--- tags: - sentence-transformers - sentence-similarity - feature-extraction - generated_from_trainer - dataset_size:7027160 - loss:RZTKMatryoshka2dLoss base_model: intfloat/multilingual-e5-base widget: - source_sentence: 'query: силиконовые формы' sentences: - 'passage: Пляжні шорти та плавки David Man Країна-виробник товару Італія Розмір M Колір Синій Доставка Доставка в магазини ROZETKA' - 'passage: Формы для льда Olin & Olin Гарантия Отсутствует Количество грузовых мест 1 Страна регистрации бренда Украина Материал Пластик Материал Силикон Страна-производитель товара Китай Количество отверстий 8 Вид формы Классическая Цвет Голубой' - 'passage: Ножи тактические Abeer Поверхность клинка Матовое покрытие Материал Металл' - source_sentence: 'query: светящийся ошейник' sentences: - 'passage: Cтруны для акустической гитары Avzhezh AZB11 Звичайні (11-50)' - 'passage: Нашийники AnimAll Габарити С Стандарт (до 300x200x250 мм) Тип Нашийники Матеріал Нейлон Вид собаки Для всіх порід собак Колір Синій Кількість вантажних місць 1 Країна реєстрації бренда Німеччина Країна-виробник товару Китай Тип гарантійного талона Гарантія по чеку Можливість доставки Почтомати Доставка Premium Немає Тварина Собака Наявність товара по містах Західний регіон Наявність товара по містах Київ і область Особливості Зі світловідбиваючими елементами Особливості З підсвіткою Розмір L' - 'passage: Детский термос с трубочкой А Плюс 1776 Голубой (AP112104)' - source_sentence: 'query: светящийся ошейник' sentences: - 'passage: Пляжні шорти та плавки' - 'passage: Нашийник світний AnimAll LED S 2.5/30-40 см Рожевий (64791) (2000981125615)' - 'passage: Пляжні шорти та плавки Atlantic beach Країна-виробник товару Тайвань Розмір 48 Колір Синій Матеріал Нейлон' - source_sentence: 'query: силиконовые формы' sentences: - 'passage: Формы и противни для выпечки Kamille Можно мыть в посудомоечной машине Нет Страна регистрации бренда Польша Тип Форма Назначение Универсальная Форма Прямоугольная Количество секций для выпекания 1 Материал Силикон Страна-производитель товара Польша Цвет Красный' - 'passage: Туристичні ножі RUIKE Гарантія 5 років Вид Кишенькові Матеріал ручки Сталь Габарити B Дрібний (до 50x150x200 мм) Кількість вантажних місць 1 Країна реєстрації бренда Китай Країна-виробник товару Китай Тип гарантійного талона Гарантія по чеку Наявність товара по містах Київ і область Доставка Доставка в магазини ROZETKA Марка сталі Sandvik 14C28N Тип Складані Тип складного ножа На підшипнику Примітка *Ножі, представлені в нашому магазині, не належать до холодної зброї за сукупністю характеристик згідно з висновком НДІ ЕКЦ МВС України Тип замка Frame Lock' - 'passage: Дитячий килимок NEWDAY Мадагаскар 2000×1200×8мм теплоізоляційний розвиваючий ігровий килимок' - source_sentence: 'query: йоршик для унітазу' sentences: - 'passage: Ёршики и стойки Kroner Гарантия 36 месяцев официальной гарантии от производителя Габариты_old D Большой (до 1000x200x600 мм) Тип Ёршики Комплектация Колба Комплектация Монтажные элементы Комплектация Ёршик Тип установки Настенный (подвесной) Крепление Шурупы Материал Металл / Стекло Цвет Хром с белым Количество грузовых мест 1 Страна регистрации бренда Германия Страна-производитель товара Китай Тип гарантийного талона Гарантия по чеку Наличие товара по городам Киев и область Доставка Доставка в магазины ROZETKA' - 'passage: Термосы и термокружки CON BRIO Страна регистрации бренда Украина Тип Термос Материал колбы Нержавеющая сталь Материал Нержавеющая сталь Объем 350 мл Страна-производитель товара Китай' - 'passage: Форми та деко для випікання Calve Габарити D Великий (до 1000x200x600 мм) Можна мити в посудомийній машині Так Країна реєстрації бренда Іспанія Тип поставки Один предмет Тип Форма Призначення Для тортів і чізкейків Призначення Для піци Вид_old Один предмет Кількість предметів, шт 1 Форма Кругла Діаметр Ø 28 см Матеріал Силікон Зовнішнє антипригарне покриття_old Немає Кришка_old Немає Ручки_old Є Особливості З ручками Країна-виробник товару Китай Тип гарантійного талона Гарантія по чеку Можливість доставки Почтомати Доставка Premium Немає' pipeline_tag: sentence-similarity library_name: sentence-transformers metrics: - dot_accuracy_10 - dot_precision_10 - dot_recall_10 - dot_ndcg_10 - dot_mrr_10 - dot_map_60 - dot_accuracy_1 - dot_accuracy_3 - dot_accuracy_5 - dot_precision_1 - dot_precision_3 - dot_precision_5 - dot_recall_1 - dot_recall_3 - dot_recall_5 - dot_map_100 - dot_ndcg_1 - dot_mrr_1 model-index: - name: SentenceTransformer based on intfloat/multilingual-e5-base results: - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: 'validation matryoshka dim 768 ' type: validation--matryoshka_dim-768-- metrics: - type: dot_accuracy_10 value: 0.5660196863278202 name: Dot Accuracy 10 - type: dot_precision_10 value: 0.1145683860735594 name: Dot Precision 10 - type: dot_recall_10 value: 0.4021495026845541 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.29730053742212376 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.3021168116988048 name: Dot Mrr 10 - type: dot_map_60 value: 0.25690215532549737 name: Dot Map 60 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: bm full type: bm-full metrics: - type: dot_accuracy_1 value: 0.5035385704175513 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.6726822363765039 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.7473460721868365 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.8333333333333334 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.5035385704175513 name: Dot Precision 1 - type: dot_precision_3 value: 0.5047180938900684 name: Dot Precision 3 - type: dot_precision_5 value: 0.5002123142250531 name: Dot Precision 5 - type: dot_precision_10 value: 0.49529370134465667 name: Dot Precision 10 - type: dot_recall_1 value: 0.011675176874642076 name: Dot Recall 1 - type: dot_recall_3 value: 0.035479655122023765 name: Dot Recall 3 - type: dot_recall_5 value: 0.05820220258723965 name: Dot Recall 5 - type: dot_recall_10 value: 0.11408174487658303 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.49773455898124164 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.6029184780777128 name: Dot Mrr 10 - type: dot_map_100 value: 0.34697975642189044 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: core uk title type: core-uk-title metrics: - type: dot_accuracy_1 value: 0.6437371663244353 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.851129363449692 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.9117043121149897 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.9671457905544147 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.6437371663244353 name: Dot Precision 1 - type: dot_precision_3 value: 0.6341546885694729 name: Dot Precision 3 - type: dot_precision_5 value: 0.6188911704312114 name: Dot Precision 5 - type: dot_precision_10 value: 0.5157084188911705 name: Dot Precision 10 - type: dot_recall_1 value: 0.06649123346490177 name: Dot Recall 1 - type: dot_recall_3 value: 0.1943973593108452 name: Dot Recall 3 - type: dot_recall_5 value: 0.3142245364350993 name: Dot Recall 5 - type: dot_recall_10 value: 0.510158440658803 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.5812457455535947 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.7578782471236273 name: Dot Mrr 10 - type: dot_map_100 value: 0.5543972240150046 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: core ru title type: core-ru-title metrics: - type: dot_accuracy_1 value: 0.6652977412731006 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.8675564681724846 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.919917864476386 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.9681724845995893 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.6652977412731006 name: Dot Precision 1 - type: dot_precision_3 value: 0.6529774127310062 name: Dot Precision 3 - type: dot_precision_5 value: 0.63347022587269 name: Dot Precision 5 - type: dot_precision_10 value: 0.5220739219712526 name: Dot Precision 10 - type: dot_recall_1 value: 0.06810947462369736 name: Dot Recall 1 - type: dot_recall_3 value: 0.19983224313834896 name: Dot Recall 3 - type: dot_recall_5 value: 0.3208524649814358 name: Dot Recall 5 - type: dot_recall_10 value: 0.5167609061497211 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.5911022725662979 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.7723257064632837 name: Dot Mrr 10 - type: dot_map_100 value: 0.5641667691319417 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: core uk options type: core-uk-options metrics: - type: dot_accuracy_1 value: 0.5061601642710473 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.757700205338809 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.8439425051334702 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.9394250513347022 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.5061601642710473 name: Dot Precision 1 - type: dot_precision_3 value: 0.5078713210130048 name: Dot Precision 3 - type: dot_precision_5 value: 0.5012320328542095 name: Dot Precision 5 - type: dot_precision_10 value: 0.4514373716632443 name: Dot Precision 10 - type: dot_recall_1 value: 0.05108527906646641 name: Dot Recall 1 - type: dot_recall_3 value: 0.15307341177162412 name: Dot Recall 3 - type: dot_recall_5 value: 0.24994742519428473 name: Dot Recall 5 - type: dot_recall_10 value: 0.4442050883046172 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.49069645160108133 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.6497152146279452 name: Dot Mrr 10 - type: dot_map_100 value: 0.4894386853734429 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: core ru options type: core-ru-options metrics: - type: dot_accuracy_1 value: 0.5174537987679672 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.7669404517453798 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.8603696098562629 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.9353182751540041 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.5174537987679672 name: Dot Precision 1 - type: dot_precision_3 value: 0.5109514031485284 name: Dot Precision 3 - type: dot_precision_5 value: 0.5084188911704312 name: Dot Precision 5 - type: dot_precision_10 value: 0.45246406570841896 name: Dot Precision 10 - type: dot_recall_1 value: 0.05206866367785561 name: Dot Recall 1 - type: dot_recall_3 value: 0.15506067291005085 name: Dot Recall 3 - type: dot_recall_5 value: 0.2546829020686069 name: Dot Recall 5 - type: dot_recall_10 value: 0.4455506189063986 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.4942349865402304 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.6604588344578081 name: Dot Mrr 10 - type: dot_map_100 value: 0.4930864064690613 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: options uk title type: options-uk-title metrics: - type: dot_accuracy_1 value: 0.7037861915367484 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.9198218262806236 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.9465478841870824 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.9910913140311804 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.7037861915367484 name: Dot Precision 1 - type: dot_precision_3 value: 0.6829992576095026 name: Dot Precision 3 - type: dot_precision_5 value: 0.6454342984409801 name: Dot Precision 5 - type: dot_precision_10 value: 0.5111358574610245 name: Dot Precision 10 - type: dot_recall_1 value: 0.10724626153356664 name: Dot Recall 1 - type: dot_recall_3 value: 0.31143996439096655 name: Dot Recall 3 - type: dot_recall_5 value: 0.48373562221000976 name: Dot Recall 5 - type: dot_recall_10 value: 0.730595567510935 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.7035103179791073 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.8139852228939088 name: Dot Mrr 10 - type: dot_map_100 value: 0.674787689168559 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: options ru title type: options-ru-title metrics: - type: dot_accuracy_1 value: 0.7216035634743875 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.9220489977728286 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.9665924276169265 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.9888641425389755 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.7216035634743875 name: Dot Precision 1 - type: dot_precision_3 value: 0.6837416481069042 name: Dot Precision 3 - type: dot_precision_5 value: 0.6538975501113586 name: Dot Precision 5 - type: dot_precision_10 value: 0.5111358574610245 name: Dot Precision 10 - type: dot_recall_1 value: 0.1098755612118641 name: Dot Recall 1 - type: dot_recall_3 value: 0.310237998823745 name: Dot Recall 3 - type: dot_recall_5 value: 0.49079267058108933 name: Dot Recall 5 - type: dot_recall_10 value: 0.731284046317454 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.7058496958231204 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.8249840916321984 name: Dot Mrr 10 - type: dot_map_100 value: 0.6774861491360238 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: options uk options type: options-uk-options metrics: - type: dot_accuracy_1 value: 0.5991091314031181 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.7750556792873051 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.8619153674832962 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.9376391982182628 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.5991091314031181 name: Dot Precision 1 - type: dot_precision_3 value: 0.5835189309576837 name: Dot Precision 3 - type: dot_precision_5 value: 0.5536748329621382 name: Dot Precision 5 - type: dot_precision_10 value: 0.44743875278396433 name: Dot Precision 10 - type: dot_recall_1 value: 0.08779040805766865 name: Dot Recall 1 - type: dot_recall_3 value: 0.2530944185732604 name: Dot Recall 3 - type: dot_recall_5 value: 0.39813735509726594 name: Dot Recall 5 - type: dot_recall_10 value: 0.6176174728513258 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.5956896896779121 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.7090783752253682 name: Dot Mrr 10 - type: dot_map_100 value: 0.5793239206252456 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: options ru options type: options-ru-options metrics: - type: dot_accuracy_1 value: 0.5835189309576837 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.8173719376391982 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.8864142538975501 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.955456570155902 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.5835189309576837 name: Dot Precision 1 - type: dot_precision_3 value: 0.5887156644394951 name: Dot Precision 3 - type: dot_precision_5 value: 0.5594654788418708 name: Dot Precision 5 - type: dot_precision_10 value: 0.457238307349666 name: Dot Precision 10 - type: dot_recall_1 value: 0.08538382552859167 name: Dot Recall 1 - type: dot_recall_3 value: 0.2563989400849089 name: Dot Recall 3 - type: dot_recall_5 value: 0.40169375909910426 name: Dot Recall 5 - type: dot_recall_10 value: 0.6348241402250311 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.6055244761404566 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.7124129458761973 name: Dot Mrr 10 - type: dot_map_100 value: 0.583237331287752 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: rusisms uk title type: rusisms-uk-title metrics: - type: dot_accuracy_1 value: 0.653968253968254 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.8 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.8285714285714286 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.8698412698412699 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.653968253968254 name: Dot Precision 1 - type: dot_precision_3 value: 0.6603174603174603 name: Dot Precision 3 - type: dot_precision_5 value: 0.6374603174603175 name: Dot Precision 5 - type: dot_precision_10 value: 0.6085714285714285 name: Dot Precision 10 - type: dot_recall_1 value: 0.04725517203546882 name: Dot Recall 1 - type: dot_recall_3 value: 0.12381135996553257 name: Dot Recall 3 - type: dot_recall_5 value: 0.17539112221653216 name: Dot Recall 5 - type: dot_recall_10 value: 0.30457360991476656 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.6572547680252321 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.729973544973545 name: Dot Mrr 10 - type: dot_map_100 value: 0.5641786181198372 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: rusisms ru title type: rusisms-ru-title metrics: - type: dot_accuracy_1 value: 0.6571428571428571 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.7936507936507936 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.8253968253968254 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.873015873015873 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.6571428571428571 name: Dot Precision 1 - type: dot_precision_3 value: 0.6560846560846562 name: Dot Precision 3 - type: dot_precision_5 value: 0.6463492063492065 name: Dot Precision 5 - type: dot_precision_10 value: 0.6107936507936509 name: Dot Precision 10 - type: dot_recall_1 value: 0.04739905243486606 name: Dot Recall 1 - type: dot_recall_3 value: 0.11881740152522054 name: Dot Recall 3 - type: dot_recall_5 value: 0.17636130340176712 name: Dot Recall 5 - type: dot_recall_10 value: 0.30216223944663373 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.6571827055217352 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.7293764172335601 name: Dot Mrr 10 - type: dot_map_100 value: 0.5692580022935275 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: rusisms uk options type: rusisms-uk-options metrics: - type: dot_accuracy_1 value: 0.5142857142857142 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.6476190476190476 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.7111111111111111 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.7682539682539683 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.5142857142857142 name: Dot Precision 1 - type: dot_precision_3 value: 0.5174603174603175 name: Dot Precision 3 - type: dot_precision_5 value: 0.5174603174603175 name: Dot Precision 5 - type: dot_precision_10 value: 0.48952380952380947 name: Dot Precision 10 - type: dot_recall_1 value: 0.03351061806817676 name: Dot Recall 1 - type: dot_recall_3 value: 0.08592826294221328 name: Dot Recall 3 - type: dot_recall_5 value: 0.1422941586936591 name: Dot Recall 5 - type: dot_recall_10 value: 0.23195805736913946 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.5228268346709956 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.5950781053162004 name: Dot Mrr 10 - type: dot_map_100 value: 0.4734752692748141 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: rusisms ru options type: rusisms-ru-options metrics: - type: dot_accuracy_1 value: 0.5142857142857142 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.6666666666666666 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.7111111111111111 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.780952380952381 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.5142857142857142 name: Dot Precision 1 - type: dot_precision_3 value: 0.5259259259259259 name: Dot Precision 3 - type: dot_precision_5 value: 0.5111111111111111 name: Dot Precision 5 - type: dot_precision_10 value: 0.4977777777777778 name: Dot Precision 10 - type: dot_recall_1 value: 0.032867380941352616 name: Dot Recall 1 - type: dot_recall_3 value: 0.09098053544122864 name: Dot Recall 3 - type: dot_recall_5 value: 0.1384944134818257 name: Dot Recall 5 - type: dot_recall_10 value: 0.2363619331523165 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.5286547754411143 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.6009019904257997 name: Dot Mrr 10 - type: dot_map_100 value: 0.4758363672875093 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: rusisms corrected uk title type: rusisms_corrected-uk-title metrics: - type: dot_accuracy_1 value: 0.7278481012658228 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.8322784810126582 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.8639240506329114 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.9240506329113924 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.7278481012658228 name: Dot Precision 1 - type: dot_precision_3 value: 0.7215189873417721 name: Dot Precision 3 - type: dot_precision_5 value: 0.6981012658227848 name: Dot Precision 5 - type: dot_precision_10 value: 0.6642405063291139 name: Dot Precision 10 - type: dot_recall_1 value: 0.05253326895567305 name: Dot Recall 1 - type: dot_recall_3 value: 0.13723668751005305 name: Dot Recall 3 - type: dot_recall_5 value: 0.20030644158359812 name: Dot Recall 5 - type: dot_recall_10 value: 0.3423928135965863 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.7205624472480214 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.7918399638336349 name: Dot Mrr 10 - type: dot_map_100 value: 0.6311381617188995 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: rusisms corrected ru title type: rusisms_corrected-ru-title metrics: - type: dot_accuracy_1 value: 0.7215189873417721 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.8291139240506329 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.8639240506329114 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.9177215189873418 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.7215189873417721 name: Dot Precision 1 - type: dot_precision_3 value: 0.7046413502109705 name: Dot Precision 3 - type: dot_precision_5 value: 0.6981012658227848 name: Dot Precision 5 - type: dot_precision_10 value: 0.6572784810126582 name: Dot Precision 10 - type: dot_recall_1 value: 0.0521298374885421 name: Dot Recall 1 - type: dot_recall_3 value: 0.13290530747735393 name: Dot Recall 3 - type: dot_recall_5 value: 0.20063128384952633 name: Dot Recall 5 - type: dot_recall_10 value: 0.34357114475789763 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.7134354342778741 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.7869210870002009 name: Dot Mrr 10 - type: dot_map_100 value: 0.6309189692748127 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: rusisms corrected uk options type: rusisms_corrected-uk-options metrics: - type: dot_accuracy_1 value: 0.5981012658227848 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.7183544303797469 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.7658227848101266 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.8544303797468354 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.5981012658227848 name: Dot Precision 1 - type: dot_precision_3 value: 0.5854430379746836 name: Dot Precision 3 - type: dot_precision_5 value: 0.5772151898734177 name: Dot Precision 5 - type: dot_precision_10 value: 0.5594936708860759 name: Dot Precision 10 - type: dot_recall_1 value: 0.04081008122026118 name: Dot Recall 1 - type: dot_recall_3 value: 0.10498764582358312 name: Dot Recall 3 - type: dot_recall_5 value: 0.15626323771420525 name: Dot Recall 5 - type: dot_recall_10 value: 0.2774528867498376 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.5996673598085837 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.6754935201928871 name: Dot Mrr 10 - type: dot_map_100 value: 0.5516378564038038 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: rusisms corrected ru options type: rusisms_corrected-ru-options metrics: - type: dot_accuracy_1 value: 0.5949367088607594 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.7278481012658228 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.7753164556962026 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.8512658227848101 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.5949367088607594 name: Dot Precision 1 - type: dot_precision_3 value: 0.5791139240506329 name: Dot Precision 3 - type: dot_precision_5 value: 0.5791139240506329 name: Dot Precision 5 - type: dot_precision_10 value: 0.5575949367088607 name: Dot Precision 10 - type: dot_recall_1 value: 0.04165257095312678 name: Dot Recall 1 - type: dot_recall_3 value: 0.10222495523847674 name: Dot Recall 3 - type: dot_recall_5 value: 0.1608812252264941 name: Dot Recall 5 - type: dot_recall_10 value: 0.2795749696344959 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.5986027958973444 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.6744939220413902 name: Dot Mrr 10 - type: dot_map_100 value: 0.5503443557693128 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: core typos uk title type: core_typos-uk-title metrics: - type: dot_accuracy_1 value: 0.5687885010266941 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.7700205338809035 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.8418891170431212 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.9147843942505134 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.5687885010266941 name: Dot Precision 1 - type: dot_precision_3 value: 0.5444900752908967 name: Dot Precision 3 - type: dot_precision_5 value: 0.5305954825462011 name: Dot Precision 5 - type: dot_precision_10 value: 0.4412731006160164 name: Dot Precision 10 - type: dot_recall_1 value: 0.0580202322237894 name: Dot Recall 1 - type: dot_recall_3 value: 0.16636304737524693 name: Dot Recall 3 - type: dot_recall_5 value: 0.26900338751785186 name: Dot Recall 5 - type: dot_recall_10 value: 0.43810935075580565 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.4990424077730617 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.6822915648120983 name: Dot Mrr 10 - type: dot_map_100 value: 0.4655952449433357 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: core typos ru title type: core_typos-ru-title metrics: - type: dot_accuracy_1 value: 0.5605749486652978 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.7802874743326489 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.8480492813141683 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.9014373716632443 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.5605749486652978 name: Dot Precision 1 - type: dot_precision_3 value: 0.5595482546201233 name: Dot Precision 3 - type: dot_precision_5 value: 0.5400410677618069 name: Dot Precision 5 - type: dot_precision_10 value: 0.44435318275154007 name: Dot Precision 10 - type: dot_recall_1 value: 0.057447220798018 name: Dot Recall 1 - type: dot_recall_3 value: 0.1709708259389682 name: Dot Recall 3 - type: dot_recall_5 value: 0.2738713659144871 name: Dot Recall 5 - type: dot_recall_10 value: 0.44158409282065525 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.5037282247456906 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.6797851276034026 name: Dot Mrr 10 - type: dot_map_100 value: 0.47183985827439395 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: core typos uk options type: core_typos-uk-options metrics: - type: dot_accuracy_1 value: 0.406570841889117 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.6273100616016427 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.7197125256673511 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.8151950718685832 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.406570841889117 name: Dot Precision 1 - type: dot_precision_3 value: 0.4069130732375086 name: Dot Precision 3 - type: dot_precision_5 value: 0.4032854209445586 name: Dot Precision 5 - type: dot_precision_10 value: 0.3624229979466119 name: Dot Precision 10 - type: dot_recall_1 value: 0.040717223801684486 name: Dot Recall 1 - type: dot_recall_3 value: 0.12322182672315539 name: Dot Recall 3 - type: dot_recall_5 value: 0.20205020055771958 name: Dot Recall 5 - type: dot_recall_10 value: 0.35788220441031765 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.3946258946857381 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.5367059417880766 name: Dot Mrr 10 - type: dot_map_100 value: 0.39155808979942847 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: core typos ru options type: core_typos-ru-options metrics: - type: dot_accuracy_1 value: 0.4024640657084189 name: Dot Accuracy 1 - type: dot_accuracy_3 value: 0.6437371663244353 name: Dot Accuracy 3 - type: dot_accuracy_5 value: 0.731006160164271 name: Dot Accuracy 5 - type: dot_accuracy_10 value: 0.8203285420944558 name: Dot Accuracy 10 - type: dot_precision_1 value: 0.4024640657084189 name: Dot Precision 1 - type: dot_precision_3 value: 0.4151266255989048 name: Dot Precision 3 - type: dot_precision_5 value: 0.40780287474332655 name: Dot Precision 5 - type: dot_precision_10 value: 0.36437371663244356 name: Dot Precision 10 - type: dot_recall_1 value: 0.04068322758759405 name: Dot Recall 1 - type: dot_recall_3 value: 0.12633057201619224 name: Dot Recall 3 - type: dot_recall_5 value: 0.2059578598985532 name: Dot Recall 5 - type: dot_recall_10 value: 0.3607267194294613 name: Dot Recall 10 - type: dot_ndcg_10 value: 0.3974442914064893 name: Dot Ndcg 10 - type: dot_mrr_10 value: 0.5414723281509725 name: Dot Mrr 10 - type: dot_map_100 value: 0.3938909798430495 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: 'bm full matryoshka dim 768 ' type: bm-full--matryoshka_dim-768-- metrics: - type: dot_accuracy_1 value: 0.5035385704175513 name: Dot Accuracy 1 - type: dot_precision_1 value: 0.5035385704175513 name: Dot Precision 1 - type: dot_recall_1 value: 0.011675176874642076 name: Dot Recall 1 - type: dot_ndcg_1 value: 0.5035385704175513 name: Dot Ndcg 1 - type: dot_mrr_1 value: 0.5035385704175513 name: Dot Mrr 1 - type: dot_map_100 value: 0.34697975642189044 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: 'bm full matryoshka dim 512 ' type: bm-full--matryoshka_dim-512-- metrics: - type: dot_accuracy_1 value: 0.49221514508138714 name: Dot Accuracy 1 - type: dot_precision_1 value: 0.49221514508138714 name: Dot Precision 1 - type: dot_recall_1 value: 0.011495952577780405 name: Dot Recall 1 - type: dot_ndcg_1 value: 0.49221514508138714 name: Dot Ndcg 1 - type: dot_mrr_1 value: 0.49221514508138714 name: Dot Mrr 1 - type: dot_map_100 value: 0.3423209780846497 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: 'bm full matryoshka dim 256 ' type: bm-full--matryoshka_dim-256-- metrics: - type: dot_accuracy_1 value: 0.4826610049539986 name: Dot Accuracy 1 - type: dot_precision_1 value: 0.4826610049539986 name: Dot Precision 1 - type: dot_recall_1 value: 0.01129954090494819 name: Dot Recall 1 - type: dot_ndcg_1 value: 0.4826610049539986 name: Dot Ndcg 1 - type: dot_mrr_1 value: 0.4826610049539986 name: Dot Mrr 1 - type: dot_map_100 value: 0.327632294533896 name: Dot Map 100 - task: type: rztkinformation-retrieval name: RZTKInformation Retrieval dataset: name: 'bm full matryoshka dim 128 ' type: bm-full--matryoshka_dim-128-- metrics: - type: dot_accuracy_1 value: 0.45930644019815997 name: Dot Accuracy 1 - type: dot_precision_1 value: 0.45930644019815997 name: Dot Precision 1 - type: dot_recall_1 value: 0.010709355369926024 name: Dot Recall 1 - type: dot_ndcg_1 value: 0.45930644019815997 name: Dot Ndcg 1 - type: dot_mrr_1 value: 0.45930644019815997 name: Dot Mrr 1 - type: dot_map_100 value: 0.3015000665607735 name: Dot Map 100 --- # SentenceTransformer based on intfloat/multilingual-e5-base This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [intfloat/multilingual-e5-base](https://huggingface.co./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](https://huggingface.co./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](https://sbert.net) - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers) - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co./models?library=sentence-transformers) ### 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: ```bash pip install -U sentence-transformers ``` Then you can load this model and run inference. ```python from sentence_transformers import SentenceTransformer # Download from the 🤗 Hub model = SentenceTransformer("yklymchuk-rztk/multilingual-e5-base-matryoshka2d-mnr-6") # Run inference sentences = [ 'query: йоршик для унітазу', 'passage: Ёршики и стойки Kroner Гарантия 36 месяцев официальной гарантии от производителя Габариты_old D Большой (до 1000x200x600 мм) Тип Ёршики Комплектация Колба Комплектация Монтажные элементы Комплектация Ёршик Тип установки Настенный (подвесной) Крепление Шурупы Материал Металл / Стекло Цвет Хром с белым Количество грузовых мест 1 Страна регистрации бренда Германия Страна-производитель товара Китай Тип гарантийного талона Гарантия по чеку Наличие товара по городам Киев и область Доставка Доставка в магазины ROZETKA', 'passage: Форми та деко для випікання Calve Габарити D Великий (до 1000x200x600 мм) Можна мити в посудомийній машині Так Країна реєстрації бренда Іспанія Тип поставки Один предмет Тип Форма Призначення Для тортів і чізкейків Призначення Для піци Вид_old Один предмет Кількість предметів, шт 1 Форма Кругла Діаметр Ø 28 см Матеріал Силікон Зовнішнє антипригарне покриття_old Немає Кришка_old Немає Ручки_old Є Особливості З ручками Країна-виробник товару Китай Тип гарантійного талона Гарантія по чеку Можливість доставки Почтомати Доставка Premium Немає', ] 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 #### RZTKInformation Retrieval * Dataset: `validation--matryoshka_dim-768--` * Evaluated with sentence_transformers_training.evaluation.information_retrieval_evaluator.RZTKInformationRetrievalEvaluator | Metric | Value | |:-----------------|:-----------| | dot_accuracy_10 | 0.566 | | dot_precision_10 | 0.1146 | | dot_recall_10 | 0.4021 | | **dot_ndcg_10** | **0.2973** | | dot_mrr_10 | 0.3021 | | dot_map_60 | 0.2569 | #### RZTKInformation 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 sentence_transformers_training.evaluation.information_retrieval_evaluator.RZTKInformationRetrievalEvaluator | 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 | 0.5035 | 0.6437 | 0.6653 | 0.5062 | 0.5175 | 0.7038 | 0.7216 | 0.5991 | 0.5835 | 0.654 | 0.6571 | 0.5143 | 0.5143 | 0.7278 | 0.7215 | 0.5981 | 0.5949 | 0.5688 | 0.5606 | 0.4066 | 0.4025 | | dot_accuracy_3 | 0.6727 | 0.8511 | 0.8676 | 0.7577 | 0.7669 | 0.9198 | 0.922 | 0.7751 | 0.8174 | 0.8 | 0.7937 | 0.6476 | 0.6667 | 0.8323 | 0.8291 | 0.7184 | 0.7278 | 0.77 | 0.7803 | 0.6273 | 0.6437 | | dot_accuracy_5 | 0.7473 | 0.9117 | 0.9199 | 0.8439 | 0.8604 | 0.9465 | 0.9666 | 0.8619 | 0.8864 | 0.8286 | 0.8254 | 0.7111 | 0.7111 | 0.8639 | 0.8639 | 0.7658 | 0.7753 | 0.8419 | 0.848 | 0.7197 | 0.731 | | dot_accuracy_10 | 0.8333 | 0.9671 | 0.9682 | 0.9394 | 0.9353 | 0.9911 | 0.9889 | 0.9376 | 0.9555 | 0.8698 | 0.873 | 0.7683 | 0.781 | 0.9241 | 0.9177 | 0.8544 | 0.8513 | 0.9148 | 0.9014 | 0.8152 | 0.8203 | | dot_precision_1 | 0.5035 | 0.6437 | 0.6653 | 0.5062 | 0.5175 | 0.7038 | 0.7216 | 0.5991 | 0.5835 | 0.654 | 0.6571 | 0.5143 | 0.5143 | 0.7278 | 0.7215 | 0.5981 | 0.5949 | 0.5688 | 0.5606 | 0.4066 | 0.4025 | | dot_precision_3 | 0.5047 | 0.6342 | 0.653 | 0.5079 | 0.511 | 0.683 | 0.6837 | 0.5835 | 0.5887 | 0.6603 | 0.6561 | 0.5175 | 0.5259 | 0.7215 | 0.7046 | 0.5854 | 0.5791 | 0.5445 | 0.5595 | 0.4069 | 0.4151 | | dot_precision_5 | 0.5002 | 0.6189 | 0.6335 | 0.5012 | 0.5084 | 0.6454 | 0.6539 | 0.5537 | 0.5595 | 0.6375 | 0.6463 | 0.5175 | 0.5111 | 0.6981 | 0.6981 | 0.5772 | 0.5791 | 0.5306 | 0.54 | 0.4033 | 0.4078 | | dot_precision_10 | 0.4953 | 0.5157 | 0.5221 | 0.4514 | 0.4525 | 0.5111 | 0.5111 | 0.4474 | 0.4572 | 0.6086 | 0.6108 | 0.4895 | 0.4978 | 0.6642 | 0.6573 | 0.5595 | 0.5576 | 0.4413 | 0.4444 | 0.3624 | 0.3644 | | dot_recall_1 | 0.0117 | 0.0665 | 0.0681 | 0.0511 | 0.0521 | 0.1072 | 0.1099 | 0.0878 | 0.0854 | 0.0473 | 0.0474 | 0.0335 | 0.0329 | 0.0525 | 0.0521 | 0.0408 | 0.0417 | 0.058 | 0.0574 | 0.0407 | 0.0407 | | dot_recall_3 | 0.0355 | 0.1944 | 0.1998 | 0.1531 | 0.1551 | 0.3114 | 0.3102 | 0.2531 | 0.2564 | 0.1238 | 0.1188 | 0.0859 | 0.091 | 0.1372 | 0.1329 | 0.105 | 0.1022 | 0.1664 | 0.171 | 0.1232 | 0.1263 | | dot_recall_5 | 0.0582 | 0.3142 | 0.3209 | 0.2499 | 0.2547 | 0.4837 | 0.4908 | 0.3981 | 0.4017 | 0.1754 | 0.1764 | 0.1423 | 0.1385 | 0.2003 | 0.2006 | 0.1563 | 0.1609 | 0.269 | 0.2739 | 0.2021 | 0.206 | | dot_recall_10 | 0.1141 | 0.5102 | 0.5168 | 0.4442 | 0.4456 | 0.7306 | 0.7313 | 0.6176 | 0.6348 | 0.3046 | 0.3022 | 0.232 | 0.2364 | 0.3424 | 0.3436 | 0.2775 | 0.2796 | 0.4381 | 0.4416 | 0.3579 | 0.3607 | | **dot_ndcg_10** | **0.4977** | **0.5812** | **0.5911** | **0.4907** | **0.4942** | **0.7035** | **0.7058** | **0.5957** | **0.6055** | **0.6573** | **0.6572** | **0.5228** | **0.5287** | **0.7206** | **0.7134** | **0.5997** | **0.5986** | **0.499** | **0.5037** | **0.3946** | **0.3974** | | dot_mrr_10 | 0.6029 | 0.7579 | 0.7723 | 0.6497 | 0.6605 | 0.814 | 0.825 | 0.7091 | 0.7124 | 0.73 | 0.7294 | 0.5951 | 0.6009 | 0.7918 | 0.7869 | 0.6755 | 0.6745 | 0.6823 | 0.6798 | 0.5367 | 0.5415 | | dot_map_100 | 0.347 | 0.5544 | 0.5642 | 0.4894 | 0.4931 | 0.6748 | 0.6775 | 0.5793 | 0.5832 | 0.5642 | 0.5693 | 0.4735 | 0.4758 | 0.6311 | 0.6309 | 0.5516 | 0.5503 | 0.4656 | 0.4718 | 0.3916 | 0.3939 | #### RZTKInformation 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 sentence_transformers_training.evaluation.information_retrieval_evaluator.RZTKInformationRetrievalEvaluator | Metric | bm-full--matryoshka_dim-768-- | bm-full--matryoshka_dim-512-- | bm-full--matryoshka_dim-256-- | bm-full--matryoshka_dim-128-- | |:----------------|:------------------------------|:------------------------------|:------------------------------|:------------------------------| | dot_accuracy_1 | 0.5035 | 0.4922 | 0.4827 | 0.4593 | | dot_precision_1 | 0.5035 | 0.4922 | 0.4827 | 0.4593 | | dot_recall_1 | 0.0117 | 0.0115 | 0.0113 | 0.0107 | | **dot_ndcg_1** | **0.5035** | **0.4922** | **0.4827** | **0.4593** | | dot_mrr_1 | 0.5035 | 0.4922 | 0.4827 | 0.4593 | | dot_map_100 | 0.347 | 0.3423 | 0.3276 | 0.3015 | ## Training Details ### Training Dataset #### rozetka_positive_pairs * Dataset: rozetka_positive_pairs * Size: 7,027,160 training samples * Columns: query and text * Approximate statistics based on the first 1000 samples: | | query | text | |:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | query | text | |:-----------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | query: gws 13-125 cie | passage: Кутова шліфмашина Bosch Professional GWS 13-125 CIE (060179F002) | | query: gws 13-125 cie | passage: Шліфувальні та полірувальні машини (болгарки) Bosch Гарантія 12 місяців Габарити D Великий (до 1000x200x600 мм) Тип Болгарки (КШМ) Джерело живлення Мережа Кількість вантажних місць 1 Країна-виробник товару Німеччина Додаткові гарантійні умови 24 місяці додаткової гарантії за умови реєстрації протягом 4 тижнів Тип гарантійного талона Оригінальний гарантійний талон Тип гарантійного талона Гарантійний талон магазина Діаметр диска, мм 125 Споживана потужність, кВт 1.3 Джерело живлення_old Мережа 220 В Клас товару Професійні Доставка Premium Немає Доставка Доставка в магазини ROZETKA | | query: gws 13-125 cie | passage: Угловая шлифмашина Bosch Professional GWS 13-125 CIE (060179F002) | * Loss: sentence_transformers_training.model.matryoshka2d_loss.RZTKMatryoshka2dLoss with these parameters: ```json { "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: 681,643 evaluation samples * Columns: query and text * Approximate statistics based on the first 1000 samples: | | query | text | |:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | query | text | |:------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | query: ніж | passage: Мисливський Ніж з Нержавіючої Сталі HK6 SSH BPS Knives - Ніж для риболовлі, мисливства, походів | | query: ніж | passage: Ножі тактичні BPS Knives Гарантія 14 днів Тип Нескладані Кількість вантажних місць 1 Країна реєстрації бренда Україна Країна-виробник товару Україна Вид Туристичні Вид Авторські вироби Вид Сувенірні Вид Мисливські Вид Рибальські Вид Клинки | | query: ніж | passage: Охотничий Нож из Нержавеющей Стали HK6 SSH BPS Knives - Нож для рыбалки, охоты, походов | * Loss: sentence_transformers_training.model.matryoshka2d_loss.RZTKMatryoshka2dLoss with these parameters: ```json { "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 - `warmup_ratio`: 0.1 - `bf16`: True - `bf16_full_eval`: True - `tf32`: True - `dataloader_num_workers`: 4 - `load_best_model_at_end`: True - `optim`: adafactor - `push_to_hub`: True - `hub_model_id`: yklymchuk-rztk/multilingual-e5-base-matryoshka2d-mnr-6 - `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`: 3 - `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`: 4 - `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-6 - `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 | validation--matryoshka_dim-768--_dot_ndcg_10 | 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 | |:-------:|:---------:|:-------------:|:---------------:|:--------------------------------------------:|:-------------------:|:-------------------------:|:-------------------------:|:---------------------------:|:---------------------------:|:----------------------------:|:----------------------------:|:------------------------------:|:------------------------------:|:----------------------------:|:----------------------------:|:------------------------------:|:------------------------------:|:--------------------------------------:|:--------------------------------------:|:----------------------------------------:|:----------------------------------------:|:-------------------------------:|:-------------------------------:|:---------------------------------:|:---------------------------------:|:----------------------------------------:|:----------------------------------------:|:----------------------------------------:|:----------------------------------------:| | 0.0150 | 300 | 4.8614 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0301 | 600 | 4.7573 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0451 | 900 | 4.5829 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0601 | 1200 | 4.0041 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0751 | 1500 | 3.3461 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0902 | 1800 | 2.7905 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1052 | 2100 | 2.3993 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1202 | 2400 | 2.2219 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1353 | 2700 | 2.2147 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1503 | 3000 | 1.9414 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1653 | 3300 | 1.991 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1803 | 3600 | 1.7915 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1954 | 3900 | 1.7364 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2104 | 4200 | 1.6924 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2254 | 4500 | 1.5486 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2404 | 4800 | 1.6097 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2555 | 5100 | 1.5473 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2705 | 5400 | 1.4683 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2855 | 5700 | 1.4155 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3000 | 5989 | - | 1.1422 | 0.2496 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3006 | 6000 | 1.4506 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3156 | 6300 | 1.3072 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3306 | 6600 | 1.31 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3456 | 6900 | 1.3277 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3607 | 7200 | 1.2698 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3757 | 7500 | 1.2529 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3907 | 7800 | 1.2409 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4058 | 8100 | 1.2067 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4208 | 8400 | 1.1565 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4358 | 8700 | 1.1996 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4508 | 9000 | 1.1334 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4659 | 9300 | 1.1668 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4809 | 9600 | 1.154 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4959 | 9900 | 1.1907 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5109 | 10200 | 1.1464 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5260 | 10500 | 1.113 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5410 | 10800 | 1.1337 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5560 | 11100 | 1.0705 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5711 | 11400 | 1.0964 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5861 | 11700 | 1.1065 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6000 | 11978 | - | 0.7612 | 0.2749 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6011 | 12000 | 1.0762 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6161 | 12300 | 1.0871 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6312 | 12600 | 1.0518 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6462 | 12900 | 1.0332 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6612 | 13200 | 1.0398 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6763 | 13500 | 1.0505 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6913 | 13800 | 1.0269 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7063 | 14100 | 0.9854 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7213 | 14400 | 1.0585 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7364 | 14700 | 1.0216 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7514 | 15000 | 1.0136 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7664 | 15300 | 1.0035 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7814 | 15600 | 0.9941 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7965 | 15900 | 1.0222 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8115 | 16200 | 0.9819 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8265 | 16500 | 0.9892 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8416 | 16800 | 1.0494 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8566 | 17100 | 1.0689 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8716 | 17400 | 1.0247 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8866 | 17700 | 1.0267 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9000 | 17967 | - | 0.6666 | 0.2865 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9017 | 18000 | 1.0058 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9167 | 18300 | 0.9838 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9317 | 18600 | 0.943 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9468 | 18900 | 0.9497 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9618 | 19200 | 0.9703 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9768 | 19500 | 0.9431 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9918 | 19800 | 0.9892 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0069 | 20100 | 1.0199 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0219 | 20400 | 0.9968 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0369 | 20700 | 0.9648 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0519 | 21000 | 1.103 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0670 | 21300 | 1.1038 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0820 | 21600 | 0.956 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0970 | 21900 | 0.9474 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1121 | 22200 | 0.9687 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1271 | 22500 | 0.9362 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1421 | 22800 | 0.9379 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1571 | 23100 | 0.9206 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1722 | 23400 | 0.9595 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1872 | 23700 | 0.8968 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2000 | 23956 | - | 0.6197 | 0.2857 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2022 | 24000 | 0.8941 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2173 | 24300 | 0.8933 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2323 | 24600 | 0.8699 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2473 | 24900 | 0.851 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2623 | 25200 | 0.9203 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2774 | 25500 | 0.906 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2924 | 25800 | 0.925 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3074 | 26100 | 0.8379 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3224 | 26400 | 0.8087 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3375 | 26700 | 0.8271 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3525 | 27000 | 0.8983 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3675 | 27300 | 0.8835 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3826 | 27600 | 0.856 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3976 | 27900 | 0.7816 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4126 | 28200 | 0.7851 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4276 | 28500 | 0.789 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4427 | 28800 | 0.8596 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4577 | 29100 | 0.9125 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4727 | 29400 | 0.8439 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4878 | 29700 | 0.7995 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5000 | 29945 | - | 0.5678 | 0.2926 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5028 | 30000 | 0.8341 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5178 | 30300 | 0.7588 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5328 | 30600 | 0.7941 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5479 | 30900 | 0.8292 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5629 | 31200 | 0.8013 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5779 | 31500 | 0.8066 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5929 | 31800 | 0.8354 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6080 | 32100 | 0.8302 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6230 | 32400 | 0.8426 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6380 | 32700 | 0.8118 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6531 | 33000 | 0.8562 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6681 | 33300 | 0.8185 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6831 | 33600 | 0.8325 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6981 | 33900 | 0.821 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7132 | 34200 | 0.8239 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7282 | 34500 | 0.8832 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7432 | 34800 | 0.8945 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7583 | 35100 | 0.8821 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7733 | 35400 | 0.8385 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7883 | 35700 | 0.7837 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8000 | 35934 | - | 0.5493 | 0.2962 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8033 | 36000 | 0.8835 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8184 | 36300 | 0.8061 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8334 | 36600 | 0.8819 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8484 | 36900 | 0.8818 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8634 | 37200 | 0.8467 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8785 | 37500 | 0.846 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8935 | 37800 | 0.833 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9085 | 38100 | 0.8877 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9236 | 38400 | 0.8326 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9386 | 38700 | 0.8752 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9536 | 39000 | 0.8849 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9686 | 39300 | 0.8875 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9837 | 39600 | 0.857 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9987 | 39900 | 0.8688 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.0137 | 40200 | 0.8821 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.0288 | 40500 | 0.8725 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.0438 | 40800 | 0.9175 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.0588 | 41100 | 0.9029 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.0738 | 41400 | 0.914 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.0889 | 41700 | 0.9188 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.1000 | 41923 | - | 0.5398 | 0.2901 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.1039 | 42000 | 0.8824 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.1189 | 42300 | 0.8396 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.1339 | 42600 | 0.8388 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.1490 | 42900 | 0.8561 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.1640 | 43200 | 0.8928 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.1790 | 43500 | 0.8779 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.1941 | 43800 | 0.8449 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.2091 | 44100 | 0.8604 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.2241 | 44400 | 0.8673 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.2391 | 44700 | 0.8691 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.2542 | 45000 | 0.855 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.2692 | 45300 | 0.8293 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.2842 | 45600 | 0.8288 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.2993 | 45900 | 0.7727 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.3143 | 46200 | 0.858 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.3293 | 46500 | 0.8598 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.3443 | 46800 | 0.815 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.3594 | 47100 | 0.7948 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.3744 | 47400 | 0.7922 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.3894 | 47700 | 0.7789 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.4000 | 47912 | - | 0.5479 | 0.2963 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.4044 | 48000 | 0.7633 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.4195 | 48300 | 0.7901 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.4345 | 48600 | 0.7494 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.4495 | 48900 | 0.7383 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.4646 | 49200 | 0.801 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.4796 | 49500 | 0.7348 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.4946 | 49800 | 0.8138 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.5096 | 50100 | 0.7631 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.5247 | 50400 | 0.774 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.5397 | 50700 | 0.8215 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.5547 | 51000 | 0.7842 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.5698 | 51300 | 0.7638 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.5848 | 51600 | 0.778 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.5998 | 51900 | 0.7867 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.6148 | 52200 | 0.7967 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.6299 | 52500 | 0.8159 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.6449 | 52800 | 0.7875 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.6599 | 53100 | 0.8115 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.6749 | 53400 | 0.8179 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.6900 | 53700 | 0.8488 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | **2.7** | **53901** | **-** | **0.5301** | **0.2973** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | **-** | | 2.7050 | 54000 | 0.8515 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.7200 | 54300 | 0.8296 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.7351 | 54600 | 0.828 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.7501 | 54900 | 0.8567 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.7651 | 55200 | 0.8466 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.7801 | 55500 | 0.8333 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.7952 | 55800 | 0.8056 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.8102 | 56100 | 0.8383 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.8252 | 56400 | 0.8986 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.8403 | 56700 | 0.8429 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.8553 | 57000 | 0.8619 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.8703 | 57300 | 0.7962 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.8853 | 57600 | 0.8068 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.9004 | 57900 | 0.8273 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.9154 | 58200 | 0.8335 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.9304 | 58500 | 0.7848 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.9454 | 58800 | 0.8359 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.9605 | 59100 | 0.8926 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.9755 | 59400 | 0.9048 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.9905 | 59700 | 0.8693 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 3.0 | 59889 | - | - | - | 0.4977 | 0.5812 | 0.5911 | 0.4907 | 0.4942 | 0.7035 | 0.7058 | 0.5957 | 0.6055 | 0.6573 | 0.6572 | 0.5228 | 0.5287 | 0.7206 | 0.7134 | 0.5997 | 0.5986 | 0.4990 | 0.5037 | 0.3946 | 0.3974 | 0.5035 | 0.4922 | 0.4827 | 0.4593 | * 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 ```bibtex @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", } ```