---
base_model: nreimers/MiniLM-L6-H384-uncased
datasets: []
language: []
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:730454
- loss:MultipleNegativesRankingLoss
widget:
- source_sentence: Markov chains and performance comparison of switched diversity
systems
sentences:
- An algorithm for speaker's lip segmentation and features extraction is presented.
A color video sequence of speaker's face is acquired, under natural lighting conditions
and without any particular make-up. First, a logarithmic color transform is performed
from the RGB to HI (hue, intensity) color space. Second, a statistical approach
using Markov random field modeling determines the red hue prevailing region and
motion in a spatiotemporal neighborhood. Third, the final label field is used
to extract ROI (region of interest) and geometrical features.
- There are about 90 million high performance mobile phones used in Japan. We are
now planning to develop new applications of mobile phone to support children and
elder and disabled people who are out of scope of major mobile phone application
based on their requirements. We have a responsibility to extend the application
filed of mobile phone as a leading country of ubiquitous life. This paper discusses
possibilities to realize mobile ad hoc networks using Bluetooth functions equipped
on a mobile phone. Hierarchical mobile ad hoc networks using Bluetooth in a mobile
phone are firstly developed as a test platform. The test platform proves the possibility
of developing mobile ad hoc network by mobile phone built-in Bluetooth functions.
We demonstrate their capabilities by showing results of implementing game applications
on the test platform. The paper also describes some example applications using
mobile ad hoc network technologies, which include a location tracking system for
children on the way to a school and an alarm system for hearing impaired people
- Switch-and-stay combining (SSC) diversity systems have the advantage of offering
one of the least complex solutions to mitigating the effect of fading. In this
paper, we present a Markov chain-based analytical framework for the performance
analysis of various switching strategies used in conjunction with SSC systems.
The resulting expressions are quite general, and are applicable to dual-branch
diversity systems operating over a variety of correlated and/or unbalanced fading
channels. The mathematical formalism is illustrated by some selected numerical
examples, along with their discussion and interpretation. As a result, this paper
presents a thorough comparison and highlights the main differences and tradeoffs
between the various SSC switching strategies.
- source_sentence: 'Effect of age on the failure properties of human meniscus: High-speed
strain mapping of tissue tears.'
sentences:
- 'The knee meniscus is a soft fibrous tissue with a high incidence of injury in
older populations. The objective of this study was to determine the effect of
age on the failure behavior of human knee meniscus when applying uniaxial tensile
loads parallel or perpendicular to the primary circumferential fiber orientation.
Two age groups were tested: under 40 and over 65 years old. We paired high-speed
video with digital image correlation to quantify for the first time the planar
strains occurring in the tear region at precise time points, including at ultimate
tensile stress, when the tissue begins losing load-bearing capacity. On average,
older meniscus specimens loaded parallel to the fiber axis had approximately one-third
less ultimate tensile strain and absorbed 60% less energy to failure within the
tear region than younger specimens (p < 0.05). Older specimens also had significantly
reduced strength and material toughness when loaded perpendicular to the fibers
(p < 0.05). These age-related changes indicate a loss of collagen fiber extensibility
and weakening of the non-fibrous matrix with age. In addition, we found that when
loaded perpendicular to the circumferential fibers, tears propagated near the
planes of maximum tensile stress and strain. Whereas when loaded parallel to the
circumferential fibers, tears propagated oblique to the loading axis, closer to
the planes of maximum shear stress and strain. Our experimental results can assist
the selection of valid failure criteria for meniscus, and provide insight into
the effect of age on the failure mechanisms of soft fibrous tissue.'
- 'Objectives: We aimed to identify key demographic risk factors for hospital attendance
with COVID-19 infection. Design: Community survey Setting: The COVID Symptom Tracker
mobile application co-developed by physicians and scientists at Kings College
London, Massachusetts General Hospital, Boston and Zoe Global Limited was launched
in the UK and US on 24th and 29th March 2020 respectively. It captured self-reported
information related to COVID-19 symptoms and testing. Participants: 2,618,948
users of the COVID Symptom Tracker App. UK (95.7%) and US (4.3%) population. Data
cut-off for this analysis was 21st April 2020. Main outcome measures: Visit to
hospital and for those who attended hospital, the need for respiratory support
in three subgroups (i) self-reported COVID-19 infection with classical symptoms
(SR-COVID-19), (ii) self-reported positive COVID-19 test results (T-COVID-19),
and (iii) imputed/predicted COVID-19 infection based on symptomatology (I-COVID-19).
Multivariate logistic regressions for each outcome and each subgroup were adjusted
for age and gender, with sensitivity analyses adjusted for comorbidities. Classical
symptoms were defined as high fever and persistent cough for several days. Results:
Older age and all comorbidities tested were found to be associated with increased
odds of requiring hospital care for COVID-19. Obesity (BMI >30) predicted hospital
care in all models, with odds ratios (OR) varying from 1.20 [1.11; 1.31] to 1.40
[1.23; 1.60] across population groups. Pre-existing lung disease and diabetes
were consistently found to be associated with hospital visit with a maximum OR
of 1.79 [1.64,1.95] and 1.72 [1.27; 2.31]) respectively. Findings were similar
when assessing the need for respiratory support, for which age and male gender
played an additional role. Conclusions: Being older, obese, diabetic or suffering
from pre-existing lung, heart or renal disease placed participants at increased
risk of visiting hospital with COVID-19. It is of utmost importance for governments
and the scientific and medical communities to work together to find evidence-based
means of protecting those deemed most vulnerable from COVID-19. Trial registration:
The App Ethics have been approved by KCL ethics Committee REMAS ID 18210, review
reference LRS-19/20-18210'
- Social networking sites (SNS) have growing popularity and several sites compete
with each other. This study examines three models to determine how competition
between Facebook and other social networking sites may affect continuance intention
on Facebook. The first model examines the relationship between having an account
on four different SNSs and its impact on Facebook. Twitter users have lower intentions
to continue using Facebook, Instagram users have higher intentions. The second
model examines attitudes toward specific alternatives and found that users who
felt alternatives were attractive have lower intentions to continue using Facebook.
The third model examined general attitudes about alternative attractiveness and
attitudes toward switching, this model explained a moderate to substantial amount
of the variance in continuance intention. This study makes important contributions
to both research and practice.
- source_sentence: Bayesian duration modeling and learning for speech recognition
sentences:
- Measuring solar irradiance allows for direct maximization of the efficiency in
photovoltaic power plants. However, devices for solar irradiance sensing, such
as pyranometers and pyrheliometers, are expensive and difficult to calibrate and
thus seldom utilized in photovoltaic power plants. Indirect methods are instead
implemented in order to maximize efficiency. This paper proposes a novel approach
for solar irradiance measurement based on neural networks, which may, in turn,
be used to maximize efficiency directly. An initial estimate suggests the cost
of the sensor proposed herein may be price competitive with other inexpensive
solutions available in the market, making the device a good candidate for large
deployment in photovoltaic power plants. The proposed sensor is implemented through
a photovoltaic cell, a temperature sensor, and a low-cost microcontroller. The
use of a microcontroller allows for easy calibration, updates, and enhancement
by simply adding code libraries. Furthermore, it can be interfaced via standard
communication means with other control devices, integrated into control schemes,
and remote-controlled through its embedded web server. The proposed approach is
validated through experimental prototyping and compared against a commercial device.
- Form is a framework used to construct tools for analyzing the runtime behavior
of standalone and distributed software systems. The architecture of Form is based
on the event broadcast and pipe and filter styles. In the implementation of this
architecture, execution profiles may be generated from standalone or distributed
systems. The profile data is subsequently broadcast by Form to one or more views.
Each view is a tool used to support program understanding or other software development
activities. The authors describe the Form architecture and implementation, as
well as a tool that was built using Form. This tool profiles Java-based distributed
systems and generates UML sequence diagrams to describe their execution. We also
present a case study that shows how this tool was used to extract sequence diagrams
from a three-tiered EJB-based distributed application.
- We present Bayesian duration modeling and learning for speech recognition under
nonstationary speaking rates and noise conditions. In this study, the Gaussian,
Poisson and gamma distributions are investigated, to characterize duration models.
The maximum a posteriori (MAP) estimate of the gamma duration model is developed.
To exploit the sequential learning, we adopt the Poisson duration model, incorporated
with gamma prior density, which belongs to the conjugate prior family. When the
adaptation data are sequentially observed, the gamma posterior density is produced
for twofold advantages. One is to determine the optimal quasi-Bayes (QB) duration
parameter, which can be merged in HMM's for speech recognition. The other one
is to build the updating mechanism of gamma prior statistics for sequential learning.
An expectation-maximization algorithm is applied to fulfill parameter estimation.
In the experiments, the proposed Bayesian approaches significantly improve the
speech recognition performance of Mandarin broadcast news. Batch and sequential
learning are investigated for MAP and QB duration models, respectively.
- source_sentence: Configurable security for scavenged storage systems
sentences:
- Scavenged storage systems harness unused disk space from individual workstations
the same way idle CPU cycles are harnessed by desktop grid applications like Seti@Home.
These systems provide a promising low cost, high-performance storage solution
in certain high-end computing scenarios. However, selecting the security level
and designing the security mechanisms for such systems is challenging as scavenging
idle storage opens the door for security threats absent in traditional storage
systems that use dedicated nodes under a single administrative domain. Moreover,
increased security often comes at the price of performance and scalability. This
paper develops a general threat model for systems that use scavenged storage,
presents the design of a protocol that addresses these threats and is optimized
for throughput, and evaluates the overheads brought by the new security protocol
when configured to provide a number of different security properties.
- Histone methyltransferases are involved in many important biological processes,
and abnormalities in these enzymes are associated with tumorigenesis and progression.
Disruptor of telomeric silencing 1-like (DOT1L), a key hub in histone lysine methyltransferases,
has been reported to play an important role in the processes of mixed-lineage
leukemia (MLL)-rearranged leukemias and validated to be a potential therapeutic
target. In this study, we identified a novel DOT1L inhibitor, DC_L115 (CAS no.
1163729-79-0), by combining structure-based virtual screening with biochemical
analyses. This potent inhibitor DC_L115 shows high inhibitory activity toward
DOT1L (IC50 = 1.5 μM). Through a process of surface plasmon resonance-based binding
assays, DC_L115 was founded to bind to DOT1L with a binding affinity of 0.6 μM
in vitro. Moreover, this compound selectively inhibits MLL-rearranged cell proliferation
with an IC50 value of 37.1 μM. We further predicted the binding modes of DC_L115
through molecular docking anal...
- Employing channel state information at the network layer, efficient routing protocols
for equal-power and optimal-power allocation in a multihop network in fading are
proposed. The end-to-end outage probability from source to destination is used
as the optimization criterion. The problem of finding the optimal route is investigated
under either known mean channel state information (CSI) or known instantaneous
CSI. The analysis shows that the proposed routing strategy achieves full diversity
order, equal to the total number of nodes in the network excluding the destination,
only when instantaneous CSI is known and used. The optimal routing algorithm requires
a centralized exhaustive search which leads to an exponential complexity, which
is infeasible for large networks. An algorithm of polynomial complexity for a
centralized environment is developed by reducing the search space. A distributed
approach based on the Bellman-Ford routing algorithm is proposed which achieves
a good implementation complexity-performance trade-off.
- source_sentence: Computationally efficient fixed complexity LLL algorithm for lattice-reduction-aided
multiple-input–multiple-output precoding
sentences:
- ABSTRACTThe success of the open innovation (OI) paradigm is still debated and
literature is searching for its determinants. Although firms’ internal social
context is crucial to explain the success or failure of OI practices, such context
is still poorly investigated. The aim of the paper is to analyse whether internal
social capital (SC), intended as employees’ propensity to interact and work in
groups in order to solve innovation issues, mediates the relationship between
OI practices and innovation ambidexterity (IA). Results, based on a survey research
developed in Finland, Italy and Sweden, suggest that collaborations with different
typologies of partners (scientific and business) achieve good results in terms
of IA, through the partial mediation of the internal SC.
- In multiple-input–multiple-output broadcast channels, lattice reduction (LR) preprocessing
technique can significantly improve the precoding performance. Among the existing
LR algorithms, the fixed complexity Lenstra–Lenstra–Lovasz (fcLLL) algorithm applying
limited number of LLL loops is suitable for the real-time communication system.
However, fcLLL algorithm suffers from higher average complexity. Aiming at this
problem, a computationally efficient fcLLL (CE-fcLLL) algorithm for LR-aided (LRA)
precoding is developed in this study. First, the authors analyse the impact of
fcLLL algorithm on the signal-to-noise ratio performance of LRA precoding by a
power factor (PF) which is defined to measure the relation of reduced basis and
transmit power of LRA precoding. Then, they propose a CE-fcLLL algorithm by designing
a new LLL loop and introducing new early termination conditions to reduce redundant
and inefficient LR operation in fcLLL algorithm. Finally, they define a PF loss
factor to optimise the PF threshold and the number of LLL loops, which can lead
to a performance-complexity tradeoff. Simulation results show that the proposed
algorithm for LRA precoding can achieve better bit-error-rate performance than
the fcLLL algorithm with remarkable complexity savings in the same upper complexity
bound.
- 'While multistage switching networks for vector multiprocessors have been studied
extensively, detailed evaluations of their performance are rare. Indeed, analytical
models, simulations with pseudo-synthetic loads, studies focused on average-value
parameters, and measurements of networks disconnected from the machine all provide
limited information. In this paper, instead, we present an in-depth empirical
analysis of a multistage switching network in a realistic setting: we use hardware
probes to examine the performance of the omega network of the Cedar shared-memory
machine executing real applications. The machine is configured with 16 vector
processors. The analysis suggests that the performance of multistage switching
networks is limited by traffic non-uniformities. We identify two major non-uniformities
that degrade Cedar''s performance and are likely to slow down other networks too.
The first one is the contention caused by the return messages in a vector access
as they converge from the memories to one processor port. This traffic convergence
penalizes vector reads and, more importantly, causes tree saturation. The second
non-uniformity is the uneven contention delays induced by even a relatively fair
scheme to resolve message collisions. Based on our observations, we argue that
intuitive optimizations for multistage switching networks may not be cost-effective.
Instead, we suggest changes to increase the network bandwidth at the root of the
traffic convergence tree and to delay traffic convergence up until the final stages
of the network. >'
---
# SentenceTransformer based on nreimers/MiniLM-L6-H384-uncased
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [nreimers/MiniLM-L6-H384-uncased](https://huggingface.co/nreimers/MiniLM-L6-H384-uncased). 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:** [nreimers/MiniLM-L6-H384-uncased](https://huggingface.co/nreimers/MiniLM-L6-H384-uncased)
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 384 tokens
- **Similarity Function:** Cosine Similarity
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
### Full Model Architecture
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel
(1): Pooling({'word_embedding_dimension': 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})
)
```
## 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("sentence_transformers_model_id")
# Run inference
sentences = [
'Computationally efficient fixed complexity LLL algorithm for lattice-reduction-aided multiple-input–multiple-output precoding',
'In multiple-input–multiple-output broadcast channels, lattice reduction (LR) preprocessing technique can significantly improve the precoding performance. Among the existing LR algorithms, the fixed complexity Lenstra–Lenstra–Lovasz (fcLLL) algorithm applying limited number of LLL loops is suitable for the real-time communication system. However, fcLLL algorithm suffers from higher average complexity. Aiming at this problem, a computationally efficient fcLLL (CE-fcLLL) algorithm for LR-aided (LRA) precoding is developed in this study. First, the authors analyse the impact of fcLLL algorithm on the signal-to-noise ratio performance of LRA precoding by a power factor (PF) which is defined to measure the relation of reduced basis and transmit power of LRA precoding. Then, they propose a CE-fcLLL algorithm by designing a new LLL loop and introducing new early termination conditions to reduce redundant and inefficient LR operation in fcLLL algorithm. Finally, they define a PF loss factor to optimise the PF threshold and the number of LLL loops, which can lead to a performance-complexity tradeoff. Simulation results show that the proposed algorithm for LRA precoding can achieve better bit-error-rate performance than the fcLLL algorithm with remarkable complexity savings in the same upper complexity bound.',
'ABSTRACTThe success of the open innovation (OI) paradigm is still debated and literature is searching for its determinants. Although firms’ internal social context is crucial to explain the success or failure of OI practices, such context is still poorly investigated. The aim of the paper is to analyse whether internal social capital (SC), intended as employees’ propensity to interact and work in groups in order to solve innovation issues, mediates the relationship between OI practices and innovation ambidexterity (IA). Results, based on a survey research developed in Finland, Italy and Sweden, suggest that collaborations with different typologies of partners (scientific and business) achieve good results in terms of IA, through the partial mediation of the internal SC.',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 384]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
```
## Training Details
### Training Dataset
#### Unnamed Dataset
* Size: 730,454 training samples
* Columns: sentence_0 and sentence_1
* Approximate statistics based on the first 1000 samples:
| | sentence_0 | sentence_1 |
|:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
| type | string | string |
| details | - min: 4 tokens
- mean: 15.97 tokens
- max: 48 tokens
| - min: 18 tokens
- mean: 193.95 tokens
- max: 512 tokens
|
* Samples:
| sentence_0 | sentence_1 |
|:------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| E-government in a corporatist, communitarian society: the case of Singapore | Singapore was one of the early adopters of e-government initiatives in keeping with its status as one of the few developed Asian countries and has continued to be at the forefront of developing e-government structures. While crediting the city-state for the speed of its development, observers have critiqued that the republic limits pluralism, which directly affects e-governance initiatives. This article draws on two recent government initiatives, the notions of corporatism and communitarianism and the concept of symmetry and asymmetry in communication to present the e-government and e-governance structures in Singapore. Four factors are presented as critical for the creation of a successful e-government infrastructure: an educated citizenry; adequate technical infrastructures; offering e-services that citizens need; and commitment from top government officials to support the necessary changes with financial resources and leadership. However, to have meaningful e-governance there has to be political plural... |
| Multicast routing representation in ad hoc networks using fuzzy Petri nets | In an ad hoc network, each mobile node plays the role of a router and relays packets to final destinations. The network topology of an ad hoc network changes frequently and unpredictable, so that the routing and multicast become extremely challenging. We describe the multicast routing representation using fuzzy Petri net model with the concept of immediately reachable set in wireless ad hoc networks which all nodes equipped with GPS unit. It allows structured representation of network topology, and has a fuzzy reasoning algorithm for finding multicast tree and improves the efficiency of the ad hoc network routing scheme. Therefore when a packet is to be multicast to a group by a multicast source, a heuristic algorithm is used to compute the multicast tree based on the local network topology with a multicast source. Finally, the simulation shows that the percentage of the improvement is more than 15% when compared the IRS method with the original method. |
| A Prognosis Tool Based on Fuzzy Anthropometric and Questionnaire Data for Obstructive Sleep Apnea Severity | Obstructive sleep apnea (OSA) are linked to the augmented risk of morbidity and mortality. Although polysomnography is considered a well-established method for diagnosing OSA, it suffers the weakness of time consuming and labor intensive, and requires doctors and attending personnel to conduct an overnight evaluation in sleep laboratories with dedicated systems. This study aims at proposing an efficient diagnosis approach for OSA on the basis of anthropometric and questionnaire data. The proposed approach integrates fuzzy set theory and decision tree to predict OSA patterns. A total of 3343 subjects who were referred for clinical suspicion of OSA (eventually 2869 confirmed with OSA and 474 otherwise) were collected, and then classified by the degree of severity. According to an assessment of experiment results on g-means, our proposed method outperforms other methods such as linear regression, decision tree, back propagation neural network, support vector machine, and learning vector quantization. The proposed method is highly viable and capable of detecting the severity of OSA. It can assist doctors in pre-diagnosis of OSA before running the formal PSG test, thereby enabling the more effective use of medical resources. |
* Loss: [MultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
```json
{
"scale": 20.0,
"similarity_fct": "cos_sim"
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `per_device_train_batch_size`: 16
- `per_device_eval_batch_size`: 16
- `num_train_epochs`: 1
- `multi_dataset_batch_sampler`: round_robin
#### All Hyperparameters
Click to expand
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: no
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 16
- `per_device_eval_batch_size`: 16
- `per_gpu_train_batch_size`: None
- `per_gpu_eval_batch_size`: None
- `gradient_accumulation_steps`: 1
- `eval_accumulation_steps`: None
- `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`: -1
- `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`: False
- `hub_always_push`: False
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_inputs_for_metrics`: False
- `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
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: round_robin