readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: electra-small-discriminator-finetuned-HC3-mix
    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-small-discriminator-finetuned-HC3-mix
  
  This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1812
  - F1: 0.9206
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.1116        | 1.0   | 8956  | 0.2602          | 0.8838 |
  | 0.0826        | 2.0   | 17912 | 0.1812          | 0.9206 |
  | 0.0692        | 3.0   | 26868 | 0.2226          | 0.9143 |
  | 0.0539        | 4.0   | 35824 | 0.2544          | 0.9126 |
  | 0.0492        | 5.0   | 44780 | 0.2500          | 0.9175 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  