biobert_model / README.md
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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: biobert_model
    results: []

biobert_model

This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9645
  • Accuracy: 0.8711
  • F1: 0.8475

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: 1e-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: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 1.0 334 0.6463 0.6897 0.7129
0.4503 2.0 668 0.3590 0.8651 0.8269
0.2715 3.0 1002 0.4549 0.8711 0.8252
0.2715 4.0 1336 0.6012 0.8681 0.8434
0.1335 5.0 1670 0.6307 0.8576 0.8313
0.0746 6.0 2004 0.7658 0.8636 0.8366
0.0746 7.0 2338 0.8658 0.8666 0.8436
0.0307 8.0 2672 0.8312 0.8711 0.8453
0.0148 9.0 3006 0.8922 0.8651 0.8421
0.0148 10.0 3340 0.8761 0.8726 0.8490
0.0128 11.0 3674 0.9329 0.8681 0.8462
0.0105 12.0 4008 0.9512 0.8666 0.8441
0.0105 13.0 4342 0.9553 0.8711 0.8475
0.0069 14.0 4676 0.9731 0.8681 0.8445
0.0046 15.0 5010 0.9645 0.8711 0.8475

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3