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ICU_Returns_ClinicalBERT

Text Classification
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PyTorch
distilbert
Generated from Trainer
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ICU_Returns_ClinicalBERT / README.md
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ClinicalBERT Versione dopo 13 epochs
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metadata
base_model: medicalai/ClinicalBERT
tags:
  - generated_from_trainer
model-index:
  - name: ICU_Returns_ClinicalBERT
    results: []

ICU_Returns_ClinicalBERT

This model is a fine-tuned version of medicalai/ClinicalBERT on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3201
  • F1:: 0.7134
  • Roc Auc: 0.7225
  • Precision with 0:: 0.8462
  • Precision with 1:: 0.6640
  • Recall with 0:: 0.5440
  • Recal with 1:: 0.9011
  • Accuracy:: 0.7225

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 13

Training results

Training Loss Epoch Step Validation Loss F1: Roc Auc Precision with 0: Precision with 1: Recall with 0: Recal with 1: Accuracy:
No log 1.0 46 0.7057 0.3454 0.5055 1.0 0.5028 0.0110 1.0 0.5055
No log 2.0 92 0.6827 0.5715 0.5742 0.5882 0.5640 0.4945 0.6538 0.5742
No log 3.0 138 0.7221 0.4612 0.5467 0.7297 0.5260 0.1484 0.9451 0.5467
No log 4.0 184 0.6284 0.6693 0.6841 0.6293 0.8190 0.8956 0.4725 0.6841
No log 5.0 230 0.9235 0.6283 0.6401 0.7179 0.6032 0.4615 0.8187 0.6401
No log 6.0 276 0.8772 0.6534 0.6648 0.7586 0.6210 0.4835 0.8462 0.6648
No log 7.0 322 0.7968 0.7677 0.7692 0.8224 0.7311 0.6868 0.8516 0.7692
No log 8.0 368 0.6826 0.8132 0.8132 0.8167 0.8098 0.8077 0.8187 0.8132
No log 9.0 414 1.2195 0.6950 0.7033 0.8033 0.6529 0.5385 0.8681 0.7033
No log 10.0 460 0.9542 0.7617 0.7637 0.8243 0.7222 0.6703 0.8571 0.7637
0.3635 11.0 506 1.3032 0.7079 0.7143 0.8047 0.6653 0.5659 0.8626 0.7143
0.3635 12.0 552 1.4170 0.7063 0.7143 0.8197 0.6612 0.5495 0.8791 0.7143
0.3635 13.0 598 1.3201 0.7134 0.7225 0.8462 0.6640 0.5440 0.9011 0.7225

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.5
  • Tokenizers 0.14.1