs
Size: 18,644,575 training samples
Columns: query and text
Approximate statistics based on the first 1000 samples:
query text
type string string
details
min: 6 tokens
mean: 12.04 tokens
max: 30 tokens

min: 8 tokens
mean: 55.98 tokens
max: 512 tokens

	query	text
type	string	string
details	min: 6 tokens mean: 12.04 tokens max: 30 tokens	min: 8 tokens mean: 55.98 tokens max: 512 tokens

Samples:

query	text
`query: xsiomi 9c скло`	`passage: Защитные стекла Назначение Для мобильных телефонов Цвет Черный Теги Теги Наличие рамки C рамкой Форм-фактор Плоское Клеевой слой По всей поверхности`
`query: xsiomi 9c скло`	`passage: Захисне скло Glass Full Glue для Xiaomi Redmi 9A/9C/10A (Чорний)`
`query: xsiomi 9c скло`	`passage: Захисне скло Призначення Для мобільних телефонів Колір Чорний Теги Теги Наявність рамки З рамкою Форм-фактор Плоске Клейовий шар По всій поверхні`

Loss: sentence_transformers_training.model.matryoshka2d_loss.RZTKMatryoshka2dLoss with these parameters:

{
    "loss": "RZTKMultipleNegativesRankingLoss",
    "n_layers_per_step": 1,
    "last_layer_weight": 1.0,
    "prior_layers_weight": 1.0,
    "kl_div_weight": 1.0,
    "kl_temperature": 0.3,
    "matryoshka_dims": [
        768,
        512,
        256,
        128
    ],
    "matryoshka_weights": [
        1,
        1,
        1,
        1
    ],
    "n_dims_per_step": 1
}

Evaluation Dataset

rozetka_positive_pairs

Dataset: rozetka_positive_pairs
Size: 202,564 evaluation samples
Columns: query and text
Approximate statistics based on the first 1000 samples:
query text
type string string
details
min: 6 tokens
mean: 8.57 tokens
max: 17 tokens

min: 8 tokens
mean: 53.17 tokens
max: 512 tokens

	query	text
type	string	string
details	min: 6 tokens mean: 8.57 tokens max: 17 tokens	min: 8 tokens mean: 53.17 tokens max: 512 tokens

Samples:

query	text
`query: создаем нейронную сеть`	`passage: Створюємо нейронну мережу`
`query: создаем нейронную сеть`	`passage: Научная и техническая литература Переплет Мягкий`
`query: создаем нейронную сеть`	`passage: Создаем нейронную сеть (1666498)`

Loss: sentence_transformers_training.model.matryoshka2d_loss.RZTKMatryoshka2dLoss with these parameters:

{
    "loss": "RZTKMultipleNegativesRankingLoss",
    "n_layers_per_step": 1,
    "last_layer_weight": 1.0,
    "prior_layers_weight": 1.0,
    "kl_div_weight": 1.0,
    "kl_temperature": 0.3,
    "matryoshka_dims": [
        768,
        512,
        256,
        128
    ],
    "matryoshka_weights": [
        1,
        1,
        1,
        1
    ],
    "n_dims_per_step": 1
}

Training Hyperparameters

Non-Default Hyperparameters

eval_strategy: steps
per_device_train_batch_size: 88
per_device_eval_batch_size: 88
learning_rate: 2e-05
num_train_epochs: 5.0
warmup_ratio: 0.1
bf16: True
bf16_full_eval: True
tf32: True
dataloader_num_workers: 8
load_best_model_at_end: True
optim: adafactor
push_to_hub: True
hub_model_id: yklymchuk-rztk/multilingual-e5-base-matryoshka2d-mnr-4-continue
hub_private_repo: True
prompts: {'query': 'query: ', 'text': 'passage: '}
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: 88
per_device_eval_batch_size: 88
per_gpu_train_batch_size: None
per_gpu_eval_batch_size: None
gradient_accumulation_steps: 1
eval_accumulation_steps: None
torch_empty_cache_steps: None
learning_rate: 2e-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: 5.0
max_steps: -1
lr_scheduler_type: linear
lr_scheduler_kwargs: {}
warmup_ratio: 0.1
warmup_steps: 0
log_level: passive
log_level_replica: warning
log_on_each_node: True
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: True
fp16: False
fp16_opt_level: O1
half_precision_backend: auto
bf16_full_eval: True
fp16_full_eval: False
tf32: True
local_rank: 0
ddp_backend: None
tpu_num_cores: None
tpu_metrics_debug: False
debug: []
dataloader_drop_last: True
dataloader_num_workers: 8
dataloader_prefetch_factor: None
past_index: -1
disable_tqdm: False
remove_unused_columns: True
label_names: None
load_best_model_at_end: True
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}
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: adafactor
optim_args: None
adafactor: False
group_by_length: False
length_column_name: length
ddp_find_unused_parameters: None
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: True
resume_from_checkpoint: None
hub_model_id: yklymchuk-rztk/multilingual-e5-base-matryoshka2d-mnr-4-continue
hub_strategy: every_save
hub_private_repo: True
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
dispatch_batches: None
split_batches: 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: {'query': 'query: ', 'text': 'passage: '}
batch_sampler: no_duplicates
multi_dataset_batch_sampler: proportional
ddp_static_graph: False
ddp_comm_hook: bf16
gradient_as_bucket_view: False
num_proc: 30

Training Logs

Click to expand

Epoch	Step	Training Loss	Validation Loss	bm-full_dot_ndcg@10	core-uk-title_dot_ndcg@10	core-ru-title_dot_ndcg@10	core-uk-options_dot_ndcg@10	core-ru-options_dot_ndcg@10	options-uk-title_dot_ndcg@10	options-ru-title_dot_ndcg@10	options-uk-options_dot_ndcg@10	options-ru-options_dot_ndcg@10	rusisms-uk-title_dot_ndcg@10	rusisms-ru-title_dot_ndcg@10	rusisms-uk-options_dot_ndcg@10	rusisms-ru-options_dot_ndcg@10	rusisms_corrected-uk-title_dot_ndcg@10	rusisms_corrected-ru-title_dot_ndcg@10	rusisms_corrected-uk-options_dot_ndcg@10	rusisms_corrected-ru-options_dot_ndcg@10	core_typos-uk-title_dot_ndcg@10	core_typos-ru-title_dot_ndcg@10	core_typos-uk-options_dot_ndcg@10	core_typos-ru-options_dot_ndcg@10	bm-full--matryoshka_dim-768--_dot_ndcg@1	bm-full--matryoshka_dim-512--_dot_ndcg@1	bm-full--matryoshka_dim-256--_dot_ndcg@1	bm-full--matryoshka_dim-128--_dot_ndcg@1
2.7017	143100	0.7397	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.7167	143895	0.7745	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.7317	144690	0.8018	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.7467	145485	0.7712	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.7617	146280	0.7634	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.7767	147075	0.7801	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.7917	147870	0.7608	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.8067	148665	0.7886	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.8218	149460	0.7534	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.8368	150255	0.7848	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.8518	151050	0.7657	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.8668	151845	0.7943	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.8818	152640	0.7683	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.8968	153435	0.7555	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.9118	154230	0.7575	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.9268	155025	0.7253	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.9418	155820	0.7538	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.9568	156615	0.7708	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.9719	157410	0.7582	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
2.9869	158205	0.7987	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.0002	158910	-	0.4537	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.0019	159000	0.7604	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.0169	159795	0.7485	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.0319	160590	0.7761	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.0469	161385	0.7606	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.0619	162180	0.7752	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.0769	162975	0.7624	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.0919	163770	0.7764	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.1070	164565	0.7714	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.1220	165360	0.7916	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.1370	166155	0.7484	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.1520	166950	0.7751	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.1670	167745	0.7634	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.1820	168540	0.7549	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.1970	169335	0.7538	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.2120	170130	0.7545	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.2270	170925	0.7738	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.2420	171720	0.7513	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.2570	172515	0.7479	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.2721	173310	0.751	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.2871	174105	0.7583	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.3002	174801	-	0.4436	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.3021	174900	0.7593	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.3171	175695	0.7346	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.3321	176490	0.759	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.3471	177285	0.7639	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.3621	178080	0.7699	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.3771	178875	0.7463	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.3921	179670	0.7659	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.4071	180465	0.7811	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.4221	181260	0.7658	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.4372	182055	0.7529	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.4522	182850	0.7448	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.4672	183645	0.7308	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.4822	184440	0.7567	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.4972	185235	0.7634	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.5122	186030	0.7619	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.5272	186825	0.7184	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.5422	187620	0.7555	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.5572	188415	0.7801	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.5722	189210	0.7764	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.5873	190005	0.7659	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.6002	190692	-	0.4584	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.6023	190800	0.7329	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.6173	191595	0.7439	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.6323	192390	0.7605	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.6473	193185	0.7511	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.6623	193980	0.7458	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.6773	194775	0.7508	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.6923	195570	0.7467	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.7073	196365	0.7463	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.7223	197160	0.7389	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.7373	197955	0.772	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.7524	198750	0.7859	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.7674	199545	0.7543	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.7824	200340	0.7635	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.7974	201135	0.7706	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.8124	201930	0.7748	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.8274	202725	0.7552	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.8424	203520	0.7484	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.8574	204315	0.7535	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.8724	205110	0.7615	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.8874	205905	0.7536	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.9002	206583	-	0.4789	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.9024	206700	0.7566	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.9175	207495	0.7747	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.9325	208290	0.7526	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.9475	209085	0.759	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.9625	209880	0.7477	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.9775	210675	0.7632	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
3.9925	211470	0.7625	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.0075	212265	0.7535	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.0225	213060	0.745	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.0376	213855	0.7311	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.0526	214650	0.7327	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.0676	215445	0.7385	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.0826	216240	0.7521	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.0976	217035	0.7579	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.1126	217830	0.7378	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.1276	218625	0.7641	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.1426	219420	0.7637	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.1576	220215	0.7676	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.1726	221010	0.7789	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.1876	221805	0.7677	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.2003	222474	-	0.4703	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.2027	222600	0.77	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.2177	223395	0.7386	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.2327	224190	0.7432	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.2477	224985	0.7436	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.2627	225780	0.7366	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.2777	226575	0.7254	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.2927	227370	0.7594	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.3077	228165	0.7646	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.3227	228960	0.7524	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.3377	229755	0.7625	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.3527	230550	0.7647	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.3678	231345	0.7425	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.3828	232140	0.7568	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.3978	232935	0.7809	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.4128	233730	0.7762	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.4278	234525	0.7579	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.4428	235320	0.7625	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.4578	236115	0.7664	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.4728	236910	0.7357	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.4878	237705	0.7316	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.5003	238365	-	0.4811	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.5028	238500	0.7568	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.5179	239295	0.7522	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.5329	240090	0.7529	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.5479	240885	0.7468	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.5629	241680	0.7304	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.5779	242475	0.749	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.5929	243270	0.7391	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.6079	244065	0.7483	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.6229	244860	0.7682	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.6379	245655	0.7636	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.6529	246450	0.7705	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.6679	247245	0.7516	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.6830	248040	0.7632	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.6980	248835	0.7659	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.7130	249630	0.7254	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.7280	250425	0.7163	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.7430	251220	0.7552	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.7580	252015	0.7654	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.7730	252810	0.7308	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.7880	253605	0.7513	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
4.8003	254256	-	0.4811	0.4893	0.5825	0.5898	0.4895	0.4883	0.7650	0.7638	0.6590	0.6610	0.6648	0.6683	0.5372	0.5433	0.7195	0.7127	0.5966	0.5987	0.5010	0.5093	0.4117	0.4101	0.4784	0.4759	0.4759	0.4522

The bold row denotes the saved checkpoint.

Framework Versions

Python: 3.11.10
Sentence Transformers: 3.3.0
Transformers: 4.46.3
PyTorch: 2.5.1+cu124
Accelerate: 1.1.1
Datasets: 3.1.0
Tokenizers: 0.20.3

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",
}