Edit model card

clinical_document_summarization

This model is a fine-tuned version of flax-community/spanish-t5-small on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4429
  • Rouge1: 0.3814
  • Rouge2: 0.3162
  • Rougel: 0.3727
  • Rougelsum: 0.3727
  • Gen Len: 19.0

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: 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: 8
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
0.9449 1.0 592 0.6076 0.3739 0.303 0.3633 0.3632 18.9996
0.6902 2.0 1184 0.5278 0.3771 0.3101 0.3686 0.3685 19.0
0.601 3.0 1776 0.4962 0.3797 0.3143 0.3721 0.3721 19.0
0.568 4.0 2368 0.4721 0.3792 0.3134 0.3701 0.3701 19.0
0.5334 5.0 2960 0.4597 0.3795 0.3143 0.3713 0.3713 19.0
0.4968 6.0 3552 0.4496 0.3816 0.3165 0.3729 0.3729 19.0
0.4873 7.0 4144 0.4449 0.3812 0.316 0.3726 0.3726 19.0
0.4794 8.0 4736 0.4429 0.3814 0.3162 0.3727 0.3727 19.0

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
Downloads last month
13
Safetensors
Model size
60.5M params
Tensor type
F32
·
Inference API
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for biololab/clinical_document_summarization

Finetuned
this model