readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlnet-base-cased_fold_1_binary
    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. -->
  
  # xlnet-base-cased_fold_1_binary
  
  This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7607
  - F1: 0.7778
  
  ## 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: 25
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 288  | 0.4111          | 0.7555 |
  | 0.4387        | 2.0   | 576  | 0.4075          | 0.7540 |
  | 0.4387        | 3.0   | 864  | 0.5344          | 0.7567 |
  | 0.2471        | 4.0   | 1152 | 0.7405          | 0.7597 |
  | 0.2471        | 5.0   | 1440 | 1.0564          | 0.7508 |
  | 0.1419        | 6.0   | 1728 | 1.0703          | 0.7751 |
  | 0.0845        | 7.0   | 2016 | 1.0866          | 0.7609 |
  | 0.0845        | 8.0   | 2304 | 1.2135          | 0.7751 |
  | 0.05          | 9.0   | 2592 | 1.3649          | 0.7516 |
  | 0.05          | 10.0  | 2880 | 1.4943          | 0.7590 |
  | 0.0267        | 11.0  | 3168 | 1.5174          | 0.7412 |
  | 0.0267        | 12.0  | 3456 | 1.4884          | 0.7559 |
  | 0.0278        | 13.0  | 3744 | 1.5109          | 0.7405 |
  | 0.0201        | 14.0  | 4032 | 1.7251          | 0.7409 |
  | 0.0201        | 15.0  | 4320 | 1.5833          | 0.7354 |
  | 0.0185        | 16.0  | 4608 | 1.7744          | 0.7598 |
  | 0.0185        | 17.0  | 4896 | 1.8283          | 0.7619 |
  | 0.0066        | 18.0  | 5184 | 1.7607          | 0.7778 |
  | 0.0066        | 19.0  | 5472 | 1.7503          | 0.7719 |
  | 0.0078        | 20.0  | 5760 | 1.7807          | 0.7508 |
  | 0.006         | 21.0  | 6048 | 1.6887          | 0.7629 |
  | 0.006         | 22.0  | 6336 | 1.7041          | 0.7678 |
  | 0.0074        | 23.0  | 6624 | 1.7337          | 0.7633 |
  | 0.0074        | 24.0  | 6912 | 1.7548          | 0.7645 |
  | 0.0035        | 25.0  | 7200 | 1.7685          | 0.7621 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  