readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlnet-base-cased_fold_3_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_3_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: 1.3616
  - F1: 0.7758
  
  ## 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   | 289  | 0.4668          | 0.7666 |
  | 0.4142        | 2.0   | 578  | 0.4259          | 0.7631 |
  | 0.4142        | 3.0   | 867  | 0.6744          | 0.7492 |
  | 0.235         | 4.0   | 1156 | 0.8879          | 0.7678 |
  | 0.235         | 5.0   | 1445 | 1.0036          | 0.7639 |
  | 0.1297        | 6.0   | 1734 | 1.1427          | 0.7616 |
  | 0.0894        | 7.0   | 2023 | 1.2126          | 0.7626 |
  | 0.0894        | 8.0   | 2312 | 1.5098          | 0.7433 |
  | 0.0473        | 9.0   | 2601 | 1.3616          | 0.7758 |
  | 0.0473        | 10.0  | 2890 | 1.5966          | 0.7579 |
  | 0.0325        | 11.0  | 3179 | 1.6669          | 0.7508 |
  | 0.0325        | 12.0  | 3468 | 1.7401          | 0.7437 |
  | 0.0227        | 13.0  | 3757 | 1.7797          | 0.7515 |
  | 0.0224        | 14.0  | 4046 | 1.7349          | 0.7418 |
  | 0.0224        | 15.0  | 4335 | 1.7527          | 0.7595 |
  | 0.0152        | 16.0  | 4624 | 1.7492          | 0.7634 |
  | 0.0152        | 17.0  | 4913 | 1.8178          | 0.7628 |
  | 0.0117        | 18.0  | 5202 | 1.7736          | 0.7688 |
  | 0.0117        | 19.0  | 5491 | 1.8449          | 0.7704 |
  | 0.0055        | 20.0  | 5780 | 1.8687          | 0.7652 |
  | 0.0065        | 21.0  | 6069 | 1.8083          | 0.7669 |
  | 0.0065        | 22.0  | 6358 | 1.8568          | 0.7559 |
  | 0.0054        | 23.0  | 6647 | 1.8760          | 0.7678 |
  | 0.0054        | 24.0  | 6936 | 1.8948          | 0.7697 |
  | 0.0048        | 25.0  | 7225 | 1.9109          | 0.7680 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  