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---
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tags:
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- sentence-transformers
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- sentence-similarity
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- feature-extraction
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- generated_from_trainer
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- dataset_size:900
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- loss:MultipleNegativesRankingLoss
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base_model: sentence-transformers/all-MiniLM-L6-v2
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widget:
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- source_sentence: 'Which of the following statements accurately describes the relationship
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between gene compaction and locus volume in genomic loci?
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A) Increased locus volume correlates with higher gene compaction.
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B) A high level of compaction is associated with a high volume of the genomic
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locus.
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C) Gene compaction is directly proportional to locus volume.
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D) Loci with low volume exhibit high levels of compaction.
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**Correct Answer: D) Loci with low volume exhibit high levels of compaction.**'
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sentences:
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- 'The QoS negotiation is supported by the PRACK request, that starts resource reservation
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in the calling party network, and it is answered by a 2XX response code. Once
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this response has been sent, the called party has selected the codec too, and
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starts resource reservation on its side. Subsequent UPDATE requests are sent to
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inform about the reservation progress, and they are answered by 2XX response codes.
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In a typical offer/answer exchange, one UPDATE will be sent by the calling party
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when its reservation is completed, then the called party will respond and eventually
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finish allocating the resources. It is then, when all the resources for the call
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are in place, when the caller is alerted.
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If the individual has undergone stenting, an anticoagulant will be a necessity
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to prevent build-up around the stent(s), as the body will perceive the foreign
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body as a wound and attempt to heal it. Some patients who had alternate corrective
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surgery, such as the Mustard or Senning procedure, may have issues with SA and
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VA nodal transmissions in later life. Typical symptoms include palpitations and
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problems with low heart rates. This is commonly solved with a Pacemaker unit,
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providing scar tissue from the original operation does not block its functionality.
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More recently, ACE inhibitors have been prescribed to patients in the hope of
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relieving stress on the heart.
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Using this method which results in a relatively high control of size and shape,
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semiconductor nanostructures could be synthesized in the form of dots, tubes,
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wires and other forms which show interesting optic and electronic size-dependent
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properties. Since the synergistic properties resulting from the intimate contact
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and interaction between the core and shell, CSSNCs can provide novel functions
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and enhanced properties which are not observed in single nanoparticles.The size
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of core materials and the thickness of shell can be controlled during synthesis.
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For example, in the synthesis of CdSe core nanocrystals, the volume of H2S gas
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can determine the size of core nanocrystals.'
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- 'In mathematics, the Chang number of an irreducible representation of a simple
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complex Lie algebra is its dimension modulo 1 + h, where h is the Coxeter number.
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Chang numbers are named after Chang (1982), who rediscovered an element of order
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h + 1 found by Kac (1981). Kac (1981) showed that there is a unique class of regular
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elements σ of order h + 1, in the complex points of the corresponding Chevalley
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group. He showed that the trace of σ on an irreducible representation is −1, 0,
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or +1, and if h + 1 is prime then the trace is congruent to the dimension mod
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h+1. This implies that the dimension of an irreducible representation is always
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−1, 0, or +1 mod h + 1 whenever h + 1 is prime.
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Mosquito bite allergies are informally classified as 1) the skeeter syndrome,
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i.e., severe local skin reactions sometimes associated with low-grade fever; 2)
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systemic reactions that range from high-grade fever, lymphadenopathy, abdominal
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pain, and/or diarrhea to, very rarely, life-threatening symptoms of anaphylaxis;
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and 3) severe and often systemic reactions occurring in individuals that have
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an Epstein-Barr virus-associated lymphoproliferative disease, Epstein-Barr virus-negative
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lymphoid malignancy, or another predisposing condition such as eosinophilic cellulitis
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or chronic lymphocytic leukemia. The term papular urticaria is commonly used for
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a reaction to mosquito bites that is dominated by widely spread hives.'
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- 'All LIRR bilevel passenger rail cars have two wide quarter-point doors on each
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side, for high level platforms only. The bilevel cars used by NJ Transit and Exo
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have four doors on each side, two quarter-point doors at high level platform height
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and one at each end vestibule, with traps used to reach low level platforms. The
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bilevel cars used by MBTA have side doors with traps at each end vestibule.
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For 128 bits of security and the smallest signature size in a Rainbow multivariate
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quadratic equation signature scheme, Petzoldt, Bulygin and Buchmann, recommend
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using equations in F 31 {\displaystyle \mathbb {F} _{31}} with a public key size
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of just over 991,000 bits, a private key of just over 740,000 bits and digital
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signatures which are 424 bits in length.
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A 2020 study identified a habitat-specific and relatively abundant core microbiome
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in the manuka phyllosphere, which was persistent across all samples. In contrast,
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non-core phyllosphere microorganisms exhibited significant variation across individual
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host trees and populations that was strongly driven by environmental and spatial
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factors. The results demonstrated the existence of a dominant and ubiquitous core
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microbiome in the phyllosphere of manuka.
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It seems that weak polarizations are ordinarily unable to form a component of
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a vector soliton. However, due to the cross-polarization modulation between strong
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and weak polarization components, a "weak soliton" could also be formed. It thus
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demonstrates that the soliton obtained is not a "scalar" soliton with a linear
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polarization mode, but rather a vector soliton with a large ellipticity.
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The GAMtools command gamtools compaction can be used to calculate an estimation
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of chromatin compaction. Compaction is a value assigned to a gene that represents
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how large the gene is. The level of compaction is inversely proportional to the
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locus volume. Genomic loci with a low volume are said to have a high level of
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compaction, and loci with a high volume have a low level of compaction.'
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- source_sentence: "What condition must be satisfied for the observation of Landau\
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\ levels in a system?\n\nA) The mean thermal energy must be greater than the energy\
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\ level separation, kT > ħωc. \nB) The mean thermal energy must be equal to the\
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\ energy level separation, kT = ħωc. \nC) The mean thermal energy must be smaller\
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\ than the energy level separation, kT ≪ ħωc. \nD) The mean thermal energy must\
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\ be independent of the energy level separation, kT ≠ ħωc. \n\n**Correct Answer:\
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\ C) The mean thermal energy must be smaller than the energy level separation,\
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\ kT ≪ ħωc.**"
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sentences:
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- 'The effects of Landau levels may only be observed when the mean thermal energy
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kT is smaller than the energy level separation, kT ≪ ħωc, meaning low temperatures
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and strong magnetic fields. Each Landau level is degenerate because of the second
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quantum number ky, which can take the values where N is an integer. The allowed
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values of N are further restricted by the condition that the center of force of
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the oscillator, x0, must physically lie within the system, 0 ≤ x0 < Lx. This gives
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the following range for N, For particles with charge q = Ze, the upper bound on
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N can be simply written as a ratio of fluxes, where Φ0 = h/e is the fundamental
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magnetic flux quantum and Φ = BA is the flux through the system (with area A =
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LxLy).
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The study of X-ray astronomy continued to be carried out using data from a host
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of satellites that were active from the 1980s to the early 2000s: the HEAO Program,
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EXOSAT, Ginga, RXTE, ROSAT, ASCA, as well as BeppoSAX, which detected the first
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afterglow of a gamma-ray burst (GRB). Data from these satellites continues to
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aid our further understanding of the nature of these sources and the mechanisms
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by which the X-rays and gamma rays are emitted. Understanding these mechanisms
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can in turn shed light on the fundamental physics of our universe. By looking
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at the sky with X-ray and gamma-ray instruments, we collect important information
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in our attempt to address questions such as how the universe began and how it
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evolves, and gain some insight into its eventual fate.'
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- 'In a centrosymmetric ligand field, such as in octahedral complexes of transition
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metals, the arrangement of electrons in the d-orbital is not only limited by electron
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repulsion energy, but it is also related to the splitting of the orbitals due
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to the ligand field. This leads to many more electron configuration states than
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is the case for the free ion. The relative energy of the repulsion energy and
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splitting energy defines the high-spin and low-spin states. Considering both weak
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and strong ligand fields, a Tanabe–Sugano diagram shows the energy splitting of
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the spectral terms with the increase of the ligand field strength.
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In nature, limonene is formed from geranyl pyrophosphate, via cyclization of a
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neryl carbocation or its equivalent as shown. The final step involves loss of
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a proton from the cation to form the alkene. The most widely practiced conversion
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of limonene is to carvone. The three-step reaction begins with the regioselective
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addition of nitrosyl chloride across the trisubstituted double bond. This species
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is then converted to the oxime with a base, and the hydroxylamine is removed to
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give the ketone-containing carvone.
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{\displaystyle x_{1}y_{1},\,x_{1}y_{2},\,x_{2}y_{1},\,x_{2}y_{2},\,x_{1}/x_{2}.}
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All the above conjectures and theorems are consequences of the unproven extension
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of Baker''s theorem, that logarithms of algebraic numbers that are linearly independent
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over the rational numbers are automatically algebraically independent too. The
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diagram on the right shows the logical implications between all these results.'
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- 'Over 50% of the languages tracked have 100% UTF-8 use. Many standards only support
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UTF-8, e.g. JSON exchange requires it (without a byte order mark (BOM)). UTF-8
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is also the recommendation from the WHATWG for HTML and DOM specifications, and
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stating "UTF-8 encoding is the most appropriate encoding for interchange of Unicode"
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and the Internet Mail Consortium recommends that all e‑mail programs be able to
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display and create mail using UTF-8.
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The radiant temperature is related to the amount of radiant heat transferred from
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a surface, and it depends on the material''s ability to absorb or emit heat, or
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its emissivity. The mean radiant temperature depends on the temperatures and emissivities
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of the surrounding surfaces as well as the view factor, or the amount of the surface
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that is “seen” by the object. So the mean radiant temperature experienced by a
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person in a room with the sunlight streaming in varies based on how much of their
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body is in the sun.
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In the American Saddlebred show ring, the gait is performed with speed and action,
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appearing unrestrained, while the slow gait is expected be performed with restraint
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and precision. The rack is also closely associated with the Racking Horse breed.The
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rack, like other intermediate gaits, is smoother than the trot because the hooves
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hitting the ground individually rather than in pairs minimizes the force and bounce
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the horse transmits to the rider. To achieve this gait the horse must be in a
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"hollow position".
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Ultrasensitivity can be achieved through several mechanisms: Multistep mechanisms
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(examples: cooperativity) and multisite phosphorylation Buffering mechanisms (examples:
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decoy phosphorylation sites) or stoichiometric inhibitors Changes in localisation
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(such as translocation across the nuclear envelope) Saturation mechanisms (also
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known as zero-order ultrasensitivity) Positive feedback Allovalency Non-Zero-Order
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Ultrasensitivity in Membrane Proteins Dissipative Allostery'
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- source_sentence: "What is the primary significance of the process described in the\
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\ reduction of sulfate to sulfide in relation to sulfur isotopes?\n\nA) It indicates\
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\ that sulfate-reducing microorganisms can thrive in high-temperature environments.\
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\ \nB) It demonstrates how sulfur disproportionation can lead to the enrichment\
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\ of seawater sulfate. \nC) It provides evidence for the historical burial of\
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\ reduced sulfur in the Earth's crust. \nD) It explains the mechanisms by which\
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\ sulfate is converted to organic matter in marine environments. \n\n**Correct\
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\ Answer: C) It provides evidence for the historical burial of reduced sulfur\
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\ in the Earth's crust.**"
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sentences:
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- 'Scoring. Score each element from left to right, top to bottom in the matrix,
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considering the outcomes of substitutions (diagonal scores) or adding gaps (horizontal
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and vertical scores).
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This set of ionic and electrical functional alterations thus generates the fields
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of electromagnetic potentials or electromagnetic dipoles. These can be defined
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also as single equivalent dipoles. == References ==
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A double pendulum is a simple pendulum hanging under another one; the epitome
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of the compound pendulum system. It shows abundant dynamic behavior. The motion
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of a double pendulum seems chaotic.
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This is a fully journaled, distributed file system used by Isilon. OneFS uses
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FlexProtect and Reed–Solomon encodings to support up to four simultaneous disk
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failures.
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Subclassing of Class is disallowed. Following the standard definition of metaclasses
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we can conclude that Class and Struct are the only metaclasses in Ruby.
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Nile University - master''s The American University in Cairo - master''s Zewail
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City of Science and Technology - B.Sc Cairo University - Faculty of Engineering
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- Masters of Science
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In mechanical engineering, the cylinders of reciprocating engines are often classified
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by whether they are single- or double-acting, depending on how the working fluid
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acts on the piston.
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A clock constraint defines a set of valuations. Two kinds of such sets are considered
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in the literature. A zone is a non-empty set of valuations satisfying a clock
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constraint.
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This might sound paradoxical but becomes clear when one takes into account that
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POC increases during the period of PI. In summary, all these findings are consistent
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with POC-theory.
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Austria has only daylight QRA readiness. Austrian Air Force Air Surveillance Command
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is located at Salzburg. Fighter Squadron 1 & 2 with Eurofighter Typhoon are at
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Zeltweg Air Base.
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Data for 126,251 water points across 37 countries that are being monitored with
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Akvo FLOW in 2015 show that 20% are not functional, and 10% are functional but
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have problems.
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If conditions are not corrected, the cycle will usually repeat. This is called
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surge. Depending on the engine this can be highly damaging to the engine and creates
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worrying vibrations for the crew.'
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- 'In the Liber Abaci, Fibonacci says the following introducing the affirmative
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Modus Indorum (the method of the Indians), today known as Hindu–Arabic numeral
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system or base-10 positional notation. It also introduced digits that greatly
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resembled the modern Arabic numerals. As my father was a public official away
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from our homeland in the Bugia customshouse established for the Pisan merchants
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who frequently gathered there, he had me in my youth brought to him, looking to
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find for me a useful and comfortable future; there he wanted me to be in the study
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of mathematics and to be taught for some days. There from a marvelous instruction
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in the art of the nine Indian figures, the introduction and knowledge of the art
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pleased me so much above all else, and I learnt from them, whoever was learned
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in it, from nearby Egypt, Syria, Greece, Sicily and Provence, and their various
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methods, to which locations of business I travelled considerably afterwards for
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much study, and I learnt from the assembled disputations.
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This is because sulfate''s reduction to sulfide is typically accompanied by a
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negative isotope effect, which (depending on the sulfate-reducing microorganism''s
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enzymatic machinery, temperature, and other factors) can be tens of per mille.
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This effect can be compounded through sulfur disproportionation, a process by
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which some microbes reduce sulfate to sulfides and thiosulfate, both of which
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can be 34S-depleted by tens of per mille relative to the starting sulfate pool.
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Depleted sulfides and thiosulfate can then be repeatedly oxidized and reduced
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again, until the final, total sulfide pool that is measured has δ34S values of
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-70 or -80‰. The formation of a "lighter" S-isotope pool leaves behind an enriched
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pool, and so the enrichment of seawater sulfate is taken as evidence that some
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large amount of reduced sulfur (in the form, perhaps, of metal-sulfide minerals)
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was buried and incorporated into the crust.'
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- 'In clinical trials SPINA-GT was significantly elevated in patients with Graves''
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disease and toxic adenoma compared to normal subjects. It is also elevated in
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diffuse and nodular goiters, and reduced in untreated autoimmune thyroiditis.
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In patients with toxic adenoma it has higher specificity and positive likelihood
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ratio for diagnosis of thyrotoxicosis than serum concentrations of thyrotropin,
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free T4 or free T3. GT''s specificity is also high in thyroid disorders of secondary
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or tertiary origin.Calculating SPINA-GT has proved to be useful in challenging
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clinical situations, e.g. for differential diagnosis of subclinical hypothyroidism
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and elevated TSH concentration due to type 2 allostatic load (as it is typical
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for obesity and certain psychiatric diseases). For this purpose, its usage has
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been recommended in sociomedical assessment.
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Relevant concepts: (geodesic, exponential map, injectivity radius) The exponential
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map exp: TpM → Mis defined as exp(X) = γ(1) where γ: I → M is the unique geodesic
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passing through p at 0 and whose tangent vector at 0 is X. Here I is the maximal
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open interval of R for which the geodesic is defined. Let M be a pseudo-Riemannian
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manifold (or any manifold with an affine connection) and let p be a point in M.
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Then for every V in TpM there exists a unique geodesic γ: I → M for which γ(0)
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= p and γ ˙ ( 0 ) = V . {\displaystyle {\dot {\gamma }}(0)=V.} Let Dp be the subset
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of TpM for which 1 lies in I.'
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- source_sentence: "Which of the following statements accurately describes a characteristic\
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\ of chlorins in organic chemistry?\n\nA) Chlorins are stable compounds that do\
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\ not react with oxygen. \nB) Chlorins are derived from porphyrins through a\
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\ process of complete hydrogenation. \nC) The parent chlorin compound undergoes\
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\ air oxidation to form porphine. \nD) Chlorins do not have any structural similarities\
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\ to chlorophyll. \n\nCorrect Answer: C) The parent chlorin compound undergoes\
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\ air oxidation to form porphine."
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sentences:
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- 'In 2000, Gurtej Singh Sandhu and Trung T. Doan of Micron Technology initiated
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the development of atomic layer deposition high-κ films for DRAM memory devices.
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This helped drive cost-effective implementation of semiconductor memory, starting
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with 90-nm node DRAM. Intel Corporation has reported using ALD to deposit high-κ
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gate dielectric for its 45 nm CMOS technology.ALD has been developed in two independent
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discoveries under names atomic layer epitaxy (ALE, Finland) and molecular layering
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(ML, Soviet Union). To clarify the early history, the Virtual Project on the History
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of ALD (VPHA) has been set up in summer 2013. it resulted in several publications
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reviewing the historical development of ALD under the names ALE and ML.
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During the dry period (late gestation, non-lactating), dairy cattle have relatively
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low calcium requirements, with a need to replace approximately 30 g of calcium
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per day due to utilization for fetal growth and fecal and urinary losses. At parturition,
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the requirement for calcium is greatly increased due to initiation of lactation,
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when mammary drainage of calcium may exceed 50g per day. Due to this large increase
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in demand for calcium, most cows will experience some degree of hypocalcemia for
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a short period following parturition as the metabolism adjusts to the increased
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demand. When the mammary drain of plasma calcium causes hypocalcemia severe enough
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to compromise neuromuscular function, the cow is considered to have clinical milk
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fever.
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In probability theory and statistics, a Gaussian process is a stochastic process
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(a collection of random variables indexed by time or space), such that every finite
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collection of those random variables has a multivariate normal distribution, i.e.
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every finite linear combination of them is normally distributed. The distribution
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of a Gaussian process is the joint distribution of all those (infinitely many)
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random variables, and as such, it is a distribution over functions with a continuous
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domain, e.g. time or space. The concept of Gaussian processes is named after Carl
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Friedrich Gauss because it is based on the notion of the Gaussian distribution
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(normal distribution). Gaussian processes can be seen as an infinite-dimensional
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generalization of multivariate normal distributions.'
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- 'The Tutte polynomial factors into connected components. If G {\displaystyle G}
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is the union of disjoint graphs H {\displaystyle H} and H ′ {\displaystyle H''}
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then T G = T H ⋅ T H ′ {\displaystyle T_{G}=T_{H}\cdot T_{H''}} If G {\displaystyle
|
|
|
G} is planar and G ∗ {\displaystyle G^{*}} denotes its dual graph then T G ( x
|
|
|
, y ) = T G ∗ ( y , x ) {\displaystyle T_{G}(x,y)=T_{G^{*}}(y,x)} Especially,
|
|
|
the chromatic polynomial of a planar graph is the flow polynomial of its dual.
|
|
|
Tutte refers to such functions as V-functions.
|
|
|
|
|
|
If a periodic function is instead represented using the quotient space domain
|
|
|
R / ( P Z ) {\displaystyle \mathbb {R} /(P\mathbb {Z} )} then one can write: φ
|
|
|
P: R / ( P Z ) → R {\displaystyle \varphi _{P}:\mathbb {R} /(P\mathbb {Z} )\to
|
|
|
\mathbb {R} } φ P ( x ) = ∑ τ ∈ x s ( τ ) . {\displaystyle \varphi _{P}(x)=\sum
|
|
|
_{\tau \in x}s(\tau )~.} The arguments of φ P {\displaystyle \varphi _{P}} are
|
|
|
equivalence classes of real numbers that share the same fractional part when divided
|
|
|
by P {\displaystyle P} .'
|
|
|
- 'In mathematics, the Goncharov conjecture is a conjecture introduced by Goncharov
|
|
|
(1995) suggesting that the cohomology of certain motivic complexes coincides with
|
|
|
pieces of K-groups. It extends a conjecture due to Zagier (1991).
|
|
|
|
|
|
The renewal effect is seen when a participant is first conditioned in a context
|
|
|
(context A) and then shows extinction in another context (B). Returning to context
|
|
|
A may renew the conditioned response. This evidence demonstrates that appropriate
|
|
|
responses underlying extinction may be linked to contextual information.
|
|
|
|
|
|
Modern measurement systems are characterized by multi-channeling, synchronicity,
|
|
|
and accuracy. Due to the advanced protocol features of EtherCAT, efficient synchronous
|
|
|
data throughput is assured. The network features based on Ethernet enable a measurement
|
|
|
network with distributed measurement modules.
|
|
|
|
|
|
These rules reverse the conversion described above. They convert from a let expression
|
|
|
to a lambda expression, without altering the structure. Not all let expressions
|
|
|
may be converted using these rules. The rules assume that the expressions are
|
|
|
already arranged as if they had been generated by de-lambda.
|
|
|
|
|
|
In organic chemistry, chlorins are tetrapyrrole pigments that are partially hydrogenated
|
|
|
porphyrins. The parent chlorin is an unstable compound which undergoes air oxidation
|
|
|
to porphine. The name chlorin derives from chlorophyll.
|
|
|
|
|
|
So by the lemma, we have for some partial isometry U, which is unique if Ker(A*)
|
|
|
⊂ Ker(U). Take P to be (A*A)1/2 and one obtains the polar decomposition A = UP.
|
|
|
|
|
|
MISRA C:1998, C:2004, C:2012, C++:2008. Klocwork by Rogue Wave Software (now owned
|
|
|
by Perforce Software). MISRA C:2012, C:2012 Amendment 1, C++:2008.
|
|
|
|
|
|
Transmitters usually have directional devices installed along with the filters
|
|
|
that block any reflected power in the event the antenna malfunctions. The antenna
|
|
|
must have a power rating that will handle the sum of energy of all connected transmitters
|
|
|
at the same time. Transmitter combining systems are lossy.'
|
|
|
- source_sentence: "Which of the following statements accurately describes a key implication\
|
|
|
\ of the parameter μ in population dynamics?\n\nA) If μ equals 1, the population\
|
|
|
\ will certainly grow indefinitely. \nB) If μ is less than 1, the population\
|
|
|
\ will face a high probability of extinction. \nC) If μ is greater than 1, the\
|
|
|
\ population will go extinct with certainty. \nD) If μ is equal to 0, the population\
|
|
|
\ will persist indefinitely.\n\n**Correct Answer: B) If μ is less than 1, the\
|
|
|
\ population will face a high probability of extinction.**"
|
|
|
sentences:
|
|
|
- 'The input is two reduced divisors D 1 = ( u 1 , v 1 ) {\displaystyle D_{1}=(u_{1},v_{1})}
|
|
|
and D 2 = ( u 2 , v 2 ) {\displaystyle D_{2}=(u_{2},v_{2})} in their Mumford representation
|
|
|
of the hyperelliptic curve C: y 2 + h ( x ) y = f ( x ) {\displaystyle C:y^{2}+h(x)y=f(x)}
|
|
|
of genus g {\displaystyle g} over the field K {\displaystyle K} . The algorithm
|
|
|
works as follows Using the extended Euclidean algorithm compute the polynomials
|
|
|
d 1 , e 1 , e 2 ∈ K {\displaystyle d_{1},e_{1},e_{2}\in K} such that d 1 = gcd
|
|
|
( u 1 , u 2 ) {\displaystyle d_{1}=\gcd(u_{1},u_{2})} and d 1 = e 1 u 1 + e 2
|
|
|
u 2 {\displaystyle d_{1}=e_{1}u_{1}+e_{2}u_{2}} . Again with the use of the extended
|
|
|
Euclidean algorithm compute the polynomials d , c 1 , c 2 ∈ K {\displaystyle
|
|
|
d,c_{1},c_{2}\in K} with d = gcd ( d 1 , v 1 + v 2 + h ) {\displaystyle d=\gcd(d_{1},v_{1}+v_{2}+h)}
|
|
|
and d = c 1 d 1 + c 2 ( v 1 + v 2 + h ) {\displaystyle d=c_{1}d_{1}+c_{2}(v_{1}+v_{2}+h)}
|
|
|
.'
|
|
|
- 'Micro-encapsulation allows for metabolism within the membrane, exchange of small
|
|
|
molecules and prevention of passage of large substances across it. The main advantages
|
|
|
of encapsulation include improved mimicry in the body, increased solubility of
|
|
|
the cargo and decreased immune responses. Notably, artificial cells have been
|
|
|
clinically successful in hemoperfusion.
|
|
|
|
|
|
If μ < 1, then the expected number of individuals goes rapidly to zero, which
|
|
|
implies ultimate extinction with probability 1 by Markov''s inequality. Alternatively,
|
|
|
if μ > 1, then the probability of ultimate extinction is less than 1 (but not
|
|
|
necessarily zero; consider a process where each individual either has 0 or 100
|
|
|
children with equal probability.
|
|
|
|
|
|
The decision to tolerate up to 10 μg/liter of “nonrelevant” metabolites in groundwater
|
|
|
and drinking water is politically highly contentious in Europe. Some consider
|
|
|
the higher limit acceptable as no imminent health risk can be proven, whereas
|
|
|
others regard it as a fundamental deviation from the precautionary principle.
|
|
|
== References ==
|
|
|
|
|
|
Informally, dynamical systems describe the time evolution of the phase space of
|
|
|
some mechanical system. Commonly, such evolution is given by some differential
|
|
|
equations, or quite often in terms of discrete time steps. However, in the present
|
|
|
case, instead of focusing on the time evolution of discrete points, one shifts
|
|
|
attention to the time evolution of collections of points.
|
|
|
|
|
|
Commercial Crew Development (CCDev) is a human spaceflight development program
|
|
|
that is funded by the U.S. government and administered by NASA. CCDev will result
|
|
|
in US and international astronauts flying to the International Space Station (ISS)
|
|
|
on privately operated crew vehicles. Operational contracts to fly astronauts were
|
|
|
awarded in September 2014 to SpaceX and Boeing.
|
|
|
|
|
|
To do so, one needs precise disease definitions and a probabilistic analysis of
|
|
|
symptoms and molecular profiles. Physicists have been studying similar problems
|
|
|
for years, utilizing microscopic elements and their interactions to extract macroscopic
|
|
|
states of various physical systems. Physics inspired machine learning approaches
|
|
|
can thus be applied to study disease processes and to perform biomarker analysis.
|
|
|
|
|
|
During the second stage, the light-independent reactions use these products to
|
|
|
capture and reduce carbon dioxide. Most organisms that use oxygenic photosynthesis
|
|
|
use visible light for the light-dependent reactions, although at least three use
|
|
|
shortwave infrared or, more specifically, far-red radiation.Some organisms employ
|
|
|
even more radical variants of photosynthesis.'
|
|
|
- 'Structuring elements are particular cases of binary images, usually being small
|
|
|
and simple. In mathematical morphology, binary images are subsets of a Euclidean
|
|
|
space Rd or the integer grid Zd, for some dimension d. Here are some examples
|
|
|
of widely used structuring elements (denoted by B): Let E=R2; B is an open disk
|
|
|
of radius r, centered at the origin. Let E=Z2; B is a 3x3 square, that is, B={(-1,-1),(-1,0),(-1,1),(0,-1),(0,0),(0,1),(1,-1),(1,0),(1,1)}.
|
|
|
Let E=Z2; B is the "cross" given by: B={(-1,0),(0,-1),(0,0),(0,1),(1,0)}.In the
|
|
|
discrete case, a structuring element can also be represented as a set of pixels
|
|
|
on a grid, assuming the values 1 (if the pixel belongs to the structuring element)
|
|
|
or 0 (otherwise). When used by a hit-or-miss transform, usually the structuring
|
|
|
element is a composite of two disjoint sets (two simple structuring elements),
|
|
|
one associated to the foreground, and one associated to the background of the
|
|
|
image to be probed. In this case, an alternative representation of the composite
|
|
|
structuring element is as a set of pixels which are either set (1, associated
|
|
|
to the foreground), not set (0, associated to the background) or "don''t care".'
|
|
|
pipeline_tag: sentence-similarity
|
|
|
library_name: sentence-transformers
|
|
|
metrics:
|
|
|
- cosine_accuracy@1
|
|
|
- cosine_accuracy@3
|
|
|
- cosine_accuracy@5
|
|
|
- cosine_accuracy@10
|
|
|
- cosine_precision@1
|
|
|
- cosine_precision@3
|
|
|
- cosine_precision@5
|
|
|
- cosine_precision@10
|
|
|
- cosine_recall@1
|
|
|
- cosine_recall@3
|
|
|
- cosine_recall@5
|
|
|
- cosine_recall@10
|
|
|
- cosine_ndcg@10
|
|
|
- cosine_mrr@10
|
|
|
- cosine_map@100
|
|
|
model-index:
|
|
|
- name: SentenceTransformer based on sentence-transformers/all-MiniLM-L6-v2
|
|
|
results:
|
|
|
- task:
|
|
|
type: information-retrieval
|
|
|
name: Information Retrieval
|
|
|
dataset:
|
|
|
name: baseline
|
|
|
type: baseline
|
|
|
metrics:
|
|
|
- type: cosine_accuracy@1
|
|
|
value: 0.68
|
|
|
name: Cosine Accuracy@1
|
|
|
- type: cosine_accuracy@3
|
|
|
value: 0.78
|
|
|
name: Cosine Accuracy@3
|
|
|
- type: cosine_accuracy@5
|
|
|
value: 0.78
|
|
|
name: Cosine Accuracy@5
|
|
|
- type: cosine_accuracy@10
|
|
|
value: 0.8
|
|
|
name: Cosine Accuracy@10
|
|
|
- type: cosine_precision@1
|
|
|
value: 0.68
|
|
|
name: Cosine Precision@1
|
|
|
- type: cosine_precision@3
|
|
|
value: 0.25999999999999995
|
|
|
name: Cosine Precision@3
|
|
|
- type: cosine_precision@5
|
|
|
value: 0.15599999999999994
|
|
|
name: Cosine Precision@5
|
|
|
- type: cosine_precision@10
|
|
|
value: 0.07999999999999999
|
|
|
name: Cosine Precision@10
|
|
|
- type: cosine_recall@1
|
|
|
value: 0.68
|
|
|
name: Cosine Recall@1
|
|
|
- type: cosine_recall@3
|
|
|
value: 0.78
|
|
|
name: Cosine Recall@3
|
|
|
- type: cosine_recall@5
|
|
|
value: 0.78
|
|
|
name: Cosine Recall@5
|
|
|
- type: cosine_recall@10
|
|
|
value: 0.8
|
|
|
name: Cosine Recall@10
|
|
|
- type: cosine_ndcg@10
|
|
|
value: 0.7440207339387845
|
|
|
name: Cosine Ndcg@10
|
|
|
- type: cosine_mrr@10
|
|
|
value: 0.7256944444444444
|
|
|
name: Cosine Mrr@10
|
|
|
- type: cosine_map@100
|
|
|
value: 0.7280566718520438
|
|
|
name: Cosine Map@100
|
|
|
---
|
|
|
|
|
|
# SentenceTransformer based on sentence-transformers/all-MiniLM-L6-v2
|
|
|
|
|
|
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) on the json dataset. It maps sentences & paragraphs to a 384-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:** [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) <!-- at revision c9745ed1d9f207416be6d2e6f8de32d1f16199bf -->
|
|
|
- **Maximum Sequence Length:** 256 tokens
|
|
|
- **Output Dimensionality:** 384 dimensions
|
|
|
- **Similarity Function:** Cosine Similarity
|
|
|
- **Training Dataset:**
|
|
|
- json
|
|
|
<!-- - **Language:** Unknown -->
|
|
|
<!-- - **License:** Unknown -->
|
|
|
|
|
|
### 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
|
|
|
|
|
|
```
|
|
|
SentenceTransformer(
|
|
|
(0): Transformer({'max_seq_length': 256, 'do_lower_case': False}) with Transformer model: BertModel
|
|
|
(1): Pooling({'word_embedding_dimension': 384, '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("amene-gafsi/minilm-finetuned-embedding")
|
|
|
# Run inference
|
|
|
sentences = [
|
|
|
'Which of the following statements accurately describes a key implication of the parameter μ in population dynamics?\n\nA) If μ equals 1, the population will certainly grow indefinitely. \nB) If μ is less than 1, the population will face a high probability of extinction. \nC) If μ is greater than 1, the population will go extinct with certainty. \nD) If μ is equal to 0, the population will persist indefinitely.\n\n**Correct Answer: B) If μ is less than 1, the population will face a high probability of extinction.**',
|
|
|
"Micro-encapsulation allows for metabolism within the membrane, exchange of small molecules and prevention of passage of large substances across it. The main advantages of encapsulation include improved mimicry in the body, increased solubility of the cargo and decreased immune responses. Notably, artificial cells have been clinically successful in hemoperfusion.\nIf μ < 1, then the expected number of individuals goes rapidly to zero, which implies ultimate extinction with probability 1 by Markov's inequality. Alternatively, if μ > 1, then the probability of ultimate extinction is less than 1 (but not necessarily zero; consider a process where each individual either has 0 or 100 children with equal probability.\nThe decision to tolerate up to 10 μg/liter of “nonrelevant” metabolites in groundwater and drinking water is politically highly contentious in Europe. Some consider the higher limit acceptable as no imminent health risk can be proven, whereas others regard it as a fundamental deviation from the precautionary principle. == References ==\nInformally, dynamical systems describe the time evolution of the phase space of some mechanical system. Commonly, such evolution is given by some differential equations, or quite often in terms of discrete time steps. However, in the present case, instead of focusing on the time evolution of discrete points, one shifts attention to the time evolution of collections of points.\nCommercial Crew Development (CCDev) is a human spaceflight development program that is funded by the U.S. government and administered by NASA. CCDev will result in US and international astronauts flying to the International Space Station (ISS) on privately operated crew vehicles. Operational contracts to fly astronauts were awarded in September 2014 to SpaceX and Boeing.\nTo do so, one needs precise disease definitions and a probabilistic analysis of symptoms and molecular profiles. Physicists have been studying similar problems for years, utilizing microscopic elements and their interactions to extract macroscopic states of various physical systems. Physics inspired machine learning approaches can thus be applied to study disease processes and to perform biomarker analysis.\nDuring the second stage, the light-independent reactions use these products to capture and reduce carbon dioxide. Most organisms that use oxygenic photosynthesis use visible light for the light-dependent reactions, although at least three use shortwave infrared or, more specifically, far-red radiation.Some organisms employ even more radical variants of photosynthesis.",
|
|
|
'Structuring elements are particular cases of binary images, usually being small and simple. In mathematical morphology, binary images are subsets of a Euclidean space Rd or the integer grid Zd, for some dimension d. Here are some examples of widely used structuring elements (denoted by B): Let E=R2; B is an open disk of radius r, centered at the origin. Let E=Z2; B is a 3x3 square, that is, B={(-1,-1),(-1,0),(-1,1),(0,-1),(0,0),(0,1),(1,-1),(1,0),(1,1)}. Let E=Z2; B is the "cross" given by: B={(-1,0),(0,-1),(0,0),(0,1),(1,0)}.In the discrete case, a structuring element can also be represented as a set of pixels on a grid, assuming the values 1 (if the pixel belongs to the structuring element) or 0 (otherwise). When used by a hit-or-miss transform, usually the structuring element is a composite of two disjoint sets (two simple structuring elements), one associated to the foreground, and one associated to the background of the image to be probed. In this case, an alternative representation of the composite structuring element is as a set of pixels which are either set (1, associated to the foreground), not set (0, associated to the background) or "don\'t care".',
|
|
|
]
|
|
|
embeddings = model.encode(sentences)
|
|
|
print(embeddings.shape)
|
|
|
# [3, 384]
|
|
|
|
|
|
# Get the similarity scores for the embeddings
|
|
|
similarities = model.similarity(embeddings, embeddings)
|
|
|
print(similarities.shape)
|
|
|
# [3, 3]
|
|
|
```
|
|
|
|
|
|
<!--
|
|
|
### Direct Usage (Transformers)
|
|
|
|
|
|
<details><summary>Click to see the direct usage in Transformers</summary>
|
|
|
|
|
|
</details>
|
|
|
-->
|
|
|
|
|
|
<!--
|
|
|
### Downstream Usage (Sentence Transformers)
|
|
|
|
|
|
You can finetune this model on your own dataset.
|
|
|
|
|
|
<details><summary>Click to expand</summary>
|
|
|
|
|
|
</details>
|
|
|
-->
|
|
|
|
|
|
<!--
|
|
|
### Out-of-Scope Use
|
|
|
|
|
|
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
|
|
|
-->
|
|
|
|
|
|
## Evaluation
|
|
|
|
|
|
### Metrics
|
|
|
|
|
|
#### Information Retrieval
|
|
|
|
|
|
* Dataset: `baseline`
|
|
|
* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
|
|
|
|
|
|
| Metric | Value |
|
|
|
|:--------------------|:----------|
|
|
|
| cosine_accuracy@1 | 0.68 |
|
|
|
| cosine_accuracy@3 | 0.78 |
|
|
|
| cosine_accuracy@5 | 0.78 |
|
|
|
| cosine_accuracy@10 | 0.8 |
|
|
|
| cosine_precision@1 | 0.68 |
|
|
|
| cosine_precision@3 | 0.26 |
|
|
|
| cosine_precision@5 | 0.156 |
|
|
|
| cosine_precision@10 | 0.08 |
|
|
|
| cosine_recall@1 | 0.68 |
|
|
|
| cosine_recall@3 | 0.78 |
|
|
|
| cosine_recall@5 | 0.78 |
|
|
|
| cosine_recall@10 | 0.8 |
|
|
|
| **cosine_ndcg@10** | **0.744** |
|
|
|
| cosine_mrr@10 | 0.7257 |
|
|
|
| cosine_map@100 | 0.7281 |
|
|
|
|
|
|
<!--
|
|
|
## Bias, Risks and Limitations
|
|
|
|
|
|
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
|
|
|
-->
|
|
|
|
|
|
<!--
|
|
|
### Recommendations
|
|
|
|
|
|
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
|
|
|
-->
|
|
|
|
|
|
## Training Details
|
|
|
|
|
|
### Training Dataset
|
|
|
|
|
|
#### json
|
|
|
|
|
|
* Dataset: json
|
|
|
* Size: 900 training samples
|
|
|
* Columns: <code>anchor</code> and <code>positive</code>
|
|
|
* Approximate statistics based on the first 900 samples:
|
|
|
| | anchor | positive |
|
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| type | string | string |
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| details | <ul><li>min: 41 tokens</li><li>mean: 138.75 tokens</li><li>max: 256 tokens</li></ul> | <ul><li>min: 256 tokens</li><li>mean: 256.0 tokens</li><li>max: 256 tokens</li></ul> |
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* Samples:
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| anchor | positive |
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|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| <code>Which of the following milestones in tin smelting occurred in 1978?<br><br>A) The installation of a five tonne plant for recovering tin from slag at Associated Tin Smelters <br>B) The construction of a four tonne per hour tin matte fuming pilot plant at the Kalgoorlie Nickel Smelter <br>C) The first sulfidic smelting test work in collaboration with Aberfoyle Limited <br>D) The completion of the Port Kembla converter slag treatment trials <br><br>Correct Answer: A) The installation of a five tonne plant for recovering tin from slag at Associated Tin Smelters</code> | <code>The work then proceeded to smelting tin concentrates (1975) and then sulfidic tin concentrates (1977).MIM and ER&S jointly funded the 1975 Port Kembla converter slag treatment trials and MIM’s involvement continued with the slag treatment work in Townsville and Mount Isa.In parallel with the copper slag treatment work, the CSIRO was continuing to work in tin smelting. Projects included a five tonne ("t") plant for recovering tin from slag being installed at Associated Tin Smelters in 1978, and the first sulfidic smelting test work being done in collaboration with Aberfoyle Limited, in which tin was fumed from pyritic tin ore and from mixed tin and copper concentrates. Aberfoyle was investigating the possibility of using the Sirosmelt lance approach to improve the recovery of tin from complex ores, such as its mine at Cleveland, Tasmania, and the Queen Hill ore zone near Zeehan in Tasmania.The Aberfoyle work led to the construction and operation in late 1980 of a four t/h tin matte fumi...</code> |
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| <code>Which of the following conditions is necessary for the application of Theorem GF3 in the context of the product defined recursively by \( f_n(z) = z(1 + g_n(z)) \)?<br><br>A) \( |z g_n(z)| \leq C \beta_n \) and \( \sum_{k=1}^{\infty} \beta_k < \infty \) <br>B) \( |z g_n(z)| \geq C \beta_n \) and \( \sum_{k=1}^{\infty} \beta_k < \infty \) <br>C) \( |z g_n(z)| \leq C \beta_n \) and \( \sum_{k=1}^{\infty} \beta_k = \infty \) <br>D) \( |z g_n(z)| \geq C \beta_n \) and \( \sum_{k=1}^{\infty} \beta_k = \infty \) <br><br>Correct Answer: A) \( |z g_n(z)| \leq C \beta_n \) and \( \sum_{k=1}^{\infty} \beta_k < \infty \)</code> | <code>The product defined recursively by f n ( z ) = z ( 1 + g n ( z ) ) , | z | ⩽ M , {\displaystyle f_{n}(z)=z(1+g_{n}(z)),\qquad |z|\leqslant M,} has the appearance G n ( z ) = z ∏ k = 1 n ( 1 + g k ( G k − 1 ( z ) ) ) . {\displaystyle G_{n}(z)=z\prod _{k=1}^{n}\left(1+g_{k}\left(G_{k-1}(z)\right)\right).} In order to apply Theorem GF3 it is required that: | z g n ( z ) | ≤ C β n , ∑ k = 1 ∞ β k < ∞ . {\displaystyle \left|zg_{n}(z)\right|\leq C\beta _{n},\qquad \sum _{k=1}^{\infty }\beta _{k}<\infty .}</code> |
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| <code>Which of the following statements correctly describes the relationship between axonometry and axonometric projection?<br><br>A) Axonometry and axonometric projection refer to the same concept in parallel projection techniques.<br><br>B) Axonometric projection is a broader term that includes all types of axonometric representations.<br><br>C) Axonometry is a technique used to measure along axes, while axonometric projection refers specifically to a type of pictorial representation.<br><br>D) Axonometric projection relies solely on orthographic images where rays are perpendicular to the image plane.<br><br>**Correct Answer: C) Axonometry is a technique used to measure along axes, while axonometric projection refers specifically to a type of pictorial representation.**</code> | <code>Images drawn in parallel projection rely upon the technique of axonometry ("to measure along axes"), as described in Pohlke's theorem. In general, the resulting image is oblique (the rays are not perpendicular to the image plane); but in special cases the result is orthographic (the rays are perpendicular to the image plane). Axonometry should not be confused with axonometric projection, as in English literature the latter usually refers only to a specific class of pictorials (see below).<br>This is the case if and only if the unit vector bases of ℓ M {\displaystyle \ell _{M}} and ℓ N {\displaystyle \ell _{N}} are equivalent. ℓ M {\displaystyle \ell _{M}} can be isomorphic to ℓ N {\displaystyle \ell _{N}} without their unit vector bases being equivalent. (See the example below of an Orlicz sequence space with two nonequivalent symmetric bases.)<br>The main involution is the map that "flips" the generators: α ( Γ a ) = i 2 Γ a {\displaystyle \alpha (\Gamma _{a})=i^{2}\Gamma _{a}} but leaves i...</code> |
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* Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
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```json
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{
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"scale": 20.0,
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"similarity_fct": "cos_sim"
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}
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```
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### Training Hyperparameters
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#### Non-Default Hyperparameters
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- `eval_strategy`: epoch
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- `per_device_train_batch_size`: 32
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- `gradient_accumulation_steps`: 8
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- `learning_rate`: 1e-06
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- `num_train_epochs`: 4
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- `lr_scheduler_type`: cosine
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- `warmup_ratio`: 0.1
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- `bf16`: True
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- `tf32`: True
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- `load_best_model_at_end`: True
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- `optim`: adamw_torch_fused
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- `batch_sampler`: no_duplicates
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#### All Hyperparameters
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<details><summary>Click to expand</summary>
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- `overwrite_output_dir`: False
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- `do_predict`: False
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- `eval_strategy`: epoch
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- `prediction_loss_only`: True
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- `per_device_train_batch_size`: 32
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- `per_device_eval_batch_size`: 8
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- `per_gpu_train_batch_size`: None
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- `per_gpu_eval_batch_size`: None
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- `gradient_accumulation_steps`: 8
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- `eval_accumulation_steps`: None
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- `torch_empty_cache_steps`: None
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- `learning_rate`: 1e-06
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- `weight_decay`: 0.0
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- `adam_beta1`: 0.9
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- `adam_beta2`: 0.999
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- `adam_epsilon`: 1e-08
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- `max_grad_norm`: 1.0
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- `num_train_epochs`: 4
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- `max_steps`: -1
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- `lr_scheduler_type`: cosine
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- `lr_scheduler_kwargs`: {}
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- `warmup_ratio`: 0.1
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- `warmup_steps`: 0
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- `log_level`: passive
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- `log_level_replica`: warning
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- `log_on_each_node`: True
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- `logging_nan_inf_filter`: True
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- `save_safetensors`: True
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- `save_on_each_node`: False
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- `save_only_model`: False
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- `restore_callback_states_from_checkpoint`: False
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- `no_cuda`: False
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- `use_cpu`: False
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- `use_mps_device`: False
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- `seed`: 42
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- `data_seed`: None
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- `jit_mode_eval`: False
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- `use_ipex`: False
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- `bf16`: True
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- `fp16`: False
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- `fp16_opt_level`: O1
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- `half_precision_backend`: auto
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- `bf16_full_eval`: False
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- `fp16_full_eval`: False
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- `tf32`: True
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- `local_rank`: 0
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- `ddp_backend`: None
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- `tpu_num_cores`: None
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- `tpu_metrics_debug`: False
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- `debug`: []
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- `dataloader_drop_last`: False
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- `dataloader_num_workers`: 0
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- `dataloader_prefetch_factor`: None
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- `past_index`: -1
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- `disable_tqdm`: False
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- `remove_unused_columns`: True
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- `label_names`: None
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- `load_best_model_at_end`: True
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- `ignore_data_skip`: False
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- `fsdp`: []
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- `fsdp_min_num_params`: 0
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- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
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- `tp_size`: 0
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- `fsdp_transformer_layer_cls_to_wrap`: None
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- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
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- `deepspeed`: None
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- `label_smoothing_factor`: 0.0
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- `optim`: adamw_torch_fused
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- `optim_args`: None
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- `adafactor`: False
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- `group_by_length`: False
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- `length_column_name`: length
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- `ddp_find_unused_parameters`: None
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- `ddp_bucket_cap_mb`: None
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- `ddp_broadcast_buffers`: False
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- `dataloader_pin_memory`: True
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- `dataloader_persistent_workers`: False
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- `skip_memory_metrics`: True
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- `use_legacy_prediction_loop`: False
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- `push_to_hub`: False
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- `resume_from_checkpoint`: None
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- `hub_model_id`: None
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- `hub_strategy`: every_save
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- `hub_private_repo`: None
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- `hub_always_push`: False
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- `gradient_checkpointing`: False
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- `gradient_checkpointing_kwargs`: None
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- `include_inputs_for_metrics`: False
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- `include_for_metrics`: []
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- `eval_do_concat_batches`: True
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- `fp16_backend`: auto
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- `push_to_hub_model_id`: None
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- `push_to_hub_organization`: None
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- `mp_parameters`:
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- `auto_find_batch_size`: False
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- `full_determinism`: False
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- `torchdynamo`: None
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- `ray_scope`: last
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- `ddp_timeout`: 1800
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- `torch_compile`: False
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- `torch_compile_backend`: None
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- `torch_compile_mode`: None
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- `include_tokens_per_second`: False
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- `include_num_input_tokens_seen`: False
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- `neftune_noise_alpha`: None
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- `optim_target_modules`: None
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- `batch_eval_metrics`: False
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- `eval_on_start`: False
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- `use_liger_kernel`: False
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- `eval_use_gather_object`: False
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- `average_tokens_across_devices`: False
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- `prompts`: None
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- `batch_sampler`: no_duplicates
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- `multi_dataset_batch_sampler`: proportional
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</details>
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### Training Logs
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| Epoch | Step | Training Loss | baseline_cosine_ndcg@10 |
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|:----------:|:------:|:-------------:|:-----------------------:|
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| -1 | -1 | - | 0.7290 |
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| 0.8276 | 3 | - | 0.7365 |
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| 1.8276 | 6 | - | 0.7427 |
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| 2.8276 | 9 | - | 0.7420 |
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| 3.2759 | 10 | 7.0507 | - |
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| **3.8276** | **12** | **-** | **0.744** |
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* The bold row denotes the saved checkpoint.
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### Framework Versions
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- Python: 3.12.8
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- Sentence Transformers: 4.1.0
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- Transformers: 4.51.3
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- PyTorch: 2.7.0+cu126
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- Accelerate: 1.3.0
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- Datasets: 3.2.0
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- Tokenizers: 0.21.0
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## Citation
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### BibTeX
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#### Sentence Transformers
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```bibtex
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@inproceedings{reimers-2019-sentence-bert,
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title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
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author = "Reimers, Nils and Gurevych, Iryna",
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booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
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month = "11",
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year = "2019",
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publisher = "Association for Computational Linguistics",
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url = "https://arxiv.org/abs/1908.10084",
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}
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```
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#### MultipleNegativesRankingLoss
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```bibtex
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@misc{henderson2017efficient,
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title={Efficient Natural Language Response Suggestion for Smart Reply},
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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},
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year={2017},
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eprint={1705.00652},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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*Clearly define terms in order to be accessible across audiences.*
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