readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: CancerTextV1
    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. -->
  
  # CancerTextV1
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5476
  - Accuracy: 0.8683
  - Precision: 0.8558
  - Recall: 0.8870
  - F1: 0.8711
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.3268        | 1.0   | 600  | 0.3939          | 0.8475   | 0.8268    | 0.8804 | 0.8528 |
  | 0.3132        | 2.0   | 1200 | 0.3510          | 0.8475   | 0.8509    | 0.8439 | 0.8474 |
  | 0.2595        | 3.0   | 1800 | 0.3631          | 0.8617   | 0.8505    | 0.8787 | 0.8644 |
  | 0.2256        | 4.0   | 2400 | 0.4303          | 0.8625   | 0.8507    | 0.8804 | 0.8653 |
  | 0.1944        | 5.0   | 3000 | 0.4551          | 0.8642   | 0.8592    | 0.8721 | 0.8656 |
  | 0.1734        | 6.0   | 3600 | 0.4673          | 0.86     | 0.8434    | 0.8854 | 0.8639 |
  | 0.1446        | 7.0   | 4200 | 0.4960          | 0.87     | 0.8562    | 0.8904 | 0.8730 |
  | 0.1371        | 8.0   | 4800 | 0.5162          | 0.8708   | 0.8646    | 0.8804 | 0.8724 |
  | 0.123         | 9.0   | 5400 | 0.5396          | 0.8642   | 0.8604    | 0.8704 | 0.8654 |
  | 0.1174        | 10.0  | 6000 | 0.5476          | 0.8683   | 0.8558    | 0.8870 | 0.8711 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  