sentence-transformers safetensors bert sentence-similarity feature-extraction generated_from_trainer dataset_size:43494 loss:TripletLoss arxiv:1908.10084 arxiv:1703.07737 base_model:allenai/specter2_aug2023refresh_base base_model:finetune:allenai/specter2_aug2023refresh_base model-index autotrain_compatible text-embeddings-inference endpoints_compatible region:us
---
base_model: allenai/specter2_aug2023refresh_base
library_name: sentence-transformers
metrics:
- cosine_accuracy
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:43494
- loss:TripletLoss
widget:
- source_sentence: As a result of technological progress, environmental aspects and
    social change, the automotive industry is undergoing a radical transformation.
    The focus is no longer on the product "vehicle" but much more on the mobility
    service itself and the users individual experience and well-being during travel
    time. In that field of innovation, the study deals with a explorative investigation
    of using the travel time for a improvement of the mental health of the passenger.
    The vision is to integrate breathwork relaxation in combination with a human centric
    lighting scenario as an immersive service within luxury ride-hailing vehicles
    to enhance the mental health during automated rides and utilizing the time spent
    in cars for personal pleasure. To enable a user-centered and experimental approach,
    a test vehicle from the non-profit company bq.Labs was equipped with the bq breath
    work app and a spezialized LED-based lighting screen that was developed by Fraunhofer.
    The effects were tested on randomly selected and voluntary users in a guerrilla
    testing at three different locations in San Diego. The tests explored user acceptance
    of the innovative technologies by combining surveys, vital data collection, qualitative
    interviews and observations. Initial data analysis provides insights into the
    feasibility and potential effects on well-being and user perception. The study
    illustrates those innovations in the field of mobility, involve systemic dependencies
    and considerations beyond technology, encompassing social and psychological dimensions.
    It underscores that successful innovations require a holistic, user-centered approach
    that considers technological, social, and psychological dimensions. The findings
    lay the groundwork for future research and development of innovation strategies
    in the evolving field of mobility and personalized strength.
  sentences:
  - 'We examined casual decision-making among a group of participants, which frequently
    occurs in daily life. In such a situation, participants do not have strong preferences
    for the decision. In addition, because the process of decision-making among people
    is part of the time they spend together, it is important to feel enjoyment in
    the process and satisfaction with the final decision. In this paper, we propose
    a game mechanism for generating a sense of enjoyment in the decision-making process
    through communication and a sense of acceptance of the final decision. We experimentally
    compared two ways to make decisions about beverages: ) majority voting and ) the
    proposed game. In the latter case, the participants enjoyed playing the game and
    were satisfied with the decision-making process.'
  - This paper presents several important factors affecting the resale prices of used
    rental cars. In fact, this paper empirically shows and proves several conjectures
    regarding the determinants for used rental car resale values through the use of
    detailed micro data from one of the biggest rental car companies. Specifically,
    the age of a used car has two composite effects on its resale value, even though
    overall the two effects work negatively with a concavity, as rental cars ages.
    On the other hand, two mileage variables interact with each other and produce
    overall decreasing effects on the resale prices with the opposite interactions.
    In terms of the effects of brand image, Hyundai and Renault-Samsung have positive
    effects on resale values generally. Ssangyong has a positive effect on the resale
    values in the SUV category, and Kia and GM-Daewoo are generally inferior to the
    other brands in terms of resale values in all categories. In terms of seasonal
    effects, we can conclude that this paper confirms the general perception regarding
    seasonal effects on resale values. In details, from November to February, resale
    values are affected negatively, and March is the recovering month of increasing
    demand in the used car market. August seems to be the highest season for the used
    car market due to several demand increases. As a result, this paper plays an important
    role in providing a substantial amount of information on the factors affecting
    the resale prices of rental cars.
  - In this paper we present an approach used to enhance students' competency in software
    verification. Students were asked to apply software verification techniques to
    a complex formal specification system. The complexity of the system stems from
    its sophisticated requirements. Selecting such system for this study was intentional
    for the following two reasons ) the system is difficult to understand and analyze
    because of the domain knowledge required to generate formal specifications in
    temporal logic and ) the system is large and complex which lends itself to a wide
    range of applicable verification techniques, and thus highlights the differences
    in the capabilities of each of the software verification approaches. Students
    were assessed using multiple criteria including; examination in applying learned
    techniques, students' attitude toward the technique, perceived efficiency of the
    techniques in discovering software defects, and the ability of the technique to
    locate errors in the code beyond simply indicating their presence. The results
    of this work show that the students applied the learned techniques successfully
    and their attitudes towards software verification improved.
- source_sentence: EnglishThe literature has argued that, contrary to what claimed
    by the rational economic theory, trade unions have progressively moved towards
    the representation of atypical workers by adopting more inclusive strategies of
    collective bargaining. The strength and modalities of such strategies are affected
    by national institutions of labour market and company-level union representation
    to which trade unions can draw in workplaces. Within this context, still remain
    to be discovered how the aforementioned institutions are enacted and in what subjects
    of employment relations can be used by unions in order to protect atypical work.
    This paper deals with these issues. It analyzes how unions have used distinctive
    institutional factors with regards of both external and interna! flexibility and
    in reference to regular and temporary workers to be able to improve the working
    conditions of atypical work. Trade unions negotiated a promotion system to permanent
    positions and allowed temporary workers to develop the same skills acquired by
    regular employees, which were also beneficial for permanent workers' employment
    conditions. The defense of regular workers' employrnent conditions was crucial
    in order to maintain an inclusive strategy of collective bargaining. italianoIntroduzione.
    - Contesto istituzionale e mobilizazione delle risorse. - Flessibilita ed interessi
    della forza del lavoro atipica e regolare. - Disegno e metodo della ricerca. -
    La strategia di contrattazione colletiva inclusiva fra flessibilita esterna ed
    interna. - Analisi e discussione. - Conclusioni.
  sentences:
  - Much has been invested in big data and artificial intelligence-based solutions
    for healthcare. However, few applications have been implemented in clinical practice.
    Early economic evaluations can help to improve decision-making by developers of
    analytics underlying these solutions aiming to increase the likelihood of successful
    implementation, but recommendations about their use are lacking. The aim of this
    study was to develop and apply a framework that positions best practice methods
    for economic evaluations alongside development of analytics, thereby enabling
    developers to identify barriers to success and to select analytics worth further
    investments.
  - An in situ field test on nine commonly-used soil water sensors was carried out
    in a sandy loam soil located in the Potato Research Center, Fredericton, NB (Canada)
    using the gravimetric method as a reference. The results showed that among the
    tested sensors, regardless of installation depths and soil water regimes, CS000,
    Trase, and Troxler performed the best with the factory calibrations, with a relative
    root mean square error (RRMSE) of , , and %, and a r( ) of , , and , respectively.
    TRIME, Moisture Point (MP000), and Gopher performed slightly worse with the factory
    calibrations, with a RRMSE of , , and %, and a r( ) of , , and , respectively,
    while the Gypsum, WaterMark, and Netafim showed a frequent need for calibration
    in the application in this region.
  - 'The article proposes a comparison between British devolution and Italian one,
    both have occurred at about the same time (from the end of Nineties years until
    now), looking what is common in devolution process inside two cultural and institutional
    context deeply different. About the constitutional innovation, British and Italian
    political systems know different method to pass a reform: in British system, Westminster
    parliament is sovereign not only in ordinary law-making but above all in constitutional
    matter (this is the meaning of parliament sovereignty in Dicey''s thought); in
    Italian system, constitutional power isn''t on the same degree of ordinary law,
    because the parliament makes ordinary law and an ad hoc convention makes the constitution
    (or at least its fundamental reforms), as it''s in French tradition. In spite
    of so, it''s possible to see a common element in British and Italian devolution,
    on the side of its limits: that is the difficult to compatible the post-centralistic
    state and its fiscal autonomy with the universalistic principles of welfare state.
    This may be one of the mains challenge that Western states will have to face,
    looking for a new political balances for the new era that follows the cold war
    end.'
- source_sentence: 'Objective Compared with povidone iodine solution to clean,glutaraldehyde
    immersion,highpressure steam sterilization of three disinfection methods for dental
    handpiece sterilization effect.Methods Select the dental clinical used over phone,were
    randomly divided into A group,B group,C group,D group ,A group for the control
    group,only cleaning method did not use any disinfection,B group was % Polyvinylpyrrolidone
    iodine solution,wipe,C group were soaked in % glutaraldehyde soluton,D group were
    treated with high-pressure steam sterilization,after each phone were inoculated
    with bacteria sample dish,the more monitoring of four groups of bacterial culture.Results
    A group of bacterial culture for the intensive growth of bacteria,B group had
    bacterial growth for the(+ ~+ + +),bacterial growth;C group had bacterial culturegrowth
    was(+ ~ + +),bacterial growth;D group of bacterial culture Growth of(-),no bacterial
    growth.Conclusion High-pressure steam sterilization was the disinfection of dental
    handpieces most effective way. Key words: Disinfection;Dental high-speed equipment'
  sentences:
  - 'Objective To study the self-locking brackets SmartclipTM 0MXTM MBTTM brackets
    and traditional pain comparison.Methods patients with non-extraction orthodontic
    treatment were randomly divided into two groups,a group treated with self-locking
    brackets,the other group treated with traditional care slot.Patients in orthodontic
    treatment of pain within a week were inoestigated by way of a questionnaire survey,including
    orthodontic pain,soft tissue irritation,and the strength of a normal life for
    patients with the impact.Results Questionnaire response rate was %.The level of
    pain was similar in self-ligating bracket group and the traditional bracket group.However,time-related,including
    pain after orthodontic treatment was 0h,0 d time,the most intense pain and continued
    to 0d,back pain relief,0w about pain relief.Conclusion Self-locking brackets and
    brackets have noobvious pain intensity differences,but related with orthodontic
    force to the clinical use of force should pay attention to light. Key words: Self-ligating
    bracket;Traditional brackets;Orthodontic treatment;Pain'
  - Simulation of inflorescences is an important part of virtual plant growth. The
    past works about simulation of inflorescences focus mainly on how to generate
    inflorescences by However, the productions of L system are difficult to understand
    and implement since it is described with rule based language, and especially it
    needs too many parameters in simulating inflorescence development and flowering
    sequences. Dual scale automaton is a plant growth model based on plant growth
    mechanisms, which is easy to understand and implement in programming. In this
    paper, the method of simulating inflorescence using dual scale automaton model
    is discussed. The dual scale automaton model is improved by introducing the rule
    of synchronization development, mechanism of reiteration and delay law of plant
    growth from the viewpoints of botany,which make it possible to generate almost
    all types of the inflorescences defined by botanists, and to simulate acropetal
    and basipetal flowering sequences. Several examples of simulation of typical inflorescences
    are given for explaining the theory. The improved model is demonstrated a simpler
    but more effective method in simulating inflorescences in comparison with L system.
  - 'I N late and through the summer of , the York County Court launched a concerted
    attack against Quakers in its part of Massachusetts.* York county magistrate Richard
    Waldron arrested three visiting Quaker women and had them beaten out of the jurisdiction;
    then, apparently in response to his recommendations, the court proceeded to cite
    local Quakers living in Kittery for their failure to attend orthodox church services.l
    Although Waldron''s actions did not occur until five years after the General Court
    had begun its program of suppressing Quakerism, they seemed consistent with the
    general pattern of persecution in seventeenth-century Massachusetts Bay: the discovery
    of heterodoxy followed by an immediate attempt to produce local conformity.0 Yet
    the considerable delay in Kittery in attacking Quakerism and the lack of any subsequent
    systematic effort to produce conformity raise a number of questions regarding
    the extent to which prejudice against heterodoxy was the sole motive for suppressing
    Quakerism in Massachusetts. Between and the York County Court attacked Quaker
    heterodoxy only on a limited number of occasions. Each of the incidents suggests
    that Kittery Quakers were punished not because their religious beliefs offended
    the court but because those beliefs denoted certain positions on secular issues,
    and men like Waldron could employ ecclesiastical sanctions to enlist sources'
- source_sentence: Androgen therapy is the mainstay of treatment for the hypogonadotropic
    hypogonadal micropenis because it obviously enhances penis growth in prepubescent
    microphallic patients. However, the molecular mechanisms of androgen treatment
    leading to penis growth are still largely unknown. To clarify this well-known
    phenomenon, we successfully generated a castrated male Sprague Dawley rat model
    at puberty followed by testosterone administration. Interestingly, compared with
    the control group, testosterone treatment stimulated a dose-dependent increase
    of penis weight, length, and width in castrated rats accompanied with a dramatic
    recovery of the pathological changes of the penis. Mechanistically, testosterone
    administration substantially increased the expression of androgen receptor (AR)
    protein. Increased AR protein in the penis could subsequently initiate transcription
    of its target genes, including keratin 00B (Krt00b). Importantly, we demonstrated
    that KRT00B is generally expressed in the rat penis and that most KRT00B expression
    is cytoplasmic. Furthermore, AR could directly modulate its expression by binding
    to a putative androgen response element sequence of the Krt00b promoter. Overall,
    this study reveals a novel mechanism facilitating penis growth after testosterone
    treatment in precastrated prepubescent animals, in which androgen enhances the
    expression of AR protein as well as its target genes, such as Krt00b.
  sentences:
  - This study develops statistical learning models to assess the probability of undergraduate
    students graduating within a predetermined period, utilizing admission, performance,
    and demographic data. The urgency of addressing student attrition is highlighted
    by recent data from the National Center for Education Statistics (NCES), indicating
    a % completion rate by full-time undergraduates within six years. This research
    leverages institutional data from a Saudi University, focusing on freshmen enrolled
    in the - and - academic years, to identify students at risk of dropping out, thereby
    enabling timely interventions. Ten algorithms, including decision trees, ensemble
    models, SVM, and ANN, were built and evaluated on a test set representing % of
    the entire dataset using precision, recall, accuracy, and Matthews correlation
    coefficient (MCC). The findings show that SVM and Random Forest models were the
    most reliable, achieving accuracies of and respectively, and maintaining balance
    in precision, recall, and MCC. Conversely, the naive Bayes model recorded the
    worst performance. The comparative analysis revealed the superior performance
    of ensemble models over decision tree models in predicting student attrition,
    emphasizing the importance of model selection in developing effective early intervention
    strategies. In addition, our analysis revealed that academic data is a better
    predictor of on-time graduation than admission data, emphasizing the need for
    institutions to focus on continuous academic assessment data.
  - 'Timely and accurate prediction of human movement in urban areas offers instructive
    insights into transportation management, public safety, and location-based services,
    to name a few. Yet, modeling urban mobility is challenging and complex because
    of the spatiotemporal dynamics of movement behavior and the influence of exogenous
    factors such as weather, holidays, and local events. In this paper, we use bus
    transportation as a proxy to mine spatiotemporal travel patterns. We propose a
    deep-learning-based urban mobility prediction model that collectively forecasts
    passenger flows between pairs of city regions in an origin-destination (OD) matrix.
    We first process OD matrices in a convolutional neural network to capture spatial
    correlations. Intermediate results are reconstructed into three multivariate time
    series: hourly, daily, and weekly time series. Each time series is aggregated
    in a long short-term memory (LSTM) network with a novel attention mechanism to
    guide the aggregation. In addition, our model is context-aware by using contextual
    embeddings learned from exogenous factors. We dynamically merge results from LSTM
    components and context embeddings in a late fusion network to make a final prediction.
    The proposed model is implemented and evaluated using a large-scale transportation
    data set of more than million bus trips with a suite of Big Data technologies
    developed for data processing. Through performance comparison, we show that our
    approach achieves sizable accuracy improvements in urban mobility prediction.
    Our work has major implications for efficient transportation system design and
    performance improvement. The proposed deep neural network structure is generally
    applicable for sequential graph data prediction.'
  - Various methods are currently under investigation to preserve fertility in males
    treated with high-dose chemotherapy and radiation for malignant and nonmalignant
    disorders. Human umbilical cord mesenchymal stem cells (HUC-MSCs), which possess
    potent immunosuppressive function and secrete various cytokines and growth factors,
    have the potential clinical applications. As a potential alternative, we investigate
    whether injection of HUC-MSCs into the interstitial compartment of the testes
    to promote spermatogenic regeneration efficiently. HUC-MSCs were isolated from
    different sources of umbilical cords and injected into the interstitial space
    of one testis from busulfan-treated mice (saline and HEK000 cells injections were
    performed in a separate set of mice) and the other testis remained uninjected.
    Three weeks after MSCs injection, Relative quantitative reverse transcription
    polymerase chain reaction was used to identify the expression of of germ cell
    associated, which are all related to meiosis, demonstrated higher levels of spermatogenic
    gene expression ( fold) in HUC-MSCs injected testes compared to the contralateral
    uninjected testes (five mice). Protein levels for germ cell-specific genes, miwi,
    vasa and synaptonemal complex protein (Scp0) were also higher in MSC-treated testes
    compared to injected controls weeks after treatment. However, no different expression
    was detected in saline water and HEK000 cells injection control group. We have
    demonstrated HUC-MSCs could affect mouse germ cell-specific genes expression.
    The results also provide a possibility that the transplanted HUC-MSCs may promote
    the recovery of spermatogenesis. This study provides further evidence for preclinical
    therapeutic effects of HUC-MSCs, and explores a new approach to the treatment
    of azoospermia.
- source_sentence: Twenty one surviving infants of pregnancies complicated by rupture
    of the membranes during the second trimester that lasted at least one week have
    been followed up for a median of months. Five infants ( %) had recurrent respiratory
    problems (episodes of wheezing and coughing occurring at least once a week) which
    related significantly to the use of neonatal ventilation and to very preterm delivery.
    Five of the infants who were born preterm and with birth weights of less than
    g had recurrent respiratory symptoms ( %). This compares favourably with an incidence
    of symptoms of % among surviving low birthweight infants born at this hospital
    after pregnancies not complicated by premature rupture of the membranes. Neither
    recurrent respiratory symptoms nor admission to hospital for chest related disorders
    were associated with the timing of onset or duration of rupture of the membranes.
    We conclude that, among survivors of premature rupture of the membranes, chronic
    respiratory morbidity would best be prevented by avoiding very preterm delivery,
    regardless of the duration of the rupture.
  sentences:
  - We report a case of prosthetic valve nocardia endocarditis. A year old farmer
    underwent aortic valve replacement with a bioprosthetic valve. The immediate post-operative
    course was uneventful but weeks later he developed fever. A trans-oesophageal
    echocardiogram (TEE) showed a string like structure attached to the prosthetic
    valve. Blood cultures grew N. farcinica. He was initially treated with trimethoprim/sulfamethoxazole
    (TMP/SMZ), but due to eosinophilia and leucopenia his treatment was changed to
    imipenem and amikacin. He developed a rash, presumed to be due to imipenem, which
    was then substituted with linezolid. He completed a week course of intravenous
    (i.v.) antibiotics. Desensitization with amoxicillin/clavulanic acid was successful
    and the patient received oral amoxicillin/clavulanic acid for months. At present,
    months from diagnosis, he is afebrile and TEE is normal. To our knowledge, this
    case is the fifth reported case of successful treatment of prosthetic valve nocardia
    endocarditis treated without surgery.
  - 'The effect of different variants of compiling integrated samples for biochemical
    oxygen demand (BOD) kinetics was studied in long-term experiments (up to days)
    with water samples taken from the central deep-water region of Lake Onego. It
    was a series of experiments carried out simultaneously at and in different seasons
    of . Five sampling variants were employed with different horizon combinations:
    near surface, near bottom, from different depths in the water column, from the
    photic and profundal layers. Two experiments were performed with winter water,
    three with summer water, four with autumn water, and seven experiments with spring
    water. The most representative sample for studying BOD in long-term experiments
    is an sample composed of water from different horizons of the photic layer ( m).
    For each variant of integrated sample composition, BOD development in the experiments
    was modeled by a corresponding kinetic equation whose parameters represented the
    oxidation characteristics of components of the organic matter present in the water
    and transformed in the long-term BOD experiment. The resultant kinetic parameters
    of BOD were analyzed in relation to the factors determining the final oxidation
    of the organic matter components. The patterns in which the type of BOD development
    is formed depend on the integrated water sample collection/compilation conditions
    and are characterized by the average values of the organic matter contained in
    the water, estimated either analytically or from empirical equations, as well
    as by the temperature of exposure of water samples in the experiment. Synthesis
    of the resultant information showed that the values of BOD kinetic parameters
    were generally lower in spring water taken from the central part of Lake Onego
    as compared with other seasons, since the oxidation potential of organic matter
    components in spring water is higher.'
  - Doppler ultrasound measurements of pulmonary blood flow in babies with severe
    respiratory distress syndrome treated in a randomised controlled trial of surfactant
    replacement showed that the immediate improvement of oxygenation was not associated
    with a significant increase in pulmonary blood flow. Reduction in ventilator settings
    and increases in the extent of chest wall movements measured by a cardiorespiratory
    monitor suggested that the improvement after surfactant had been given was a result
    of alveolar stabilisation and increased pulmonary compliance. Further simultaneous
    studies of pulmonary blood flow and pulmonary compliance are needed to confirm
    these findings.
model-index:
- name: SentenceTransformer based on allenai/specter2_aug2023refresh_base
  results:
  - task:
      type: triplet
      name: Triplet
    dataset:
      name: discipline tuned specter 2 022
      type: discipline-tuned_specter_2_022
    metrics:
    - type: cosine_accuracy
      value: 0.9713793103448276
      name: Cosine Accuracy
  - task:
      type: triplet
      name: Triplet
    dataset:
      name: discipline tuned specter 2 024
      type: discipline-tuned_specter_2_024
    metrics:
    - type: cosine_accuracy
      value: 0.9710344827586207
      name: Cosine Accuracy
---

# SentenceTransformer based on allenai/specter2_aug2023refresh_base

This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [allenai/specter2_aug2023refresh_base](https://huggingface.co/allenai/specter2_aug2023refresh_base). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

## Model Details

### Model Description
- **Model Type:** Sentence Transformer
- **Base model:** [allenai/specter2_aug2023refresh_base](https://huggingface.co/allenai/specter2_aug2023refresh_base) <!-- at revision 084e9624d354a1cbc464ef6cc1e3646d236b95d9 -->
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 768 dimensions
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
<!-- - **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': 512, 'do_lower_case': False}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
  (2): Normalize()
)
```

## Usage

### Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

```bash
pip install -U sentence-transformers
```

Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("m7n/discipline-tuned_specter_2_024")
# Run inference
sentences = [
    'Twenty one surviving infants of pregnancies complicated by rupture of the membranes during the second trimester that lasted at least one week have been followed up for a median of months. Five infants ( %) had recurrent respiratory problems (episodes of wheezing and coughing occurring at least once a week) which related significantly to the use of neonatal ventilation and to very preterm delivery. Five of the infants who were born preterm and with birth weights of less than g had recurrent respiratory symptoms ( %). This compares favourably with an incidence of symptoms of % among surviving low birthweight infants born at this hospital after pregnancies not complicated by premature rupture of the membranes. Neither recurrent respiratory symptoms nor admission to hospital for chest related disorders were associated with the timing of onset or duration of rupture of the membranes. We conclude that, among survivors of premature rupture of the membranes, chronic respiratory morbidity would best be prevented by avoiding very preterm delivery, regardless of the duration of the rupture.',
    'Doppler ultrasound measurements of pulmonary blood flow in babies with severe respiratory distress syndrome treated in a randomised controlled trial of surfactant replacement showed that the immediate improvement of oxygenation was not associated with a significant increase in pulmonary blood flow. Reduction in ventilator settings and increases in the extent of chest wall movements measured by a cardiorespiratory monitor suggested that the improvement after surfactant had been given was a result of alveolar stabilisation and increased pulmonary compliance. Further simultaneous studies of pulmonary blood flow and pulmonary compliance are needed to confirm these findings.',
    'The effect of different variants of compiling integrated samples for biochemical oxygen demand (BOD) kinetics was studied in long-term experiments (up to days) with water samples taken from the central deep-water region of Lake Onego. It was a series of experiments carried out simultaneously at and in different seasons of . Five sampling variants were employed with different horizon combinations: near surface, near bottom, from different depths in the water column, from the photic and profundal layers. Two experiments were performed with winter water, three with summer water, four with autumn water, and seven experiments with spring water. The most representative sample for studying BOD in long-term experiments is an sample composed of water from different horizons of the photic layer ( m). For each variant of integrated sample composition, BOD development in the experiments was modeled by a corresponding kinetic equation whose parameters represented the oxidation characteristics of components of the organic matter present in the water and transformed in the long-term BOD experiment. The resultant kinetic parameters of BOD were analyzed in relation to the factors determining the final oxidation of the organic matter components. The patterns in which the type of BOD development is formed depend on the integrated water sample collection/compilation conditions and are characterized by the average values of the organic matter contained in the water, estimated either analytically or from empirical equations, as well as by the temperature of exposure of water samples in the experiment. Synthesis of the resultant information showed that the values of BOD kinetic parameters were generally lower in spring water taken from the central part of Lake Onego as compared with other seasons, since the oxidation potential of organic matter components in spring water is higher.',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

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

<!--
### 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

#### Triplet

* Datasets: `discipline-tuned_specter_2_022` and `discipline-tuned_specter_2_024`
* Evaluated with [<code>TripletEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)

| Metric              | discipline-tuned_specter_2_022 | discipline-tuned_specter_2_024 |
|:--------------------|:-------------------------------|:-------------------------------|
| **cosine_accuracy** | **0.9714**                     | **0.971**                      |

<!--
## 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

#### Unnamed Dataset


* Size: 43,494 training samples
* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
* Approximate statistics based on the first 1000 samples:
  |         | anchor                                                                               | positive                                                                             | negative                                                                             |
  |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
  | type    | string                                                                               | string                                                                               | string                                                                               |
  | details | <ul><li>min: 80 tokens</li><li>mean: 232.53 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 81 tokens</li><li>mean: 230.16 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 86 tokens</li><li>mean: 229.66 tokens</li><li>max: 512 tokens</li></ul> |
* Samples:
  | anchor                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   | positive                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | negative                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
  | <code>Lupus nephritis (LN) is one of the major risk factors for morbidity and overall mortality in systemic lupus erythematosus (SLE). Its pathogenesis is multifactorial, and a number of risk factors, including serological markers, have been identified in recent years, correlating with clinical course and disease severity. Furthermore, a distinctive autoantibody profile has recently been reported in African- American SLE women with LN. The aim of this study was to characterize the autoantibody profile in African-American SLE patients, with LN and without. Only anti-dsDNA achieved statistical significance between the two groups (P < ). Fourteen ( %) patients with LN and ( %) without it exhibited positive anti-Ro/SS-A, anti-Sm, and anti-nRNP, but without anti-La/SS B (P > ). We conclude that African-American SLE patients with LN do not exhibit a specific or distinctive autoantibody profile. However, our data confirm the value of anti-dsDNA in SLE patients with LN.</code>                                  | <code>TRIM00 is a member of the tripartite motif family proteins and is one of the autoantigens which react with anti-SS-A antibody (Ab) present in sera of patients with systemic lupus erythematosus (SLE) and Sjogren's syndrome. Previous studies have shown that TRIM00 dysfunction promotes aberrant B-cell differentiation and Ab production in SLE, and anti-TRIM00 Ab may be related to the TRIM00 dysfunction in human SLE pathogenesis. Here, we examined the relationship between anti-TRIM00 Ab and clinical and immunological characteristics in SLE patients.Twenty-seven patients with SLE ( women and four men) before immunosuppressive therapies, who fulfilled the revised American College of Rheumatology criteria for SLE, and four healthy controls ( women and one man) were enrolled in the study. SLE patients were divided into two groups according to the seropositivity for anti-TRIM00 Ab. Serum anti-TRIM00 Ab levels were measured using enzyme-linked immunosorbent assays. The serum levels of cytokines a...</code> | <code>We construct a stochastic model of real estate pricing. The method of the pricing construction is based on a sequential comparison of the supply prices. We proof that under standard assumptions imposed upon the comparison coefficients there exists an unique non-degenerated limit in distribution and this limit has the lognormal law of distribution. The accordance of empirical distributions of prices to thetheoretically obtained log-normal distribution we verify by numerous statistical data of real estate prices from Saint-Petersburg (Russia). For establishing this accordance we essentially apply the efficient and sensitive test of fit of Kolmogorov-Smirnov. Basing on "The Russian Federal Estimation Standard N0", we conclude that the most probable price, i.e. mode of distribution, is correctly and uniquely defined under the log-normal approximation. Since the mean value of log-normal distribution exceeds the mode - most probable value, it follows that the prices valued by the mathematica...</code> |
  | <code>A laboratory prototype of an enzyme biosensor based on pHsensitive field-effect transistors has been developed to determine the total content of indole alkaloids in Rauwolfia serpentina Benth. Ex Kurz tissue culture. The biosensor was characterized by high sensitivity to th A laboratory prototype of an enzyme biosensor based on pHsensitive field effect transistors has been developed to determine the total content of indole alkaloids in Rauwolfia serpentina Benth. Ex Kurz tissue culture. The biosensor was characterized by high sensitivity to the total content of indole alkaloids (minimum limit of determination g/ml of the total content of indole alkaloids contained in the juice obtained from tissue culture of Rauwolfia serpentina). The linear range of biosensor determination of the analyte was from to g / ml of the total content of indole alkaloids. Analysis of indole alkaloids using a biosensor is simple and fast and does not require expensive equipment and special sample preparation f...</code> | <code>A procedure of separate biosensor analysis of the multicomponent sample with aflatoxins and pesticides has been developed and optimized. Biosensor determination of aflatoxins and pesticides was performed using enzyme inhibition analysis. For creation of bioselective element we used enzyme acetylcholinesterase which is co-immobilized with bovine serum albumin on the surface of potentiometric transducer by glutaraldehyde covalent crosslinking. As transducers were pH-sensitive field effect transistors. The concentration of acetylcholine chloride as a substrate for subsequent inhibition analysis was fit; optimal time of inhibition by toxins solution was determinate together with concentration of reactivator (pyridine- -aldoxymmethyliodyd) and time of enzyme reactivation after inhibition. A synergism between trichlorfon and aflatoxin B0 in inhibition of immobilized on a surface pH-sensitive field-effect transistors acetylcholinesterase was investigated. The proposed procedure allows selecti...</code> | <code>Objective: To observe the effect of modified Zhenwu decoction on blood glucose and blood lipid of experimental diabetic rats.Methods: Diabetic model rats randomly were divided into normal control group,diabetic modeling group,modified Zhenwu decoction group.Establish intraperitoneal injection of Streptozotocin diabetic animal models by,after eight weeks blood glucose and blood lipids were detrmined.Results: After the treatment by modified Zhenwu decoction,blood glucose,blood lipid and other indicators improved significantly.Conclusion: Modified Zhenwu decotion can improve the level of renal lower blood glucose and lipid in diabetic rats.</code>                                                                                                                                                                                                                                                                                                                                                                       |
  | <code>In two successive years ( and ), a set of commercial sugar beet cultivars was established in Randomized Complete Block experiments at two sites in central Greece. Cultivar combination was different between years, but not between sites. Leaf sampling took place once during the growing season and leaf area, LA [cm0], leaf midvein length, L [cm] and maximum leaf width, W [cm] were determined using an image analysis system. Leaf parameters were mainly affected by cultivars. Leaf dimensions and their squares (L0, W0) did not provide an accurate model for LA predictions. Using LW as an independent variable, a quadratic model (y = x0 - x + , r = , p< , n = ) provided the most accurate estimation of LA. With compromises in accuracy, the linear relationship between LW and LA (y = x + , r = , p< , n = ) could be used as a prediction model thanks to its simplicity.</code>                                                                                                                                          | <code>The general increase in temperature, together with sudden episodes of extreme temperatures, are increasingly impacting plant species in the present climate change scenario. Limoniastrum monopetalum is a halophyte from the Mediterranean Basin, exposed to broad daily and seasonal changes in temperature and extreme high temperatures. We studied the photosynthetic responses (chlorophyll fluorescence dynamics and gas exchange) of L. monopetalum leaves exposed to temperatures from .0C to .0C under darkness in controlled laboratory conditions. L. monopetalum presented its optimum temperature for photosynthesis around +00C. The photosynthetic apparatus of L. monopetalum exhibited permanent damages at > .0C. L. monopetalum tolerated, without permanent damages, temperatures as low as .0C in darkness. L. monopetalum appears as a plant species very well adapted to the seasonality of the Mediterranean climate, which may work as a pre-adaptation to stand more extreme temperatures in the actual conte...</code> | <code>The article depicts direct and hidden (implicit and explicit) information giving in advertisement discourse, meaning advertising slogans. Having investigated this topic thoroughly, the author found out that cognitive types of presupposition and communicative implicatures played a great role in advertising slogans. There are definitions of phenomena "implicit" and "explicit" with examples. The cognitive types of presupposition (semantic and pragmatic) and their typology is discussed in the article. There is a possibility to figure out what strategy of communicative influence on human's cognition is. Some laws of neurolinguistic programming is also discussed.</code>                                                                                                                                                                                                                                                                                                                                                   |
* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
  ```json
  {
      "distance_metric": "TripletDistanceMetric.COSINE",
      "triplet_margin": 0.4
  }
  ```

### Evaluation Dataset

#### Unnamed Dataset


* Size: 2,174 evaluation samples
* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
* Approximate statistics based on the first 1000 samples:
  |         | anchor                                                                               | positive                                                                             | negative                                                                             |
  |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
  | type    | string                                                                               | string                                                                               | string                                                                               |
  | details | <ul><li>min: 83 tokens</li><li>mean: 235.71 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 82 tokens</li><li>mean: 234.64 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 86 tokens</li><li>mean: 225.92 tokens</li><li>max: 512 tokens</li></ul> |
* Samples:
  | anchor                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   | positive                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | negative                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
  | <code>In Organic Law / of 0rd October of the general arrangement of the educational system (LOGSE), the educational system includes the general regime education and the special regime education. Dance is included in the special regime as part of the artistic disciplines together with music, drama, the plastic arts and design. The aim of this article is to analyse the treatment given to Dance in the general regime. Thus, we will try to emphasize the inconsistency that exists between the areas of primary education, which will be obligatory and will have a global and integrated character, and the training of future teachers.</code>                                                                                                                                                                                                                                                                                                                                                                                             | <code>This work aims to analyze the treatment of health education in school textbooks during the period , and to compare it with the one that is conducted at present. It will attempt to verify how many current concepts and ideas were already present in those decades. In addition, the differences in the way of carrying out health education then and now will be outlined, especially those referred to pedagogic strategies and didactic materials. All this will be done from a double perspective: . The concept of health, hygiene and pedagogy of health education. . The program contents of health education in the didactic materials.</code>                                                                                                                                                                                                                                                                                                                                                                                           | <code>The vane-in-cup (VIC) geometry has been widely used for the rheological characterization of yield-stress fluids because it minimizes slip effects at the liquid/solid interface of the rotating geometry and reduces sample damage during the loading process. However, severe kinematic limitations arising from the spatial complexity of mixed shear and extensional flow have been identified for quantitative rheometrical measurements in complex fluids. Recently, vanes with fractal cross sections have been suggested as alternatives for accurate rheometry of elastoviscoplastic fluids. In this work, the steady fractal vane-in-cup (fVIC) flow of a Newtonian fluid and a nonthixotropic Carbopol®️ microgel as well as the unsteady flow of a thixotropic -Carrageenan gel are analyzed using rheo-particle image velocimetry (Rheo-PIV). We describe the velocity distributions in all cases and show that the fVIC produces an almost axisymmetric flow field and rotation rate-independent "effective radius" when us...</code> |
  | <code>An ultrahigh vacuum three-axis cryogenic sample manipulator suitable for angle-resolved photoelectron spectroscopy experiments was developed. The sample manipulator is constructed by combining three modules with translation, polar rotation, and azimuthal-tilt rotation capabilities. Polar rotation and the azimuthal-tilt rotation are performed using a differentially pumped rotary stage and a sample goniometer, respectively. Continuous rotation around the polar axis is possible. The sample goniometer is capable of azimuthal rotation of up to and tilt rotation from to , measured from the plane normal to the polar axis. Nonmagnetic materials are used near the sample holder of the goniometer. The sample holder can be cooled using a continuous-flow cryostat. To serve as a radiation shield, the lower portion of the goniometer surrounding the sample holder is cooled separately by another cell filled with liquid nitrogen. With liquid nitrogen or liquid helium for the cryostat, the sample holder ...</code> | <code>In the soft x-ray region below keV, various electron yield (EY) techniques have been employed in x-ray absorption fine structure (XAFS) measurements of bulk materials. The fluorescent x-ray yield (FY) is also utilized for samples of low concentration. Although FY becomes much smaller for lighter elements, it has several advantages compared with EY to measure XAFS spectra; for example, a higher signal-to-background ratio and applicability to insulating materials. However, it has been thought to be unsuitable for concentrated samples due to a self-absorption effect. In this report, the sampling depth and self-absorption effect for bulk concentrated samples are discussed concerning XAFS measurements in a few keV energy region. Some typical FY XAFS spectra of concentrated materials, including insulators, are presented.</code>                                                                                                                                                                                  | <code>To investigate the distribution characteristics of TCM syndromes and the related herbal prescriptions for malignant tumors (MT). A clinical database of the TCM syndromes and the herbal prescriptions in treatment of MT patients were established. The data were then analyzed using cluster and frequency analysis. According to the cluster analysis, the TCM syndromes in MT patients mainly included two patterns: deficiency of both Qi and Yin and internal accumulation of toxic heat. The commonly-prescribed herbs were Huangqi (Astraglus), Nuzhenzi (Fructus Ligustri Lucidi), Lingzhi (Ganoderma Lucidum), Huaishan (Dioscorea Opposita), Xiakucao (Prunella Vulgaris), and Baihuasheshecao (Herba Hedyotidis). Deficiency of Qi and Yin is the primary syndrome of MT, and internal accumulation of toxic heat is the secondary syndrome. The herbs for Qi supplementation and Yin nourishment are mainly used, with the assistance of herbs for heat-clearance and detoxification.</code>                                          |
  | <code>Abstract Abstract Worldwide opposition to different aspects of globalisation indicates the emergence of a global social movement that typically targets the international bodies that regulate global trade and global finance, as well as the regulations themselves. The significance of the movement calls for a synthetic analysis that moves beyond the currently used fragmentary descriptions. A more profound conceptual framework will enable researchers to better understand the full dynamic of the movement within its global context In this article we explore the possibilities of applying David Korten's ideal-typical notion of fourth generation development to the anti-globalisation movement. We ask whether anti-globalisation organisation exhibits so-called Fourth Generation characteristics and activities. Our goal is to determine the extent to which the movement as a whole, and the individual organisations which constitute it, conform to the fourth generation development conceptual framework. ...</code> | <code>Abstract Globalisation is a complex, multi-faceted, phenomenon with widely contested meanings. While it has roots in the history of colonialism, capitalist development and imperialism, there are strong indications that what we are witnessing, since the 0000s, is a qualitative break with the past. Old boundaries, categories and meanings are being challenged in profound ways. New forms of exploitation and subjugation emerge in such a way that stark brutal force coexists with and may be increasingly supplanted by more subtle, pervasive forces of hegemonic rule. The latter, however, has opened up new terrains of struggle for people, movements, and governments opposed to one-dimensional 'corporate globalisation', seeking instead the globalisation of social and environmental justice. A continent like Africa much of which has sunk deeper into a 'fourth world' status of extreme under-development, social instability and neo-colonial dependence faces stark choices. Does it seek to partially or f...</code> | <code>So much has been written about the nation vis-a-vis other fields in the humanities, literature in particular. My interest in dance lies in its peculiar location within and vis-a-vis the discourse of the nation. An ephemeral form, dance has elicited various, and even contradictory, valuations; most of the time it is considered a mere form of entertainment. It is undeniable, though, that dance has articulated and informed our ideas of the nation and nationhood. In this paper, I explore how three contemporary dance companies based in Quezon City (The University of the Philippines Dance Company, Airdance, and Dance Forum) have rendered their imaginings of the Philippine nation. I focus on Philippine contemporary dance because as a cultural practice, I believe that it has choreographed the many trajectories and issues embodied in the Philippines's imagining of itself. A number of choreographies by the three companies mobilize motifs, forms, structures, and styles that constitute and signify...</code> |
* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
  ```json
  {
      "distance_metric": "TripletDistanceMetric.COSINE",
      "triplet_margin": 0.4
  }
  ```

### Training Hyperparameters
#### Non-Default Hyperparameters

- `eval_strategy`: steps
- `per_device_train_batch_size`: 4
- `per_device_eval_batch_size`: 32
- `learning_rate`: 7e-06
- `weight_decay`: 0.01
- `num_train_epochs`: 1
- `warmup_ratio`: 0.5
- `fp16`: True
- `batch_sampler`: no_duplicates

#### All Hyperparameters
<details><summary>Click to expand</summary>

- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: steps
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 4
- `per_device_eval_batch_size`: 32
- `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`: 7e-06
- `weight_decay`: 0.01
- `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`: 0.5
- `warmup_steps`: 0
- `log_level`: passive
- `log_level_replica`: warning
- `log_on_each_node`: True
- `logging_nan_inf_filter`: True
- `save_safetensors`: True
- `save_on_each_node`: False
- `save_only_model`: False
- `restore_callback_states_from_checkpoint`: False
- `no_cuda`: False
- `use_cpu`: False
- `use_mps_device`: False
- `seed`: 42
- `data_seed`: None
- `jit_mode_eval`: False
- `use_ipex`: False
- `bf16`: False
- `fp16`: True
- `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`: False
- `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}
- `deepspeed`: None
- `label_smoothing_factor`: 0.0
- `optim`: adamw_torch
- `optim_args`: None
- `adafactor`: False
- `group_by_length`: False
- `length_column_name`: length
- `ddp_find_unused_parameters`: None
- `ddp_bucket_cap_mb`: None
- `ddp_broadcast_buffers`: False
- `dataloader_pin_memory`: True
- `dataloader_persistent_workers`: False
- `skip_memory_metrics`: True
- `use_legacy_prediction_loop`: False
- `push_to_hub`: False
- `resume_from_checkpoint`: None
- `hub_model_id`: None
- `hub_strategy`: every_save
- `hub_private_repo`: None
- `hub_always_push`: False
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_inputs_for_metrics`: False
- `include_for_metrics`: []
- `eval_do_concat_batches`: True
- `fp16_backend`: auto
- `push_to_hub_model_id`: None
- `push_to_hub_organization`: None
- `mp_parameters`: 
- `auto_find_batch_size`: False
- `full_determinism`: False
- `torchdynamo`: None
- `ray_scope`: last
- `ddp_timeout`: 1800
- `torch_compile`: False
- `torch_compile_backend`: None
- `torch_compile_mode`: None
- `dispatch_batches`: None
- `split_batches`: None
- `include_tokens_per_second`: False
- `include_num_input_tokens_seen`: False
- `neftune_noise_alpha`: None
- `optim_target_modules`: None
- `batch_eval_metrics`: False
- `eval_on_start`: False
- `use_liger_kernel`: False
- `eval_use_gather_object`: False
- `average_tokens_across_devices`: False
- `prompts`: None
- `batch_sampler`: no_duplicates
- `multi_dataset_batch_sampler`: proportional

</details>

### Training Logs
| Epoch  | Step | Training Loss | Validation Loss | discipline-tuned_specter_2_022_cosine_accuracy | discipline-tuned_specter_2_024_cosine_accuracy |
|:------:|:----:|:-------------:|:---------------:|:----------------------------------------------:|:----------------------------------------------:|
| 0.0023 | 25   | 0.2976        | 0.2980          | 0.9518                                         | -                                              |
| 0.0046 | 50   | 0.3008        | 0.2969          | 0.9518                                         | -                                              |
| 0.0069 | 75   | 0.3088        | 0.2953          | 0.9524                                         | -                                              |
| 0.0092 | 100  | 0.3047        | 0.2929          | 0.9530                                         | -                                              |
| 0.0115 | 125  | 0.2879        | 0.2897          | 0.9530                                         | -                                              |
| 0.0138 | 150  | 0.2705        | 0.2855          | 0.9532                                         | -                                              |
| 0.0161 | 175  | 0.2771        | 0.2804          | 0.9536                                         | -                                              |
| 0.0184 | 200  | 0.2737        | 0.2744          | 0.9548                                         | -                                              |
| 0.0207 | 225  | 0.2737        | 0.2676          | 0.9553                                         | -                                              |
| 0.0230 | 250  | 0.2569        | 0.2600          | 0.9557                                         | -                                              |
| 0.0253 | 275  | 0.2518        | 0.2512          | 0.9579                                         | -                                              |
| 0.0276 | 300  | 0.2445        | 0.2416          | 0.9580                                         | -                                              |
| 0.0299 | 325  | 0.2214        | 0.2310          | 0.9591                                         | -                                              |
| 0.0322 | 350  | 0.2359        | 0.2204          | 0.9606                                         | -                                              |
| 0.0345 | 375  | 0.2072        | 0.2090          | 0.9615                                         | -                                              |
| 0.0368 | 400  | 0.1907        | 0.1976          | 0.9618                                         | -                                              |
| 0.0391 | 425  | 0.1881        | 0.1850          | 0.9624                                         | -                                              |
| 0.0414 | 450  | 0.1842        | 0.1733          | 0.9637                                         | -                                              |
| 0.0437 | 475  | 0.1618        | 0.1628          | 0.9646                                         | -                                              |
| 0.0460 | 500  | 0.1638        | 0.1533          | 0.9645                                         | -                                              |
| 0.0483 | 525  | 0.1569        | 0.1440          | 0.9648                                         | -                                              |
| 0.0506 | 550  | 0.1473        | 0.1354          | 0.9657                                         | -                                              |
| 0.0529 | 575  | 0.1333        | 0.1281          | 0.9671                                         | -                                              |
| 0.0552 | 600  | 0.1481        | 0.1223          | 0.9671                                         | -                                              |
| 0.0575 | 625  | 0.1263        | 0.1167          | 0.9675                                         | -                                              |
| 0.0598 | 650  | 0.114         | 0.1120          | 0.9684                                         | -                                              |
| 0.0621 | 675  | 0.1097        | 0.1081          | 0.9693                                         | -                                              |
| 0.0644 | 700  | 0.1152        | 0.1044          | 0.9698                                         | -                                              |
| 0.0667 | 725  | 0.1009        | 0.0999          | 0.9705                                         | -                                              |
| 0.0690 | 750  | 0.0895        | 0.0961          | 0.9709                                         | -                                              |
| 0.0713 | 775  | 0.0855        | 0.0934          | 0.9711                                         | -                                              |
| 0.0736 | 800  | 0.0853        | 0.0912          | 0.9715                                         | -                                              |
| 0.0759 | 825  | 0.0942        | 0.0885          | 0.9714                                         | -                                              |
| 0.0782 | 850  | 0.1035        | -               | -                                              | 0.9710                                         |


### Framework Versions
- Python: 3.10.12
- Sentence Transformers: 3.3.1
- Transformers: 4.49.0.dev0
- PyTorch: 2.5.1+cu121
- Accelerate: 1.2.1
- Datasets: 3.2.0
- Tokenizers: 0.21.0

## Citation

### BibTeX

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

#### TripletLoss
```bibtex
@misc{hermans2017defense,
    title={In Defense of the Triplet Loss for Person Re-Identification},
    author={Alexander Hermans and Lucas Beyer and Bastian Leibe},
    year={2017},
    eprint={1703.07737},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}
```

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