SentenceTransformer based on intfloat/multilingual-e5-large-instruct

Model Details

Model Description

• Model Type: Sentence Transformer
• Base model: intfloat/multilingual-e5-large-instruct
• Maximum Sequence Length: 512 tokens
• Output Dimensionality: 1024 dimensions
• Similarity Function: Cosine Similarity
• Supported Modality: Text

Model Sources

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

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'transformer_task': 'feature-extraction', 'modality_config': {'text': {'method': 'forward', 'method_output_name': 'last_hidden_state'}}, 'module_output_name': 'token_embeddings', 'architecture': 'XLMRobertaModel'})
  (1): Pooling({'embedding_dimension': 1024, 'pooling_mode': 'mean', 'include_prompt': True})
  (2): Normalize({})
)

Usage

Direct Usage (Sentence Transformers)

Evaluation

Metrics

Information Retrieval

• Dataset: 10-percent-dev-split
• Evaluated with InformationRetrievalEvaluator

Training Details

Training Dataset

Unnamed Dataset

• Size: 17,319 training samples
• Columns: sentence_0, sentence_1, and sentence_2
• Approximate statistics based on the first 1000 samples:

  	sentence_0	sentence_1	sentence_2
  type	string	string	string
  details	min: 25 tokens mean: 58.26 tokens max: 105 tokens	min: 28 tokens mean: 311.97 tokens max: 512 tokens	min: 20 tokens mean: 320.42 tokens max: 512 tokens

• Samples:

  sentence_0	sentence_1	sentence_2
  query: I was fact-checked when I covered this topic for @user last year. Since the story back then was, apparently, that damp strips of fabric dangling over people's faces for hours on end couldn't possibly spawn anything nasty - because Science™!!	passage: title: Bacterial and fungal isolation from face masks under the COVID-19 pandemic
  abstract: Abstract The COVID-19 pandemic has led people to wear face masks daily in public. Although the effectiveness of face masks against viral transmission has been extensively studied, there have been few reports on potential hygiene issues due to bacteria and fungi attached to the face masks. We aimed to (1) quantify and identify the bacteria and fungi attaching to the masks, and (2) investigate whether the mask-attached microbes could be associated with the types and usage of the masks and individual lifestyles. We surveyed 109 volunteers on their mask usage and lifestyles, and cultured bacteria and fungi from either the face-side or outer-side of their masks. The bacterial colony numbers were greater on the face-side than the outer-side; the fungal colony numbers were fewer on the face-side than the outer-side. A longer mask usage significantly increased the fungal colony numbers but not ...	passage: is very low.

  title: Do facemasks protect against COVID‐19? Symptomatic health-care workers should not return to work until they have been tested and found to be negative for COVID-19. The public might wear masks to avoid infection or to protect others. During the 2009 pandemic of H1N1 influenza (swine flu), encouraging the public to wash their hands reduced the incidence of infection significantly whereas wearing facemasks did not.5 There is no good evidence that facemasks protect the public against infection with respiratory viruses, including COVID-19.6 However, absence of proof of an effect is not the same as proof of absence of an effect. During the pandemics caused by swine flu and by the coronaviruses which caused SARS and MERS, many people in Asia and elsewhere walked around wearing surgical or homemade cotton masks to protect themselves. One danger of doing this is the illusion of protection. Surgical facemasks are designed to be discarded after single use.... | | query: @user If just the US government had some National Institution of Health entity which could’ve been showcasing, studying and verifying this type of advantage from data years earlier .. to apply immediately without political spin |

  passage: title: Chloroquine is a potent inhibitor of SARS coronavirus infection and spread
  abstract: Abstract Background Severe acute respiratory syndrome (SARS) is caused by a newly discovered coronavirus (SARS-CoV). No effective prophylactic or post-exposure therapy is currently available. Results We report, however, that chloroquine has strong antiviral effects on SARS-CoV infection of primate cells. These inhibitory effects are observed when the cells are treated with the drug either before or after exposure to the virus, suggesting both prophylactic and therapeutic advantage. In addition to the well-known functions of chloroquine such as elevations of endosomal pH, the drug appears to interfere with terminal glycosylation of the cellular receptor, angiotensin-converting enzyme 2. This may negatively influence the virus-receptor binding and abrogate the infection, with further ramifications by the elevation of vesicular pH, resulting in the inhibition of infection and spread of SAR...

  | passage: title: A National Medical Response to Crisis — The Legacy of World War II[object Object]abstract: A National Medical Response to Crisis World War II’s massive casualties were mitigated by lives saved as a result of medical care. Many of the advances made would persist long after the war conclud... | | query: UNDENIABLE EVIDENCE OF MY SPIKE PROTEIN TRIGGERED WIDESPREAD AMYLOIDOSES THEORY. IT. IS. OCCURRING. |

  passage: title: Amyloidogenesis of SARS-CoV-2 Spike Protein
  abstract: ABSTRACT SARS-CoV-2 infection is associated with a surprising number of morbidities. Uncanny similarities with amyloid-disease associated blood coagulation and fibrinolytic disturbances together with neurologic and cardiac problems led us to investigate the amyloidogenicity of the SARS-CoV-2 Spike protein (S-protein). Amyloid fibril assays of peptide library mixtures and theoretical predictions identified seven amyloidogenic sequences within the S-protein. All seven peptides in isolation formed aggregates during incubation at 37°C. Three 20-amino acid long synthetic Spike peptides (sequence 191-210, 599-618, 1165-1184) fulfilled three amyloid fibril criteria: nucleation dependent polymerization kinetics by ThT, Congo red positivity and ultrastructural fibrillar morphology. Full-length folded S-protein did not form amyloid fibrils, but amyloid-like fibrils with evident branching were formed during 24 hours of S-protei...

  |

  passage: title: Amyloidogenesis of SARS-CoV-2 Spike Protein
  abstract: SARS-CoV-2 infection is associated with a surprising number of morbidities. Uncanny similarities with amyloid-disease associated blood coagulation and fibrinolytic disturbances together with neurologic and cardiac problems led us to investigate the amyloidogenicity of the SARS-CoV-2 spike protein (S-protein). Amyloid fibril assays of peptide library mixtures and theoretical predictions identified seven amyloidogenic sequences within the S-protein. All seven peptides in isolation formed aggregates during incubation at 37 °C. Three 20-amino acid long synthetic spike peptides (sequence 192–211, 601–620, 1166–1185) fulfilled three amyloid fibril criteria: nucleation dependent polymerization kinetics by ThT, Congo red positivity, and ultrastructural fibrillar morphology. Full-length folded S-protein did not form amyloid fibrils, but amyloid-like fibrils with evident branching were formed during 24 h of S-protein coincubat...

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• Loss: [object Object].TripletMNRLCombinedLoss

Training Hyperparameters

Non-Default Hyperparameters

• per_device_train_batch_size: 48
• per_device_eval_batch_size: 48
• num_train_epochs: 20
• fp16: True
• multi_dataset_batch_sampler: round_robin

All Hyperparameters

Training Logs

Training Time

• Training: 2.2 hours

Framework Versions

• Python: 3.12.6
• Sentence Transformers: 5.4.1
• Transformers: 4.56.0
• PyTorch: 2.8.0+cu129
• Accelerate: 1.10.1
• Datasets: 4.8.5
• Tokenizers: 0.22.0

Citation

BibTeX

Sentence Transformers