metadata

tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:160000
  - loss:MarginDistillationLoss
base_model: sentence-transformers/all-MiniLM-L6-v2
widget:
  - source_sentence: why is it a healthy thing to be in a dynamic work environment?
    sentences:
      - >-
        Workplace Mindfulness In spite of the advancements in the field, a major
        limita tion of the extant research is the lack of an effective means  to
        measure workplace mindfulness. Workplace mindfulness  is particularly
        concerned with events in the workplace (e.g.,  work tasks and meetings)
        rather than with events occurring  outside of the work setting, such as
        life situations (e.g., driv ing and showering). At work, employees are
        embedded in  task-oriented workflows, processes, and employment rela
        tionships (Zivnuska et al., 2016). Hence, prior research has  theorized
        that workplace mindfulness depends on the par ticular context—namely,
        the work environment (Dane &  Brummel, 2014)—and focusing on this
        specific setting can  help mindfulness scholars tackle issues of
        theoretical impor tance and practical concern (Dane, 2011; Dane &
        Brummel,  2014). Further, scholars have indicated that some employees 
        may be more mindful at work than others due to specific  experiences
        they have accrued (Dane & Brummel, 2014). It  is therefore possible
        that, for some employees, certain fea tures and events in the
        workplace—that is, contextual stimuli encountered in this setting (Dane
        & Brummel, 2014; Ziv nuska et al., 2016)—may induce workplace
        mindfulness. As  such, any measure of workplace mindfulness should essen
        tially capture an employee’s awareness and attention to the 
        work-related issues that an individual encounters within the  work
        setting (Elsbach & Pratt, 2007; George, 2009).
      - >-
        Examining workplace mindfulness 

        and its relations to job  

        performance and  

        turnover intention Dynamic work environments tend to be associated with
        high levels of emotional  arousal and stress – byproducts of the time
        pressure and unpredictability pervading such  environments (Brehmer,
        1992; Klein, 1998). Over time, these pressures may become  difficult to
        bear, leading people to consider relinquishing their employment in the 
        dynamic work setting. On this point, research demonstrates negative
        relationships  between psychological and physiological job-related
        demands and people’s intentions to  leave their organizations (Begley,
        1998; Kemery et al., 1987). With that said, intention to  leave (i.e.
        turnover intention) is subject to a number of influences, including not
        only  features of the work context, but also individual-level factors
        (Cardador et al., 2011;  Meyer et al., 2002). As such, even within the
        same work setting, people may differ in  their turnover intentions.
      - >-
        Workplace Mindfulness Mindfulness can also be conceptualized as a trait
        character ized by receptive awareness and attention to ongoing events 
        and experiences (Brown & Ryan, 2003; Feldman et al.,  2007). Compared
        with the traditional conceptualization of a  trait, mindfulness as an
        individual difference is less stable and  can be affected more by
        internal and external stimuli, though  it remains more stable than a
        state. For instance, Brown and  Ryan (2003, p. 823) indicated that
        mindfulness involves  “an open, undivided observation of what is
        occurring both  internally and externally.” Cardaciotto et al., (2008,
        p. 205)defined mindfulness as “the tendency to be highly aware of  one’s
        internal and external experiences in the context of an  accepting,
        nonjudgmental stance toward those experiences.”
  - source_sentence: what is workplace mindfulness
    sentences:
      - >-
        Examining workplace mindfulness 

        and its relations to job  

        performance and  

        turnover intention Drawing on these observations, we consider whether
        workplace mindfulness relates  to turnover intention within dynamic work
        environments. Here, research indicates that  mindfulness leads people to
        cope with challenging or stressful situations proactively and 
        adaptively (e.g. Shapiro et al., 2007; Weinstein et al., 2009). In
        particular, mindfulness  facilitates self-regulation (Atkins and Parker,
        2012; Glomb et al., 2011) and enables peo ple to respond to potentially
        stressful events with greater equanimity and less rumination  (Brown et
        al., 2007; Carlson, 2013; Shapiro et al., 2006). Consequently,
        mindfulness  may guard against emotional exhaustion at work – a
        possibility supported by recent  empirical research (Hülsheger et al.,
        2013). Given these lines of theory and evidence,  mindfulness should
        enhance one’s ability to cope with the stresses and strains of a 
        dynamic work environment. Accordingly, we predict that those high in
        workplace mind fulness will feel less compelled than others to
        permanently depart from such an  environment.
      - >-
        Measuring State and Trait Mindfulness at the Workplace While a variety
        of definitions of Mindfulness seem to emphasize on similar  and
        overlapping  elements such as "presence", awareness" and "non judgment";
        there remains dissent  among  researchers in the area of mindfulness
        regarding the scope and nature of the phenomenon, and  a lack of
        consensus regarding the definitions and components of mindfulness
        (Cigolla &  Brown, 2011; Grossman, 2011; Sutcliffe et al., 2016).  In
        the field of organizational science, Good et al. (2016) has
        conceptualized mindfulness as a  state, trait, practice and
        intervention.   A trait is referred to as a stable characteristic or
        behavioural pattern exhibited by an  individual over the long term
        (Hamaker et al., 2007). Therefore, trait mindfulness is a  dispositional
        individual difference in mindfulness (Allen & Kiburz, 2012). It is a
        stable  individual characteristic exhibited over a long period going
        much beyond any mindfulness based intervention or practice.
      - >-
        MAAS FMI Mindfulness is defined differently by various practitioners, 
        researchers and clinicians, as well as according to the various  schools
        of thought, which place more emphasis on particular  aspects of the
        concept compared to others (Brown et al., 2007).  Dane (2011) provides a
        synopsis of various academic and  philosophical conceptualisations of
        mindfulness showing that  scholars display noticeably high consensus on
        the nature of  mindfulness. One of the features common across multiple 
        conceptualisations is that mindfulness is a state of  consciousness
        (Brown & Ryan, 2003). It refers to ‘… a  heightened state of involvement
        and wakefulness or being in  the present’ (Langer & Moldoveanu, 2000, p.
        2). Brown, Kasser,  Ryan, Linley and Orzech (2009) explain that
        mindfulness is not  deliberative in nature. Inputs are allowed to enter
        one’s  awareness by simply noticing what is taking place. Mindfulness 
        refers to the simple act of observing without scrutiny, making 
        comparisons or evaluating events and experience and is thus  dissimilar
        to ‘self-awareness’ or reflexive consciousness in  other forms. Instead,
        mindfulness concerns a non-interference  with experience. Walach et al.
        (2006, p. 1544) explain that it is ‘a  warm and friendly, accepting and
        non-judgemental attitude  towards those elements of our mind. Suspending
        categorical  judgements, which normally follow every perception rather 
        quickly, is an integral part of mindfulness’. Therefore,  mindfulness is
        not a cold, cognitive process.
  - source_sentence: what kind of skill is mindfulness in workplace
    sentences:
      - >-
        Workplace Mindfulness Supporting this rationale, Kudesia (2019) and
        Kudesia  and Nyima (2015) highlighted the context-specific nature  of
        mindfulness, recognizing that mindfulness reflects the  individual’s
        metacognitive skills, which are engaged in a  particular situation.
        Bishop (2002) suggested that mindful ness practice actually encompasses
        several metacognitive  processes, proposing that mindfulness can be
        described as  a type of metacognitive skill. In essence, the
        metacognitive  skills embedded in workplace mindfulness are a crucial
        part  of the self-regulatory loop, and their core purpose is to reduce 
        the discrepancy between the actual state and an undesired  state, or
        between an actual state and a desired state (Carver  & Scheier, 2002).
        As such, workplace mindfulness com prises employees’ metacognitive
        skills within the work set ting through which they demonstrate their
        regulation ability  when dealing with work-related activities. We argue
        that the  individual’s specific skills become especially pertinent when 
        we consider particular aspects of the metacognitive practice  pathway of
        mindfulness, such as self-regulating attention and  noticing subtle
        affective sensations. For example, mindfulness  is associated with the
        ability to distance oneself from stimuli  (Chambers et al., 2009). This
        distancing allows employees to  notice, prioritize, and respond to
        distractions in a conscious  way, without impulsivity or defensiveness
        (Bishop et al.,  2004; Teasdale, 1999; Teasdale et al., 1995).
      - >-
        integrative review Most of the existing literature reviews on workplace
        mindfulness have focused on the  characteristics and outcomes of
        mindfulness interventions in the workplace (Allen et al.,  2015; Eby et
        al., 2019; Jamieson & Tuckey, 2017; Johnson et al., 2020). These reviews
        have  not integrated individual and workplace factors as antecedents of
        workplace mindfulness as  well as the factors that can mediate or
        moderate the mindfulness/outcomes relationship.  While two reviews have
        integrated a broader range of factors that can mediate the  relationship
        between workplace mindfulness and workplace outcomes (Glomb et al.,
        2011;  Good et al., 2016), a key limitation is that they have not
        encompassed antecedents of  workplace mindfulness and moderators of the
        mindfulness/outcomes relationship. Another  review by Sutcliffe et al.
        (2016) discussed the antecedents of workplace mindfulness and  mediators
        of the mindfulness/outcomes relationship. However, their review has not
        provided  a comprehensive framework of workplace mindfulness that
        integrates individual and  workplace factors as antecedents, mediators,
        and moderators. Overall, knowledge of  antecedents, mediators, and
        moderators related to workplace mindfulness is fragmented in the  extant
        organizational literature and existing reviews have not provided a
        comprehensive  model with which to organize and reconcile understandings
        of antecedents of workplace mindfulness as well as mediating and
        moderating factors of the mindfulness/outcomes  relationship.
      - >-
        Measuring State and Trait Mindfulness at the Workplace On the other
        hand, "state"  is defined  as the experience of an individual while
        interacting  with a given situation (Hamaker et al., 2007).Therefore,
        state mindfulness is described as a  temporary state of attention in the
        present moment occurring both externally and internally  (Dane, 2011). 
        Some researchers (Lau et al., 2006) believe mindfulness to be a
        psychological state that  varies across situations within individuals,
        while others (Baer et al., 2006) argue that   mindfulness is a stable
        characteristic.  If one were to view state mindfulness as the within
        (intra) person variation of mindfulness  experiences; and trait
        mindfulness as between (inter) person variation of mindfulness ability, 
        the two conceptualizations of mindfulness can be integrated into a
        meaningful whole.In fact, Jamieson & Tuckey (2016) assert that the
        intensity, duration and frequency with  which an individual engages in
        different states of mindfulness determine the trait mindfulness  of an
        individual (Hulsheger et al., 2013) (See Figure 1)
  - source_sentence: what are the dimensions of mindfulness in workplaces?
    sentences:
      - >-
        Measuring State and Trait Mindfulness at the Workplace Mindfulness is
        known to be cultivated through mindfulness practices and interventions. 
        Linkage, therefore, exists between mindfulness practice and intervention
        along with trait and  6 | P a g e  state mindfulness as asserted by
        Jamieson & Tuckey (2016) who propose that mindfulness  practice along
        with mindfulness-based intervention (MBI) enhances an individuals’
        state  mindfulness which leads to development of trait mindfulness
        (Hulsheger et al., 2013).  Although, this particular pathway hasn't been
        specifically investigated, evidence suggest that  State and Trait
        Mindfulness are indeed linked to each other. Brown & Rayn (2003) and 
        Hulsheger et al. (2013) have reported considerable variance in the state
        (within a person) and  trait (between person) mindfulness among
        individuals over a series of days. Additionally,  a  moderately strong
        association has also been reported between experiences of state and
        trait  mindfulness (Brown & Ryan, 2003).
      - >-
        Assessing Facets of Doing so, the present endeavor makes three
        contributions to the literature.  First, using the multidimensional
        scale developed in the present work, we  will provide first insights
        into the differential validities of subfacets of mind fulness for key
        work outcomes. This will foster a refined understanding of  the
        mechanisms of action inherent to mindfulness and help understand why 
        mindfulness matters for which work outcome (Bishop, Lau, Shapiro,
        Carlson,  Anderson, Carmody, Segal, Abbey, Speca, Velting, & Devins,
        2004; Shapiro,  Carlson, Astin, & Freedman, 2006). Second, although
        prominent mindfulness  theories and scholarly work on mindfulness in the
        clinical area suggest that  mindfulness consists of multiple subfacets
        (Baer et al., 2006; Bishop et al.,  2004), research on mindfulness in
        the context of work has almost exclusively  operationalized mindfulness
        by assessing the awareness component (for an  exception see Liang et
        al., 2017). This bears the risk of construct deficiency  due to which
        mindfulness might not have been considered in its entirety in  relation
        to work outcomes. By equating a sub-aspect with the overall con struct,
        the role of the overall construct of mindfulness in the context of work 
        might have been underestimated. The present work takes a course
        correction  and informs the organizational mindfulness literature by
        revealing the extent  to which a work-related scale capturing the
        construct of mindfulness compre hensively provides a better
        understanding of the extent to which mindfulness  relates to important
        work outcomes. Third, the present work makes a practi cal contribution
        to the organizational mindfulness literature by offering a reli able and
        valid multidimensional scale that is applicable in the context of work 
        and that enables other researchers to use this refined, multidimensional
        oper ationalization of mindfulness in their work and thereby helps move
        this field  forward. Apart from the benefits of capturing the construct
        of mindfulness  comprehensively and being able to differentiate between
        subfacets, a contex tualized trait mindfulness scale bears important
        advantages over non-contex tualized generic mindfulness scales. This has
        been documented by research in  the area of personality and personnel
        psychology, providing ample evidence  that contextualizing items and
        providing participants with a context-specific   frame of reference that
        conceptually overlaps with the criterion domain  improves
        criterion-related validity (Bing, Whanger, Davison, & VanHook,  2004;
        Lievens, De Corte, & Schollaert, 2008; Shaffer & Postlethwaite, 2012).
      - >-
        Workplace Mindfulness In our model, we conceptualize workplace
        mindfulness as  a reflective construct because its components share a
        common  theme and each component depends on the construct of work place
        mindfulness (e.g., Diamantopoulos et al., 2008; Edwards  & Bagozzi,
        2000; MacKenzie et al., 2005). Workplace mind fulness is composed of
        three dimensions: awareness, attention,  and acceptance. These three
        dimensions do not form a sequen tial process. That is, one or two might
        potentially emerge first,  with the others appearing later; however, the
        three aspects are  ultimately integrated to represent workplace
        mindfulness. Put  differently, awareness, attention, and acceptance are
        specific  manifestations of workplace mindfulness, which together 
        reflect the concept of workplace mindfulness.
  - source_sentence: what is mindfulness?
    sentences:
      - >-
        Examining workplace mindfulness 

        and its relations to job  

        performance and  

        turnover intention To begin, one of the most theoretically and
        practically important outcomes in work place settings is job
        performance. While job performance commands much scholarly  attention
        (see Motowidlo, 2003, for a review), little research has empirically
        connected  mindfulness to job performance. Nevertheless, an emerging
        body of research has dem onstrated linkages between mindfulness and
        performance across a number of tasks (e.g.  Ostafin and Kassman, 2012;
        Ruedy and Schweitzer, 2010; Shao and Skarlicki, 2009). As  research in
        this vein suggests, mindfulness contributes to performance by improving 
        cognitive flexibility and alertness (Moore and Malinowski, 2009; Zeidan
        et al., 2010)  and guarding against distractions and performance
        blunders (Herndon, 2008). Taken  together, these findings raise the
        possibility that workplace mindfulness facilitates job  performance.
      - >-
        Workplace Mindfulness Mindfulness is also defined as a state (e.g.,
        Bishop et al.,  2004; Good et al., 2016; Lau et al., 2006; Tanay &
        Bernstein,  2013) of being aware of and attentive to what is taking
        place  internally and externally at that moment (Good et al., 2016;  Lau
        et al., 2006; Tanay & Bernstein, 2013). For example, Lau  et al., (2006,
        p. 1447) described mindfulness as “a mode, or  state-like quality that
        is maintained only when attention to  experience is intentionally
        cultivated with an open, nonjudg mental orientation to experience.” More
        recently, Good et al.,  (2016, p. 117) defined mindfulness as “receptive
        attention to  and awareness of present events and experience.”
      - >-
        Workplace Mindfulness Brown and Ryan (2003) further propose that,
        despite their  intertwined nature, distinctions exist between attention
        and  awareness—the insights gained by sustained awareness can  only be
        translated into specific actions by paying focused  attention to our
        behaviors or the tasks at hand (Martin,  1997). Hence, heightened
        attention to and awareness of  experiences and events should capture two
        different aspects  of mindfulness. Recent research has also emphasized
        that  attention and awareness should be distinguished from each  other
        because attention reflects an ever-changing factor of  consciousness,
        whereas awareness refers to a specific and  stable state of
        consciousness (Selart et al., in press). In the  past, attention and
        awareness have proved important to the  study of mindfulness-promoting
        practices (Brown & Ryan,  2004), as some of these practices highlight
        focused attention  whereas others emphasize awareness (Bishop et al.,
        2004).  Notably, research has yielded empirical support confirming 
        these distinctions (Feldman et al., 2007).
pipeline_tag: sentence-similarity
library_name: sentence-transformers

SentenceTransformer based on sentence-transformers/all-MiniLM-L6-v2

This is a sentence-transformers model finetuned from sentence-transformers/all-MiniLM-L6-v2. 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
Maximum Sequence Length: 350 tokens
Output Dimensionality: 384 dimensions
Similarity Function: Cosine Similarity

Model Sources

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

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 350, '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:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("zihoo/all-MiniLM-L6-v2-WMGPL")
# Run inference
sentences = [
    'what is mindfulness?',
    'Workplace Mindfulness Mindfulness is also defined as a state (e.g., Bishop et al.,  2004; Good et al., 2016; Lau et al., 2006; Tanay & Bernstein,  2013) of being aware of and attentive to what is taking place  internally and externally at that moment (Good et al., 2016;  Lau et al., 2006; Tanay & Bernstein, 2013). For example, Lau  et al., (2006, p. 1447) described mindfulness as “a mode, or  state-like quality that is maintained only when attention to  experience is intentionally cultivated with an open, nonjudg mental orientation to experience.” More recently, Good et al.,  (2016, p. 117) defined mindfulness as “receptive attention to  and awareness of present events and experience.”',
    'Workplace Mindfulness Brown and Ryan (2003) further propose that, despite their  intertwined nature, distinctions exist between attention and  awareness—the insights gained by sustained awareness can  only be translated into specific actions by paying focused  attention to our behaviors or the tasks at hand (Martin,  1997). Hence, heightened attention to and awareness of  experiences and events should capture two different aspects  of mindfulness. Recent research has also emphasized that  attention and awareness should be distinguished from each  other because attention reflects an ever-changing factor of  consciousness, whereas awareness refers to a specific and  stable state of consciousness (Selart et al., in press). In the  past, attention and awareness have proved important to the  study of mindfulness-promoting practices (Brown & Ryan,  2004), as some of these practices highlight focused attention  whereas others emphasize awareness (Bishop et al., 2004).  Notably, research has yielded empirical support confirming  these distinctions (Feldman et al., 2007).',
]
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]

Training Details

Training Dataset

Unnamed Dataset

Size: 160,000 training samples
Columns: sentence_0, sentence_1, sentence_2, and label

Approximate statistics based on the first 1000 samples:

	sentence_0	sentence_1	sentence_2	label
type	string	string	string	float
details	min: 5 tokens mean: 9.0 tokens max: 25 tokens	min: 94 tokens mean: 254.31 tokens max: 350 tokens	min: 94 tokens mean: 253.05 tokens max: 350 tokens	min: -9.79 mean: 3.84 max: 20.17

Samples:

sentence_0	sentence_1	sentence_2	label
`why is mindfulness used at work`	Assessing Facets of Doing so, the present endeavor makes three contributions to the literature. First, using the multidimensional scale developed in the present work, we will provide first insights into the differential validities of subfacets of mind fulness for key work outcomes. This will foster a refined understanding of the mechanisms of action inherent to mindfulness and help understand why mindfulness matters for which work outcome (Bishop, Lau, Shapiro, Carlson, Anderson, Carmody, Segal, Abbey, Speca, Velting, & Devins, 2004; Shapiro, Carlson, Astin, & Freedman, 2006). Second, although prominent mindfulness theories and scholarly work on mindfulness in the clinical area suggest that mindfulness consists of multiple subfacets (Baer et al., 2006; Bishop et al., 2004), research on mindfulness in the context of work has almost exclusively operationalized mindfulness by assessing the awareness component (for an exception see Liang et al., 2017). This bears the risk of con...	Assessing Facets of Over the last 7 years, research into mindfulness in the context of work has been gaining momentum and there is a growing body of research pro viding initial evidence on the benefits of mindfulness for core workplace outcomes. Especially health and well-being-related outcomes have been at the center of research attention, but also interpersonal relationships, lead ership and performance outcomes (for reviews and meta-analyses see Eby, Allen, Conley, Williamson, Henderson, & Mancini, 2019; Good, Lyddy, Glomb, Bono, Brown, Duffy, Baer, Brewer, & Lazar, 2016; Mesmer-Magnus, Manapragada, Viswesvaran, & Allen, 2017). Also, practitioners have become increasingly interested in mindfulness and its applications in the context of work. Organizations including Google, AETNA, IBM, or SAP, have started offering mindfulness trainings to their workforce (Hyland, Lee, & Mills, 2015). With the first empirical studies appearing in the scientific IO literature 8 years ago (H...	`-1.3994250297546387`
`who developed mindfulness scales`	MAAS FMI A variety of measures of mindfulness have been constructed such as the MAAS (Brown & Ryan, 2003), the FMI (Buchheld et al., 2001), the Toronto Mindfulness Scale (TMS) (Lau et al., 2006), the Kentucky Inventory of Mindfulness (KIMS) (Baer, Smith & Allen, 2004), the Cognitive and Affective Mindfulness Scale (Feldman, Hayes, Kumar, Greeson & Laurenceau, 2007) and the Southampton Mindfulness Questionnaire (Chadwick, Hember, Symes, Peters, Kuipers, & Dagnan, 2008). These scales differ because some measure mindfulness as a unidimensional construct versus a multi-faceted construct (Baer et al., 2006), while others measure mindfulness as a trait-like or state-like construct (Dane, 2011). Some consider only the mental state, whereas others include bodily sensations and experience (Grossman, 2008). Furthermore, some measures (e.g. KIMS) include the reported ability to verbally describe experience (e.g. ‘I am good at finding the words to describe my feelings’), while othe...	`Workplace Mindfulness Mindfulness is widely considered as “paying attention in a par ticular way: on purpose, in the present moment, and nonjudg mentally” (Kabat-Zinn, 1994, p. 4). However, scholars have not reached a consensus on the essential features of mindful ness, with various conceptualizations such as a set of skills, a state, a trait, and a cognitive process. In what follows, we sum marize the prevailing views of mindfulness in the literature.`	`8.103286743164062`
`what measures mindfulness`	Workplace Mindfulness Scholars have developed several measures of mindfulness (Table 1). These measures help us understand the construct of mindfulness, but they are very different in terms of con ceptualization, factor structure, scoring, reliability, and validity. For example, the Freiburg Mindfulness Inventory (FMI; Buchheld et al., 2001) and Toronto Mindfulness Scale (TMS; Lau et al., 2006) were developed to measure states of mindfulness. The Mindfulness Attention and Awareness Scale (MAAS; Brown & Ryan, 2003), Cognitive and Affec tive Mindfulness Scale—Revised (CAMS-R; Feldman et al., 2007), and Philadelphia Mindfulness Questionnaire (PMQ; Cardaciotto et al., 2008) have been employed to measure mindfulness as a trait. The Five Facet Mindfulness Question naire (FFMQ; Baer et al., 2006), Experiences Questionnaire (EQ; Fresco et al., 2007), and Kentucky Inventory of Mind fulness Skills (KIMS; Baer et al., 2004) seek to measure mindfulness skills. The Southampton Mindfulne...	Workplace Mindfulness Given this background, our conceptualization is expected to be appropriate and valuable in the workplace because compared with the general mindfulness scales, the Work place Mindfulness Scale can measure individual mindfulness in the work context more accurately and relevantly. Practi cally speaking, adopting a skill perspective emphasizing the variability of mindfulness provides useful guidance to employees and organizations, as they aim to improve indi viduals’ mindfulness by implementing interventions. The skill view also assumes a degree of stability for mindful ness—that is, this construct is influenced by contextual fac tors but remains steady over a period of time.	`1.8723740577697754`

Loss: gpl.toolkit.loss.MarginDistillationLoss

Training Hyperparameters

Non-Default Hyperparameters

per_device_train_batch_size: 16
per_device_eval_batch_size: 16
num_train_epochs: 1
max_steps: 10000
multi_dataset_batch_sampler: round_robin

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: no
prediction_loss_only: True
per_device_train_batch_size: 16
per_device_eval_batch_size: 16
per_gpu_train_batch_size: None
per_gpu_eval_batch_size: None
gradient_accumulation_steps: 1
eval_accumulation_steps: None
torch_empty_cache_steps: None
learning_rate: 5e-05
weight_decay: 0.0
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
max_grad_norm: 1
num_train_epochs: 1
max_steps: 10000
lr_scheduler_type: linear
lr_scheduler_kwargs: {}
warmup_ratio: 0.0
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: False
fp16_opt_level: O1
half_precision_backend: auto
bf16_full_eval: False
fp16_full_eval: False
tf32: None
local_rank: 0
ddp_backend: None
tpu_num_cores: None
tpu_metrics_debug: False
debug: []
dataloader_drop_last: 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: batch_sampler
multi_dataset_batch_sampler: round_robin

Training Logs

Epoch	Step	Training Loss
0.05	500	32.954
0.1	1000	29.8033
0.15	1500	29.0685
0.2	2000	29.799
0.25	2500	28.8365
0.3	3000	28.9655
0.35	3500	29.0616
0.4	4000	29.378
0.45	4500	29.0731
0.5	5000	27.8961
0.55	5500	28.9225
0.6	6000	29.1866
0.65	6500	28.4707
0.7	7000	28.291
0.75	7500	28.4819
0.8	8000	28.5333
0.85	8500	27.9674
0.9	9000	29.8078
0.95	9500	27.0718
1.0	10000	29.6496

Framework Versions

Python: 3.11.11
Sentence Transformers: 3.3.1
Transformers: 4.47.1
PyTorch: 2.5.1+cu124
Accelerate: 1.2.1
Datasets: 3.2.0
Tokenizers: 0.21.0

Citation

BibTeX

Sentence Transformers

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