readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlnet-base-cased_fold_10_binary_v1
    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_10_binary_v1
  
  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: 1.7782
  - F1: 0.8137
  
  ## 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  | 0.3796          | 0.8145 |
  | 0.4196        | 2.0   | 576  | 0.4319          | 0.7810 |
  | 0.4196        | 3.0   | 864  | 0.6227          | 0.8002 |
  | 0.231         | 4.0   | 1152 | 0.6258          | 0.7941 |
  | 0.231         | 5.0   | 1440 | 1.0692          | 0.7866 |
  | 0.1307        | 6.0   | 1728 | 1.1257          | 0.8005 |
  | 0.0756        | 7.0   | 2016 | 1.2283          | 0.8072 |
  | 0.0756        | 8.0   | 2304 | 1.3407          | 0.8061 |
  | 0.0486        | 9.0   | 2592 | 1.5232          | 0.8059 |
  | 0.0486        | 10.0  | 2880 | 1.6731          | 0.8053 |
  | 0.0339        | 11.0  | 3168 | 1.6536          | 0.8087 |
  | 0.0339        | 12.0  | 3456 | 1.7526          | 0.7996 |
  | 0.019         | 13.0  | 3744 | 1.6662          | 0.7909 |
  | 0.0237        | 14.0  | 4032 | 1.6028          | 0.8071 |
  | 0.0237        | 15.0  | 4320 | 1.7627          | 0.7964 |
  | 0.0078        | 16.0  | 4608 | 1.6513          | 0.8169 |
  | 0.0078        | 17.0  | 4896 | 1.7795          | 0.8039 |
  | 0.015         | 18.0  | 5184 | 1.8669          | 0.7935 |
  | 0.015         | 19.0  | 5472 | 1.6288          | 0.8118 |
  | 0.0124        | 20.0  | 5760 | 1.6630          | 0.8104 |
  | 0.004         | 21.0  | 6048 | 1.7418          | 0.8167 |
  | 0.004         | 22.0  | 6336 | 1.7651          | 0.8128 |
  | 0.0043        | 23.0  | 6624 | 1.7279          | 0.8163 |
  | 0.0043        | 24.0  | 6912 | 1.8177          | 0.8093 |
  | 0.004         | 25.0  | 7200 | 1.7782          | 0.8137 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  