Add new SentenceTransformer model.

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "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
+}

README.md

@@ -0,0 +1,540 @@
+---
+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: what is mindfulness at work
+  sentences:
+  - First, we define awareness as employees’ skills of being aware of their internal
+    experiences (e.g., mood and body) and the external environment (e.g., colleagues,
+    working relationships, and office environment) in work situations. Thus, the awareness
+    dimension incorporates both internal and external factors (Brown & Ryan, 2003).
+    Individuals have awareness when they are able to observe their own thoughts and
+    feelings as well as what is occurring in the environment. Thus, mindfulness entails
+    awareness of “phenomena occurring both externally and internally” (Dane, 2011,
+    p. 1000). This understanding is embedded in metacognitive skills, in the sense
+    that employees’ conscious return to mindfulness is an actionable practice that
+    involves recognizing that multiple response options exist for every stimulus encountered
+    at work (Dane & Brummel, 2014; Zivnuska et al., 2016). Prior research has suggested
+    that the basic feature of mindfulness is a metacognitive skill related to one’s
+    awareness—that is, objective awareness and following of internal experiences and
+    external events (Wells, 2002). As such, workplace mindfulness induces a metacognitive
+    mode of being fully aware of the current moment.
+  - 'A widely recognized and accepted view argues that mindfulness can be learned
+    and practiced as a set of skills through specific training (e.g., Baer et al.,
+    2004, 2006; Fresco et al., 2007). For example, Baer et al. (2004) emphasized that
+    mindfulness skills are characterized by observing, describing, acting with awareness,
+    and accepting without judgment. Baer et al. (2006) indicated that mindfulness
+    encompasses five clear and interpretable facets of skills: nonreactivity, observing,
+    acting with awareness, describing, and nonjudging. Considering the malleability
+    of individuals at work, we adopt the skill view when developing our workplace
+    mindfulness scale to highlight that individual mindfulness at work can be trained
+    and improved. Indeed, individuals differ from one another in terms of their ability
+    to be mindful (Brown & Ryan, 2003; Kabat-Zinn, 1994). The changeability of mindfulness
+    underlines that this skill can be learned, trained, and improved through mindfulness
+    practices (Bishop et al., 2004; Walach et al., 2006). Workplace mindfulness differs
+    from both personality, which is difficult to change in the short term, and an
+    individual state that experiences large fluctuations on a daily basis (Hülsheger
+    et al., 2013; Olafsen, 2017).'
+  - 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 conceptualization, 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 Affective 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
+    Questionnaire (FFMQ; Baer et al., 2006), Experiences Questionnaire (EQ; Fresco
+    et al., 2007), and Kentucky Inventory of Mindfulness Skills (KIMS; Baer et al.,
+    2004) seek to measure mindfulness skills. The Southampton Mindfulness Questionnaire
+    (SMQ; Chadwick et al., 2008) and Mindfulness/Mindlessness Scale (MMS; Haigh et
+    al., 2011) are intended to measure mindfulness as a cognitive process.
+- source_sentence: define mindful attention
+  sentences:
+  - Second, we define attention as the skills of employees to focus their attention
+    on the present moment in work situations, and effectively turn their attention
+    back to the present in the face of interference. Sustained attention to the present
+    experience has been widely acknowledged as a key factor in mindfulness research
+    (Bishop et al., 2004). As a heightened sensitivity to a restricted range of experience,
+    attention implies that individuals pay full attention to the present and are not
+    susceptible to any distractions; even when they encounter interference, they do
+    not take too long to address it or have difficulty refocusing. Indeed, self-regulation
+    of attention allows for increased recognition of mental events in the present
+    moment (Bishop et al., 2004), which is also in line with the notion of metacognitive
+    skills—that is, mindful employees have the ability to intentionally regulate and
+    control their attention (Baer, 2003; Jankowski & Holas, 2014). This skill helps
+    employees not only maintain sustained attention, but also return from distractions
+    caused by irrelevant stimuli (Bishop et al., 2004; Teasdale, 1999). In essence,
+    it prevents their minds from wandering away from the present situation to potentially
+    negative conceptualizing (Kudesia, 2019; Schooler et al., 2011). Supporting this
+    notion, Fernandez-Duque et al. (2000) have stated that conscious regulation of
+    and control for attention directly refers to metacognitive skills.
+  - 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 mindfulness 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 comprises employees’ metacognitive skills within the work
+    setting 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).
+  - 'A widely recognized and accepted view argues that mindfulness can be learned
+    and practiced as a set of skills through specific training (e.g., Baer et al.,
+    2004, 2006; Fresco et al., 2007). For example, Baer et al. (2004) emphasized that
+    mindfulness skills are characterized by observing, describing, acting with awareness,
+    and accepting without judgment. Baer et al. (2006) indicated that mindfulness
+    encompasses five clear and interpretable facets of skills: nonreactivity, observing,
+    acting with awareness, describing, and nonjudging. Considering the malleability
+    of individuals at work, we adopt the skill view when developing our workplace
+    mindfulness scale to highlight that individual mindfulness at work can be trained
+    and improved. Indeed, individuals differ from one another in terms of their ability
+    to be mindful (Brown & Ryan, 2003; Kabat-Zinn, 1994). The changeability of mindfulness
+    underlines that this skill can be learned, trained, and improved through mindfulness
+    practices (Bishop et al., 2004; Walach et al., 2006). Workplace mindfulness differs
+    from both personality, which is difficult to change in the short term, and an
+    individual state that experiences large fluctuations on a daily basis (Hülsheger
+    et al., 2013; Olafsen, 2017).'
+- source_sentence: which definition of mindfulness is based on the cognitive process?
+  sentences:
+  - In the information processing framework, mindfulness is regarded as a cognitive
+    process (Chadwick et al., 2008; Haigh et al., 2011; Langer, 1989). According to
+    Langer (1989, p. 4), mindfulness is “a general style or mode of functioning through
+    which the individual actively engages in reconstructing the environment through
+    creating new categories or distinctions, thus directing attention to new contextual
+    cues that may be consciously controlled or manipulated as appropriate.” She proposed
+    that mindfulness includes novelty seeking, engagement, novelty producing, and
+    flexibility. The first two aspects refer to one’s orientation to the environment;
+    the latter two refer to how an individual operates within the environment (Bodner
+    & Langer, 2001).
+  - We adopt the view of mindfulness as a set of skills (Baer et al., 2004, 2006;
+    Fresco et al., 2007). The practice of mindfulness meditation highlights the necessity
+    of conceptualizing mindfulness as a skill that can be cultivated (Baer et al.,
+    2004). To be specific, mindfulness can be a metacognitive practice that entails
+    monitoring and adjusting one’s information processing (Fernandez-Duque et al.,
+    2000; Kudesia, 2019; Nelson, 1996); it can be improved by the fundamental meditation
+    technique (Kabat-Zinn, 1994). Mindfulness training allows individuals to become
+    aware of their internal feelings and external stimuli without reacting to them
+    (Hofmann et al., 2010). In addition to allowing for mindfulness interventions,
+    a skill-based conceptualization of workplace mindfulness is sensitive to other
+    external factors, such as the working environment (Kudesia, 2019; Kudesia & Nyima,
+    2015). Indeed, skills should be considered context-specific because they have
+    varied expressions in different situations (Attewell, 1990), reflecting the focal
+    individual’s behavioral reactions at work toward unique experiences, events, and
+    environments. This view aligns with our definition and focus—that is, the workplace
+    situation as a specific context. We also emphasize that in a working system, we
+    cannot assess a person’s mindfulness without considering the people and the external
+    environment surrounding that individual.
+  - First, we define awareness as employees’ skills of being aware of their internal
+    experiences (e.g., mood and body) and the external environment (e.g., colleagues,
+    working relationships, and office environment) in work situations. Thus, the awareness
+    dimension incorporates both internal and external factors (Brown & Ryan, 2003).
+    Individuals have awareness when they are able to observe their own thoughts and
+    feelings as well as what is occurring in the environment. Thus, mindfulness entails
+    awareness of “phenomena occurring both externally and internally” (Dane, 2011,
+    p. 1000). This understanding is embedded in metacognitive skills, in the sense
+    that employees’ conscious return to mindfulness is an actionable practice that
+    involves recognizing that multiple response options exist for every stimulus encountered
+    at work (Dane & Brummel, 2014; Zivnuska et al., 2016). Prior research has suggested
+    that the basic feature of mindfulness is a metacognitive skill related to one’s
+    awareness—that is, objective awareness and following of internal experiences and
+    external events (Wells, 2002). As such, workplace mindfulness induces a metacognitive
+    mode of being fully aware of the current moment.
+- source_sentence: what is acceptance in mindfulness
+  sentences:
+  - 'Mindfulness is widely considered as “paying attention in a particular way: on
+    purpose, in the present moment, and nonjudgmentally” (Kabat-Zinn, 1994, p. 4).
+    However, scholars have not reached a consensus on the essential features of mindfulness,
+    with various conceptualizations such as a set of skills, a state, a trait, and
+    a cognitive process. In what follows, we summarize the prevailing views of mindfulness
+    in the literature.'
+  - Second, we define attention as the skills of employees to focus their attention
+    on the present moment in work situations, and effectively turn their attention
+    back to the present in the face of interference. Sustained attention to the present
+    experience has been widely acknowledged as a key factor in mindfulness research
+    (Bishop et al., 2004). As a heightened sensitivity to a restricted range of experience,
+    attention implies that individuals pay full attention to the present and are not
+    susceptible to any distractions; even when they encounter interference, they do
+    not take too long to address it or have difficulty refocusing. Indeed, self-regulation
+    of attention allows for increased recognition of mental events in the present
+    moment (Bishop et al., 2004), which is also in line with the notion of metacognitive
+    skills—that is, mindful employees have the ability to intentionally regulate and
+    control their attention (Baer, 2003; Jankowski & Holas, 2014). This skill helps
+    employees not only maintain sustained attention, but also return from distractions
+    caused by irrelevant stimuli (Bishop et al., 2004; Teasdale, 1999). In essence,
+    it prevents their minds from wandering away from the present situation to potentially
+    negative conceptualizing (Kudesia, 2019; Schooler et al., 2011). Supporting this
+    notion, Fernandez-Duque et al. (2000) have stated that conscious regulation of
+    and control for attention directly refers to metacognitive skills.
+  - Brown and Ryan (2003, 2004) also suggest that acceptance, which is characterized
+    by openness or receptivity to experiences and events, is a key component of mindfulness
+    and is not redundant with awareness. Although they consider this dimension to
+    be subsumed within the individual’s capacity to sustain attention to and remain
+    aware of the present moment, acceptance remains a useful facet of mindfulness
+    to address. It reflects the individual’s acceptance of internal and external phenomena
+    without judging them (Baer, 2003). Research has also supported the recognition
+    of acceptance as a dimension of mindfulness (Baer et al., 2004, 2006; Buchheld
+    et al., 2001).
+- source_sentence: what is acceptance in mindfulness
+  sentences:
+  - Second, we define attention as the skills of employees to focus their attention
+    on the present moment in work situations, and effectively turn their attention
+    back to the present in the face of interference. Sustained attention to the present
+    experience has been widely acknowledged as a key factor in mindfulness research
+    (Bishop et al., 2004). As a heightened sensitivity to a restricted range of experience,
+    attention implies that individuals pay full attention to the present and are not
+    susceptible to any distractions; even when they encounter interference, they do
+    not take too long to address it or have difficulty refocusing. Indeed, self-regulation
+    of attention allows for increased recognition of mental events in the present
+    moment (Bishop et al., 2004), which is also in line with the notion of metacognitive
+    skills—that is, mindful employees have the ability to intentionally regulate and
+    control their attention (Baer, 2003; Jankowski & Holas, 2014). This skill helps
+    employees not only maintain sustained attention, but also return from distractions
+    caused by irrelevant stimuli (Bishop et al., 2004; Teasdale, 1999). In essence,
+    it prevents their minds from wandering away from the present situation to potentially
+    negative conceptualizing (Kudesia, 2019; Schooler et al., 2011). Supporting this
+    notion, Fernandez-Duque et al. (2000) have stated that conscious regulation of
+    and control for attention directly refers to metacognitive skills.
+  - Brown and Ryan (2003, 2004) also suggest that acceptance, which is characterized
+    by openness or receptivity to experiences and events, is a key component of mindfulness
+    and is not redundant with awareness. Although they consider this dimension to
+    be subsumed within the individual’s capacity to sustain attention to and remain
+    aware of the present moment, acceptance remains a useful facet of mindfulness
+    to address. It reflects the individual’s acceptance of internal and external phenomena
+    without judging them (Baer, 2003). Research has also supported the recognition
+    of acceptance as a dimension of mindfulness (Baer et al., 2004, 2006; Buchheld
+    et al., 2001).
+  - 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](https://www.SBERT.net) model finetuned from [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/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](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) <!-- at revision fa97f6e7cb1a59073dff9e6b13e2715cf7475ac9 -->
+- **Maximum Sequence Length:** 350 tokens
+- **Output Dimensionality:** 384 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': 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:
+
+```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("zihoo/all-MiniLM-L6-v2-WMGPL")
+# Run inference
+sentences = [
+    'what is acceptance in mindfulness',
+    'Brown and Ryan (2003, 2004) also suggest that acceptance, which is characterized by openness or receptivity to experiences and events, is a key component of mindfulness and is not redundant with awareness. Although they consider this dimension to be subsumed within the individual’s capacity to sustain attention to and remain aware of the present moment, acceptance remains a useful facet of mindfulness to address. It reflects the individual’s acceptance of internal and external phenomena without judging them (Baer, 2003). Research has also supported the recognition of acceptance as a dimension of mindfulness (Baer et al., 2004, 2006; Buchheld et al., 2001).',
+    '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]
+```
+
+<!--
+### 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.*
+-->
+
+<!--
+## 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: 160,000 training samples
+* Columns: <code>sentence_0</code>, <code>sentence_1</code>, <code>sentence_2</code>, and <code>label</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | sentence_0                                                                       | sentence_1                                                                            | sentence_2                                                                            | label                                                              |
+  |:--------|:---------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:-------------------------------------------------------------------|
+  | type    | string                                                                           | string                                                                                | string                                                                                | float                                                              |
+  | details | <ul><li>min: 5 tokens</li><li>mean: 8.74 tokens</li><li>max: 14 tokens</li></ul> | <ul><li>min: 102 tokens</li><li>mean: 234.76 tokens</li><li>max: 350 tokens</li></ul> | <ul><li>min: 102 tokens</li><li>mean: 232.57 tokens</li><li>max: 350 tokens</li></ul> | <ul><li>min: -6.82</li><li>mean: 5.05</li><li>max: 19.99</li></ul> |
+* Samples:
+  | sentence_0                                                               | sentence_1                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | sentence_2                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | label                            |
+  |:-------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------|
+  | <code>which dimensions of mindfulness are useful in the workplace</code> | <code>While Brown and Ryan (2003, 2004) highlight the three key components of mindfulness and subsequent research has largely agreed upon this framework (Bishop et al., 2004), existing scales—including the one developed by Brown and Ryan (2003)—do not actually include all three components. Only by capturing the entire set of dimensions of workplace mindfulness can we fully understand this construct and examine its applicability in the workplace. Notably, although other dimensions have been examined in existing scales, some of them are not primarily relevant to the work context. More importantly, this research does not adopt an all-encompassing approach, but rather draws on just Brown and Ryan’s theory (2003, 2004) to develop the dimensions.</code>                                                                                                                                                                                                                                                                    | <code>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, nonjudgmental orientation to experience.” More recently, Good et al., (2016, p. 117) defined mindfulness as “receptive attention to and awareness of present events and experience.</code>                                                                                                                                                                                                                                                                                                                                                       | <code>7.988612174987793</code>   |
+  | <code>how do we understand mindfulness in the workplace?</code>          | <code>While Brown and Ryan (2003, 2004) highlight the three key components of mindfulness and subsequent research has largely agreed upon this framework (Bishop et al., 2004), existing scales—including the one developed by Brown and Ryan (2003)—do not actually include all three components. Only by capturing the entire set of dimensions of workplace mindfulness can we fully understand this construct and examine its applicability in the workplace. Notably, although other dimensions have been examined in existing scales, some of them are not primarily relevant to the work context. More importantly, this research does not adopt an all-encompassing approach, but rather draws on just Brown and Ryan’s theory (2003, 2004) to develop the dimensions.</code>                                                                                                                                                                                                                                                                    | <code>In the information processing framework, mindfulness is regarded as a cognitive process (Chadwick et al., 2008; Haigh et al., 2011; Langer, 1989). According to Langer (1989, p. 4), mindfulness is “a general style or mode of functioning through which the individual actively engages in reconstructing the environment through creating new categories or distinctions, thus directing attention to new contextual cues that may be consciously controlled or manipulated as appropriate.” She proposed that mindfulness includes novelty seeking, engagement, novelty producing, and flexibility. The first two aspects refer to one’s orientation to the environment; the latter two refer to how an individual operates within the environment (Bodner & Langer, 2001).</code>                                                                                                                                                                                                                                                             | <code>3.691136598587036</code>   |
+  | <code>what does mindfulness mean</code>                                  | <code>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 conceptualization, 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 Affective 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 Questionnaire (FFMQ; Baer et al., 2006), Experiences Questionnaire (EQ; Fresco et al., 2007), and Kentucky Inventory of Mindfulness Skills (KIMS; Baer et al., 2004) seek to measure mindfulness skills. The Southampton Mindfulness Questionnaire (SMQ; Chadwick et al....</code> | <code>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 th...</code> | <code>0.38913965225219727</code> |
+* Loss: <code>gpl.toolkit.loss.MarginDistillationLoss</code>
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `num_train_epochs`: 1
+- `max_steps`: 1000
+- `multi_dataset_batch_sampler`: round_robin
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `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`: 1000
+- `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
+
+</details>
+
+### Training Logs
+| Epoch | Step | Training Loss |
+|:-----:|:----:|:-------------:|
+| 0.05  | 500  | 44.9354       |
+| 0.1   | 1000 | 41.9204       |
+
+
+### Framework Versions
+- Python: 3.11.11
+- Sentence Transformers: 3.3.1
+- Transformers: 4.47.1
+- 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",
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,26 @@
+{
+  "_name_or_path": "./output/WM_model",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

config_sentence_transformers.json

@@ -0,0 +1,10 @@
+{
+  "__version__": {
+    "sentence_transformers": "3.3.1",
+    "transformers": "4.47.1",
+    "pytorch": "2.5.1+cu121"
+  },
+  "prompts": {},
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4bb605f19cf448a4322540993221f3180386193ad66ecf3f36cf8df8ef93b44c
+size 90864192

modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 350,
+  "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,37 @@
+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,65 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "max_length": 128,
+  "model_max_length": 350,
+  "never_split": null,
+  "pad_to_multiple_of": null,
+  "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}