readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: electra-base-discriminator-finetuned-removed-0530
    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-removed-0530
  
  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: 0.9713
  - Accuracy: 0.8824
  - F1: 0.8824
  
  ## 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 | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | No log        | 1.0   | 3180  | 0.6265          | 0.8107   | 0.8128 |
  | No log        | 2.0   | 6360  | 0.5158          | 0.8544   | 0.8541 |
  | No log        | 3.0   | 9540  | 0.6686          | 0.8563   | 0.8567 |
  | No log        | 4.0   | 12720 | 0.6491          | 0.8711   | 0.8709 |
  | No log        | 5.0   | 15900 | 0.8048          | 0.8660   | 0.8672 |
  | No log        | 6.0   | 19080 | 0.8110          | 0.8708   | 0.8710 |
  | No log        | 7.0   | 22260 | 1.0082          | 0.8651   | 0.8640 |
  | 0.2976        | 8.0   | 25440 | 0.8343          | 0.8811   | 0.8814 |
  | 0.2976        | 9.0   | 28620 | 0.9366          | 0.8780   | 0.8780 |
  | 0.2976        | 10.0  | 31800 | 0.9713          | 0.8824   | 0.8824 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.9.0
  - Datasets 1.16.1
  - Tokenizers 0.12.1
  