metadata

widget:
  - text: >-
      Patient A, a 67-year-old male with a history of hypertension and obesity,
      received his first dose of the Pfizer COVID-19 vaccine on January 5th,
      2022. He reported no adverse reactions following the vaccine and was
      discharged home. However, two days later, he presented to the emergency
      department with complaints of chest pain, shortness of breath, and cough.
      He was found to have an elevated troponin level and was diagnosed with an
      acute myocardial infarction (AMI) as his primary diagnosis. The cause of
      death was determined to be due to complications of the AMI, which led to
      cardiogenic shock and subsequent multi-organ failure. Secondary diagnoses
      included acute respiratory distress syndrome (ARDS) and acute renal
      failure. Symptoms included chest pain, shortness of breath, cough, and
      hypotension. Rule out diagnoses included COVID-19 infection and pulmonary
      embolism. The patient had a medical history of hypertension, obesity, and
      hyperlipidemia. There was no significant family history. The patient was
      treated with thrombolytic therapy and mechanical ventilation but
      unfortunately, he succumbed to his illness and passed away on January
      13th, 2022. The Pfizer COVID-19 vaccine was noted as part of his medical
      history. The case was reported to the Vaccine Adverse Event Reporting
      System (VAERS) for further investigation.
    example_title: Medical Case
license: apache-2.0
tags:
  - summarization
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: t5-small-finetuned-pubmed
    results: []

t5-small-finetuned-pubmed

This model is a fine-tuned version of t5-small on a truncated PubMed Summarization dataset. It achieves the following results on the evaluation set:

Loss: 2.7252
Rouge1: 19.4457
Rouge2: 3.125
Rougel: 18.3168
Rougelsum: 18.5625

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5.6e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
3.2735	1.0	13	2.9820	18.745	3.7918	15.7876	15.8512
3.0428	2.0	26	2.8828	17.953	2.5	15.49	15.468
2.6259	3.0	39	2.8283	21.5532	5.9278	19.7523	19.9232
3.0795	4.0	52	2.7910	20.9244	5.9278	19.8685	20.0181
2.8276	5.0	65	2.7613	20.6403	3.125	18.0574	18.2227
2.64	6.0	78	2.7404	19.4457	3.125	18.3168	18.5625
2.5525	7.0	91	2.7286	19.4457	3.125	18.3168	18.5625
2.4951	8.0	104	2.7252	19.4457	3.125	18.3168	18.5625

Framework versions

Transformers 4.25.1
Pytorch 1.13.0
Datasets 2.8.0
Tokenizers 0.13.2