Edit model card

BioClinicalBERT-full-finetuned-ner-pablo

This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on the n2c2 2018 dataset for the paper https://arxiv.org/abs/2409.19467. It achieves the following results on the evaluation set:

  • Loss: 0.0834
  • Precision: 0.7938
  • Recall: 0.7935
  • F1: 0.7936
  • Accuracy: 0.9750

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 231 0.0943 0.7464 0.7612 0.7537 0.9720
No log 2.0 462 0.0801 0.7861 0.7821 0.7841 0.9750
0.2571 3.0 693 0.0806 0.7900 0.7911 0.7906 0.9748
0.2571 4.0 924 0.0834 0.7938 0.7935 0.7936 0.9750

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
Downloads last month
29
Safetensors
Model size
108M params
Tensor type
F32
·
Inference Examples
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 pabRomero/BioClinicalBERT-full-finetuned-ner-pablo

Finetuned
(15)
this model