ksg-dfci/TrialSpace-0526

SentenceTransformer

This is a sentence-transformers model trained on the mnridataset and contrastivedataset datasets. It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for retrieval.

Model Details

Model Description

• —Model Type: Sentence Transformer <!-- - Base model: Unknown -->
• —Maximum Sequence Length: 2500 tokens
• —Output Dimensionality: 1024 dimensions
• —Similarity Function: Cosine Similarity
• —Supported Modality: Text
• —Training Datasets:
• —mnri_dataset
• —contrastive_dataset <!-- - Language: Unknown --> <!-- - License: Unknown -->

Model Sources

• —Documentation: Sentence Transformers Documentation
• —Repository: Sentence Transformers on GitHub
• —Hugging Face: Sentence Transformers on Hugging Face

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'transformer_task': 'feature-extraction', 'modality_config': {'text': {'method': 'forward', 'method_output_name': 'last_hidden_state'}}, 'module_output_name': 'token_embeddings', 'architecture': 'Qwen3Model'})
  (1): Pooling({'embedding_dimension': 1024, 'pooling_mode': 'lasttoken', 'include_prompt': True})
  (2): Normalize({})
)

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("sentence_transformers_model_id")
# Run inference
queries = [
    'Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age: 12\nSex: Male\nCancer type: Mediastinal mixed germ cell tumor\nHistology: Embryonal carcinoma, choriocarcinoma, and yolk sac tumor\nCurrent extent: Metastatic (mediastinal mass, mediastinal lymphadenopathy, and brain metastases in the right frontal and left parietal lobes). Most recent tumor markers (2018-03-30): AFP 310 ng/mL, Beta-hCG 850 mIU/mL, LDH 410 U/L; increasing trend.\nBiomarkers: SALL4 positive, AFP positive (yolk sac), Beta-hCG positive (choriocarcinoma), CD30 positive (embryonal carcinoma), Glypican-3 positive (yolk sac), Cytokeratin (AE1/AE3) positive. NGS: KRAS p.G12D pathogenic mutation, PTEN homozygous deletion, TP53 p.P72R (variant of uncertain significance), isochromosome 12p, gain of 20q.\nTreatment history:\n# 2015: bleomycin, etoposide, cisplatin; achieved partial response\n# 2016-02-09: Partial resection of anterior mediastinal mass\n# 2016-12-05-present: ifosfamide, cisplatin; achieved partial response, subsequently progressed',
]
documents = [
    'Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age range allowed: 1 to 21 years. Sex allowed: Both. Cancer type allowed: mediastinal mixed germ cell tumor. Histology allowed: pediatric malignant solid tumor. Cancer burden allowed: high-risk (expected 5-year Event-Free Survival < 60%) and < 30% chance at long-term cure and disease status of Stable Disease or better. Prior treatment required: prior primary therapy. Prior treatment excluded: NA. Biomarkers required: satisfactory TIL cellular product availability (assessed during screening). Biomarkers excluded: NA.',
    'Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age range allowed: 0 to 50 years. Sex allowed: Male. Cancer type allowed: Any cancer. Histology allowed: Hematologic. Cancer burden allowed: Any. Prior treatment required: NA. Prior treatment excluded: NA. Biomarkers required: NA. Biomarkers excluded: NA.',
    'Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age range allowed: 0 to 29 years. Sex allowed: both. Cancer type allowed: mixed phenotype acute leukemia with T cell dominant phenotype. Histology allowed: mixed phenotype acute leukemia with T cell dominant phenotype. Cancer burden allowed: Second or greater relapse or first relapse post-allogeneic hematopoietic stem cell transplant or primary refractory disease or relapsed and refractory disease. Prior treatment required: NA. Prior treatment excluded: CD7 targeted therapy. Biomarkers required: CD7 expression on leukemic blasts (at least 90% of blasts positive by flow cytometry or immunohistochemistry) assessed during screening. Biomarkers excluded: NA.',
]
query_embeddings = model.encode_query(queries)
document_embeddings = model.encode_document(documents)
print(query_embeddings.shape, document_embeddings.shape)
# [1, 1024] [3, 1024]

# Get the similarity scores for the embeddings
similarities = model.similarity(query_embeddings, document_embeddings)
print(similarities)
# tensor([[0.4132, 0.2552, 0.1695]])

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Direct Usage (Transformers)

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Downstream Usage (Sentence Transformers)

You can finetune this model on your own dataset.

<details><summary>Click to expand</summary>

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Training Details

Training Datasets

mnri_dataset

• —Dataset: mnri_dataset
• —Size: 1,174,581 training samples
• —Columns: <code>patientsummarytrunc</code> and <code>thisspacetrunc</code>
• —Approximate statistics based on the first 1000 samples: | | patientsummarytrunc | thisspacetrunc | |:--------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | type | string | string | | details | <ul><li>min: 146 tokens</li><li>mean: 323.8 tokens</li><li>max: 554 tokens</li></ul> | <ul><li>min: 101 tokens</li><li>mean: 155.35 tokens</li><li>max: 283 tokens</li></ul> |
• —Samples: | patientsummarytrunc | thisspacetrunc | |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age: 6<br>Sex: Male<br>Cancer type: Kaposiform hemangioendothelioma of the right lower extremity<br>Histology: Spindle cell vascular neoplasm (CD31 positive, CD34 positive, ERG positive, HHV-8 negative)<br>Current extent: Localized; status post wide local excision on 2023-02-06 with negative margins<br>Biomarkers: PIK3CA p.E542K mutant; PTEN, AKT1, KRAS, and TP53 wild-type<br>Treatment history:<br># 2020-10-28 to 2021-04-04: vincristine; achieved partial response (tumor decreased from 7 cm to 5.2 cm)<br># 2021-11-29 to 2022-10-18: paclitaxel; achieved partial response (tumor decreased from 9 cm to 6.4 cm)<br># 2023-02-06: wide local excision of right calf mass; negative margins</code> | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age range allowed: 0 to 14 years. Sex allowed: Male or Female. Cancer type allowed: Kaposiform hemangioendothelioma. Histology allowed: NA. Cancer burden allowed: NA. Prior treatment required: NA. Prior treatment excluded: sirolimus or other mTOR inhibitors. Biomarkers required: NA. Biomarkers excluded: NA.</code> | | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age: 14<br>Sex: Male<br>Cancer type: Kaposiform Hemangioendothelioma of the right lateral neck<br>Histology: Spindle cell proliferation with kaposiform architecture<br>Current extent: Stage T1N0M0; stable 3.1 cm mass in the right lateral neck as of 2021-02-08; platelets 228,000/uL as of 2020-12-12 (stable, no Kasabach-Merritt phenomenon)<br>Biomarkers: CD31 positive, CD34 positive, ERG positive, HHV-8 negative, GLUT1 negative/patchy, Ki-67 less than 5%, PIK3CA p.H1047R mutation, PTEN p.S167R mutation, STK11 wild-type, TSC1 wild-type<br>Treatment history:<br># 2018-11-21-2021-02-08: observation; stable disease</code> | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age range allowed: 0 to 14 years. Sex allowed: Male or Female. Cancer type allowed: Kaposiform hemangioendothelioma. Histology allowed: NA. Cancer burden allowed: NA. Prior treatment required: NA. Prior treatment excluded: sirolimus or other mTOR inhibitors. Biomarkers required: NA. Biomarkers excluded: NA.</code> | | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age: 17 Sex: Male Cancer type: T-cell lymphoblastic lymphoma Histology: T-cell lymphoblastic lymphoma Current extent: Relapsed and refractory. As of 2019-12-06, anterior mediastinal mass measuring 5.5 cm with associated superior vena cava narrowing and bilateral hilar lymphadenopathy. As of 2020-04-21, bone marrow involvement with 22% lymphoblasts. LDH is elevated (normalized during remission, rose to 412 U/L at relapse in 2019-03-26, and remains elevated as of 2020-08-21). Biomarkers: TdT positive, CD3 positive, CD7 positive, CD2 positive, CD5 positive, CD19 negative, CD20 negative, CD45 positive, Ki-67 >95%; NOTCH1 p.V1744G, CDKN2A homozygous deletion, PTEN p.R130Q, 12q gain Treatment history: # 2016-07 to 2016-12: vincristine, prednisone, L-asparaginase; best response ...</code> | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age range allowed: 0 to 29 years. Sex allowed: both. Cancer type allowed: T-cell acute lymphoblastic leukemia. Histology allowed: T-cell acute lymphoblastic leukemia. Cancer burden allowed: Second or greater relapse or first relapse post-allogeneic hematopoietic stem cell transplant or primary refractory disease or relapsed and refractory disease. Prior treatment required: NA. Prior treatment excluded: CD7 targeted therapy. Biomarkers required: CD7 expression on leukemic blasts (at least 90% of blasts positive by flow cytometry or immunohistochemistry) assessed during screening. Biomarkers excluded: NA.</code> |
• —Loss: <code>MultipleNegativesRankingLoss</code> with these parameters:

  {
      "scale": 20.0,
      "similarity_fct": "cos_sim",
      "gather_across_devices": false,
      "directions": [
          "query_to_doc"
      ],
      "partition_mode": "joint",
      "hardness_mode": null,
      "hardness_strength": 0.0
  }

contrastive_dataset

• —Dataset: contrastive_dataset
• —Size: 1,824,636 training samples
• —Columns: <code>patientsummarytrunc</code>, <code>thisspacetrunc</code>, and <code>label</code>
• —Approximate statistics based on the first 1000 samples: | | patientsummarytrunc | thisspacetrunc | label | |:--------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|:----------------------------------------------------------------| | type | string | string | float | | details | <ul><li>min: 76 tokens</li><li>mean: 294.03 tokens</li><li>max: 525 tokens</li></ul> | <ul><li>min: 101 tokens</li><li>mean: 132.43 tokens</li><li>max: 179 tokens</li></ul> | <ul><li>min: -1.0</li><li>mean: -0.7</li><li>max: 1.0</li></ul> |
• —Samples: | patientsummarytrunc | thisspacetrunc | label | |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------| | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age: 6<br>Sex: Male<br>Cancer type: Kaposiform hemangioendothelioma of the right lower extremity<br>Histology: Spindle cell vascular neoplasm (CD31 positive, CD34 positive, ERG positive, HHV-8 negative)<br>Current extent: Localized; status post wide local excision on 2023-02-06 with negative margins<br>Biomarkers: PIK3CA p.E542K mutant; PTEN, AKT1, KRAS, and TP53 wild-type<br>Treatment history:<br># 2020-10-28 to 2021-04-04: vincristine; achieved partial response (tumor decreased from 7 cm to 5.2 cm)<br># 2021-11-29 to 2022-10-18: paclitaxel; achieved partial response (tumor decreased from 9 cm to 6.4 cm)<br># 2023-02-06: wide local excision of right calf mass; negative margins</code> | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age range allowed: 0 to 14 years. Sex allowed: Male or Female. Cancer type allowed: Kaposiform hemangioendothelioma. Histology allowed: NA. Cancer burden allowed: NA. Prior treatment required: NA. Prior treatment excluded: sirolimus or other mTOR inhibitors. Biomarkers required: NA. Biomarkers excluded: NA.</code> | <code>-0.19999999999999996</code> | | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age: 14<br>Sex: Male<br>Cancer type: Kaposiform Hemangioendothelioma of the right lateral neck<br>Histology: Spindle cell proliferation with kaposiform architecture<br>Current extent: Stage T1N0M0; stable 3.1 cm mass in the right lateral neck as of 2021-02-08; platelets 228,000/uL as of 2020-12-12 (stable, no Kasabach-Merritt phenomenon)<br>Biomarkers: CD31 positive, CD34 positive, ERG positive, HHV-8 negative, GLUT1 negative/patchy, Ki-67 less than 5%, PIK3CA p.H1047R mutation, PTEN p.S167R mutation, STK11 wild-type, TSC1 wild-type<br>Treatment history:<br># 2018-11-21-2021-02-08: observation; stable disease</code> | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age range allowed: 0 to 14 years. Sex allowed: Male or Female. Cancer type allowed: Kaposiform hemangioendothelioma. Histology allowed: NA. Cancer burden allowed: NA. Prior treatment required: NA. Prior treatment excluded: sirolimus or other mTOR inhibitors. Biomarkers required: NA. Biomarkers excluded: NA.</code> | <code>-0.19999999999999996</code> | | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age: 46<br>Sex: Female<br>Cancer type: Retroperitoneal cancer<br>Histology: Epithelioid Hemangioendothelioma<br>Current extent: Metastatic (retroperitoneal mass, liver metastases, and ascites); progressive disease as of 2018-04-09<br>Biomarkers: CD31 positive, ERG positive, CD34 patchy positive, Pan-Cytokeratin negative, S100 negative, HMB-45 negative, SMA negative, Ki-67 15%, WWTR1-YAP1 fusion, PIK3CA p.E545K mutation, RB1 hemizygous loss, STK11 p.T123M mutation<br>Treatment history:<br># 2014-11-12: retroperitoneal debulking surgery; achieved no evidence of disease as of 2015-07-11<br># 2016-04-10-2017-05-16: paclitaxel; best response partial response (30 percent reduction in tumor diameter)<br># 2017-05-16-2018-04-09: capecitabine; best response stable disease</code> | <code>Instruct: Given a cancer patient summary, retrieve clinical trial options that are reasonable for that patient; or, given a clinical trial option, retrieve cancer patients who are reasonable candidates for that trial. Age range allowed: 0 to 14 years. Sex allowed: Male or Female. Cancer type allowed: Kaposiform hemangioendothelioma. Histology allowed: NA. Cancer burden allowed: NA. Prior treatment required: NA. Prior treatment excluded: sirolimus or other mTOR inhibitors. Biomarkers required: NA. Biomarkers excluded: NA.</code> | <code>-1.0</code> |
• —Loss: <code>CoSENTLoss</code> with these parameters:

  {
      "scale": 20.0,
      "similarity_fct": "pairwise_cos_sim"
  }

Training Hyperparameters

Non-Default Hyperparameters

• —per_device_train_batch_size: 10
• —learning_rate: 2e-05
• —warmup_steps: 0.01
• —bf16: True

All Hyperparameters

<details><summary>Click to expand</summary>

• —per_device_train_batch_size: 10
• —num_train_epochs: 3
• —max_steps: -1
• —learning_rate: 2e-05
• —lr_scheduler_type: linear
• —lr_scheduler_kwargs: None
• —warmup_steps: 0.01
• —optim: adamwtorchfused
• —optim_args: None
• —weight_decay: 0.0
• —adam_beta1: 0.9
• —adam_beta2: 0.999
• —adam_epsilon: 1e-08
• —optim_target_modules: None
• —gradient_accumulation_steps: 1
• —average_tokens_across_devices: True
• —max_grad_norm: 1.0
• —label_smoothing_factor: 0.0
• —bf16: True
• —fp16: False
• —bf16_full_eval: False
• —fp16_full_eval: False
• —tf32: None
• —gradient_checkpointing: False
• —gradient_checkpointing_kwargs: None
• —torch_compile: False
• —torch_compile_backend: None
• —torch_compile_mode: None
• —use_liger_kernel: False
• —liger_kernel_config: None
• —use_cache: False
• —neftune_noise_alpha: None
• —torch_empty_cache_steps: None
• —auto_find_batch_size: False
• —log_on_each_node: True
• —logging_nan_inf_filter: True
• —include_num_input_tokens_seen: no
• —log_level: passive
• —log_level_replica: warning
• —disable_tqdm: False
• —project: huggingface
• —trackio_space_id: None
• —trackio_bucket_id: None
• —trackio_static_space_id: None
• —per_device_eval_batch_size: 8
• —prediction_loss_only: True
• —eval_on_start: False
• —eval_do_concat_batches: True
• —eval_use_gather_object: False
• —eval_accumulation_steps: None
• —include_for_metrics: []
• —batch_eval_metrics: False
• —save_only_model: False
• —save_on_each_node: False
• —enable_jit_checkpoint: False
• —push_to_hub: False
• —hub_private_repo: None
• —hub_model_id: None
• —hub_strategy: every_save
• —hub_always_push: False
• —hub_revision: None
• —load_best_model_at_end: False
• —ignore_data_skip: False
• —restore_callback_states_from_checkpoint: False
• —full_determinism: False
• —seed: 42
• —data_seed: None
• —use_cpu: False
• —accelerator_config: {'splitbatches': False, 'dispatchbatches': None, 'evenbatches': True, 'useseedablesampler': True, 'nonblocking': False, 'gradientaccumulationkwargs': None}
• —parallelism_config: None
• —dataloader_drop_last: True
• —dataloader_num_workers: 0
• —dataloader_pin_memory: True
• —dataloader_persistent_workers: False
• —dataloader_prefetch_factor: None
• —remove_unused_columns: True
• —label_names: None
• —train_sampling_strategy: random
• —length_column_name: length
• —ddp_find_unused_parameters: None
• —ddp_bucket_cap_mb: None
• —ddp_broadcast_buffers: False
• —ddp_static_graph: None
• —ddp_backend: None
• —ddp_timeout: 1800
• —fsdp: []
• —fsdp_config: {'minnumparams': 0, 'xla': False, 'xlafsdpv2': False, 'xlafsdpgrad_ckpt': False}
• —deepspeed: None
• —debug: []
• —skip_memory_metrics: True
• —do_predict: False
• —resume_from_checkpoint: None
• —warmup_ratio: None
• —local_rank: -1
• —prompts: None
• —batch_sampler: batch_sampler
• —multi_dataset_batch_sampler: proportional
• —router_mapping: {}
• —learning_rate_mapping: {}

</details>

Training Logs

<details><summary>Click to expand</summary>

</details>

Training Time

• —Training: 7.8 hours

Framework Versions

• —Python: 3.13.13
• —Sentence Transformers: 5.4.1
• —Transformers: 5.8.0
• —PyTorch: 2.11.0+cu130
• —Accelerate: 1.13.0
• —Datasets: 4.8.5
• —Tokenizers: 0.22.2

Citation

BibTeX

Sentence Transformers

@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

@misc{oord2019representationlearningcontrastivepredictive,
      title={Representation Learning with Contrastive Predictive Coding},
      author={Aaron van den Oord and Yazhe Li and Oriol Vinyals},
      year={2019},
      eprint={1807.03748},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1807.03748},
}

CoSENTLoss

@article{10531646,
    author={Huang, Xiang and Peng, Hao and Zou, Dongcheng and Liu, Zhiwei and Li, Jianxin and Liu, Kay and Wu, Jia and Su, Jianlin and Yu, Philip S.},
    journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
    title={CoSENT: Consistent Sentence Embedding via Similarity Ranking},
    year={2024},
    doi={10.1109/TASLP.2024.3402087}
}

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