samehkhattab/biomed-retrieval-qwen3-0.6b-base-checkpoint

SentenceTransformer based on Qwen/Qwen3-0.6B

This is a sentence-transformers model finetuned from Qwen/Qwen3-0.6B on the biomed_retrieval_dataset dataset. It maps sentences & paragraphs to a 1024-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: Qwen/Qwen3-0.6B
• Maximum Sequence Length: 512 tokens
• Output Dimensionality: 1024 dimensions
• Similarity Function: Cosine Similarity
• Training Dataset:
  • biomed_retrieval_dataset

Model Sources

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

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: Qwen3Model 
  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': True, '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("sentence_transformers_model_id")
# Run inference
sentences = [
    'Given a question, retrieve relevant Pubmed passages that answer the question: Do experimental pain models reveal no sex differences in pentazocine analgesia in humans?',
    'Accumulating evidence suggests that there are sex differences in analgesic responses to opioid agonists. Several studies using an oral surgery pain model have reported more robust analgesia to kappa-agonist-antagonists (e.g., pentazocine, nalbuphine, butorphanol) among women than among men. However, evidence of sex differences in kappa-agonist-antagonist effects from studies of experimentally induced pain in humans is lacking. Therefore, the analgesic effects of intravenous pentazocine (0.5 mg/kg) were determined in healthy women (n = 41) and men (n = 38) using three experimental pain models: heat pain, pressure pain, and ischemic pain. Each pain procedure was conducted before and after double-blind administration of both pentazocine and saline, which occurred on separate days in counterbalanced order. Compared with saline, pentazocine produced significant analgesic responses for all pain stimuli. However, no sex differences in pentazocine analgesia emerged. Effect sizes for the sex differences were computed; the magnitude of effects was small, and an equal number of measures showed greater analgesia in men than in women. Also, analgesic responses were not highly correlated across pain modalities, suggesting that different mechanisms may underlie analgesia for disparate types of pain',
    "The purpose of this study was to elucidate the relationship between thermal and mechanical sensation, as well as pain thresholds degrees and the dynamics of the TRPV1 level in almost healthy young males and females in the follicular and luteal phases of the OMC. We found gender differences for some pain sensation indices, taking into account OMC phases of females. Mechanical pain tolerance and heat pain thresholds were significantly higher in males compared with females in both phases of the OMC, also, mechanical pain, mechanical pressure, cold pain and heat sensation thresholds were insignificantly higher in males compared with females in follicular phase of the OMC and significantly higher - in luteal phase of the OMC. We haven't found any differences in cold sensation threshold between males and females in both phases of OMC. Moreover, we found significant gender and interphase differences in receptor protein TRPV1 level - the maximal level in females in luteal phase of the OMC, lower in males and minimal in females in follicular phase of the OMC. Worldwide, women account for approximately 51% of human immunodeficiency virus-1 (HIV) seropositive individuals. The prevalence of neuropathic pain among individuals with HIV and a lack of preclinical data characterizing sex differences prompted us to address this knowledge gap. C57BL/6 male and female mice received multiple intrathecal injections of HIV-glycoprotein 120 (gp120), followed by determination of mechanical allodynia and thermal hypersensitivity for four weeks. The influence of ovarian hormones in the gp120 pain model was evaluated by comparison of ovariectomized (OVX) mice versus sham control. We found that gp120-induced neuropathic pain-like behaviors are sex-dependent. Female mice showed both increased mechanical allodynia and increased cold sensitivity relative to their male counterparts. The OVX mice showed reduced pain sensitivity compared to sham, suggesting a role of the ovarian hormones in sex differences in pain sensitivity to gp120. Gp120-induced neuropathic pain caused a shift in estrous cycle toward the estrus phase. However, there is a lack of clear correlation between the estrous cycle and the development of neuropathic pain-like behaviors during the four week recording period. This data provided the first evidence for sex differences in a rodent model of HIV-related neuropathic pain, along with a potential role of ovarian hormones.",
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1024]

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

Evaluation

Metrics

Triplet

• Dataset: bmretriever
• Evaluated with TripletEvaluator

Metric	Value
cosine_accuracy	0.9784

Training Details

Training Dataset

biomed_retrieval_dataset

• Dataset: biomed_retrieval_dataset at dff25ba
• Size: 1,260,000 training samples
• Columns: anchor, positive, negative, and source
• Approximate statistics based on the first 1000 samples:

  	anchor	positive	negative	source
  type	string	string	string	string
  details	min: 16 tokens mean: 30.12 tokens max: 512 tokens	min: 3 tokens mean: 207.95 tokens max: 512 tokens	min: 2 tokens mean: 323.72 tokens max: 512 tokens	min: 1 tokens mean: 2.3 tokens max: 4 tokens

• Samples:

  anchor	positive	negative	source
  Given a question, retrieve relevant passages that answer the question: when does the new season of real housewives of beverly hills air?	The Real Housewives of Beverly Hills (season 10) This is the latest accepted revision, reviewed on 27 July 2020. The tenth season of The Real Housewives of Beverly Hills, an American reality television series, is broadcast on Bravo. It premiered on April 15 2020, and is primarily filmed in Beverly Hills, California.	Seasons 1–4. The Real Housewives of Beverly Hills was announced in March 2010 as the sixth installment of The Real Housewives franchise. The first season premiered on October 14, 2010, and starred Kyle Richards, Adrienne Maloof, Kim Richards, Lisa Vanderpump, Camille Grammer and Taylor Armstrong. This is the latest accepted revision, reviewed on 27 July 2020. The tenth season of The Real Housewives of Beverly Hills, an American reality television series, is broadcast on Bravo. It premiered on April 15 2020, and is primarily filmed in Beverly Hills, California.	gooaq
  Given a question, retrieve Pubmed passages that answer the question: determinants of the pathway to emergency obstetric care in south africa	BACKGROUND: Maternity referral systems have been under-documented, under-researched, and under-theorised. Responsive emergency referral systems and appropriate transportation are cornerstones in the continuum of care and central to the complex health system. The pathways that women follow to reach Emergency Obstetric and Neonatal Care (EmONC) once a decision has been made to seek care have received relatively little attention. The aim of this research was to identify patterns and determinants of the pathways pregnant women follow from the onset of labour or complications until they reach an appropriate health facility.METHODS: This study was conducted in Renk County in South Sudan between 2010 and 2012. Data was collected using Critical Incident Technique (CIT) and stakeholder interviews. CIT systematically identified pathways to healthcare during labour, and factors associated with an event of maternal mortality or near miss through a series of in-depth interviews with witnesses or th...	OBJECTIVES: In a rural district hospital in Burundi offering Emergency Obstetric care-(EmOC), we assessed the a) characteristics of women at risk of, or with an obstetric complication and their types b) the number and type of obstetric surgical procedures and anaesthesia performed c) human resource cadres who performed surgery and anaesthesia and d) hospital exit outcomes.METHODS: A retrospective analysis of EmOC data (2011 and 2012).RESULTS: A total of 6084 women were referred for EmOC of whom 2534(42%) underwent a major surgical procedure while 1345(22%) required a minor procedure (36% women did not require any surgical procedure). All cases with uterine rupture(73) and extra-uterine pregnancy(10) and the majority with pre-uterine rupture and foetal distress required major surgery. The two most prevalent conditions requiring a minor surgical procedure were abortions (61%) and normal delivery (34%). A total of 2544 major procedures were performed on 2534 admitted individuals. Of these...	synthetic
  Given a question, retrieve Wikipedia passages that answer the question: hindi festival where sisters give bracelets to brothers	Raksha Bandhan Raksha Bandhan, also Rakshabandhan, or Rakhi, is a popular, traditionally Hindu, annual rite, or ceremony, which is central to a festival of the same name, originating from the Indian subcontinent, celebrated in parts of Indian subcontinent, and among people influenced by Hindu and Indian culture around the world. On this day, sisters of all ages tie a talisman, or amulet, called the ""rakhi"", around the wrists of their brothers, symbolically protecting them, receiving a gift in return, and traditionally investing the brothers with a share of the responsibility of their potential care. Raksha Bandhan is observed on the	Bonalu Bonalu or Goddess Mahankali bonalu (Telugu: బోనాలు ) is a Hindu Festival, Goddess Mahakali is worshiped. Bonalu is an annual festival of Telangana celebrated in Twin Cities Hyderabad, Secunderabad and other parts of Telangana. It is celebrated in the month of Ashada Masam, in July/August. Special poojas are performed for Yellamma on the first and last day of the festival. The festival is also considered a thanksgiving to the Goddess for fulfillment of vows. The word ""Bonam"" is a contraction of the word ""Bhojanam"", a Sanskrit loanword which means a meal or a feast in Telugu, is an ""Offering related to the sixth Guru, Guru Hargobind. According to Sikh history, on this day, Guru Hargobind was released from prison by the Mughal Emperor Jahangir who freed 52 other Hindu kings with him. The Bandi Chhor Divas is celebrated in a manner similar to Diwali, with the lighting of homes and Gurdwaras, feasts, gift giving and family time. It is an important Sikh celebration along with Vai...	nq

• Loss: MultipleNegativesRankingLoss with these parameters:

  {
      "scale": 20.0,
      "similarity_fct": "cos_sim"
  }
  

Evaluation Dataset

biomed_retrieval_dataset

• Dataset: biomed_retrieval_dataset at dff25ba
• Size: 70,000 evaluation samples
• Columns: anchor, positive, negative, and source
• Approximate statistics based on the first 1000 samples:

  	anchor	positive	negative	source
  type	string	string	string	string
  details	min: 16 tokens mean: 29.95 tokens max: 305 tokens	min: 3 tokens mean: 196.37 tokens max: 512 tokens	min: 3 tokens mean: 317.98 tokens max: 512 tokens	min: 1 tokens mean: 2.31 tokens max: 4 tokens

• Samples:

  anchor	positive	negative	source
  Given a question, retrieve Pubmed passages that answer the question: what is considered the reference gene for bone marrow osteoblasts?	Quantitative real-time polymerase chain reaction (qRT-PCR) is a powerful tool to evaluate gene expression, but its accuracy depends on the choice and stability of the reference genes used for normalization. In this study, we aimed to identify reference genes for studies on osteoblasts derived from rat bone marrow mesenchymal stem cells (bone marrow osteoblasts), osteoblasts derived from newborn rat calvarial (calvarial osteoblasts), and rat osteosarcoma cell line UMR-106. The osteoblast phenotype was characterized by ALP activity and extracellular matrix mineralization. Thirty-one candidates for reference genes from a Taqman array were assessed by qRT-PCR, and their expressions were analyzed by five different approaches. The data showed that several of the most traditional reference genes, such as Actb and Gapdh, were inadequate for normalization and that the experimental conditions may affect gene stability. Eif2b1 was frequently identified among the best reference genes in bone marro...	Fast progress of the next generation sequencing (NGS) technology has allowed global transcriptional profiling and genome-wide mapping of transcription factor binding sites in various cellular contexts. However, limited number of replicates and high amount of data processing may weaken the significance of the findings. Comparative analyses of independent data sets acquired in the different laboratories would greatly increase the validity of the data. Runx2 is the key transcription factor regulating osteoblast differentiation and bone formation. We performed a comparative analysis of three published Runx2 data sets of chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) analysis in osteoblasts from mouse and human origin. Moreover, we assessed the similarity of the corresponding transcription data of these studies available online. The ChIP-seq data analysis confirmed general features of Runx2 binding, including location at genic vs intergenic regions and abundant Runx2 b...	synthetic
  Given a question, retrieve Pubmed passages that answer the question: what does gper1 do in the oviduct	Oviducts play roles in reproductive processes, including gametes transport, fertilization and early embryo development. Oviductal transport is controlled by various factors such as endothelins (EDNs) and nitric oxide (NO), smooth muscle contracting and relaxing factor, respectively. EDNs and NO production depend on an ovarian steroid hormone, oestradiol-17 (E2) and E2 quickly exerts their biological functions through G protein-coupled oestrogen receptor 1 (GPER1), which mediates rapid intracellular signalling. Because follicular fluid which contains a high concentration of E2 enters the oviduct, we hypothesized that E2 in the follicular fluid participates via GPER1 in producing EDNs and NO. To test this hypothesis, we investigated 1) the expression and localization of GPER1 in bovine oviductal tissues and 2) rapid effects of E2 via GPER1 on EDN1, EDN2 and inducible NO synthase (iNOS) expression in cultured bovine oviductal isthmic epithelial cells. GPER1 was observed in the oviductal e...	BACKGROUND: The G protein estrogen receptor GPER/GPR30 mediates estrogen action in breast cancer cells as well as in breast cancer-associated fibroblasts (CAFs), which are key components of microenvironment driving tumor progression. GPER is a transcriptional target of hypoxia inducible factor 1 alpha (HIF-1) and activates VEGF expression and angiogenesis in hypoxic breast tumor microenvironment. Furthermore, IGF1/IGF1R signaling, which has angiogenic effects, has been shown to activate GPER in breast cancer cells.METHODS: We analyzed gene expression data from published studies representing almost 5000 breast cancer patients to investigate whether GPER and IGF1 signaling establish an angiocrine gene signature in breast cancer patients. Next, we used GPER-positive but estrogen receptor (ER)-negative primary CAF cells derived from patient breast tumours and SKBR3 breast cancer cells to investigate the role of GPER in the regulation of VEGF expression and angiogenesis triggered by IGF1. W...	synthetic
  Given a question, retrieve Pubmed passages that answer the question: what are ovine hair follicle stem cells	Hair follicle stem cells (HFSCs) possess fascinating self-renewal capacity and multipotency, which play important roles in mammalian hair growth and skin wound repair. Although HFSCs from other mammalian species have been obtained, the characteristics of ovine HFSCs, as well as the methods to isolate them have not been well addressed. Here, we report an efficient strategy to obtain multipotent ovine HFSCs. Through microdissection and organ culture, we obtained keratinocytes that grew from the bulge area of vibrissa hair follicles, and even abundant keratinocytes were harvested from a single hair follicle. These bulge-derived keratinocytes are highly positive for Krt15, Krt14, Tp63, Krt19 and Itga6; in addition to their strong proliferation abilities in vitro, these keratinocytes formed new epidermis, hair follicles and sebaceous glands in skin reconstitution experiments, showing that these are HFSCs from the bulge outer root sheath. Taken together, we developed an efficient in vitro sy...	Hair differentiates from follicle stem cells through progenitor cells in the matrix. In contrast to stem cells in the bulge, the identities of the progenitors and the mechanisms by which they regulate hair shaft components are poorly understood. Hair is also pigmented by melanocytes in the follicle. However, the niche that regulates follicular melanocytes is not well characterized. Here, we report the identification of hair shaft progenitors in the matrix that are differentiated from follicular epithelial cells expressing transcription factor KROX20. Depletion of Krox20 lineage cells results in arrest of hair growth, confirming the critical role of KROX20+ cells as antecedents of structural cells found in hair. Expression of stem cell factor (SCF) by these cells is necessary for the maintenance of differentiated melanocytes and for hair pigmentation. Our findings reveal the identities of hair matrix progenitors that regulate hair growth and pigmentation, partly by creating an SCF-depen...	synthetic

• Loss: MultipleNegativesRankingLoss with these parameters:

  {
      "scale": 20.0,
      "similarity_fct": "cos_sim"
  }
  

Training Hyperparameters

Non-Default Hyperparameters

• eval_strategy: epoch
• per_device_train_batch_size: 256
• per_device_eval_batch_size: 256
• num_train_epochs: 1
• warmup_steps: 100
• bf16: True
• dataloader_drop_last: True
• optim: adamw_bnb_8bit
• ddp_find_unused_parameters: False
• gradient_checkpointing: True
• gradient_checkpointing_kwargs: {'use_reentrant': False}
• use_liger_kernel: True

All Hyperparameters

Click to expand

• overwrite_output_dir: False
• do_predict: False
• eval_strategy: epoch
• prediction_loss_only: True
• per_device_train_batch_size: 256
• per_device_eval_batch_size: 256
• 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: 5e-05
• weight_decay: 0.0
• adam_beta1: 0.9
• adam_beta2: 0.999
• adam_epsilon: 1e-08
• max_grad_norm: 1.0
• num_train_epochs: 1
• max_steps: -1
• lr_scheduler_type: linear
• lr_scheduler_kwargs: {}
• warmup_ratio: 0.0
• warmup_steps: 100
• 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
• bf16: True
• fp16: False
• fp16_opt_level: O1
• half_precision_backend: auto
• bf16_full_eval: False
• fp16_full_eval: False
• tf32: None
• local_rank: 0
• ddp_backend: None
• tpu_num_cores: None
• tpu_metrics_debug: False
• debug: []
• dataloader_drop_last: True
• dataloader_num_workers: 0
• dataloader_prefetch_factor: None
• past_index: -1
• disable_tqdm: False
• remove_unused_columns: True
• label_names: None
• load_best_model_at_end: False
• ignore_data_skip: False
• fsdp: []
• fsdp_min_num_params: 0
• fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
• 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}
• parallelism_config: None
• deepspeed: None
• label_smoothing_factor: 0.0
• optim: adamw_bnb_8bit
• optim_args: None
• adafactor: False
• group_by_length: False
• length_column_name: length
• project: huggingface
• trackio_space_id: trackio
• ddp_find_unused_parameters: False
• ddp_bucket_cap_mb: None
• ddp_broadcast_buffers: False
• dataloader_pin_memory: True
• dataloader_persistent_workers: False
• skip_memory_metrics: True
• use_legacy_prediction_loop: False
• push_to_hub: False
• resume_from_checkpoint: None
• hub_model_id: None
• hub_strategy: every_save
• hub_private_repo: None
• hub_always_push: False
• hub_revision: None
• gradient_checkpointing: True
• gradient_checkpointing_kwargs: {'use_reentrant': False}
• include_inputs_for_metrics: False
• include_for_metrics: []
• eval_do_concat_batches: True
• fp16_backend: auto
• push_to_hub_model_id: None
• push_to_hub_organization: None
• mp_parameters:
• auto_find_batch_size: False
• full_determinism: False
• torchdynamo: None
• ray_scope: last
• ddp_timeout: 1800
• torch_compile: False
• torch_compile_backend: None
• torch_compile_mode: None
• include_tokens_per_second: False
• include_num_input_tokens_seen: no
• neftune_noise_alpha: None
• optim_target_modules: None
• batch_eval_metrics: False
• eval_on_start: False
• use_liger_kernel: True
• liger_kernel_config: None
• eval_use_gather_object: False
• average_tokens_across_devices: True
• prompts: None
• batch_sampler: batch_sampler
• multi_dataset_batch_sampler: proportional

Training Logs

Epoch	Step	Training Loss	Validation Loss	bmretriever_cosine_accuracy
0.0102	50	4.6537	-	-
0.0203	100	0.3978	-	-
0.0305	150	0.1825	-	-
0.0406	200	0.1429	-	-
0.0508	250	0.1217	-	-
0.0610	300	0.1185	-	-
0.0711	350	0.1121	-	-
0.0813	400	0.1088	-	-
0.0914	450	0.0943	-	-
0.1016	500	0.0935	-	-
0.1118	550	0.0948	-	-
0.1219	600	0.0911	-	-
0.1321	650	0.0847	-	-
0.1422	700	0.0839	-	-
0.1524	750	0.0809	-	-
0.1626	800	0.083	-	-
0.1727	850	0.0815	-	-
0.1829	900	0.0726	-	-
0.1931	950	0.0748	-	-
0.2032	1000	0.0753	-	-
0.2134	1050	0.0707	-	-
0.2235	1100	0.0672	-	-
0.2337	1150	0.0739	-	-
0.2439	1200	0.0678	-	-
0.2540	1250	0.0685	-	-
0.2642	1300	0.068	-	-
0.2743	1350	0.0658	-	-
0.2845	1400	0.0636	-	-
0.2947	1450	0.0683	-	-
0.3048	1500	0.0641	-	-
0.3150	1550	0.0569	-	-
0.3251	1600	0.064	-	-
0.3353	1650	0.0607	-	-
0.3455	1700	0.0711	-	-
0.3556	1750	0.0612	-	-
0.3658	1800	0.0587	-	-
0.3759	1850	0.0596	-	-
0.3861	1900	0.0613	-	-
0.3963	1950	0.0571	-	-
0.4064	2000	0.0672	-	-
0.4166	2050	0.0587	-	-
0.4267	2100	0.0602	-	-
0.4369	2150	0.0633	-	-
0.4471	2200	0.0601	-	-
0.4572	2250	0.0572	-	-
0.4674	2300	0.0568	-	-
0.4775	2350	0.0604	-	-
0.4877	2400	0.0615	-	-
0.4979	2450	0.0543	-	-
0.5080	2500	0.0529	-	-
0.5182	2550	0.0563	-	-
0.5283	2600	0.0538	-	-
0.5385	2650	0.0559	-	-
0.5487	2700	0.0568	-	-
0.5588	2750	0.0533	-	-
0.5690	2800	0.0543	-	-
0.5792	2850	0.0498	-	-
0.5893	2900	0.0494	-	-
0.5995	2950	0.0536	-	-
0.6096	3000	0.0492	-	-
0.6198	3050	0.053	-	-
0.6300	3100	0.0536	-	-
0.6401	3150	0.05	-	-
0.6503	3200	0.0513	-	-
0.6604	3250	0.0458	-	-
0.6706	3300	0.0509	-	-
0.6808	3350	0.0524	-	-
0.6909	3400	0.0541	-	-
0.7011	3450	0.0518	-	-
0.7112	3500	0.0501	-	-
0.7214	3550	0.0488	-	-
0.7316	3600	0.05	-	-
0.7417	3650	0.0511	-	-
0.7519	3700	0.05	-	-
0.7620	3750	0.0492	-	-
0.7722	3800	0.0511	-	-
0.7824	3850	0.0489	-	-
0.7925	3900	0.0534	-	-
0.8027	3950	0.0431	-	-
0.8128	4000	0.0492	-	-
0.8230	4050	0.0486	-	-
0.8332	4100	0.052	-	-
0.8433	4150	0.0525	-	-
0.8535	4200	0.0454	-	-
0.8636	4250	0.0488	-	-
0.8738	4300	0.0455	-	-
0.8840	4350	0.0494	-	-
0.8941	4400	0.0487	-	-
0.9043	4450	0.0482	-	-
0.9144	4500	0.0486	-	-
0.9246	4550	0.0465	-	-
0.9348	4600	0.0516	-	-
0.9449	4650	0.0481	-	-
0.9551	4700	0.0493	-	-
0.9653	4750	0.0457	-	-
0.9754	4800	0.0479	-	-
0.9856	4850	0.0427	-	-
0.9957	4900	0.0423	-	-
1.0	4921	-	0.0460	0.9784

Framework Versions

• Python: 3.11.9
• Sentence Transformers: 4.1.0
• Transformers: 4.57.1
• PyTorch: 2.6.0+cu124
• Accelerate: 1.6.0
• Datasets: 2.21.0
• Tokenizers: 0.22.1

Citation

BibTeX

Sentence Transformers

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

MultipleNegativesRankingLoss

@misc{henderson2017efficient,
    title={Efficient Natural Language Response Suggestion for Smart Reply},
    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
    year={2017},
    eprint={1705.00652},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}