readme: ---
  license: afl-3.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: covid-general-news-bert
    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. -->
  
  # covid-general-news-bert
  
  This model is a fine-tuned version of [bvrau/covid-twitter-bert-v2-struth](https://huggingface.co/bvrau/covid-twitter-bert-v2-struth) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0688
  - Accuracy: 0.9774
  - Precision: 0.9781
  - Recall: 0.9738
  - F1: 0.9760
  
  ## 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: 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: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.2183        | 1.0   | 365  | 0.0688          | 0.9774   | 0.9781    | 0.9738 | 0.9760 |
  | 0.0783        | 2.0   | 730  | 0.0754          | 0.9842   | 0.9812    | 0.9855 | 0.9833 |
  | 0.0354        | 3.0   | 1095 | 0.0766          | 0.9856   | 0.9785    | 0.9913 | 0.9848 |
  | 0.0185        | 4.0   | 1460 | 0.0956          | 0.9822   | 0.9715    | 0.9913 | 0.9813 |
  | 0.0227        | 5.0   | 1825 | 0.0693          | 0.9870   | 0.9827    | 0.9898 | 0.9862 |
  | 0.0084        | 6.0   | 2190 | 0.0870          | 0.9849   | 0.9926    | 0.9753 | 0.9839 |
  | 0.0021        | 7.0   | 2555 | 0.0729          | 0.9877   | 0.9883    | 0.9855 | 0.9869 |
  | 0.0002        | 8.0   | 2920 | 0.1197          | 0.9808   | 0.9688    | 0.9913 | 0.9799 |
  | 0.0033        | 9.0   | 3285 | 0.0768          | 0.9884   | 0.9912    | 0.9840 | 0.9876 |
  | 0.0009        | 10.0  | 3650 | 0.1013          | 0.9863   | 0.9869    | 0.9840 | 0.9854 |
  | 0.0           | 11.0  | 4015 | 0.1069          | 0.9863   | 0.9869    | 0.9840 | 0.9854 |
  | 0.0           | 12.0  | 4380 | 0.1124          | 0.9856   | 0.9854    | 0.9840 | 0.9847 |
  | 0.0           | 13.0  | 4745 | 0.1175          | 0.9849   | 0.9854    | 0.9826 | 0.9840 |
  | 0.0           | 14.0  | 5110 | 0.1221          | 0.9849   | 0.9854    | 0.9826 | 0.9840 |
  | 0.0           | 15.0  | 5475 | 0.1256          | 0.9849   | 0.9854    | 0.9826 | 0.9840 |
  | 0.0           | 16.0  | 5840 | 0.1286          | 0.9849   | 0.9854    | 0.9826 | 0.9840 |
  | 0.0           | 17.0  | 6205 | 0.1300          | 0.9856   | 0.9854    | 0.9840 | 0.9847 |
  | 0.0           | 18.0  | 6570 | 0.1293          | 0.9849   | 0.9854    | 0.9826 | 0.9840 |
  | 0.0           | 19.0  | 6935 | 0.1304          | 0.9849   | 0.9854    | 0.9826 | 0.9840 |
  | 0.0           | 20.0  | 7300 | 0.1308          | 0.9849   | 0.9854    | 0.9826 | 0.9840 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  