readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlnet-base-cased_fold_9_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_9_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: 1.7204
  - F1: 0.8203
  
  ## 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   | 291  | 0.4045          | 0.8001 |
  | 0.4262        | 2.0   | 582  | 0.3914          | 0.8297 |
  | 0.4262        | 3.0   | 873  | 0.5050          | 0.8029 |
  | 0.2488        | 4.0   | 1164 | 0.7681          | 0.8007 |
  | 0.2488        | 5.0   | 1455 | 0.8349          | 0.8262 |
  | 0.1483        | 6.0   | 1746 | 0.9045          | 0.8220 |
  | 0.0894        | 7.0   | 2037 | 1.1584          | 0.8165 |
  | 0.0894        | 8.0   | 2328 | 1.1818          | 0.8300 |
  | 0.0389        | 9.0   | 2619 | 1.3332          | 0.8147 |
  | 0.0389        | 10.0  | 2910 | 1.2373          | 0.8285 |
  | 0.038         | 11.0  | 3201 | 1.3156          | 0.8234 |
  | 0.038         | 12.0  | 3492 | 1.3251          | 0.8341 |
  | 0.0211        | 13.0  | 3783 | 1.3144          | 0.8255 |
  | 0.0158        | 14.0  | 4074 | 1.5686          | 0.8168 |
  | 0.0158        | 15.0  | 4365 | 1.5382          | 0.8185 |
  | 0.0165        | 16.0  | 4656 | 1.5203          | 0.8282 |
  | 0.0165        | 17.0  | 4947 | 1.5352          | 0.8136 |
  | 0.0142        | 18.0  | 5238 | 1.4799          | 0.8243 |
  | 0.0062        | 19.0  | 5529 | 1.5030          | 0.8294 |
  | 0.0062        | 20.0  | 5820 | 1.6264          | 0.8094 |
  | 0.0078        | 21.0  | 6111 | 1.6949          | 0.8122 |
  | 0.0078        | 22.0  | 6402 | 1.7106          | 0.8139 |
  | 0.0043        | 23.0  | 6693 | 1.7234          | 0.8218 |
  | 0.0043        | 24.0  | 6984 | 1.7344          | 0.8208 |
  | 0.0028        | 25.0  | 7275 | 1.7204          | 0.8203 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  