--- tags: - sentence-transformers - sentence-similarity - feature-extraction - dense - generated_from_trainer - dataset_size:20000 - loss:MultipleNegativesRankingLoss base_model: google/embeddinggemma-300m widget: - source_sentence: What are the main clinical manifestations and characteristics of congenital syphilis? sentences: - Trained staff in community health centers obtain information on infant weight during periodic visits scheduled at three and six months. Age- and sex-adjusted standard deviation scores (SDS) for weight are calculated using Dutch reference curves. Infant growth rates of weight gain in the first three and six months after birth are then calculated by comparing the weight at three or six months to the birth weight SDS. These growth rates provide information on the infant's growth trajectory and can help identify any deviations from the norm. - The main clinical manifestations of congenital syphilis include prematurity, low birth weight, hepatomegaly with or without splenomegaly, cutaneous lesions, limb pseudoparalysis, respiratory distress, jaundice, anemia, generalized lymphadenopathy, and osteitis and osteochondritis. Late congenital syphilis is characterized by saber shin deformity of the tibia, Clutton's joints, frontal bossing, saddle nose, deformed upper medial incisor teeth (Hutchinson's teeth), neurological deafness, and difficulty in learning. - When evaluating newborns, orthopaedic surgeons should consider risk factors such as difficult vaginal delivery of a large infant, which can be associated with fractures or brachial plexus injury, and breech position, which can be associated with developmental dysplasia of the hip (DDH). They should also be aware of conditions like Klippel-Feil syndrome, congenital muscular torticollis, arthrogryposis, and neurologic problems indicated by a high arch in the feet. - source_sentence: 'How do genetic and fetal environmental factors contribute to the increased risk of type 2 diabetes and vascular disease in infants with intrauterine growth restriction (IUGR)? ' sentences: - Radiologically, children with leukemia who develop measles-related pneumonia initially show perihilar and widespread peribronchial fine nodular opacities. In more severe cases, a diffuse honeycomb pattern with increased interstitial markings and areas of consolidation may develop. Histopathologically, lung biopsy reveals extensive alveolar exudate of mononuclear cells, with the presence of multinucleate giant cells and eosinophilic inclusions. Electron microscopy may confirm the presence of paramyxovirus group, which includes measles, in the giant cells. - According to the data from Children's Hospital Boston, the rate of urinary tract infection in infants between 0 and 3 months of age with fever and clinical bronchiolitis is 8%. The rate of bacteremia is 1.3%, and the rate of meningitis is 0.4%. - Genetic and fetal environmental factors play a role in the increased risk of type 2 diabetes and vascular disease in infants with intrauterine growth restriction (IUGR). The fetal insulin hypothesis suggests that genetically determined insulin resistance leads to decreased insulin-mediated growth in the fetus, as well as insulin resistance in adulthood, resulting in type 2 diabetes. Insulin resistance in IUGR infants can also lead to abnormal vascular development, increasing the risk of hypertension and vascular disease. Additionally, the thrifty genotype hypothesis proposes that genes responsible for causing diabetes have been retained in the genome of all individuals due to their beneficial effects during periods of starvation and undernourishment. However, in modern times of overeating and lack of exercise, these genes contribute to detrimental conditions such as early-onset obesity. - source_sentence: 'What role did psychological data play in shaping the understanding of encopretic and constipation problems in children? ' sentences: - Possible causes of neonatal jaundice in this patient could include blood group incompatibility, G6PD deficiency, or metabolic liver disease such as the cholangitic variant of congenital hepatic fibrosis. - In children, pyoderma gangrenosum is commonly associated with ulcerative colitis, followed by leukemia and Crohn's disease. - Psychological data was collected to create a psychological profile for children with encopretic and constipation problems. This data likely provided insights into the psychological factors that may contribute to these issues, helping to develop a more comprehensive understanding of the condition and potential treatment approaches. - source_sentence: 'What are the potential causes of the fractures and rickets in the 18-year-old girl with idiopathic DeToni Debre-Fanconi syndrome? ' sentences: - The management of diabetes mellitus in children requires adherence to certain standards that are different from those for adults. Children, including school-aged children, often lack the ability to control their diabetes optimally, necessitating the involvement of an adult. The responsibility of the family in the treatment of children with diabetes is crucial, with parents playing an active role in supervision and education. The management of diabetes in children disrupts their daily activities and can have an impact on their quality of life. - The fractures and rickets in the 18-year-old girl with idiopathic DeToni Debre-Fanconi syndrome may be caused by a combination of factors, including the unsuccessful treatment with vitamin D and potassium phosphate, as well as the low serum calcium levels and increased serum phosphorus levels observed during immobilization. The horizontal position with partial immobilization may have also played a role in changing the calcium-phosphate homeostasis and shifting bone minerals from inactive diaphyseal bone to the metabolically active sites of fractures and rickets. - Coats' disease is more common in males and can occur in both children and adults. While the exact cause of Coats' disease is not fully understood, it is suspected to be caused by a somatic mutation in the NDP gene. Other risk factors for developing Coats' disease are currently unknown. - source_sentence: 'How can interdisciplinary collaboration and clearly defined strategies help reduce damage and suffering for children and adolescents with mental disorders and their families? ' sentences: - 'The infant in the NICU presented with a degraded general status, intubation, and mechanical ventilation. They also had unilaterally diminished breath sounds, hypoxemia, oliguria, tachycardia, hypotension, abdominal distention, and fever. Additionally, they exhibited hepatosplenomegaly, oliguria progressing to anuria, thrombocytopenia, and hyperchromic hematuria. ' - Pneumothorax in children can have various causes, including lung cysts. In cases where there are signs of pneumothorax without a lung lesion to account for the condition, cysts of the lung should be suspected. The presence of cysts can be confirmed through radiographic evidence, which can also help determine the location and characteristics of the cysts. - Interdisciplinary collaboration, involving caregivers, mental health managers, and professionals, can play a crucial role in reducing damage and suffering for children and adolescents with mental disorders and their families. By developing a shared vision and practice, professionals can work together to establish dynamic strategies that address the complex demands of these individuals. This collaboration requires critical observation of services, conduct, and strategies to ensure that families and mental health services are brought closer together. By bridging the gap between demands and care, interdisciplinary collaboration can help improve the well-being and outcomes for children, adolescents, and their families. pipeline_tag: sentence-similarity library_name: sentence-transformers --- # SentenceTransformer based on google/embeddinggemma-300m This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [google/embeddinggemma-300m](https://huggingface.co/google/embeddinggemma-300m). 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. ## Model Details ### Model Description - **Model Type:** Sentence Transformer - **Base model:** [google/embeddinggemma-300m](https://huggingface.co/google/embeddinggemma-300m) - **Maximum Sequence Length:** 2048 tokens - **Output Dimensionality:** 768 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': 2048, 'do_lower_case': False, 'architecture': 'Gemma3TextModel'}) (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}) (2): Dense({'in_features': 768, 'out_features': 3072, 'bias': False, 'activation_function': 'torch.nn.modules.linear.Identity'}) (3): Dense({'in_features': 3072, 'out_features': 768, 'bias': False, 'activation_function': 'torch.nn.modules.linear.Identity'}) (4): Normalize() ) ``` ## Usage ### Direct Usage (Sentence Transformers) First install the Sentence Transformers library: ```bash pip install -U sentence-transformers ``` Then you can load this model and run inference. ```python from sentence_transformers import SentenceTransformer # Download from the 🤗 Hub model = SentenceTransformer("yasserrmd/pediatrics-gemma-300m-emb") # Run inference queries = [ "How can interdisciplinary collaboration and clearly defined strategies help reduce damage and suffering for children and adolescents with mental disorders and their families?\n", ] documents = [ 'Interdisciplinary collaboration, involving caregivers, mental health managers, and professionals, can play a crucial role in reducing damage and suffering for children and adolescents with mental disorders and their families. By developing a shared vision and practice, professionals can work together to establish dynamic strategies that address the complex demands of these individuals. This collaboration requires critical observation of services, conduct, and strategies to ensure that families and mental health services are brought closer together. By bridging the gap between demands and care, interdisciplinary collaboration can help improve the well-being and outcomes for children, adolescents, and their families.', 'Pneumothorax in children can have various causes, including lung cysts. In cases where there are signs of pneumothorax without a lung lesion to account for the condition, cysts of the lung should be suspected. The presence of cysts can be confirmed through radiographic evidence, which can also help determine the location and characteristics of the cysts.', 'The infant in the NICU presented with a degraded general status, intubation, and mechanical ventilation. They also had unilaterally diminished breath sounds, hypoxemia, oliguria, tachycardia, hypotension, abdominal distention, and fever. Additionally, they exhibited hepatosplenomegaly, oliguria progressing to anuria, thrombocytopenia, and hyperchromic hematuria. ', ] query_embeddings = model.encode_query(queries) document_embeddings = model.encode_document(documents) print(query_embeddings.shape, document_embeddings.shape) # [1, 768] [3, 768] # Get the similarity scores for the embeddings similarities = model.similarity(query_embeddings, document_embeddings) print(similarities) # tensor([[ 0.7673, -0.0352, 0.0221]]) ``` ## Training Details ### Training Dataset #### Unnamed Dataset * Size: 20,000 training samples * Columns: sentence_0 and sentence_1 * Approximate statistics based on the first 1000 samples: | | sentence_0 | sentence_1 | |:--------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence_0 | sentence_1 | |:--------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | What is the role of routine health check-ups in detecting and diagnosing metabolic syndrome and NAFLD in obese children? | Routine health check-ups are important in detecting and diagnosing metabolic syndrome and NAFLD in obese children. However, there is a lack of routine health check-up data specifically for these complications in obese children. To address this need, pediatric health promotion centers and pediatric obesity clinics have been developed. The aim of these centers is to provide routine health check-ups and obesity-oriented check-ups to detect and diagnose metabolic syndrome and NAFLD in children. | | How does the implementation of family-centered rounds (FCR) impact medical education?
 | The implementation of family-centered rounds (FCR) has raised concerns about its potential impact on medical education. Some evidence suggests that FCR may lead to decreased "didactic" teaching, increased discomfort in asking specific management questions, and limited time to discuss management options for residents and students (8, 9, 10, 11). However, the literature on the association between FCR and teaching has mainly focused on learners' perceptions, and there is a lack of objective data to address the relationship between FCR and medical knowledge acquisition. | | What are some common clinical symptoms of neonatal septicaemia?
 | Some common clinical symptoms of neonatal septicaemia include fever, poor feeding, excessive cry, difficulty in breathing, yellowish skin discoloration, skin rashes, jitteriness, and irritability. | * Loss: [MultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters: ```json { "scale": 20.0, "similarity_fct": "cos_sim", "gather_across_devices": false } ``` ### Training Hyperparameters #### Non-Default Hyperparameters - `per_device_train_batch_size`: 6 - `per_device_eval_batch_size`: 6 - `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`: 6 - `per_device_eval_batch_size`: 6 - `per_gpu_train_batch_size`: None - `per_gpu_eval_batch_size`: None - `gradient_accumulation_steps`: 1 - `eval_accumulation_steps`: None - `torch_empty_cache_steps`: None - `learning_rate`: 5e-05 - `weight_decay`: 0.0 - `adam_beta1`: 0.9 - `adam_beta2`: 0.999 - `adam_epsilon`: 1e-08 - `max_grad_norm`: 1 - `num_train_epochs`: 1 - `max_steps`: -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} - `parallelism_config`: None - `deepspeed`: None - `label_smoothing_factor`: 0.0 - `optim`: adamw_torch_fused - `optim_args`: None - `adafactor`: False - `group_by_length`: False - `length_column_name`: length - `ddp_find_unused_parameters`: None - `ddp_bucket_cap_mb`: None - `ddp_broadcast_buffers`: False - `dataloader_pin_memory`: True - `dataloader_persistent_workers`: False - `skip_memory_metrics`: True - `use_legacy_prediction_loop`: False - `push_to_hub`: False - `resume_from_checkpoint`: None - `hub_model_id`: None - `hub_strategy`: every_save - `hub_private_repo`: None - `hub_always_push`: False - `hub_revision`: None - `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 - `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 - `liger_kernel_config`: None - `eval_use_gather_object`: False - `average_tokens_across_devices`: False - `prompts`: None - `batch_sampler`: batch_sampler - `multi_dataset_batch_sampler`: round_robin - `router_mapping`: {} - `learning_rate_mapping`: {}
### Training Logs | Epoch | Step | Training Loss | |:------:|:----:|:-------------:| | 0.1500 | 500 | 0.0195 | | 0.2999 | 1000 | 0.0095 | | 0.4499 | 1500 | 0.0084 | | 0.5999 | 2000 | 0.0059 | | 0.7499 | 2500 | 0.0021 | | 0.8998 | 3000 | 0.0035 | ### Framework Versions - Python: 3.12.11 - Sentence Transformers: 5.1.0 - Transformers: 4.56.2 - PyTorch: 2.8.0+cu128 - Accelerate: 1.10.1 - Datasets: 4.0.0 - Tokenizers: 0.22.1 ## Citation ### BibTeX #### Sentence Transformers ```bibtex @inproceedings{reimers-2019-sentence-bert, title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", author = "Reimers, Nils and Gurevych, Iryna", booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing", month = "11", year = "2019", publisher = "Association for Computational Linguistics", url = "https://arxiv.org/abs/1908.10084", } ``` #### MultipleNegativesRankingLoss ```bibtex @misc{henderson2017efficient, title={Efficient Natural Language Response Suggestion for Smart Reply}, author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil}, year={2017}, eprint={1705.00652}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```