readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlnet-base-cased_fold_5_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_5_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: 1.7395
  - F1: 0.8206
  
  ## 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  | 0.4246          | 0.8154 |
  | 0.4211        | 2.0   | 576  | 0.5181          | 0.8063 |
  | 0.4211        | 3.0   | 864  | 0.4939          | 0.8149 |
  | 0.2483        | 4.0   | 1152 | 0.6181          | 0.8227 |
  | 0.2483        | 5.0   | 1440 | 0.9251          | 0.8006 |
  | 0.1512        | 6.0   | 1728 | 0.9639          | 0.8082 |
  | 0.0858        | 7.0   | 2016 | 1.1315          | 0.8074 |
  | 0.0858        | 8.0   | 2304 | 1.1322          | 0.8303 |
  | 0.053         | 9.0   | 2592 | 1.3171          | 0.8017 |
  | 0.053         | 10.0  | 2880 | 1.3729          | 0.8100 |
  | 0.0325        | 11.0  | 3168 | 1.2708          | 0.8252 |
  | 0.0325        | 12.0  | 3456 | 1.5105          | 0.8242 |
  | 0.0203        | 13.0  | 3744 | 1.4902          | 0.8233 |
  | 0.0179        | 14.0  | 4032 | 1.5874          | 0.8194 |
  | 0.0179        | 15.0  | 4320 | 1.5933          | 0.8135 |
  | 0.0174        | 16.0  | 4608 | 1.5908          | 0.8088 |
  | 0.0174        | 17.0  | 4896 | 1.5692          | 0.8249 |
  | 0.0129        | 18.0  | 5184 | 1.6597          | 0.8167 |
  | 0.0129        | 19.0  | 5472 | 1.6009          | 0.8218 |
  | 0.0095        | 20.0  | 5760 | 1.6962          | 0.8225 |
  | 0.0062        | 21.0  | 6048 | 1.7075          | 0.8182 |
  | 0.0062        | 22.0  | 6336 | 1.7335          | 0.8181 |
  | 0.0077        | 23.0  | 6624 | 1.7175          | 0.8204 |
  | 0.0077        | 24.0  | 6912 | 1.7680          | 0.8187 |
  | 0.0024        | 25.0  | 7200 | 1.7395          | 0.8206 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  