readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: PathologyBERT-meningioma
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # PathologyBERT-meningioma
  
  This model is a fine-tuned version of [tsantos/PathologyBERT](https://huggingface.co/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
  