readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  model-index:
  - name: distilbert-base-uncased-finetuned-category-classification
    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. -->
  
  # distilbert-base-uncased-finetuned-category-classification
  
  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: 0.0377
  - F1: 0.9943
  - Roc Auc: 0.9943
  - Accuracy: 0.9943
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
  | 0.0374        | 1.0   | 7612  | 0.0373          | 0.9916 | 0.9916  | 0.9915   |
  | 0.0255        | 2.0   | 15224 | 0.0409          | 0.9922 | 0.9922  | 0.9921   |
  | 0.0281        | 3.0   | 22836 | 0.0332          | 0.9934 | 0.9934  | 0.9934   |
  | 0.0189        | 4.0   | 30448 | 0.0359          | 0.9941 | 0.9941  | 0.9940   |
  | 0.005         | 5.0   | 38060 | 0.0377          | 0.9943 | 0.9943  | 0.9943   |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  