SentenceTransformer based on jinaai/jina-embeddings-v2-small-en
This is a sentence-transformers model finetuned from jinaai/jina-embeddings-v2-small-en. It maps sentences & paragraphs to a 512-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
Model Details
https://wandb.ai/deklanw/sentence-transformers/runs/frjg0h13?nw=nwuserdeklanw
Model Description
- Model Type: Sentence Transformer
- Base model: jinaai/jina-embeddings-v2-small-en
- Maximum Sequence Length: 2048 tokens
- Output Dimensionality: 512 dimensions
- Similarity Function: Cosine Similarity
Model Sources
- Documentation: Sentence Transformers Documentation
- Repository: Sentence Transformers on GitHub
- Hugging Face: Sentence Transformers on Hugging Face
Full Model Architecture
SentenceTransformer(
(0): Transformer({'max_seq_length': 2048, 'do_lower_case': False}) with Transformer model: JinaBertModel
(1): Pooling({'word_embedding_dimension': 512, '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})
)
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("borgcollectivegmbh/jina-embeddings-v2-small-en_linkedin_profile_model_run1")
# Run inference
sentences = [
'Experienced in SAP consultancy',
'=== PERSON ===\nMärt Ehrenpreis\nN/A\nTallinn Metropolitan Area\n470\n\n=== ROLES ===\n>>> COMPANY ROLES <<<\n\nCompany Role #1:\n Board Member CTO\n 2023-04 - N/A\n N/A\n Elron / Eesti Liinirongid AS \n eestiliinirongid\n Truck Transportation\n Loome Sulle aega – viime Sind kohale kiiresti, turvaliselt ja mugavalt\n 414\n\nCompany Role #2:\n Managing Director, Proxion Plan Estonia OÜ\n 2021-01 - 2023-04\n N/A\n Proxion\n proxion-plan-oy\n Civil Engineering\n Proxion on osa WSP-yhtiöitä.\nOtathan seurantaan WSP in Finland -tilin!\n 2563\n\n>>> SCHOOL ROLES <<<\nNo school roles listed.',
"=== PERSON ===\nHarvindar Singh Garcha\nHarvindar's passion for technology can be traced back right from his childhood, Getting into the field of computer science bought him to have more focus on his goal. He is a fast learner and easily adapts to new skills. He always has the hunger and curiosity to learn new skills. <br><br>He has expertise in the design & development of RESTful APIs and back-end services utilizing Python ecosystem, Django, Flask, Docker, and SQL with an emphasis on scalability and security.<br><br>He is currently working as a full stack developer at AI Automotive company where he has worked on technologies Django, Flask, Python, RESTful APIs, React, Redux, Celery, and JavaScript, while keeping in mind all the secure code practices of OWASP top 10.<br><br>His specialties include quickly learning new skills, Programming languages, and Critical thinking in problem-solving.<br><br>In his free time, you will find him reading articles about the latest trending technologies on Internet, Spending some time on Quora & hiking on the mountains.\nPune, Maharashtra, India\n1294\n\n=== ROLES ===\n>>> COMPANY ROLES <<<\n\nCompany Role #1:\n Software Development Analyst\n 2020-04 - 2020-08\n N/A\n Metta Social\n metta-social\n IT Services and IT Consulting\n Building world’s largest common good platform to enable sustainable impact at scale!\n 4002\n\nCompany Role #2:\n Junior Backend Engineer\n 2020-09 - 2021-03\n N/A\n SRV Media\n srv-media\n Advertising Services\n Insights | Ideas | Impact\n 49579\n\nCompany Role #3:\n Full Stack Developer\n 2021-03 - 2022-01\n N/A\n SRV Media\n srv-media\n Advertising Services\n Insights | Ideas | Impact\n 49579\n\nCompany Role #4:\n Software Development Intern\n 2019-10 - 2020-03\n Currently building a B2B social ecosystem platform where my daily work includes to develop and unit test REST API's using Flask and ORM using SQLAlchemy.<br><br>- Contributed 90% of the API's for mobile application which was build in just a month keeping in mind all the secure code practices of OWASP Top 10.<br><br>- Building REST API using Flask framework, for web app & checking the load balancing of concurrent users.<br> <br>- Building database model using SQL-Alchemy, and connecting it to Heroku.<br><br>- Security Testing of the API's !\n Metta Social\n metta-social\n IT Services and IT Consulting\n Building world’s largest common good platform to enable sustainable impact at scale!\n 4002\n\nCompany Role #5:\n Research And Development Engineer\n 2022-01 - N/A\n N/A\n Cerence Inc.\n cerence\n Software Development\n Cerence is the global industry leader in creating unique, moving experiences for the mobility world.\n 44039\n\n>>> SCHOOL ROLES <<<\nNo school roles listed.",
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 512]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
Evaluation
Metrics
Binary Classification
- Datasets: ``,
rec_test_evaluatorandquery_test_evaluator - Evaluated with custom_evaluator.BinaryClassificationEvaluator
| Metric | rec_test_evaluator | query_test_evaluator | |
|---|---|---|---|
| cosine_accuracy | 0.9527 | 0.9369 | 0.9622 |
| cosine_accuracy_threshold | 0.2778 | 0.3141 | 0.263 |
| cosine_f1 | 0.8559 | 0.7995 | 0.885 |
| cosine_f1_threshold | 0.2539 | 0.2846 | 0.2541 |
| cosine_precision | 0.8474 | 0.8165 | 0.8894 |
| cosine_recall | 0.8646 | 0.7832 | 0.8805 |
| cosine_ap | 0.9214 | 0.87 | 0.9475 |
| dot_accuracy | 0.9287 | 0.9174 | 0.9483 |
| dot_accuracy_threshold | 7.1923 | 4.7818 | 8.4253 |
| dot_f1 | 0.7795 | 0.7457 | 0.8433 |
| dot_f1_threshold | 6.0999 | 4.3656 | 7.5479 |
| dot_precision | 0.7621 | 0.7486 | 0.8372 |
| dot_recall | 0.7976 | 0.7428 | 0.8495 |
| dot_ap | 0.8651 | 0.7954 | 0.9205 |
| manhattan_accuracy | 0.8422 | 0.8619 | 0.8801 |
| manhattan_accuracy_threshold | 69.5022 | 69.5686 | 116.771 |
| manhattan_f1 | 0.3987 | 0.507 | 0.56 |
| manhattan_f1_threshold | 133.9353 | 82.6656 | 128.6138 |
| manhattan_precision | 0.2726 | 0.4506 | 0.5831 |
| manhattan_recall | 0.742 | 0.5796 | 0.5387 |
| manhattan_ap | 0.3697 | 0.5479 | 0.6344 |
| euclidean_accuracy | 0.8425 | 0.8626 | 0.8804 |
| euclidean_accuracy_threshold | 3.8574 | 3.8601 | 6.4738 |
| euclidean_f1 | 0.3999 | 0.5062 | 0.5614 |
| euclidean_f1_threshold | 7.4916 | 4.6146 | 7.1657 |
| euclidean_precision | 0.2716 | 0.4435 | 0.5753 |
| euclidean_recall | 0.7579 | 0.5894 | 0.5481 |
| euclidean_ap | 0.37 | 0.5487 | 0.6369 |
| max_accuracy | 0.9527 | 0.9369 | 0.9622 |
| max_accuracy_threshold | 69.5022 | 69.5686 | 116.771 |
| max_f1 | 0.8559 | 0.7995 | 0.885 |
| max_f1_threshold | 133.9353 | 82.6656 | 128.6138 |
| max_precision | 0.8474 | 0.8165 | 0.8894 |
| max_recall | 0.8646 | 0.7832 | 0.8805 |
| max_ap | 0.9214 | 0.87 | 0.9475 |
Training Details
Training Dataset
Unnamed Dataset
- Size: 155,651 training samples
- Columns: text1 and text2
- Approximate statistics based on the first 1000 samples:
text1 text2 type string string details min: 5 tokensmean: 231.14 tokensmax: 2048 tokens min: 51 tokensmean: 618.32 tokensmax: 2048 tokens - Samples:
text1 text2 === PERSON ===Dr. Amol CharegaonkarAlumnus of IIM Indore (FDP-Executive Education)Specialties: Data Analysis, FinancePune, Maharashtra, India4511=== ROLES ===>>> COMPANY ROLES <<<Company Role #1: Principal Consultant 2015-04 - 2021-06 N/A Maruma Consultancy maruma-consultancy Human Resources Services People Development Simplified 218Company Role #2: Assistant Manager – Credit (Policy - Unsecured loans) 2008-06 - 2009-01 Job Responsibilities: As a Team Member of the Credit Policy & Risk function1.Analysis of Delinquent cases in Personal loans and Business Loans2.Online analysis of cases booked under Personal and Business Loans 3.Auditing Pan India cases for credit underwriting w. r. t. Policy 4.Analyzing and publishing a Monthly Portfolio Review for Personal Loans from the Risk Perspective like Delinquency & Bounce Trend and Credit Appraisal Process 5.Incorporate the necessary changes required in the Lending Policy consid... === PERSON ===Rajesh BajN/AHyderabad, Telangana, India491=== ROLES ===>>> COMPANY ROLES <<<Company Role #1: Sr.Officer Finance and Accounts 2010-10 - N/A N/A JK Agri Genetics Limited jk-agri-genetics-limited Biotechnology Research Harvesting Happiness Through Innovations 107873Company Role #2: Assistant Manager 2013-10 - N/A N/A JK Agri Genetics Limited jk-agri-genetics-limited Biotechnology Research Harvesting Happiness Through Innovations 107873Company Role #3: Officer- Finance and Accounts 2007-05 - 2007-07 Market Research in following Areas:-1. Bandra-Kurla complex2. Solitaire corporate Park Andheri3. Udyog Bhavan, Garegaon HSBC hsbc Financial Services N/A N/A>>> SCHOOL ROLES <<<No school roles listed. === PERSON ===Gabriela Menezes• Experiência em localização Brasil - TAXBRA, Nota Fiscal Eletrônica.• Conhecimento em SAP Activate e ASAP.• Experiência em suporte ao Cliente - AMSSão Paulo, São Paulo, Brazil454=== ROLES ===>>> COMPANY ROLES <<<Company Role #1: Consultora SAP SD S/4HANA 2023 - N/A Atuação em - AMS Analise e resolução de chamados dentro do SLA estabelecido.Atuação nas diversas solicitações de melhoria.Resolução de problemas relacionados a NF-eTestes unitários e integradosConfiguração de impostos e leis fiscais.Configuração de conta contábil.Resolução de erros relacionados a Pricing.Conhecimento e vivência no processo de Retorno Simbólico.Apoio as frentes MM e FIApoio a equipe de projetos em configurações, testes unitários e integrados. ITGCON Integração e Consultoria em Sistemas itgcon IT Services and IT Consulting Mais que uma implementadora, somos a ITGCON consultoria. 4116Company Role #2: Co... === PERSON ===Rafael MenezesConsultor funcional SD com experiência em AMS, formado em Tecnologia da Informação.- Principais qualificações:- Conhecimento em Localização Brasil, Pricing, Nota Fiscal Eletrônica e GRC.- Conhecimento das principais tabelas do módulo SD.- Conhecimento na configuração de impostos na J1BTAX- Conhecimento no cadastro de dados mestres de clientes emateriais.São Paulo, Brazil117=== ROLES ===>>> COMPANY ROLES <<<Company Role #1: Consultor SAP SD Pleno 2023-05 - N/A N/A Capgemini capgemini IT Services and IT Consulting Get the future you want 6721701Company Role #2: Consultor Funcional SD JR/PL 2021-12 - 2023-01 - Suporte ao cliente – AMS;- Análise e resolução de chamados respeitando SLA;- Testes em cenários de vendas;- Configuração de impostos – J1BTAX;- Resolução de erros referentes a rejeição de NF-e- Resolução de erros referentes a CFOP- Resolução de erros referentes a contas contábeis- Criação de... === PERSON ===Anastasia Hanan, M.S., M.B.A (she/her)~10 years of user research in both startups and enterprise. I am a senior researcher passionate about leading research that grounds product vision in data and emotion, highlights the user voice along with immediate/long term project risks, and optimizes for radically collaborative tactical execution through ambiguous problem spaces. Specialties: Complex systems research, moving between qualitative research to quantitative insights at scale, crypto, Qualtrics, innovation and strategy, process optimization, rapid insight, cross functional collaboration, making AI make sense, visual storytelling, presentations that win contests, get millions in funding, and/or create actionable product roadmaps.United States1101=== ROLES ===>>> COMPANY ROLES <<<Company Role #1: UX Researcher 2022-11 - N/A N/A United States Digital Service united-states-digital-service Government Administration We're mission-driven professio... === PERSON ===Stephanie KokotakisN/ALos Angeles, California, United States325=== ROLES ===>>> COMPANY ROLES <<<No company roles listed.>>> SCHOOL ROLES <<<No school roles listed. - Loss: MultipleNegativesSymmetricRankingLoss with these parameters:
{ "scale": 20.0, "similarity_fct": "cos_sim" }
Evaluation Dataset
Unnamed Dataset
- Size: 47,595 evaluation samples
- Columns: text1, text2, and label
- Approximate statistics based on the first 1000 samples:
text1 text2 label type string string int details min: 5 tokensmean: 221.5 tokensmax: 2048 tokens min: 50 tokensmean: 605.95 tokensmax: 2048 tokens 0: ~82.40%1: ~17.60% - Samples:
text1 text2 label Nonprofit and association management expert === PERSON ===Marius StrydomMarius Strydom has spent 20 years producing innovative research on the SA financial services industry, with a specific focus on insurance. He was rated the top SA life assurance analyst twice and the top short-term insurance analyst 5 times while working at Investec and BJM. At Bank of America Merrill Lynch, Marius led the EEMEA Financial Sector Research team to a second place in the 2013 Institutional Investor survey. During 2013 and 2014, he worked on academic research, culminating in being published in the South African Actuarial Journal. Since 2015, as part of his work with MLAX Consulting, Marius analysed and produced bespoke research on numerous SA and UK financial companies. In 2020, Marius founded Austin Lawrence Gidon and together with global partner, Edison Investment Research, they are driving the sponsored research revolution in South Africa.City of Cape Town, Western Cape, South Africa1351=== ROLES ===>>> COMPANY ROLES <<<Company Role #... 0 Expert in Alienware product support === PERSON ===Ryan TalbotWith over 25 years of experience in physical security, Identity management, and video surveillance, Ryan is recognized as a leader in the design and implementation of major technology solutions.Ryan has managed major security and IT system implementations for government, commercial, transport, data centres, gaming & casinos, retail, law enforcement and critical infrastructure environments. Ryan has worked closely with major technology brands in the design and development of hardware and software products throughout; Australia, Europe, North America and Asia.A leader in advanced video solutions and a former committee member of the AS/NZS 62676:5 standards, an experienced project manager and is PRINCE2 certified. He has a certificate IV in security risk management and qualifications in security electronics and sports performance.Ryan has also been involved in the development and design of many new technologies for IP cameras, customised ... 0 === PERSON ===Kevin WatsonSpecialties: Parametric cost estimation,WLC / LCC analysis, Logistics and supportability modelling. Economic LORA, Spares modelling,Tools / Applications: PRICE® TruePlanning®, EDCAS®, VMetric®United Kingdom389=== ROLES ===>>> COMPANY ROLES <<<Company Role #1: Senior Consultant 2013-09 - N/A N/A QinetiQ qinetiq_2 Defense and Space Manufacturing Create It. Test It. Use It. 122597Company Role #2: Support Modelling Team Lead 2004-06 - 2011-02 N/A General Dynamics UK Limited general-dynamics-uk-limited Defense and Space Manufacturing General Dynamics UK is one of the UK’s leading defence companies and an important supplier to the UK Ministry of Defence 29195Company Role #3: Estimation Specialist Senior Engineer 2011-02 - 2013-09 N/A General Dynamics UK Limited general-dynamics-uk-limited Defense and Space Manufacturing General Dynamics UK is one of the UK’s leading defence com... === PERSON ===Kyle Biron, M.S.N/ARaleigh-Durham-Chapel Hill Area308=== ROLES ===>>> COMPANY ROLES <<<Company Role #1: Clinical Informatics Analyst Associate 2017-05 - 2018-05 • Data analyst at the Grow Baby Grow biostatistics lab at Kennesaw State University • Statistical programming and statistical modeling using the Pediatrix Medical Group, Inc. database of over 1.2 million infant records to solve medical problems• Received acknowledgement in a Neonatology publication comparing BMI with other proportionality measurements• En route to another publication comparing popular intrauterine preterm growth curves• Supervisory experience by managing and collaborating with other biostatisticians Kennesaw State University kennesaw-state-university N/A We are KSU Owls. And together, we're ascending. 167722Company Role #2: Health Data Analyst II 2022-06 - N/A N/A Nuna Inc. nuna-inc IT Services and IT Consulting Driven by Data, Guided by Com... 0 - Loss: MultipleNegativesSymmetricRankingLoss with these parameters:
{ "scale": 20.0, "similarity_fct": "cos_sim" }
Training Hyperparameters
Non-Default Hyperparameters
eval_strategy: stepsper_device_train_batch_size: 16per_device_eval_batch_size: 32learning_rate: 2e-05num_train_epochs: 1warmup_ratio: 0.1bf16: Trueload_best_model_at_end: Truebatch_sampler: no_duplicates
All Hyperparameters
overwrite_output_dir: Falsedo_predict: Falseeval_strategy: stepsprediction_loss_only: Trueper_device_train_batch_size: 16per_device_eval_batch_size: 32per_gpu_train_batch_size: Noneper_gpu_eval_batch_size: Nonegradient_accumulation_steps: 1eval_accumulation_steps: Nonetorch_empty_cache_steps: Nonelearning_rate: 2e-05weight_decay: 0.0adam_beta1: 0.9adam_beta2: 0.999adam_epsilon: 1e-08max_grad_norm: 1.0num_train_epochs: 1max_steps: -1lr_scheduler_type: linearlr_scheduler_kwargs: {}warmup_ratio: 0.1warmup_steps: 0log_level: passivelog_level_replica: warninglog_on_each_node: Truelogging_nan_inf_filter: Truesave_safetensors: Truesave_on_each_node: Falsesave_only_model: Falserestore_callback_states_from_checkpoint: Falseno_cuda: Falseuse_cpu: Falseuse_mps_device: Falseseed: 42data_seed: Nonejit_mode_eval: Falseuse_ipex: Falsebf16: Truefp16: Falsefp16_opt_level: O1half_precision_backend: autobf16_full_eval: Falsefp16_full_eval: Falsetf32: Nonelocal_rank: 0ddp_backend: Nonetpu_num_cores: Nonetpu_metrics_debug: Falsedebug: []dataloader_drop_last: Falsedataloader_num_workers: 0dataloader_prefetch_factor: Nonepast_index: -1disable_tqdm: Falseremove_unused_columns: Truelabel_names: Noneload_best_model_at_end: Trueignore_data_skip: Falsefsdp: []fsdp_min_num_params: 0fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}fsdp_transformer_layer_cls_to_wrap: Noneaccelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}deepspeed: Nonelabel_smoothing_factor: 0.0optim: adamw_torchoptim_args: Noneadafactor: Falsegroup_by_length: Falselength_column_name: lengthddp_find_unused_parameters: Noneddp_bucket_cap_mb: Noneddp_broadcast_buffers: Falsedataloader_pin_memory: Truedataloader_persistent_workers: Falseskip_memory_metrics: Trueuse_legacy_prediction_loop: Falsepush_to_hub: Falseresume_from_checkpoint: Nonehub_model_id: Nonehub_strategy: every_savehub_private_repo: Nonehub_always_push: Falsegradient_checkpointing: Falsegradient_checkpointing_kwargs: Noneinclude_inputs_for_metrics: Falseinclude_for_metrics: []eval_do_concat_batches: Truefp16_backend: autopush_to_hub_model_id: Nonepush_to_hub_organization: Nonemp_parameters:auto_find_batch_size: Falsefull_determinism: Falsetorchdynamo: Noneray_scope: lastddp_timeout: 1800torch_compile: Falsetorch_compile_backend: Nonetorch_compile_mode: Nonedispatch_batches: Nonesplit_batches: Noneinclude_tokens_per_second: Falseinclude_num_input_tokens_seen: Falseneftune_noise_alpha: Noneoptim_target_modules: Nonebatch_eval_metrics: Falseeval_on_start: Falseuse_liger_kernel: Falseeval_use_gather_object: Falseaverage_tokens_across_devices: Falseprompts: Nonebatch_sampler: no_duplicatesmulti_dataset_batch_sampler: proportional
Training Logs
| Epoch | Step | Training Loss | Validation Loss | max_ap | rec_test_evaluator_max_ap | query_test_evaluator_max_ap |
|---|---|---|---|---|---|---|
| 0 | 0 | - | - | 0.4584 | 0.5698 | 0.7804 |
| 0.0051 | 50 | 1.9282 | - | - | - | - |
| 0.0103 | 100 | 1.754 | - | - | - | - |
| 0.0154 | 150 | 1.4681 | - | - | - | - |
| 0.0206 | 200 | 1.1736 | - | - | - | - |
| 0.0257 | 250 | 1.0527 | - | - | - | - |
| 0.0308 | 300 | 0.9073 | - | - | - | - |
| 0.0360 | 350 | 0.9088 | - | - | - | - |
| 0.0411 | 400 | 0.8556 | - | - | - | - |
| 0.0463 | 450 | 0.77 | - | - | - | - |
| 0.0514 | 500 | 0.7768 | - | - | - | - |
| 0.0565 | 550 | 0.5559 | - | - | - | - |
| 0.0617 | 600 | 0.7102 | - | - | - | - |
| 0.0668 | 650 | 0.6498 | - | - | - | - |
| 0.0719 | 700 | 0.699 | - | - | - | - |
| 0.0771 | 750 | 0.6628 | - | - | - | - |
| 0.0822 | 800 | 0.7298 | - | - | - | - |
| 0.0874 | 850 | 0.6278 | - | - | - | - |
| 0.0925 | 900 | 0.6033 | - | - | - | - |
| 0.0976 | 950 | 0.5783 | - | - | - | - |
| 0.1028 | 1000 | 0.6187 | - | - | - | - |
| 0.1079 | 1050 | 0.5712 | - | - | - | - |
| 0.1131 | 1100 | 0.6375 | - | - | - | - |
| 0.1182 | 1150 | 0.6028 | - | - | - | - |
| 0.1233 | 1200 | 0.6227 | - | - | - | - |
| 0.1285 | 1250 | 0.5955 | - | - | - | - |
| 0.1336 | 1300 | 0.6402 | - | - | - | - |
| 0.1388 | 1350 | 0.5982 | - | - | - | - |
| 0.1439 | 1400 | 0.6085 | - | - | - | - |
| 0.1490 | 1450 | 0.6163 | - | - | - | - |
| 0.1542 | 1500 | 0.6304 | - | - | - | - |
| 0.1593 | 1550 | 0.5499 | - | - | - | - |
| 0.1645 | 1600 | 0.5648 | - | - | - | - |
| 0.1696 | 1650 | 0.6121 | - | - | - | - |
| 0.1747 | 1700 | 0.5499 | - | - | - | - |
| 0.1799 | 1750 | 0.518 | - | - | - | - |
| 0.1850 | 1800 | 0.565 | - | - | - | - |
| 0.1902 | 1850 | 0.5966 | - | - | - | - |
| 0.1953 | 1900 | 0.559 | - | - | - | - |
| 0 | 0 | - | - | 0.9020 | - | - |
| 0.2000 | 1946 | - | 4.7301 | - | - | - |
| 0.2004 | 1950 | 0.6196 | - | - | - | - |
| 0.2056 | 2000 | 0.5304 | - | - | - | - |
| 0.2107 | 2050 | 0.5613 | - | - | - | - |
| 0.2158 | 2100 | 0.5716 | - | - | - | - |
| 0.2210 | 2150 | 0.5914 | - | - | - | - |
| 0.2261 | 2200 | 0.5692 | - | - | - | - |
| 0.2313 | 2250 | 0.5049 | - | - | - | - |
| 0.2364 | 2300 | 0.5064 | - | - | - | - |
| 0.2415 | 2350 | 0.5624 | - | - | - | - |
| 0.2467 | 2400 | 0.482 | - | - | - | - |
| 0.2518 | 2450 | 0.5529 | - | - | - | - |
| 0.2570 | 2500 | 0.5037 | - | - | - | - |
| 0.2621 | 2550 | 0.5702 | - | - | - | - |
| 0.2672 | 2600 | 0.5219 | - | - | - | - |
| 0.2724 | 2650 | 0.4623 | - | - | - | - |
| 0.2775 | 2700 | 0.5232 | - | - | - | - |
| 0.2827 | 2750 | 0.5867 | - | - | - | - |
| 0.2878 | 2800 | 0.5514 | - | - | - | - |
| 0.2929 | 2850 | 0.5288 | - | - | - | - |
| 0.2981 | 2900 | 0.5069 | - | - | - | - |
| 0.3032 | 2950 | 0.5761 | - | - | - | - |
| 0.3084 | 3000 | 0.525 | - | - | - | - |
| 0.3135 | 3050 | 0.5664 | - | - | - | - |
| 0.3186 | 3100 | 0.6317 | - | - | - | - |
| 0.3238 | 3150 | 0.5479 | - | - | - | - |
| 0.3289 | 3200 | 0.553 | - | - | - | - |
| 0.3341 | 3250 | 0.4752 | - | - | - | - |
| 0.3392 | 3300 | 0.5127 | - | - | - | - |
| 0.3443 | 3350 | 0.5699 | - | - | - | - |
| 0.3495 | 3400 | 0.5394 | - | - | - | - |
| 0.3546 | 3450 | 0.507 | - | - | - | - |
| 0.3597 | 3500 | 0.5938 | - | - | - | - |
| 0.3649 | 3550 | 0.539 | - | - | - | - |
| 0.3700 | 3600 | 0.525 | - | - | - | - |
| 0.3752 | 3650 | 0.4864 | - | - | - | - |
| 0.3803 | 3700 | 0.5308 | - | - | - | - |
| 0.3854 | 3750 | 0.4859 | - | - | - | - |
| 0.3906 | 3800 | 0.513 | - | - | - | - |
| 0.3957 | 3850 | 0.5332 | - | - | - | - |
| 0 | 0 | - | - | 0.9121 | - | - |
| 0.4000 | 3892 | - | 4.7785 | - | - | - |
| 0.4009 | 3900 | 0.474 | - | - | - | - |
| 0.4060 | 3950 | 0.458 | - | - | - | - |
| 0.4111 | 4000 | 0.5066 | - | - | - | - |
| 0.4163 | 4050 | 0.5217 | - | - | - | - |
| 0.4214 | 4100 | 0.5381 | - | - | - | - |
| 0.4266 | 4150 | 0.4994 | - | - | - | - |
| 0.4317 | 4200 | 0.508 | - | - | - | - |
| 0.4368 | 4250 | 0.4696 | - | - | - | - |
| 0.4420 | 4300 | 0.5563 | - | - | - | - |
| 0.4471 | 4350 | 0.4831 | - | - | - | - |
| 0.4523 | 4400 | 0.4532 | - | - | - | - |
| 0.4574 | 4450 | 0.5056 | - | - | - | - |
| 0.4625 | 4500 | 0.5409 | - | - | - | - |
| 0.4677 | 4550 | 0.5122 | - | - | - | - |
| 0.4728 | 4600 | 0.4593 | - | - | - | - |
| 0.4780 | 4650 | 0.5206 | - | - | - | - |
| 0.4831 | 4700 | 0.4803 | - | - | - | - |
| 0.4882 | 4750 | 0.478 | - | - | - | - |
| 0.4934 | 4800 | 0.5563 | - | - | - | - |
| 0.4985 | 4850 | 0.5191 | - | - | - | - |
| 0.5036 | 4900 | 0.4981 | - | - | - | - |
| 0.5088 | 4950 | 0.5075 | - | - | - | - |
| 0.5139 | 5000 | 0.5035 | - | - | - | - |
| 0.5191 | 5050 | 0.4375 | - | - | - | - |
| 0.5242 | 5100 | 0.515 | - | - | - | - |
| 0.5293 | 5150 | 0.4386 | - | - | - | - |
| 0.5345 | 5200 | 0.4757 | - | - | - | - |
| 0.5396 | 5250 | 0.4715 | - | - | - | - |
| 0.5448 | 5300 | 0.452 | - | - | - | - |
| 0.5499 | 5350 | 0.4789 | - | - | - | - |
| 0.5550 | 5400 | 0.4839 | - | - | - | - |
| 0.5602 | 5450 | 0.472 | - | - | - | - |
| 0.5653 | 5500 | 0.4779 | - | - | - | - |
| 0.5705 | 5550 | 0.4804 | - | - | - | - |
| 0.5756 | 5600 | 0.4778 | - | - | - | - |
| 0.5807 | 5650 | 0.4542 | - | - | - | - |
| 0.5859 | 5700 | 0.5099 | - | - | - | - |
| 0.5910 | 5750 | 0.5326 | - | - | - | - |
| 0.5962 | 5800 | 0.4859 | - | - | - | - |
| 0 | 0 | - | - | 0.9162 | - | - |
| 0.6001 | 5838 | - | 4.7525 | - | - | - |
| 0.6013 | 5850 | 0.4558 | - | - | - | - |
| 0.6064 | 5900 | 0.4429 | - | - | - | - |
| 0.6116 | 5950 | 0.4862 | - | - | - | - |
| 0.6167 | 6000 | 0.453 | - | - | - | - |
| 0.6219 | 6050 | 0.4795 | - | - | - | - |
| 0.6270 | 6100 | 0.4835 | - | - | - | - |
| 0.6321 | 6150 | 0.4517 | - | - | - | - |
| 0.6373 | 6200 | 0.4654 | - | - | - | - |
| 0.6424 | 6250 | 0.4076 | - | - | - | - |
| 0.6475 | 6300 | 0.4213 | - | - | - | - |
| 0.6527 | 6350 | 0.5258 | - | - | - | - |
| 0.6578 | 6400 | 0.4392 | - | - | - | - |
| 0.6630 | 6450 | 0.467 | - | - | - | - |
| 0.6681 | 6500 | 0.4382 | - | - | - | - |
| 0.6732 | 6550 | 0.4254 | - | - | - | - |
| 0.6784 | 6600 | 0.4647 | - | - | - | - |
| 0.6835 | 6650 | 0.4333 | - | - | - | - |
| 0.6887 | 6700 | 0.5067 | - | - | - | - |
| 0.6938 | 6750 | 0.4584 | - | - | - | - |
| 0.6989 | 6800 | 0.4843 | - | - | - | - |
| 0.7041 | 6850 | 0.441 | - | - | - | - |
| 0.7092 | 6900 | 0.4461 | - | - | - | - |
| 0.7144 | 6950 | 0.5262 | - | - | - | - |
| 0.7195 | 7000 | 0.463 | - | - | - | - |
| 0.7246 | 7050 | 0.4917 | - | - | - | - |
| 0.7298 | 7100 | 0.4288 | - | - | - | - |
| 0.7349 | 7150 | 0.4572 | - | - | - | - |
| 0.7401 | 7200 | 0.523 | - | - | - | - |
| 0.7452 | 7250 | 0.4868 | - | - | - | - |
| 0.7503 | 7300 | 0.4292 | - | - | - | - |
| 0.7555 | 7350 | 0.3998 | - | - | - | - |
| 0.7606 | 7400 | 0.4515 | - | - | - | - |
| 0.7658 | 7450 | 0.5028 | - | - | - | - |
| 0.7709 | 7500 | 0.4417 | - | - | - | - |
| 0.7760 | 7550 | 0.4908 | - | - | - | - |
| 0.7812 | 7600 | 0.4344 | - | - | - | - |
| 0.7863 | 7650 | 0.4956 | - | - | - | - |
| 0.7914 | 7700 | 0.3898 | - | - | - | - |
| 0.7966 | 7750 | 0.4512 | - | - | - | - |
| 0 | 0 | - | - | 0.9214 | - | - |
| 0.8001 | 7784 | - | 4.7145 | - | - | - |
| 0.8017 | 7800 | 0.5104 | - | - | - | - |
| 0.8069 | 7850 | 0.4543 | - | - | - | - |
| 0.8120 | 7900 | 0.4041 | - | - | - | - |
| 0.8171 | 7950 | 0.472 | - | - | - | - |
| 0.8223 | 8000 | 0.4535 | - | - | - | - |
| 0.8274 | 8050 | 0.4412 | - | - | - | - |
| 0.8326 | 8100 | 0.4776 | - | - | - | - |
| 0.8377 | 8150 | 0.3992 | - | - | - | - |
| 0.8428 | 8200 | 0.4332 | - | - | - | - |
| 0.8480 | 8250 | 0.4767 | - | - | - | - |
| 0.8531 | 8300 | 0.453 | - | - | - | - |
| 0.8583 | 8350 | 0.4321 | - | - | - | - |
| 0.8634 | 8400 | 0.4654 | - | - | - | - |
| 0.8685 | 8450 | 0.3688 | - | - | - | - |
| 0.8737 | 8500 | 0.4515 | - | - | - | - |
| 0.8788 | 8550 | 0.4693 | - | - | - | - |
| 0.8840 | 8600 | 0.404 | - | - | - | - |
| 0.8891 | 8650 | 0.5471 | - | - | - | - |
| 0.8942 | 8700 | 0.5301 | - | - | - | - |
| 0.8994 | 8750 | 0.4714 | - | - | - | - |
| 0.9045 | 8800 | 0.4863 | - | - | - | - |
| 0.9097 | 8850 | 0.4712 | - | - | - | - |
| 0.9148 | 8900 | 0.4446 | - | - | - | - |
| 0.9199 | 8950 | 0.41 | - | - | - | - |
| 0.9251 | 9000 | 0.4175 | - | - | - | - |
| 0.9302 | 9050 | 0.4678 | - | - | - | - |
| 0.9353 | 9100 | 0.4308 | - | - | - | - |
| 0.9405 | 9150 | 0.4532 | - | - | - | - |
| 0.9456 | 9200 | 0.4643 | - | - | - | - |
| 0.9508 | 9250 | 0.4197 | - | - | - | - |
| 0.9559 | 9300 | 0.4488 | - | - | - | - |
| 0.9610 | 9350 | 0.5365 | - | - | - | - |
| 0.9662 | 9400 | 0.475 | - | - | - | - |
| 0.9713 | 9450 | 0.438 | - | - | - | - |
| 0.9765 | 9500 | 0.3648 | - | - | - | - |
| 0.9816 | 9550 | 0.4277 | - | - | - | - |
| 0.9867 | 9600 | 0.4721 | - | - | - | - |
| 0.9919 | 9650 | 0.4603 | - | - | - | - |
| 0.9970 | 9700 | 0.3954 | - | - | - | - |
| 0 | 0 | - | - | 0.9214 | 0.8700 | 0.9475 |
- The bold row denotes the saved checkpoint.
Framework Versions
- Python: 3.12.8
- Sentence Transformers: 3.4.1
- Transformers: 4.48.1
- PyTorch: 2.6.0+cu124
- Accelerate: 1.3.0
- Datasets: 3.2.0
- Tokenizers: 0.21.0
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",
}