readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-base-uncased-finetuned-fakenews
    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. -->
  
  # bert-base-uncased-finetuned-fakenews
  
  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: 0.0656
  - Accuracy: 0.9901
  - F1: 0.9909
  
  ## 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: 5e-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: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 0.0505        | 1.0   | 3045  | 0.2405          | 0.9651   | 0.9685 |
  | 0.0463        | 2.0   | 6090  | 0.0473          | 0.9872   | 0.9881 |
  | 0.0272        | 3.0   | 9135  | 0.0607          | 0.9892   | 0.9900 |
  | 0.0154        | 4.0   | 12180 | 0.0522          | 0.9892   | 0.9900 |
  | 0.0047        | 5.0   | 15225 | 0.0717          | 0.9895   | 0.9903 |
  | 0.0024        | 6.0   | 18270 | 0.0656          | 0.9901   | 0.9909 |
  
  
  ### Framework versions
  
  - Transformers 4.22.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  