readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  model-index:
  - name: bert-finetuned-gender_classification
    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-finetuned-gender_classification
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1484
  - F1: 0.9645
  - Roc Auc: 0.9732
  - Accuracy: 0.964
  
  ## 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: 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
  | 0.1679        | 1.0   | 1125  | 0.1781          | 0.928  | 0.946   | 0.927    |
  | 0.1238        | 2.0   | 2250  | 0.1252          | 0.9516 | 0.9640  | 0.95     |
  | 0.0863        | 3.0   | 3375  | 0.1283          | 0.9515 | 0.9637  | 0.95     |
  | 0.0476        | 4.0   | 4500  | 0.1419          | 0.9565 | 0.9672  | 0.956    |
  | 0.0286        | 5.0   | 5625  | 0.1428          | 0.9555 | 0.9667  | 0.954    |
  | 0.0091        | 6.0   | 6750  | 0.1515          | 0.9604 | 0.9700  | 0.959    |
  | 0.0157        | 7.0   | 7875  | 0.1535          | 0.9580 | 0.9682  | 0.957    |
  | 0.0048        | 8.0   | 9000  | 0.1484          | 0.9645 | 0.9732  | 0.964    |
  | 0.0045        | 9.0   | 10125 | 0.1769          | 0.9605 | 0.9703  | 0.96     |
  | 0.0037        | 10.0  | 11250 | 0.2007          | 0.9565 | 0.9672  | 0.956    |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  