Edit model card

PathologyBERT-meningioma

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

  • Loss: 0.8123
  • Accuracy: 0.8783
  • Precision: 0.25
  • Recall: 0.0833
  • F1: 0.125

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: 0
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.3723 1.0 71 0.5377 0.7652 0.0588 0.0833 0.0690
0.3363 2.0 142 0.4191 0.8783 0.25 0.0833 0.125
0.2773 3.0 213 0.4701 0.8870 0.3333 0.0833 0.1333
0.2303 4.0 284 0.5831 0.8957 0.5 0.0833 0.1429
0.1657 5.0 355 0.7083 0.8348 0.1111 0.0833 0.0952
0.1228 6.0 426 1.0324 0.8 0.0769 0.0833 0.08
0.0967 7.0 497 0.8103 0.8696 0.2 0.0833 0.1176
0.0729 8.0 568 0.8711 0.8696 0.2 0.0833 0.1176
0.0624 9.0 639 0.7968 0.8783 0.25 0.0833 0.125
0.0534 10.0 710 0.8123 0.8783 0.25 0.0833 0.125

Framework versions

  • Transformers 4.12.2
  • Pytorch 1.10.1
  • Datasets 1.15.0
  • Tokenizers 0.10.3
Downloads last month
6