readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: electra-base-discriminator-finetuned-filtered-0609
    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. -->
  
  # electra-base-discriminator-finetuned-filtered-0609
  
  This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1933
  - Accuracy: 0.9745
  - Precision: 0.9747
  - Recall: 0.9745
  - F1: 0.9746
  
  ## 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
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.238         | 1.0   | 3180  | 0.1861          | 0.9682   | 0.9686    | 0.9682 | 0.9682 |
  | 0.1827        | 2.0   | 6360  | 0.2262          | 0.9645   | 0.9648    | 0.9645 | 0.9644 |
  | 0.1326        | 3.0   | 9540  | 0.1904          | 0.9711   | 0.9716    | 0.9711 | 0.9712 |
  | 0.1575        | 4.0   | 12720 | 0.2065          | 0.9676   | 0.9680    | 0.9676 | 0.9676 |
  | 0.1224        | 5.0   | 15900 | 0.2666          | 0.9557   | 0.9571    | 0.9557 | 0.9558 |
  | 0.1083        | 6.0   | 19080 | 0.1697          | 0.9752   | 0.9754    | 0.9752 | 0.9752 |
  | 0.0792        | 7.0   | 22260 | 0.1684          | 0.9742   | 0.9744    | 0.9742 | 0.9742 |
  | 0.0751        | 8.0   | 25440 | 0.1784          | 0.9723   | 0.9726    | 0.9723 | 0.9723 |
  | 0.0572        | 9.0   | 28620 | 0.1868          | 0.9736   | 0.9737    | 0.9736 | 0.9736 |
  | 0.0593        | 10.0  | 31800 | 0.1933          | 0.9745   | 0.9747    | 0.9745 | 0.9746 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.9.1+cu111
  - Datasets 1.16.1
  - Tokenizers 0.12.1
  