metadata

license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: clinical-t5
    results: []
datasets:
  - AGBonnet/augmented-clinical-notes
language:
  - en
metrics:
  - rouge
pipeline_tag: summarization

clinical-t5

This is a finetuned T5-small model from Google, a checkpoint with 60 million parameters, for clinical note summarization. It was finetuned with the augmented-clinical-notes dataset, available in the Hugging Face.

Intended uses & limitations

The model was created for learning purposes. Hence, although being briefly evaluated in this notebook, it should be further refined.

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Framework versions

Transformers 4.30.0
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.13.3