Add new SentenceTransformer model
Browse files- 1_Pooling/config.json +10 -0
- README.md +797 -0
- config.json +31 -0
- config_sentence_transformers.json +10 -0
- model.safetensors +3 -0
- modules.json +20 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +58 -0
- vocab.txt +0 -0
1_Pooling/config.json
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false,
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"include_prompt": true
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}
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README.md
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1 |
+
---
|
2 |
+
tags:
|
3 |
+
- sentence-transformers
|
4 |
+
- sentence-similarity
|
5 |
+
- feature-extraction
|
6 |
+
- generated_from_trainer
|
7 |
+
- dataset_size:43494
|
8 |
+
- loss:TripletLoss
|
9 |
+
base_model: allenai/specter2_aug2023refresh_base
|
10 |
+
widget:
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11 |
+
- source_sentence: This paper aims to address the impact of a person's motivation
|
12 |
+
to study entrepreneurship on their subsequent levels of performance in terms of
|
13 |
+
the generation of business ideas, while taking into account the effect of student
|
14 |
+
team behaviour. The paper hypothesises that both intrinsic and extrinsic motivation
|
15 |
+
as well as team behaviour influence the learning outcome and that team behaviour
|
16 |
+
moderates the relationship between motivation and learning outcomes. A survey
|
17 |
+
was used to generate data. A total of students, who participated in pre-programme,
|
18 |
+
and post-programme surveys, provided the sample data. First, explorative factor
|
19 |
+
analyses were employed to examine the latent variables. Second, hierarchical lineal
|
20 |
+
regression analyses were carried out to test the proposed hypotheses. Results
|
21 |
+
show that intrinsic motivation has a negative effect on the learning outcome while
|
22 |
+
extrinsic motivation had a positive one. However, the team (and in particular
|
23 |
+
the resources that become available) positively moderates the relationship between
|
24 |
+
the intrinsic motivation and the outcomes.
|
25 |
+
sentences:
|
26 |
+
- During recent years, the development of professional competencies is more frequently
|
27 |
+
linked with the processes of performance, evaluation and career development of
|
28 |
+
the human capital. Their formation requires focused actions to improve particular
|
29 |
+
knowledge, skills and abilities. The analysis of the status and trends in the
|
30 |
+
professional competences of the human capital in the agricultural sector in Bulgaria
|
31 |
+
reveals a number of opportunities for their effective use and management. The
|
32 |
+
purpose of this article is to outline the professional competences of the human
|
33 |
+
capital in the agricultural sector by analysing and presenting the trends in their
|
34 |
+
development. The study covers the period between January and November . It is
|
35 |
+
based on data from polls specially designed for the purpose of the analysis, direct
|
36 |
+
contacts, corporate documentation, etc. The interviews are applied to specify
|
37 |
+
the data and information. The issues and prospects for the development of professional
|
38 |
+
competences of the human capital in agriculture are presented and rated according
|
39 |
+
to the responses received.
|
40 |
+
- 'Background: Phthalates are chemical compounds that have the tendency to migrate
|
41 |
+
into food and beverages, thereby leading to negative health consequences. Aims:
|
42 |
+
was to assess the knowledge of phthalates and practices relating to plastic use
|
43 |
+
among adults residing in Jeddah, Saudi Arabia, with an emphasis on cheese wrapped
|
44 |
+
in plastic materials. Material and Methods: A total of adult participants completed
|
45 |
+
an online questionnaire consisting of three sections ) socio-demographic characteristics,
|
46 |
+
) knowledge-related phthalates, and ) practices related to plastic use. All collected
|
47 |
+
data were verified and analyzed using the Statistical Package for Social Sciences
|
48 |
+
(SPSS). Results: Our findings revealed that % of the respondents had poor knowledge
|
49 |
+
regarding plastics and phthalates with gender being a significant factor (p= ).
|
50 |
+
The usage rate of plastic material was found to be remarkably high with % keeping
|
51 |
+
the purchased cheese either in its original plastic wrapping or placed inside
|
52 |
+
plastic boxes. Moreover, % never viewed the safe plastic number before purchasing
|
53 |
+
the food products. However Interestingly enough, the type of plastics did not
|
54 |
+
influence participant''s decision-making process when it came down to purchasing
|
55 |
+
or consuming cheese ( % & %, respectively). Respondents who had poor practice
|
56 |
+
represented up to %, while those with poor knowledge and practice constituted
|
57 |
+
%. However, no significant link between these two factors could be established.
|
58 |
+
Conclusions: Poor awareness levels concerning phthalates along with imprudent
|
59 |
+
usage rates for plastics were observed among adults living within Jeddah city''s
|
60 |
+
boundaries; thus, appropriate interventions aimed at raising awareness need implementation
|
61 |
+
so as minimize exposure risks associated with this issue. Keywords: Phthalate,
|
62 |
+
Plastic use, Cheese, Knowledge, Practice, Saudi Arabia.'
|
63 |
+
- 'Aims: Chronic low-grade inflammation is an important cause of systemic insulin
|
64 |
+
resistance and play a central role in the pathophysiology of gestational diabetes
|
65 |
+
mellitus (GDM). This study aimed to investigate the correlation between neutrophil(N)
|
66 |
+
in first-trimester pregnancy and the development of GDM. Methods: women with GDM
|
67 |
+
and women without GDM were included in this retrospective study. Demographic,
|
68 |
+
pregnancy variables, white blood cell(WBC), neutrophil(N) counts, Neutrophil-to-Lymphocyte
|
69 |
+
Ratio(NLR), clinical biochemical characteristics, delivery information were got
|
70 |
+
from all subjects. Logistic regression analysis with forward stepwise selection
|
71 |
+
were used to determine the independent risk factors for the development of GDM.
|
72 |
+
Result: GDM patients had much higher level of blood glucose(BG), triglyceride(TG),
|
73 |
+
fetal birth weight, WBC, N counts and NLR than women without GDM. There were significant
|
74 |
+
positive association between N counts and -hour BG, hour BG, glycosylated hemoglobin(HbA0c),
|
75 |
+
pregnancy body mass index(BMI), and homeostasis model assessment for insulin resistance(HOMA-IR).
|
76 |
+
Additionally, there were significant negative association between N and quantitative
|
77 |
+
insulin sensitivity check index (QUICKI) and low-density lipoprotein(LDL) cholesterol.
|
78 |
+
After adjusting confounding variables, we found N counts was an independent factor
|
79 |
+
for the development of GDM (OR = ; % confidence interval, to ), regardless the
|
80 |
+
history of GDM (OR = for without GDM history). Conclusion: N counts in first-trimester
|
81 |
+
pregnancy is closely associated with the development of GDM in pregnant women.
|
82 |
+
Disclosure T. Sun: None. F. Meng: None. R. Zhang: None. Z. Yu: None. S. Zang:
|
83 |
+
None. J. Liu: None. M. Yang: None. Funding Shanghai Fifth People''s Hospital Research
|
84 |
+
Project Plan; Minhang District Natural Science Research'
|
85 |
+
- source_sentence: 'ABSTRACT There are many forms of alternative medicines for treatment
|
86 |
+
of any type of ailment, applied kinesiology being one of them. It is a scientific
|
87 |
+
technique in which claims to diagnose illness or choose treatment by testing muscles
|
88 |
+
for strength and weakness. A widespread use of applied kinesiology in dentistry
|
89 |
+
has resulted in a complete reevaluation and understanding of patient''s overall
|
90 |
+
health and well-being. Concepts of structural integration, selection of materials
|
91 |
+
for restoration, adjunctive therapies, equipments used for joint vibration analysis,
|
92 |
+
have been described in this article. Review of literature has shown positive response
|
93 |
+
by many dentists for this natural type of medicine. This article presents a review
|
94 |
+
in which applied kinesiology and its uses in dentistry are reviewed and analyzed.
|
95 |
+
How to cite this article Singh DA, Ram SM, Shah N, Nadgere J. Applied Kinesiology:
|
96 |
+
An Unexplored Path in Dentistry. J Contemp Dent ; ( ): - .'
|
97 |
+
sentences:
|
98 |
+
- Abstract Anti-CD00 monoclonal antibodies are widely used in clinical transplantation
|
99 |
+
to prevent acute allograft rejection. Although their effects on T lymphocytes
|
100 |
+
have been extensively studied, their impact on human dendritic cells (DC) has
|
101 |
+
never been reported. Furthermore, the role of the IL- in DC functions has not
|
102 |
+
yet been fully elucidated. In this study, we confirm that the stimulation of human
|
103 |
+
monocyte-derived DC with LPS strongly induced the expression of CD00 and that
|
104 |
+
LPS-matured DC also expressed the and chain of the IL-0R. We also showed that
|
105 |
+
adding anti-CD00 monoclonal antibodies to LPS induced a decrease in IL- , IL-
|
106 |
+
, TNF-, IL- , and IFN- production and an increase in IL- synthesis by DC compared
|
107 |
+
with stimulation with LPS alone. Furthermore, we showed that these modifications
|
108 |
+
diminished the T helper priming ability of DC and polarized the alloimmune response
|
109 |
+
toward TH0. In contrast, humanized anti-CD00 monoclonal antibodies did not affect
|
110 |
+
the up-regulation of CD00, CD00, CD00, HLADR, or CD00 induced upon LPS stimulation.
|
111 |
+
Taken together, this study discloses some previously unrecognized effects of anti-CD00
|
112 |
+
monoclonal antibodies on DC that may contribute to their clinical efficacy. In
|
113 |
+
addition, this study also shed some light on the role of the IL- in human DC activation.
|
114 |
+
- It is argued that setting one over zero to the upthorn symbol, elsewhere used
|
115 |
+
to denote bottom, as is done in common meadows, is conceptually meaningful for
|
116 |
+
elementary mathematics. We consider the arguments in its favour, for the restricted
|
117 |
+
context of use in elementary arithmetic, to be stronger than arguments supporting
|
118 |
+
one over zero equals zero, as in Suppes-Ono division and variants of it sometimes
|
119 |
+
used in the model theory of fields as a branch of mathematical logic, or one over
|
120 |
+
zero as an unsigned infinity, as proposed by Riemann and used in the design of
|
121 |
+
wheel arithmetic, or one over zero as positive infinity, as in transrational arithmetic.
|
122 |
+
- 'ABSTRACT Background The aim of this study was to determine the prevalence and
|
123 |
+
associated risk factors for development of musculoskeletal pain among the dental
|
124 |
+
students of 0rd, 0th year and interns, at MGM Dental College, Navi Mumbai. Materials
|
125 |
+
and Methods A valid and reliable close ended questionnaire was administered to
|
126 |
+
students of 0rd year, 0th year and interns who met the inclusion criteria. A response
|
127 |
+
rate of % was achieved. The variables included in the questionnaire were ( ) presence
|
128 |
+
of pain, ( ) awareness regarding correct posture, ( ) areas of the body affected
|
129 |
+
by pain, ( ) clinical setting, ( ) practices to reduce pain. Statistical analysis
|
130 |
+
was applied using Chi-square test. Results In this study, we found a total of
|
131 |
+
% prevalence of musculoskeletal pain among the dental students. Eighty-one percent
|
132 |
+
were unaware of the correct posture for dental clinical procedures. Statistical
|
133 |
+
significance was observed between different clinical activities and musculoskeletal
|
134 |
+
pain when Chi-square test was applied. Maximum pain was observed in the hand (
|
135 |
+
%) followed by wrist ( %) and lower back ( %). Sixty-three percent of the students
|
136 |
+
having pain performed cervical flexions and torsions to improve vision of the
|
137 |
+
oral cavity. Seventy-five percent of the students reported that they were uncomfortable
|
138 |
+
with their current working stool. Five percent of the participants performed exercises
|
139 |
+
after clinical practice of which none reported musculoskeletal pain. Conclusion
|
140 |
+
Dental students are prone to development of musculoskeletal pain due to lack of
|
141 |
+
awareness regarding correct posture, prolonged static postures, inadequate operating
|
142 |
+
stools and lack of exercises. How to cite this article Madaan V, Chaudhari A.
|
143 |
+
Prevalence and Risk Factor associated with Musculoskeletal Pain among Students
|
144 |
+
of MGM Dental College: A Cross-Sectional Survey. J Contemp Dent ; ( ): - .'
|
145 |
+
- source_sentence: 'Purpose: The purpose of this study was to determine the influence
|
146 |
+
of various factors on the extent of thermal coagulation necrosis after radiofrequency
|
147 |
+
(RF) tissue ablation using a cooled-tip electrode in bovine liver.Materials and
|
148 |
+
Methods: RF ablation was induced by a monopolar KHz-RF generator (CC- ; Radionics,Burlington,
|
149 |
+
Mass., U.S.A.) and an -G cooled-tip with single or clustered electrodes. The ablation
|
150 |
+
protocol involveda combination of varying current, ablation time, power output,
|
151 |
+
gradual or abrupt increase of this out-put, and pulsed radiofrequency techniques.
|
152 |
+
The maximum diameter of all thermal lesions which showed a color change was measured
|
153 |
+
perpendicular to the electrode axis by two observers who reached their decisions
|
154 |
+
by consensus. Twenty representative lesions were pathologically examined.Results:
|
155 |
+
With increasing current lesion diameter also increased, but above mA no further
|
156 |
+
increase was induced. Extending the ablation time to minutes for a single electrode
|
157 |
+
and minutes for a clustered electrode increased lesion diameter until a steady
|
158 |
+
state was reached. Higher power levels caused larger lesions, but above W no increase
|
159 |
+
was observed. Ample exposure time coupled with a stepwise increase in power level
|
160 |
+
induced a lesion larger than that resulting from an abrupt increase. Continuous
|
161 |
+
pulsed RF with a high current led to increased coagulation necrosis diameter.Conclusion:
|
162 |
+
These experimental findings may be useful thermotherapy. The data suggest that
|
163 |
+
all involved factors significantly affect lesion size: if the factors are better
|
164 |
+
understood, cancer thermotherapy can be better controlled.'
|
165 |
+
sentences:
|
166 |
+
- 'Purpose: We wanted to evaluate the levels of effect and safety of high-intensity
|
167 |
+
focused ultrasound ablation (HIFU) for treating patients with advanced pancreatic
|
168 |
+
cancer. Materials and Methods: Nineteen sessions of HIFU, with the patients under
|
169 |
+
general anesthesia, were performed in patients with advanced pancreatic cancer.
|
170 |
+
The change of the gray-scale of the target lesion was analyzed during HIFU, and
|
171 |
+
MRI was performed before and after HIFU. We assessed the extent of coagulative
|
172 |
+
necrosis, the change of pain and the complications after HIFU. The change of tumor
|
173 |
+
size and the survival of patients were also evaluated. Results: The average size
|
174 |
+
of tumor was cm in diameter. Eighty nine percent of the target tumors showed increased
|
175 |
+
echogenicity. On MRI, necrosis of the entire target tumor occurred in % of the
|
176 |
+
patients. After treatment, effective pain relief was noted in % of the patients.
|
177 |
+
There were no major complications. No size increase of the treated tumor was noted
|
178 |
+
during weeks of follow-up for patients. Six patients among patients who were available
|
179 |
+
for follow-up are still alive and they are receiving chemotherapy. Six patients
|
180 |
+
expired due to other disease or progression of metastasis. Conclusion: HIFU is
|
181 |
+
a safe method without any major complications, and it is effective for inducing
|
182 |
+
tumor necrosis and achieving pain control for patients with advanced pancreatic
|
183 |
+
cancer.'
|
184 |
+
- Magnetic polyacrylic cation exchange resins NDMC and magnetic polyacrylic anion
|
185 |
+
exchange resins NDMP were applied for the treatment of composite pollutants composed
|
186 |
+
of Cu(II), Ni(II) and tannic. The most efficient method was the combined process
|
187 |
+
of NDMC and NDMP(named as NDMC+NDMP). NDMC+NDMP method can remove Cu(II), Ni(II)
|
188 |
+
and tannic from composite pollutants simultaneously, and the removal efficiency
|
189 |
+
of Cu(II), Ni(II) and tannic reached %, % and %, respectively. Through further
|
190 |
+
analysis of behaviors of pre-load experiments and simultaneous removal experiments,
|
191 |
+
the results showed that there were two ways in simultaneous removal of heavy metal
|
192 |
+
ions and DOM, including adsorption of Metal-DOM complex by magnetic particle and
|
193 |
+
complexation between DOM and heavy metal ions loaded on solid phase, and the former
|
194 |
+
was the main mechanism.
|
195 |
+
- The African startup ecosystem has emerged as a dynamic driver of innovation and
|
196 |
+
economic growth, addressing local challenges and contributing to global markets.
|
197 |
+
However, African startups face unique hurdles, including funding constraints,
|
198 |
+
infrastructural deficiencies, and complex regulatory landscapes. This paper explores
|
199 |
+
strategies to build resilience among African startups by harmonizing regulatory
|
200 |
+
compliance with business innovation. It highlights the importance of financial,
|
201 |
+
operational, and cultural adaptability as key factors for sustainability, emphasizing
|
202 |
+
the role of partnerships, technology, and supportive policy frameworks in fostering
|
203 |
+
growth. Recommendations for policymakers include simplifying regulatory frameworks,
|
204 |
+
promoting digital transformation, facilitating funding access, and fostering regional
|
205 |
+
integration. By adopting a balanced approach to compliance and innovation, African
|
206 |
+
startups can strengthen their capacity to navigate challenges and leverage opportunities,
|
207 |
+
ultimately driving inclusive and sustainable development across the continent.
|
208 |
+
- source_sentence: This study examined the effect of pictorial cues on Iranian pre-intermediate
|
209 |
+
EFL learners' speaking accuracy and fluency. To do this study, Iranian pre-intermediate
|
210 |
+
EFL learners were selected out of students in a private English Language Institute.
|
211 |
+
The selected participants were divided into two equal groups; experimental group
|
212 |
+
and control group. After that, both groups were pretested by a speaking pre-test.
|
213 |
+
The experimental group was taught through using the pre-speaking strategies as
|
214 |
+
the researcher provided students with pictorial inputs. On the other hand, the
|
215 |
+
students of the control group were taught through traditional speaking activities
|
216 |
+
including repetition and over-learning. The treatment took sessions of minutes
|
217 |
+
each under the guidance of the supervisor. In the first session, the participants
|
218 |
+
were homogenized. In the second session, they were pretested. During sessions,
|
219 |
+
students were taught by using pictorial input, and in the last session after the
|
220 |
+
treatment the two groups took the speaking post-test. The results of paired t-test
|
221 |
+
and MANOVA revealed that the experimental group had better performance on their
|
222 |
+
accuracy and fluency post-test compared to their pre-test. The results also showed
|
223 |
+
that the experimental group outperformed the control group on the accuracy and
|
224 |
+
fluency post-test. Finally, implications arising from the findings and suggestions
|
225 |
+
for further research were explained.
|
226 |
+
sentences:
|
227 |
+
- 'Toward the end of World War I and during World War II, whole-blood transfusions
|
228 |
+
were the primary agent in the treatment of military traumatic hemorrhage. However,
|
229 |
+
after World War II, the fractionation of whole blood into its components became
|
230 |
+
widely accepted and replaced whole-blood transfusion to better accommodate specific
|
231 |
+
blood deficiencies, logistics, and financial reasons. This transition occurred
|
232 |
+
with very few clinical trials to determine which patient populations or scenarios
|
233 |
+
would or would not benefit from the change. A smaller population of patients with
|
234 |
+
trauma hemorrhage will require massive transfusion (> U packed red blood cells
|
235 |
+
in h) occurring in % to % of civilian and % of military traumas. Advocates for
|
236 |
+
hemostatic resuscitation have turned toward a ratio-balanced component therapy
|
237 |
+
using packed red blood cellsfresh frozen plasmaplatelet concentration in a : :
|
238 |
+
ratio due to whole-blood limited availability. However, this "reconstituted" whole
|
239 |
+
blood is associated with a significantly anemic, thrombocytopenic, and coagulopathic
|
240 |
+
product compared with whole blood. In addition, several recent military studies
|
241 |
+
suggest a survival advantage of early use of whole blood, but the safety concerns
|
242 |
+
have limited is widespread civilian use. Based on extensive military experience
|
243 |
+
as well as recent published literature, low-titer leukocyte reduced cold-store
|
244 |
+
type O whole blood carries low adverse risks and maintains its hemostatic properties
|
245 |
+
for up to days. A prospective randomized trial comparing whole blood versus ratio
|
246 |
+
balanced component therapy is proposed with rationale provided.'
|
247 |
+
- Purpose This article aims to explore recent trends in farmland rental markets
|
248 |
+
using data for the state of Illinois. Trends in the types of rental agreements
|
249 |
+
used and the relationship between the rental rate for those contracts, land values,
|
250 |
+
crop revenues, production costs, and farm returns are examined. Design/methodology/approach
|
251 |
+
Data from various sources and at different levels of aggregation for the state
|
252 |
+
of Illinois are used to provide illustrations of historical trends in farmland
|
253 |
+
rental agreements and rental rates, and how they are related to various market
|
254 |
+
and industry factors. Focus is placed on the more recent period since characterized
|
255 |
+
by high commodity price levels and volatility. Findings The majority of farmland
|
256 |
+
in the Midwest is controlled under rental agreements which are increasingly of
|
257 |
+
the fixed cash rent type. Rental rates have increased, but at a slower rate than
|
258 |
+
farm returns. Average rental and interest rates imply that land values are consistent
|
259 |
+
with the current market environment. Aggregate rental rates mask considerable
|
260 |
+
variation in farmlevel rents, only a portion of which can be explained by differences
|
261 |
+
in soil productivity. Given the current level of price volatility, the tenure
|
262 |
+
position of a farm operation has a significant effect on downside risk exposure.
|
263 |
+
Originality/value The illustrations provided in this paper should be of interest
|
264 |
+
to researchers working in the area of farmland values and rental agreements, as
|
265 |
+
well as to practitioners including farmers, landowners, and professional farm
|
266 |
+
managers. The findings should motivate additional research and recognition of
|
267 |
+
the importance of tenure position to the performance and risk exposure of grain
|
268 |
+
farms.
|
269 |
+
- 'This study investigates the blind spots in Sinclair and Coulthard''s revised
|
270 |
+
classroom discourse (CD) structure of Teacher''s Initiation, Students'' Response
|
271 |
+
and Teacher''s Feedback (IRF). The study suggests the Initiation ( ), Response
|
272 |
+
( ) and Feedback ( ) (IIRRFF) pattern which may be suitable for today''s CD. This
|
273 |
+
pattern permits equal contributions by classroom participants. The study adopts
|
274 |
+
a quantitative method for data collection; a qualitative-descriptive research
|
275 |
+
design and Information Processing Theory (IPT). Data were collected through a
|
276 |
+
questionnaire distributed to English lecturers and students from three tertiary
|
277 |
+
institutions in Nigeria. The results show a high percentage of participants who
|
278 |
+
confirmed that Sinclair and Coulthard''s IRF model has blind spots; % of the respondents
|
279 |
+
agreed that the model may lead to a limited understanding of what is taught; %
|
280 |
+
agreed that dual initiations and feedback are rejected in this model, and % strongly
|
281 |
+
agreed that the model should be expanded to accommodate other fields of language
|
282 |
+
learning. The study recommends that CD should be categorized into two major types:
|
283 |
+
the teacher''s utterances and the students'' utterances. The IIRRFF pattern that
|
284 |
+
allows teachers and students to have equal slots in every CD should be implemented.
|
285 |
+
This will encourage students'' full participation and interaction.'
|
286 |
+
- source_sentence: Abstract The movement toward open education is requiring educators
|
287 |
+
to expand and update their practice in order to keep up with the new demands being
|
288 |
+
placed on them. This study explored how educators can engage in meaningful learning
|
289 |
+
opportunities, which will facilitate the creation of expertise and knowledge,
|
290 |
+
through the use of open education resources (OER). The article describes the design
|
291 |
+
of the instrument employed to measure workplace learning through OER activity
|
292 |
+
of adult educators ( n = ) and to report its internal reliability and convergent
|
293 |
+
validity. Results indicate engagement with OER promote three levels of learning,
|
294 |
+
each connected to the different types of knowledge educators require to integrate
|
295 |
+
OER into their teaching practice.
|
296 |
+
sentences:
|
297 |
+
- Abstract We aimed to analyse postoperative cognitive dysfunction (POCD) incidence
|
298 |
+
and risk factors in elderly adults who underwent surgery for oral malignancies.
|
299 |
+
A total of elderly patients (aged years) were selected for expanded resection
|
300 |
+
of oral malignancy and cervical lymphatic dissection at our institution from December
|
301 |
+
to December . Participants were cognitively evaluated using the neuropsychological
|
302 |
+
test scale day before and days after surgery to determine whether they had developed
|
303 |
+
POCD. Based on whether POCD occurred days after surgery, patients were classified
|
304 |
+
into the POCD and non-POCD groups. Logistic regression was applied to perioperative
|
305 |
+
factors to analyse the risk factors for POCD onset. Seven days after surgery for
|
306 |
+
oral malignancy, there were ( %) POCD morbidities. Multiple factor logistic regression
|
307 |
+
analysis revealed that venerable age (odds ratio [OR] = , % confidence interval
|
308 |
+
[CI] .000, P < ), low education levels (OR = , % CI .000, P < ), hypertension
|
309 |
+
(OR = , % CI .000, P < ), dyssomnia (OR = , % CI .000, P < ), prolonged anaesthesia
|
310 |
+
(OR = , % CI .000, P < ), and intraoperative hypotension (OR = , % CI .000, P
|
311 |
+
< ) increased the POCD risk in elderly patients who underwent surgery for oral
|
312 |
+
malignancies. Venerable age, low knowledge reserve, hypertension, dyssomnia, prolonged
|
313 |
+
anaesthesia, and intraoperative hypotension are independent risk factors for POCD
|
314 |
+
in elderly patients with oral malignancies.
|
315 |
+
- 'Abstract OVERVIEW: This paper provides an overview of some fundamental aspects
|
316 |
+
of electrochemical oxidation and gives updated information on the application
|
317 |
+
of this technology to wastewater treatment. In recent years, electrochemical oxidation
|
318 |
+
has gained increasing interest due to its outstanding technical characteristics
|
319 |
+
for eliminating a wide variety of pollutants normally present in wastewaters such
|
320 |
+
as refractory organic matter, nitrogen species and microorganisms. IMPACT: The
|
321 |
+
strict disposal limits and health quality standards set by legislation may be
|
322 |
+
met by applying electrochemical oxidation. However, treatment costs have to be
|
323 |
+
cut down before fullscale application of this technology. Deployment of electrochemical
|
324 |
+
oxidation in combination with other technologies and the use of renewable sources
|
325 |
+
to power this process are two steps in this direction. APPLICATIONS: Effluents
|
326 |
+
from landfill and a wide diversity of industrial effluents including the agroindustry,
|
327 |
+
chemical, textile, tannery and food industry, have been effectively treated by
|
328 |
+
this technology. Its high efficiency together with its disinfection capabilities
|
329 |
+
makes electrooxidation a suitable technology for water reuse programs. Copyright
|
330 |
+
©️ Society of Chemical Industry'
|
331 |
+
- Abstract Predictors of academic success at university are of great interest to
|
332 |
+
educators, researchers and policymakers. With more students studying online, it
|
333 |
+
is important to understand whether traditional predictors of academic outcomes
|
334 |
+
in facetoface settings are relevant to online learning. This study modelled selfregulatory
|
335 |
+
and demographic predictors of subject grades in online and facetoface undergraduate
|
336 |
+
students. Predictors were effort regulation, grade goal, academic selfefficacy,
|
337 |
+
performance selfefficacy, age, sex, socioeconomic status (SES) and firstinfamily
|
338 |
+
status. A multigroup path analysis indicated that the models were significantly
|
339 |
+
different across learning modalities. For facetoface students, none of the model
|
340 |
+
variables significantly predicted grades. For online students, only performance
|
341 |
+
selfefficacy significantly predicted grades (small effect). Findings suggest that
|
342 |
+
learner characteristics may not function in the same way across learning modes.
|
343 |
+
Further factor analytic and hierarchical research is needed to determine whether
|
344 |
+
selfregulatory predictors of academic success continue to be relevant to modern
|
345 |
+
student cohorts. Practitioner Notes What is already known about this topic Selfregulatory
|
346 |
+
and demographic variables are important predictors of university outcomes like
|
347 |
+
grades. It is unclear whether the relationships between predictor variables and
|
348 |
+
outcomes are the same across learning modalities, as research findings are mixed.
|
349 |
+
What this paper adds Models predicting university students' grades by demographic
|
350 |
+
and selfregulatory predictors differed significantly between facetoface and online
|
351 |
+
learning modalities. Performance selfefficacy significantly predicted grades for
|
352 |
+
online students. No selfregulatory variables significantly predicted grades for
|
353 |
+
facetoface students, and no demographic variables significantly predicted grades
|
354 |
+
in either cohort. Overall, traditional predictors of grades showed no/small unique
|
355 |
+
effects in both cohorts. Implications for practice and/or policy The learner characteristics
|
356 |
+
that predict success may not be the same across learning modalities. Approaches
|
357 |
+
to enhancing success in facetoface settings are not automatically applicable to
|
358 |
+
online settings. Selfregulatory variables may not predict university outcomes
|
359 |
+
as strongly as previously believed, and more research is needed.
|
360 |
+
pipeline_tag: sentence-similarity
|
361 |
+
library_name: sentence-transformers
|
362 |
+
metrics:
|
363 |
+
- cosine_accuracy
|
364 |
+
model-index:
|
365 |
+
- name: SentenceTransformer based on allenai/specter2_aug2023refresh_base
|
366 |
+
results:
|
367 |
+
- task:
|
368 |
+
type: triplet
|
369 |
+
name: Triplet
|
370 |
+
dataset:
|
371 |
+
name: 'specter 2 '
|
372 |
+
type: specter_2_
|
373 |
+
metrics:
|
374 |
+
- type: cosine_accuracy
|
375 |
+
value: 0.9548275862068966
|
376 |
+
name: Cosine Accuracy
|
377 |
+
- type: cosine_accuracy
|
378 |
+
value: 0.9739080459770115
|
379 |
+
name: Cosine Accuracy
|
380 |
+
- task:
|
381 |
+
type: triplet
|
382 |
+
name: Triplet
|
383 |
+
dataset:
|
384 |
+
name: discipline tuned specter 2 019
|
385 |
+
type: discipline-tuned_specter_2_019
|
386 |
+
metrics:
|
387 |
+
- type: cosine_accuracy
|
388 |
+
value: 0.9740229885057471
|
389 |
+
name: Cosine Accuracy
|
390 |
+
---
|
391 |
+
|
392 |
+
# SentenceTransformer based on allenai/specter2_aug2023refresh_base
|
393 |
+
|
394 |
+
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.
|
395 |
+
|
396 |
+
## Model Details
|
397 |
+
|
398 |
+
### Model Description
|
399 |
+
- **Model Type:** Sentence Transformer
|
400 |
+
- **Base model:** [allenai/specter2_aug2023refresh_base](https://huggingface.co/allenai/specter2_aug2023refresh_base) <!-- at revision 084e9624d354a1cbc464ef6cc1e3646d236b95d9 -->
|
401 |
+
- **Maximum Sequence Length:** 512 tokens
|
402 |
+
- **Output Dimensionality:** 768 dimensions
|
403 |
+
- **Similarity Function:** Cosine Similarity
|
404 |
+
<!-- - **Training Dataset:** Unknown -->
|
405 |
+
<!-- - **Language:** Unknown -->
|
406 |
+
<!-- - **License:** Unknown -->
|
407 |
+
|
408 |
+
### Model Sources
|
409 |
+
|
410 |
+
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
|
411 |
+
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
|
412 |
+
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
|
413 |
+
|
414 |
+
### Full Model Architecture
|
415 |
+
|
416 |
+
```
|
417 |
+
SentenceTransformer(
|
418 |
+
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel
|
419 |
+
(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})
|
420 |
+
(2): Normalize()
|
421 |
+
)
|
422 |
+
```
|
423 |
+
|
424 |
+
## Usage
|
425 |
+
|
426 |
+
### Direct Usage (Sentence Transformers)
|
427 |
+
|
428 |
+
First install the Sentence Transformers library:
|
429 |
+
|
430 |
+
```bash
|
431 |
+
pip install -U sentence-transformers
|
432 |
+
```
|
433 |
+
|
434 |
+
Then you can load this model and run inference.
|
435 |
+
```python
|
436 |
+
from sentence_transformers import SentenceTransformer
|
437 |
+
|
438 |
+
# Download from the 🤗 Hub
|
439 |
+
model = SentenceTransformer("m7n/discipline-tuned_specter_2_019")
|
440 |
+
# Run inference
|
441 |
+
sentences = [
|
442 |
+
'Abstract The movement toward open education is requiring educators to expand and update their practice in order to keep up with the new demands being placed on them. This study explored how educators can engage in meaningful learning opportunities, which will facilitate the creation of expertise and knowledge, through the use of open education resources (OER). The article describes the design of the instrument employed to measure workplace learning through OER activity of adult educators ( n = ) and to report its internal reliability and convergent validity. Results indicate engagement with OER promote three levels of learning, each connected to the different types of knowledge educators require to integrate OER into their teaching practice.',
|
443 |
+
"Abstract Predictors of academic success at university are of great interest to educators, researchers and policymakers. With more students studying online, it is important to understand whether traditional predictors of academic outcomes in facetoface settings are relevant to online learning. This study modelled selfregulatory and demographic predictors of subject grades in online and facetoface undergraduate students. Predictors were effort regulation, grade goal, academic selfefficacy, performance selfefficacy, age, sex, socioeconomic status (SES) and firstinfamily status. A multigroup path analysis indicated that the models were significantly different across learning modalities. For facetoface students, none of the model variables significantly predicted grades. For online students, only performance selfefficacy significantly predicted grades (small effect). Findings suggest that learner characteristics may not function in the same way across learning modes. Further factor analytic and hierarchical research is needed to determine whether selfregulatory predictors of academic success continue to be relevant to modern student cohorts. Practitioner Notes What is already known about this topic Selfregulatory and demographic variables are important predictors of university outcomes like grades. It is unclear whether the relationships between predictor variables and outcomes are the same across learning modalities, as research findings are mixed. What this paper adds Models predicting university students' grades by demographic and selfregulatory predictors differed significantly between facetoface and online learning modalities. Performance selfefficacy significantly predicted grades for online students. No selfregulatory variables significantly predicted grades for facetoface students, and no demographic variables significantly predicted grades in either cohort. Overall, traditional predictors of grades showed no/small unique effects in both cohorts. Implications for practice and/or policy The learner characteristics that predict success may not be the same across learning modalities. Approaches to enhancing success in facetoface settings are not automatically applicable to online settings. Selfregulatory variables may not predict university outcomes as strongly as previously believed, and more research is needed.",
|
444 |
+
'Abstract OVERVIEW: This paper provides an overview of some fundamental aspects of electrochemical oxidation and gives updated information on the application of this technology to wastewater treatment. In recent years, electrochemical oxidation has gained increasing interest due to its outstanding technical characteristics for eliminating a wide variety of pollutants normally present in wastewaters such as refractory organic matter, nitrogen species and microorganisms. IMPACT: The strict disposal limits and health quality standards set by legislation may be met by applying electrochemical oxidation. However, treatment costs have to be cut down before fullscale application of this technology. Deployment of electrochemical oxidation in combination with other technologies and the use of renewable sources to power this process are two steps in this direction. APPLICATIONS: Effluents from landfill and a wide diversity of industrial effluents including the agroindustry, chemical, textile, tannery and food industry, have been effectively treated by this technology. Its high efficiency together with its disinfection capabilities makes electrooxidation a suitable technology for water reuse programs. Copyright ©️ Society of Chemical Industry',
|
445 |
+
]
|
446 |
+
embeddings = model.encode(sentences)
|
447 |
+
print(embeddings.shape)
|
448 |
+
# [3, 768]
|
449 |
+
|
450 |
+
# Get the similarity scores for the embeddings
|
451 |
+
similarities = model.similarity(embeddings, embeddings)
|
452 |
+
print(similarities.shape)
|
453 |
+
# [3, 3]
|
454 |
+
```
|
455 |
+
|
456 |
+
<!--
|
457 |
+
### Direct Usage (Transformers)
|
458 |
+
|
459 |
+
<details><summary>Click to see the direct usage in Transformers</summary>
|
460 |
+
|
461 |
+
</details>
|
462 |
+
-->
|
463 |
+
|
464 |
+
<!--
|
465 |
+
### Downstream Usage (Sentence Transformers)
|
466 |
+
|
467 |
+
You can finetune this model on your own dataset.
|
468 |
+
|
469 |
+
<details><summary>Click to expand</summary>
|
470 |
+
|
471 |
+
</details>
|
472 |
+
-->
|
473 |
+
|
474 |
+
<!--
|
475 |
+
### Out-of-Scope Use
|
476 |
+
|
477 |
+
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
|
478 |
+
-->
|
479 |
+
|
480 |
+
## Evaluation
|
481 |
+
|
482 |
+
### Metrics
|
483 |
+
|
484 |
+
#### Triplet
|
485 |
+
|
486 |
+
* Datasets: `specter_2_` and `discipline-tuned_specter_2_019`
|
487 |
+
* Evaluated with [<code>TripletEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
|
488 |
+
|
489 |
+
| Metric | specter_2_ | discipline-tuned_specter_2_019 |
|
490 |
+
|:--------------------|:-----------|:-------------------------------|
|
491 |
+
| **cosine_accuracy** | **0.9548** | **0.974** |
|
492 |
+
|
493 |
+
#### Triplet
|
494 |
+
|
495 |
+
* Dataset: `specter_2_`
|
496 |
+
* Evaluated with [<code>TripletEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
|
497 |
+
|
498 |
+
| Metric | Value |
|
499 |
+
|:--------------------|:-----------|
|
500 |
+
| **cosine_accuracy** | **0.9739** |
|
501 |
+
|
502 |
+
<!--
|
503 |
+
## Bias, Risks and Limitations
|
504 |
+
|
505 |
+
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
|
506 |
+
-->
|
507 |
+
|
508 |
+
<!--
|
509 |
+
### Recommendations
|
510 |
+
|
511 |
+
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
|
512 |
+
-->
|
513 |
+
|
514 |
+
## Training Details
|
515 |
+
|
516 |
+
### Training Dataset
|
517 |
+
|
518 |
+
#### Unnamed Dataset
|
519 |
+
|
520 |
+
|
521 |
+
* Size: 43,494 training samples
|
522 |
+
* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
|
523 |
+
* Approximate statistics based on the first 1000 samples:
|
524 |
+
| | anchor | positive | negative |
|
525 |
+
|:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
|
526 |
+
| type | string | string | string |
|
527 |
+
| details | <ul><li>min: 83 tokens</li><li>mean: 232.13 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 83 tokens</li><li>mean: 231.05 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 79 tokens</li><li>mean: 226.87 tokens</li><li>max: 512 tokens</li></ul> |
|
528 |
+
* Samples:
|
529 |
+
| anchor | positive | negative |
|
530 |
+
|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
531 |
+
| <code>Nowadays consumers are bombarded with different ads and the sheer abundance of advertisements causes marketers to be increasingly concerned with advertising effectiveness. Consequently, marketers and advertising companies exploring advertising effectiveness are always looking for more effective and newer communication media and evaluation methods of advertising effectiveness that technological development could provide. This study aims to incorporate AIDA model as hierarchy effect models for measuring the effectiveness of the TV advertisements for electric conservation in Isfahan city. Specifically this study aimed to evaluate the effects of TV advertisement on audience's attention, interest, desire for action and eventually changes made in conservation behavior of audience. The study revealed that the electric conservation TV advertisements were effective. In fact, TV advertisement was successful in taking attention of audience, creating interest and desire for action, and eventually ...</code> | <code>E-retailing is entering into the Indian retail scenario in a noticeable way and online grocery retailing holds a promise of acceptance by the Indian customers. This paper attempts to discover the market potential of online grocery retailing in India and consumers' perception towards its different aspects. Confirmatory factor analysis proposes that there are five underlying dimensions (convenience, value for money, variety, loyalty and ambient factors) governing the selection of mode for grocery purchase. Thereafter Binary-Logistic Regression has been employed to analyze the impact of these five broad perceptual dimensions upon the acceptance/rejection of online grocery retailing. The respondents accorded the highest importance to the factors value for money and convenience. The study suggested that issues like meeting customer expectations and preferences in terms of delivering value for money, quick and convenient purchasing, smooth delivery process, and reducing risk perceptions are ...</code> | <code>Conserved proteins preferentially expressed in synaptic terminals of the nervous system are likely to play a significant role in brain function. We have previously identified and molecularly characterized the Sap00 gene which codes for a novel synapse associated protein of kDa in Drosophila. Sequence comparison identifies homologous proteins in numerous species including C. elegans, fish, mouse and human. First hints as to the function of this novel protein family can be obtained by generating mutants for the Sap00 gene in Drosophila.Attempts to eliminate the Sap00 gene through targeted mutagenesis by homologous recombination were unsuccessful. However, several mutants were generated by transposon remobilization after an appropriate insertion line had become available from the Drosophila P-element screen of the Bellen/Hoskins/Rubin/Spradling labs. Characterization of various deletions in the Sap00 gene due to imprecise excision of the P-element identified three null mutants and three h...</code> |
|
532 |
+
| <code>General Agreement on Tariffs and Trade (GATT) was notable in largely excluding agriculture whereas the World Trade Organization (WTO) brought agriculture into the world trade rules. This article aims to evaluate the impacts of trade on agriculture production and productivity, especially the changes between the GATT and WTO periods. Using a panel of countries from , this article derives not only spillover effects that were overlooked, but also provides more accurate productivity than was estimated with bias in literature for both periods. We find that trade hindered agriculture production and productivity in the GATT period but improved agriculture production and productivity in the WTO period.</code> | <code>Nigeria is arguably the largest importer of dairy products in Africa. Available statistics shows that up to % of the total dairy products consumed in the country are imported; and that about % of the entire dairy market is controlled by FrieslandCampina WAMCO (FCW). The purpose of this study is to examine the basis for the prevailing import orientation in the dairy industry since . Is the orientation traceable to operations of multinational companies or the institutional and governance challenges in the country? Using triangulated data collected from FCW official reports and other relevant sources, and a content analytical technique, the study finds that the problem in the industry is multifaceted. Central to the challenges are persistent institutional and infrastructural defects, as well as faulty integration designs adopted by FCW. Based on this, the paper recommends that reversing the current trend requires government's policies that dis-incentivizes importation. However, such polic...</code> | <code>Questionnaires were mailed to all persons who had been granted the B.S. degree in psychology at Iowa State University during the period to . After one follow-up letter, ( %) returns had been received, these coming from about twice as many males as fema0es.l Respondents were in different states, the District of Columbia, and Ontario. Iowa accounted for almost one-fourth, with Iowa and bordering states accounting for about one-half. The questionnaire called for information concerning advanced training and education, vocational experiences, extent of use of psychological training, membership in professional organizations, professional and/or trade publications read regularly, and relative value of the psychology courses taken. Additional comments were invited on the psychology program and the total undergraduate curriculum at Iowa State. Forty-five per cent (mostly males) had taken, or were taking, graduate work in psychology. This agrees with Gustav's ( ) findings but differs from Dole's...</code> |
|
533 |
+
| <code>As well as being the name of the physical symptom of shivering, shuddering, or goosebumps, the Greek word phrike names an emotion that is particularly associated with automatic responses to sudden visual or auditory stimuli. This makes it especially at home in a number of specialized (ritual and other) scenarios, and helps explain its recurrent role in the ancient Greek aesthetics and literary theory, a role that illustrates the importance of the visual and the physical in ancient theories of audiences' emotional responses to the portrayal of suffering in both dramatic performance and non-dramatic narrative.</code> | <code>Oedipus Tyrannos (Sophocles, BCE) is examined psychoanalytically considering the elements of the story as unfolding in such a way as to leave what Freud ( ) called, "gaps unfilled and riddles unanswered" in the history, that is to say, devoid of a truly complex portrayal of human motivation and feeling. The quality of innocence that is dependent on simultaneously knowing and not knowing, both external reality and the internal realities that accompany it, is lost during Oedipus' zealous investigation. Elements of the history, as Sophocles presents it, reveal gaps and riddles that become resolved as the play moves inexorably to its tragic conclusion, with the identification of Oedipus as the parricidal polluter. The solicitations of supernatural consultation from the Delphian oracle betoken a disowned knowing of a frightening or a shameful aspect of human nature without actually acknowledging that knowledge. As the investigation proceeds, the play devolves virtually into a play within a ...</code> | <code>Objcetive To study the advantages of treating large serious bed sores by gentamicin and infrared rays.Methods First clean the surface of the wound of the bed sores and trim the dead tissue and siuns.Then wash it with gentamicin liquid, light it with -watt infrared rays for minutes. Cover it with a wet gentamicin gauze, then bind it up with a vaseline gauze and dressing. Do this once a day.Results The treatment of bed sores by gentamicin and infrared rays could obviously shorten the treating time (P0.00),with high cure rate (P0.00) and low death rate (P0.00).Conclusion The gentamicin and infrared rays to treat bed sores can control local infections,accelerate the reproduction of the tissue and resumption,which is more effctive than the traditional treatment.</code> |
|
534 |
+
* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
|
535 |
+
```json
|
536 |
+
{
|
537 |
+
"distance_metric": "TripletDistanceMetric.COSINE",
|
538 |
+
"triplet_margin": 0.6
|
539 |
+
}
|
540 |
+
```
|
541 |
+
|
542 |
+
### Evaluation Dataset
|
543 |
+
|
544 |
+
#### Unnamed Dataset
|
545 |
+
|
546 |
+
|
547 |
+
* Size: 2,174 evaluation samples
|
548 |
+
* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
|
549 |
+
* Approximate statistics based on the first 1000 samples:
|
550 |
+
| | anchor | positive | negative |
|
551 |
+
|:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
|
552 |
+
| type | string | string | string |
|
553 |
+
| details | <ul><li>min: 88 tokens</li><li>mean: 231.0 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 87 tokens</li><li>mean: 225.6 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 77 tokens</li><li>mean: 229.89 tokens</li><li>max: 512 tokens</li></ul> |
|
554 |
+
* Samples:
|
555 |
+
| anchor | positive | negative |
|
556 |
+
|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
557 |
+
| <code>In response to mounting community concern about the use of workplace agreements to erode employee conditions, the Howard Government has introduced substantial changes to the legal framework. These changes include a new Fairness Test and the rebadging of the two main institutions responsible for supervising agreement-making. This article outlines the main elements of these reforms and considers the extent to which the redesigned 'safety net' will offer protection to employees who enter into federal workplace agreements.</code> | <code>In Canada, the question of the meaning of the constitutional guarantee of freedom of association has been raised most frequently and persistently in the labour relations context The dual nature of the core labour rights and freedoms of collective organization, collective bargaining, and collective withdrawal of labour as both fundamental human rights and key components of economic policy makes it very difficult for courts to grapple with them in the constitutional context. The Supreme Court of Canada has been badly divided over the scope of collective activities by workers and unions protected by constitutional guarantees of freedom of association over the past years. Precedents have been overturned, and reasons that appeared in dissent subsequently figured in majority decisions. Changes in the composition of the bench as well as the economic and political climate have undermined the achievement of a principled consensus over the constitutional interpretation of section (d) in the cont...</code> | <code>It is shown that the presence of an arbitrary body buried near a dielectric highly rough random surface produces a remarkable enhanced backscattering peak in the angular distribution of mean scattered intensity. This is in contrast with the distribution that the dielectric rough surface yields in the absence of the body. In order for the peak to appear, the surface must be very rough and the contrast between the dielectric constants of the body and the medium in which it is immersed must be at least. We illustrate the results with a two-dimensional ( -D) calculation of a cylinder in front of a -D rough profile immersed in a dielectric medium. Different cases have been addressed in order to investigate the dependence of the backscattering enhancement on several physical parameters such as the width of the incident beam; the size, position, and optical constant of the buried cylinder; and the surface correlation function, as well as the difficult task of performing averages that resemble...</code> |
|
558 |
+
| <code>Issues surrounding white privilege have been in continuous debate. In Japan, the subject of white privilege is also not straightforward. Past research has been conducted about white privileged males in Japanese universities. We decided to take a different standpoint and examine the presence of white privilege in Japan through the alternative voices of non-Japanese Asian female university English teachers. By interviewing and analyzing their experiences and identities, we were able to examine incidences of white privilege that happened and influenced their lives as non-Japanese Asian female English teachers in Japan. We hope that our work generates interest and attention to the current gender and racial imbalance of native-speaker university English teachers in Japanan issue that directly or indirectly relates to all students, teachers, administrators and policy makers. </code> | <code>The study aims to explore the register variation in Chinese English and language variation between Chinese English and American English. A corpus-based and comparative methodology was used to analyse the discourse features of Chinese English in the use of the lexical items perhaps and maybe. The major findings of the study can be stated as follows: ) the more formal word perhaps is used more frequently than the informal word maybe in all the four genres in Chinese English. This shows that the text of Chinese English is generally in a more formal style. ) In the Chinese English text, the ratios of the standard frequency of perhaps to maybe are greater than those in American English in the all the four genres. This indicates that the text in Chinese English is generally in a more formal style than that in American English. ) In the Chinese English text, the informal word maybe is used less frequently than in the American English text. This is a sign that Chinese English is more formal th...</code> | <code>To present a case of a -year-old male patient with primary enuresis refractory to conservative treatment.Radiologic and urodynamic tests revealed posterior urethral valves that were treated by transurethral fulguration. The patient was cured of both enuresis and infravesical obstruction and remains disease-free years after the operation with no impact on his sexual function.Posterior urethral valves are very rarely diagnosed in adolescents and adults. Very few cases have been published in the literature. To our knowledge, the case described herein is the first case presenting with persistent primary enuresis.</code> |
|
559 |
+
| <code>Abstract Reduced temperature and increased bulk density associated with conservation tillage systems cause lower seed germination, seedling emergence, and early growth rates resulting in reduced plant stands. Prediction of the influence of soil condition on seed imbibition through simple soil measurements would help make agronomic decisions such as planting date and/or density. Our objectives were to evaluate the influence of soil waterfilled pore space on winter wheat ( Triticum aestivum L.) seed imbibition and to assess the possibility of describing the relationship through simple mathematical models. We measured the rate of water uptake by heatkilled wheat seeds at three levels of waterfilled pore space (WFPS: , , and ) and temperature ( T : , , and K) and two levels of bulk density ( b : and Mg m ) in a Sharpsburg silty clay loam topsoil. The model proposed in by Blacklow to estimate seed water content ( s ) after imbibing water for time t , s(t) = ( m + ot ) ( m s( ) ) e qt , was ...</code> | <code>Abstract Camellia oleifera Abel. is an important woody oil plant that could solve the disparity between the supply and demand of edible oil in China. Although numerous excellent clones have been developed and introduced to enhance production, the interactions between high yield clones and soil ecosystem sustainability remains poorly understood. The highyielding period of a C. oleifera plant is approximately yr; therefore, appropriate clone selection is crucial. We evaluated the differences between four major clones based on soil nutrient and microbial community structure, following cultivation for yr to infer the influence of clone selection on soil sustainable utilization. The results showed significant differences in soil nutrient status and rhizosphere microorganism populations among clones. The bacterial communities in the XL0 plots had the highest species richness. According to the results, clone XL0 was found to be suitable for sustainable cultivation considering the high organic...</code> | <code>AbstractIn the wake of the present effort to shape American education to produce large numbers of scientists and engineers, education in the arts is becoming an increasingly peripheral interest of the schools. The time that public school pupils have at their disposal is limited, and so is the money available for financing schools. To a public rightly concerned with these limitations, educators in the arts must be able to present convincing arguments to show that the arts are in fact worth teaching. And to this same public, weary and perhaps disillusioned with what it takes to be a chaos of relativistic aesthetic standards, educators must be able to say that taste is not wholly an individual matter, but that some standards do in fact exist and are available for teaching. Without being able to argue in some way for the importance of education in the arts and for the existence of aesthetic standards, educators who propose that the schools teach the arts are in effect asking the public to ...</code> |
|
560 |
+
* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
|
561 |
+
```json
|
562 |
+
{
|
563 |
+
"distance_metric": "TripletDistanceMetric.COSINE",
|
564 |
+
"triplet_margin": 0.6
|
565 |
+
}
|
566 |
+
```
|
567 |
+
|
568 |
+
### Training Hyperparameters
|
569 |
+
#### Non-Default Hyperparameters
|
570 |
+
|
571 |
+
- `eval_strategy`: steps
|
572 |
+
- `per_device_train_batch_size`: 12
|
573 |
+
- `per_device_eval_batch_size`: 12
|
574 |
+
- `learning_rate`: 2e-05
|
575 |
+
- `weight_decay`: 0.01
|
576 |
+
- `num_train_epochs`: 1
|
577 |
+
- `warmup_ratio`: 0.2
|
578 |
+
- `fp16`: True
|
579 |
+
- `batch_sampler`: no_duplicates
|
580 |
+
|
581 |
+
#### All Hyperparameters
|
582 |
+
<details><summary>Click to expand</summary>
|
583 |
+
|
584 |
+
- `overwrite_output_dir`: False
|
585 |
+
- `do_predict`: False
|
586 |
+
- `eval_strategy`: steps
|
587 |
+
- `prediction_loss_only`: True
|
588 |
+
- `per_device_train_batch_size`: 12
|
589 |
+
- `per_device_eval_batch_size`: 12
|
590 |
+
- `per_gpu_train_batch_size`: None
|
591 |
+
- `per_gpu_eval_batch_size`: None
|
592 |
+
- `gradient_accumulation_steps`: 1
|
593 |
+
- `eval_accumulation_steps`: None
|
594 |
+
- `torch_empty_cache_steps`: None
|
595 |
+
- `learning_rate`: 2e-05
|
596 |
+
- `weight_decay`: 0.01
|
597 |
+
- `adam_beta1`: 0.9
|
598 |
+
- `adam_beta2`: 0.999
|
599 |
+
- `adam_epsilon`: 1e-08
|
600 |
+
- `max_grad_norm`: 1.0
|
601 |
+
- `num_train_epochs`: 1
|
602 |
+
- `max_steps`: -1
|
603 |
+
- `lr_scheduler_type`: linear
|
604 |
+
- `lr_scheduler_kwargs`: {}
|
605 |
+
- `warmup_ratio`: 0.2
|
606 |
+
- `warmup_steps`: 0
|
607 |
+
- `log_level`: passive
|
608 |
+
- `log_level_replica`: warning
|
609 |
+
- `log_on_each_node`: True
|
610 |
+
- `logging_nan_inf_filter`: True
|
611 |
+
- `save_safetensors`: True
|
612 |
+
- `save_on_each_node`: False
|
613 |
+
- `save_only_model`: False
|
614 |
+
- `restore_callback_states_from_checkpoint`: False
|
615 |
+
- `no_cuda`: False
|
616 |
+
- `use_cpu`: False
|
617 |
+
- `use_mps_device`: False
|
618 |
+
- `seed`: 42
|
619 |
+
- `data_seed`: None
|
620 |
+
- `jit_mode_eval`: False
|
621 |
+
- `use_ipex`: False
|
622 |
+
- `bf16`: False
|
623 |
+
- `fp16`: True
|
624 |
+
- `fp16_opt_level`: O1
|
625 |
+
- `half_precision_backend`: auto
|
626 |
+
- `bf16_full_eval`: False
|
627 |
+
- `fp16_full_eval`: False
|
628 |
+
- `tf32`: None
|
629 |
+
- `local_rank`: 0
|
630 |
+
- `ddp_backend`: None
|
631 |
+
- `tpu_num_cores`: None
|
632 |
+
- `tpu_metrics_debug`: False
|
633 |
+
- `debug`: []
|
634 |
+
- `dataloader_drop_last`: False
|
635 |
+
- `dataloader_num_workers`: 0
|
636 |
+
- `dataloader_prefetch_factor`: None
|
637 |
+
- `past_index`: -1
|
638 |
+
- `disable_tqdm`: False
|
639 |
+
- `remove_unused_columns`: True
|
640 |
+
- `label_names`: None
|
641 |
+
- `load_best_model_at_end`: False
|
642 |
+
- `ignore_data_skip`: False
|
643 |
+
- `fsdp`: []
|
644 |
+
- `fsdp_min_num_params`: 0
|
645 |
+
- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
|
646 |
+
- `fsdp_transformer_layer_cls_to_wrap`: None
|
647 |
+
- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
|
648 |
+
- `deepspeed`: None
|
649 |
+
- `label_smoothing_factor`: 0.0
|
650 |
+
- `optim`: adamw_torch
|
651 |
+
- `optim_args`: None
|
652 |
+
- `adafactor`: False
|
653 |
+
- `group_by_length`: False
|
654 |
+
- `length_column_name`: length
|
655 |
+
- `ddp_find_unused_parameters`: None
|
656 |
+
- `ddp_bucket_cap_mb`: None
|
657 |
+
- `ddp_broadcast_buffers`: False
|
658 |
+
- `dataloader_pin_memory`: True
|
659 |
+
- `dataloader_persistent_workers`: False
|
660 |
+
- `skip_memory_metrics`: True
|
661 |
+
- `use_legacy_prediction_loop`: False
|
662 |
+
- `push_to_hub`: False
|
663 |
+
- `resume_from_checkpoint`: None
|
664 |
+
- `hub_model_id`: None
|
665 |
+
- `hub_strategy`: every_save
|
666 |
+
- `hub_private_repo`: None
|
667 |
+
- `hub_always_push`: False
|
668 |
+
- `gradient_checkpointing`: False
|
669 |
+
- `gradient_checkpointing_kwargs`: None
|
670 |
+
- `include_inputs_for_metrics`: False
|
671 |
+
- `include_for_metrics`: []
|
672 |
+
- `eval_do_concat_batches`: True
|
673 |
+
- `fp16_backend`: auto
|
674 |
+
- `push_to_hub_model_id`: None
|
675 |
+
- `push_to_hub_organization`: None
|
676 |
+
- `mp_parameters`:
|
677 |
+
- `auto_find_batch_size`: False
|
678 |
+
- `full_determinism`: False
|
679 |
+
- `torchdynamo`: None
|
680 |
+
- `ray_scope`: last
|
681 |
+
- `ddp_timeout`: 1800
|
682 |
+
- `torch_compile`: False
|
683 |
+
- `torch_compile_backend`: None
|
684 |
+
- `torch_compile_mode`: None
|
685 |
+
- `dispatch_batches`: None
|
686 |
+
- `split_batches`: None
|
687 |
+
- `include_tokens_per_second`: False
|
688 |
+
- `include_num_input_tokens_seen`: False
|
689 |
+
- `neftune_noise_alpha`: None
|
690 |
+
- `optim_target_modules`: None
|
691 |
+
- `batch_eval_metrics`: False
|
692 |
+
- `eval_on_start`: False
|
693 |
+
- `use_liger_kernel`: False
|
694 |
+
- `eval_use_gather_object`: False
|
695 |
+
- `average_tokens_across_devices`: False
|
696 |
+
- `prompts`: None
|
697 |
+
- `batch_sampler`: no_duplicates
|
698 |
+
- `multi_dataset_batch_sampler`: proportional
|
699 |
+
|
700 |
+
</details>
|
701 |
+
|
702 |
+
### Training Logs
|
703 |
+
| Epoch | Step | Training Loss | Validation Loss | specter_2__cosine_accuracy | discipline-tuned_specter_2_019_cosine_accuracy |
|
704 |
+
|:------:|:----:|:-------------:|:---------------:|:--------------------------:|:----------------------------------------------:|
|
705 |
+
| 0 | 0 | - | - | 0.9548 | - |
|
706 |
+
| 0.0028 | 10 | 0.4852 | - | - | - |
|
707 |
+
| 0.0138 | 50 | 0.4828 | 0.4496 | 0.9609 | - |
|
708 |
+
| 0.0276 | 100 | 0.3925 | 0.3053 | 0.9667 | - |
|
709 |
+
| 0.0414 | 150 | 0.2343 | 0.1939 | 0.9675 | - |
|
710 |
+
| 0.0552 | 200 | 0.1748 | 0.1473 | 0.9718 | - |
|
711 |
+
| 0.0690 | 250 | 0.1333 | 0.1148 | 0.9726 | - |
|
712 |
+
| 0.0828 | 300 | 0.11 | 0.1008 | 0.9703 | - |
|
713 |
+
| 0.0966 | 350 | 0.1109 | 0.0944 | 0.9692 | - |
|
714 |
+
| 0.1103 | 400 | 0.0946 | 0.0918 | 0.9725 | - |
|
715 |
+
| 0.1241 | 450 | 0.1052 | 0.0897 | 0.9707 | - |
|
716 |
+
| 0.1379 | 500 | 0.0942 | 0.0836 | 0.9721 | - |
|
717 |
+
| 0.1517 | 550 | 0.0813 | 0.0870 | 0.9654 | - |
|
718 |
+
| 0.1655 | 600 | 0.091 | 0.0901 | 0.9691 | - |
|
719 |
+
| 0.1793 | 650 | 0.0942 | 0.0874 | 0.9690 | - |
|
720 |
+
| 0.1931 | 700 | 0.0825 | 0.0958 | 0.9617 | - |
|
721 |
+
| 0.2069 | 750 | 0.0971 | 0.0850 | 0.9733 | - |
|
722 |
+
| 0.2207 | 800 | 0.0872 | 0.0806 | 0.9702 | - |
|
723 |
+
| 0.2345 | 850 | 0.0801 | 0.0824 | 0.9682 | - |
|
724 |
+
| 0.2483 | 900 | 0.0851 | 0.0809 | 0.9695 | - |
|
725 |
+
| 0.2621 | 950 | 0.0914 | 0.0790 | 0.9708 | - |
|
726 |
+
| 0.2759 | 1000 | 0.0847 | 0.0799 | 0.9720 | - |
|
727 |
+
| 0.2897 | 1050 | 0.0895 | 0.0754 | 0.9717 | - |
|
728 |
+
| 0.3034 | 1100 | 0.0756 | 0.0802 | 0.9706 | - |
|
729 |
+
| 0.3172 | 1150 | 0.0814 | 0.0786 | 0.9694 | - |
|
730 |
+
| 0.3310 | 1200 | 0.0997 | 0.0744 | 0.9734 | - |
|
731 |
+
| 0.3448 | 1250 | 0.0943 | 0.0762 | 0.9730 | - |
|
732 |
+
| 0.3586 | 1300 | 0.0805 | 0.0782 | 0.9718 | - |
|
733 |
+
| 0.3724 | 1350 | 0.079 | 0.0748 | 0.9732 | - |
|
734 |
+
| 0.3862 | 1400 | 0.0818 | 0.0755 | 0.9737 | - |
|
735 |
+
| 0.4 | 1450 | 0.0671 | 0.0729 | 0.9734 | - |
|
736 |
+
| 0.4138 | 1500 | 0.0567 | 0.0737 | 0.9720 | - |
|
737 |
+
| 0.4276 | 1550 | 0.0747 | 0.0746 | 0.9726 | - |
|
738 |
+
| 0.4414 | 1600 | 0.0793 | 0.0735 | 0.9717 | - |
|
739 |
+
| 0.4552 | 1650 | 0.0812 | 0.0762 | 0.9739 | - |
|
740 |
+
| 0.4690 | 1700 | 0.075 | - | - | 0.9740 |
|
741 |
+
|
742 |
+
|
743 |
+
### Framework Versions
|
744 |
+
- Python: 3.10.12
|
745 |
+
- Sentence Transformers: 3.3.1
|
746 |
+
- Transformers: 4.49.0.dev0
|
747 |
+
- PyTorch: 2.5.1+cu121
|
748 |
+
- Accelerate: 1.2.1
|
749 |
+
- Datasets: 3.2.0
|
750 |
+
- Tokenizers: 0.21.0
|
751 |
+
|
752 |
+
## Citation
|
753 |
+
|
754 |
+
### BibTeX
|
755 |
+
|
756 |
+
#### Sentence Transformers
|
757 |
+
```bibtex
|
758 |
+
@inproceedings{reimers-2019-sentence-bert,
|
759 |
+
title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
|
760 |
+
author = "Reimers, Nils and Gurevych, Iryna",
|
761 |
+
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
|
762 |
+
month = "11",
|
763 |
+
year = "2019",
|
764 |
+
publisher = "Association for Computational Linguistics",
|
765 |
+
url = "https://arxiv.org/abs/1908.10084",
|
766 |
+
}
|
767 |
+
```
|
768 |
+
|
769 |
+
#### TripletLoss
|
770 |
+
```bibtex
|
771 |
+
@misc{hermans2017defense,
|
772 |
+
title={In Defense of the Triplet Loss for Person Re-Identification},
|
773 |
+
author={Alexander Hermans and Lucas Beyer and Bastian Leibe},
|
774 |
+
year={2017},
|
775 |
+
eprint={1703.07737},
|
776 |
+
archivePrefix={arXiv},
|
777 |
+
primaryClass={cs.CV}
|
778 |
+
}
|
779 |
+
```
|
780 |
+
|
781 |
+
<!--
|
782 |
+
## Glossary
|
783 |
+
|
784 |
+
*Clearly define terms in order to be accessible across audiences.*
|
785 |
+
-->
|
786 |
+
|
787 |
+
<!--
|
788 |
+
## Model Card Authors
|
789 |
+
|
790 |
+
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
|
791 |
+
-->
|
792 |
+
|
793 |
+
<!--
|
794 |
+
## Model Card Contact
|
795 |
+
|
796 |
+
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
|
797 |
+
-->
|
config.json
ADDED
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "allenai/specter2_aug2023refresh_base",
|
3 |
+
"adapters": {
|
4 |
+
"adapters": {},
|
5 |
+
"config_map": {},
|
6 |
+
"fusion_config_map": {},
|
7 |
+
"fusions": {}
|
8 |
+
},
|
9 |
+
"architectures": [
|
10 |
+
"BertModel"
|
11 |
+
],
|
12 |
+
"attention_probs_dropout_prob": 0.1,
|
13 |
+
"classifier_dropout": null,
|
14 |
+
"hidden_act": "gelu",
|
15 |
+
"hidden_dropout_prob": 0.1,
|
16 |
+
"hidden_size": 768,
|
17 |
+
"initializer_range": 0.02,
|
18 |
+
"intermediate_size": 3072,
|
19 |
+
"layer_norm_eps": 1e-12,
|
20 |
+
"max_position_embeddings": 512,
|
21 |
+
"model_type": "bert",
|
22 |
+
"num_attention_heads": 12,
|
23 |
+
"num_hidden_layers": 12,
|
24 |
+
"pad_token_id": 0,
|
25 |
+
"position_embedding_type": "absolute",
|
26 |
+
"torch_dtype": "float32",
|
27 |
+
"transformers_version": "4.49.0.dev0",
|
28 |
+
"type_vocab_size": 2,
|
29 |
+
"use_cache": true,
|
30 |
+
"vocab_size": 31090
|
31 |
+
}
|
config_sentence_transformers.json
ADDED
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"__version__": {
|
3 |
+
"sentence_transformers": "3.3.1",
|
4 |
+
"transformers": "4.49.0.dev0",
|
5 |
+
"pytorch": "2.5.1+cu121"
|
6 |
+
},
|
7 |
+
"prompts": {},
|
8 |
+
"default_prompt_name": null,
|
9 |
+
"similarity_fn_name": "cosine"
|
10 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2d09001ebd60961198fb2b5024ca3ff009f90d670a67eb01cfcc160ee9345bf4
|
3 |
+
size 439696224
|
modules.json
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"idx": 0,
|
4 |
+
"name": "0",
|
5 |
+
"path": "",
|
6 |
+
"type": "sentence_transformers.models.Transformer"
|
7 |
+
},
|
8 |
+
{
|
9 |
+
"idx": 1,
|
10 |
+
"name": "1",
|
11 |
+
"path": "1_Pooling",
|
12 |
+
"type": "sentence_transformers.models.Pooling"
|
13 |
+
},
|
14 |
+
{
|
15 |
+
"idx": 2,
|
16 |
+
"name": "2",
|
17 |
+
"path": "2_Normalize",
|
18 |
+
"type": "sentence_transformers.models.Normalize"
|
19 |
+
}
|
20 |
+
]
|
sentence_bert_config.json
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"max_seq_length": 512,
|
3 |
+
"do_lower_case": false
|
4 |
+
}
|
special_tokens_map.json
ADDED
@@ -0,0 +1,37 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"cls_token": {
|
3 |
+
"content": "[CLS]",
|
4 |
+
"lstrip": false,
|
5 |
+
"normalized": false,
|
6 |
+
"rstrip": false,
|
7 |
+
"single_word": false
|
8 |
+
},
|
9 |
+
"mask_token": {
|
10 |
+
"content": "[MASK]",
|
11 |
+
"lstrip": false,
|
12 |
+
"normalized": false,
|
13 |
+
"rstrip": false,
|
14 |
+
"single_word": false
|
15 |
+
},
|
16 |
+
"pad_token": {
|
17 |
+
"content": "[PAD]",
|
18 |
+
"lstrip": false,
|
19 |
+
"normalized": false,
|
20 |
+
"rstrip": false,
|
21 |
+
"single_word": false
|
22 |
+
},
|
23 |
+
"sep_token": {
|
24 |
+
"content": "[SEP]",
|
25 |
+
"lstrip": false,
|
26 |
+
"normalized": false,
|
27 |
+
"rstrip": false,
|
28 |
+
"single_word": false
|
29 |
+
},
|
30 |
+
"unk_token": {
|
31 |
+
"content": "[UNK]",
|
32 |
+
"lstrip": false,
|
33 |
+
"normalized": false,
|
34 |
+
"rstrip": false,
|
35 |
+
"single_word": false
|
36 |
+
}
|
37 |
+
}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,58 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
+
"0": {
|
4 |
+
"content": "[PAD]",
|
5 |
+
"lstrip": false,
|
6 |
+
"normalized": false,
|
7 |
+
"rstrip": false,
|
8 |
+
"single_word": false,
|
9 |
+
"special": true
|
10 |
+
},
|
11 |
+
"101": {
|
12 |
+
"content": "[UNK]",
|
13 |
+
"lstrip": false,
|
14 |
+
"normalized": false,
|
15 |
+
"rstrip": false,
|
16 |
+
"single_word": false,
|
17 |
+
"special": true
|
18 |
+
},
|
19 |
+
"102": {
|
20 |
+
"content": "[CLS]",
|
21 |
+
"lstrip": false,
|
22 |
+
"normalized": false,
|
23 |
+
"rstrip": false,
|
24 |
+
"single_word": false,
|
25 |
+
"special": true
|
26 |
+
},
|
27 |
+
"103": {
|
28 |
+
"content": "[SEP]",
|
29 |
+
"lstrip": false,
|
30 |
+
"normalized": false,
|
31 |
+
"rstrip": false,
|
32 |
+
"single_word": false,
|
33 |
+
"special": true
|
34 |
+
},
|
35 |
+
"104": {
|
36 |
+
"content": "[MASK]",
|
37 |
+
"lstrip": false,
|
38 |
+
"normalized": false,
|
39 |
+
"rstrip": false,
|
40 |
+
"single_word": false,
|
41 |
+
"special": true
|
42 |
+
}
|
43 |
+
},
|
44 |
+
"clean_up_tokenization_spaces": true,
|
45 |
+
"cls_token": "[CLS]",
|
46 |
+
"do_basic_tokenize": true,
|
47 |
+
"do_lower_case": true,
|
48 |
+
"extra_special_tokens": {},
|
49 |
+
"mask_token": "[MASK]",
|
50 |
+
"model_max_length": 512,
|
51 |
+
"never_split": null,
|
52 |
+
"pad_token": "[PAD]",
|
53 |
+
"sep_token": "[SEP]",
|
54 |
+
"strip_accents": null,
|
55 |
+
"tokenize_chinese_chars": true,
|
56 |
+
"tokenizer_class": "BertTokenizer",
|
57 |
+
"unk_token": "[UNK]"
|
58 |
+
}
|
vocab.txt
ADDED
The diff for this file is too large to render.
See raw diff
|
|