---
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:246166
- loss:MultipleNegativesRankingLoss
base_model: pankajrajdeo/UMLS-Pubmed-ST-TCE-Epoch-1-QA_10K-BioASQ
widget:
- source_sentence: Does innate defense regulator peptide 1018 protect against perinatal
brain injury?
sentences:
- pFR-Z is a specific gene therapy vehicle for EBV-positive carcinomas.
- There is emerging evidence that the VEGF system can play either a beneficial or
a detrimental role depending on the specific pathologic situations. Therefore,
modulating the renal VEGF axis by using an SRL-based regimen may influence the
evolution of kidney injury associated with renal transplantation.
- IDR-1018 suppresses proinflammatory mediators and cell injurious mechanisms in
the developing brain, and postinsult treatment is efficacious in reducing LPS-induced
hypoxic-ischemic brain damage. IDR-1018 is effective in the brain when given systemically,
confers neuroprotection of both gray and white matter, and lacks significant effects
on the brain under normal conditions. Thus, this peptide provides the features
of a promising neuroprotective agent in newborns with brain injury.
- source_sentence: Does decitabine induce G2/M cell cycle arrest by suppressing p38/NF-κB
signaling in human renal clear cell carcinoma?
sentences:
- We investigated gene expression profiling and pathways modulated by decitabine
in RCC cells. Decitabine was shown to suppress the growth of RCC cells via G2/M
cell cycle arrest and the p38-NF-κB signaling pathway may play a role in the anti-neoplastic
effect of decitabine in RCC cells.
- The CST and the MIST are safe and can be used as an alternative test to assess
functional capacity in patients hospitalized for acute lung diseases. The worse
the performance on the step tests, the lower the pulmonary function and the distance
walked on the 6MWT, the greater the dyspnea, and the longer the hospitalization.
- These findings implicate ENT1 in liver protection from ischemia and reperfusion
injury and suggest ENT inhibitors may be of benefit in the prevention or treatment
of ischemic liver injury.
- source_sentence: Does demineralized Bone Matrix Injection in Consolidation Phase
enhance Bone Regeneration in Distraction Osteogenesis via Endochondral Bone Formation?
sentences:
- In 10 consecutive patients with CECS, a 6-week forefoot strike running intervention
led to decreased postrunning lower leg intracompartmental pressures. Pain and
disability typically associated with CECS were greatly reduced for up to 1 year
after intervention. Surgical intervention was avoided for all patients.
- DBM administration into the distraction gap at the end of the distraction period
resulted in a significantly greater regenerate bone area, trabecular number, and
cortical thickness in the rabbit tibial DO model. These data suggest that percutaneous
DBM administration at the end of the distraction period or in the early consolidation
period may stimulate regenerate bone formation and consolidation in a clinical
situation with delayed bone healing during DO.
- The chemical reaction of DPGP and dentin indicated that DPGP combined with CO2
laser is a potential regimen for the treatment of vertical root fracture.
- source_sentence: Does hDAC inhibitor MS-275 attenuate the inflammatory reaction
in rat experimental autoimmune prostatitis?
sentences:
- In summary, our data demonstrated that MS-275 could effectively suppress inflammatory
reaction in EAP, through suppressing immune cells and pro-inflammatory molecules,
and inducing anti-inflammatory immune cells and molecules, which may suggest MS-275
as a potential candidate for treatment of inflammatory prostatitis.
- The quality and completeness of reporting should be enhanced as a priority, because
without this policymakers and practitioners will continue lack the evidence base
they need to inform decision-making about health inequity. Furthermore, there
is a need to develop methods to systematically consider impacts on equity in health
status that is currently lacking in systematic reviews.
- No HIV stage dominated the epidemical though the latent stage provided the largest
contribution. The role of each stage depends on the phase of the epidemic and
on the prevailing levels of sexual risk behavior in the populations in which HIV
is spreading. These findings may influence the design and implementation of different
HIV interventions.
- source_sentence: Are circulating microparticles elevated in carriers of factor V
Leiden?
sentences:
- Isovolemic hemodilution (approximately 5% hematocrit) with albumin, pentastarch,
or hetastarch solutions does not result in significant hepatic ischemia or injury
assessed by histology.
- Serial electrocardiogram recordings and troponin I assessments may be proposed
for initial screening in high-risk trauma patients to detect anatomical cardiac
injuries through the time course of circulating protein. Troponin I release does
not have a prognosis value in trauma patients.
- This is the first study on circulating MP levels in subjects who are heterozygote
for factor V Leiden. We report that circulating platelet and leukocyte MP are
elevated in carriers of this mutation and may be important contributors to risk
of thrombosis.
pipeline_tag: sentence-similarity
library_name: sentence-transformers
---
# SentenceTransformer based on pankajrajdeo/UMLS-Pubmed-ST-TCE-Epoch-1-QA_10K-BioASQ
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [pankajrajdeo/UMLS-Pubmed-ST-TCE-Epoch-1-QA_10K-BioASQ](https://huggingface.co/pankajrajdeo/UMLS-Pubmed-ST-TCE-Epoch-1-QA_10K-BioASQ). 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:** [pankajrajdeo/UMLS-Pubmed-ST-TCE-Epoch-1-QA_10K-BioASQ](https://huggingface.co/pankajrajdeo/UMLS-Pubmed-ST-TCE-Epoch-1-QA_10K-BioASQ)
- **Maximum Sequence Length:** 1024 tokens
- **Output Dimensionality:** 384 dimensions
- **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': 1024, '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("pankajrajdeo/UMLS-Pubmed-ST-TCE-Epoch-1-QA_10K-BioASQ-PQA")
# Run inference
sentences = [
'Are circulating microparticles elevated in carriers of factor V Leiden?',
'This is the first study on circulating MP levels in subjects who are heterozygote for factor V Leiden. We report that circulating platelet and leukocyte MP are elevated in carriers of this mutation and may be important contributors to risk of thrombosis.',
'Isovolemic hemodilution (approximately 5% hematocrit) with albumin, pentastarch, or hetastarch solutions does not result in significant hepatic ischemia or injury assessed by histology.',
]
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: 246,166 training samples
* Columns: anchor and positive
* Approximate statistics based on the first 1000 samples:
| | anchor | positive |
|:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
| type | string | string |
| details | - min: 6 tokens
- mean: 21.28 tokens
- max: 48 tokens
| - min: 9 tokens
- mean: 50.22 tokens
- max: 241 tokens
|
* Samples:
| anchor | positive |
|:---------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Survival of women with gestational trophoblastic neoplasia and liver metastases: is it improving? | The prognosis of patients with liver metastases from GTN has improved. Outcome may be best in those patients presenting within 2.8 years of the causative pregnancy and without very large volumes of disease. |
| Do serum nitrites predict the response to prostaglandin-induced delivery at term? | A reduced level of NOx is associated with a prompt clinical response to PGE-induced labor. Provided we do not know the origin of NOx in the general circulation, these data indicate NOx levels as predictors of the response to PGE-induced delivery at term and support the hypothesis that labor onset is modulated by the endogenous NO activity. |
| Is sleep deprivation an additional stress for parents staying in hospital? | Parental sleep deprivation needs to be acknowledged and accommodated when nurses and parents negotiate the care of children in hospital. |
* Loss: [MultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
```json
{
"scale": 20.0,
"similarity_fct": "cos_sim"
}
```
### Evaluation Dataset
#### Unnamed Dataset
* Size: 27,352 evaluation samples
* Columns: anchor and positive
* Approximate statistics based on the first 1000 samples:
| | anchor | positive |
|:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
| type | string | string |
| details | - min: 7 tokens
- mean: 21.61 tokens
- max: 63 tokens
| - min: 6 tokens
- mean: 48.56 tokens
- max: 223 tokens
|
* Samples:
| anchor | positive |
|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Is dEAD-box protein p68 regulated by β-catenin/transcription factor 4 to maintain a positive feedback loop in control of breast cancer progression? | Our findings indicate that Wnt/β-catenin signaling plays an important role in breast cancer progression through p68 upregulation. |
| Are obstetric medical emergency teams a step forward in maternal safety? | In the literature, there is a lack of reporting and probably of implementation of Obstetrics METs. Therefore, there is a need for more standardized experiences and reports on the implementation of various types of Obstetrics METs. We propose here a design for Obstetrics METs to be implemented in developing countries, aiming to reduce maternal mortality and morbidity resulting from obstetric hemorrhage. |
| Is monocyte-Induced Prostate Cancer Cell Invasion Mediated by Chemokine ligand 2 and Nuclear Factor-κB Activity? | Co-cultures with monocyte-lineage cell lines stimulated increased prostate cancer cell invasion through increased CCL2 expression and increased prostate cancer cell NF-κB activity. CCL2 and NF-κB may be useful therapeutic targets to interfere with inflammation-induced prostate cancer invasion. |
* 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
- `eval_strategy`: epoch
- `per_device_train_batch_size`: 16
- `per_device_eval_batch_size`: 16
- `gradient_accumulation_steps`: 4
- `learning_rate`: 2e-05
- `weight_decay`: 0.01
- `num_train_epochs`: 1
- `warmup_ratio`: 0.1
- `fp16`: True
- `load_best_model_at_end`: True
- `push_to_hub`: True
- `resume_from_checkpoint`: True
#### All Hyperparameters
Click to expand
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: epoch
- `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`: 4
- `eval_accumulation_steps`: None
- `torch_empty_cache_steps`: None
- `learning_rate`: 2e-05
- `weight_decay`: 0.01
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1.0
- `num_train_epochs`: 1
- `max_steps`: -1
- `lr_scheduler_type`: linear
- `lr_scheduler_kwargs`: {}
- `warmup_ratio`: 0.1
- `warmup_steps`: 0
- `log_level`: passive
- `log_level_replica`: warning
- `log_on_each_node`: True
- `logging_nan_inf_filter`: True
- `save_safetensors`: True
- `save_on_each_node`: False
- `save_only_model`: False
- `restore_callback_states_from_checkpoint`: False
- `no_cuda`: False
- `use_cpu`: False
- `use_mps_device`: False
- `seed`: 42
- `data_seed`: None
- `jit_mode_eval`: False
- `use_ipex`: False
- `bf16`: False
- `fp16`: True
- `fp16_opt_level`: O1
- `half_precision_backend`: auto
- `bf16_full_eval`: False
- `fp16_full_eval`: False
- `tf32`: None
- `local_rank`: 0
- `ddp_backend`: None
- `tpu_num_cores`: None
- `tpu_metrics_debug`: False
- `debug`: []
- `dataloader_drop_last`: False
- `dataloader_num_workers`: 0
- `dataloader_prefetch_factor`: None
- `past_index`: -1
- `disable_tqdm`: False
- `remove_unused_columns`: True
- `label_names`: None
- `load_best_model_at_end`: True
- `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`: True
- `resume_from_checkpoint`: True
- `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
- `include_for_metrics`: []
- `eval_do_concat_batches`: True
- `fp16_backend`: auto
- `push_to_hub_model_id`: None
- `push_to_hub_organization`: None
- `mp_parameters`:
- `auto_find_batch_size`: False
- `full_determinism`: False
- `torchdynamo`: None
- `ray_scope`: last
- `ddp_timeout`: 1800
- `torch_compile`: False
- `torch_compile_backend`: None
- `torch_compile_mode`: None
- `dispatch_batches`: None
- `split_batches`: None
- `include_tokens_per_second`: False
- `include_num_input_tokens_seen`: False
- `neftune_noise_alpha`: None
- `optim_target_modules`: None
- `batch_eval_metrics`: False
- `eval_on_start`: False
- `use_liger_kernel`: False
- `eval_use_gather_object`: False
- `average_tokens_across_devices`: False
- `prompts`: None
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: proportional