readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: sciBERT-case-finetuned-breastcancer
    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. -->
  
  # sciBERT-case-finetuned-breastcancer
  
  This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0058
  
  ## 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: 2e-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: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | No log        | 1.0   | 53   | 0.0126          |
  | No log        | 2.0   | 106  | 0.0097          |
  | No log        | 3.0   | 159  | 0.0113          |
  | No log        | 4.0   | 212  | 0.0094          |
  | No log        | 5.0   | 265  | 0.0080          |
  | No log        | 6.0   | 318  | 0.0091          |
  | No log        | 7.0   | 371  | 0.0078          |
  | No log        | 8.0   | 424  | 0.0087          |
  | No log        | 9.0   | 477  | 0.0077          |
  | 0.0037        | 10.0  | 530  | 0.0074          |
  | 0.0037        | 11.0  | 583  | 0.0072          |
  | 0.0037        | 12.0  | 636  | 0.0066          |
  | 0.0037        | 13.0  | 689  | 0.0069          |
  | 0.0037        | 14.0  | 742  | 0.0064          |
  | 0.0037        | 15.0  | 795  | 0.0063          |
  | 0.0037        | 16.0  | 848  | 0.0063          |
  | 0.0037        | 17.0  | 901  | 0.0058          |
  | 0.0037        | 18.0  | 954  | 0.0060          |
  | 0.0011        | 19.0  | 1007 | 0.0059          |
  | 0.0011        | 20.0  | 1060 | 0.0058          |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  