readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlnet-base-cased_fold_2_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_2_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: 0.4858
  - F1: 0.7648
  
  ## 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   | 290  | 0.4361          | 0.7404 |
  | 0.4403        | 2.0   | 580  | 0.5363          | 0.7515 |
  | 0.4403        | 3.0   | 870  | 0.4858          | 0.7648 |
  | 0.2505        | 4.0   | 1160 | 0.7127          | 0.7612 |
  | 0.2505        | 5.0   | 1450 | 0.8930          | 0.7554 |
  | 0.1425        | 6.0   | 1740 | 0.9897          | 0.7580 |
  | 0.0869        | 7.0   | 2030 | 1.2683          | 0.7615 |
  | 0.0869        | 8.0   | 2320 | 1.4988          | 0.7343 |
  | 0.0411        | 9.0   | 2610 | 1.5082          | 0.7492 |
  | 0.0411        | 10.0  | 2900 | 1.4974          | 0.7450 |
  | 0.0306        | 11.0  | 3190 | 1.5723          | 0.7435 |
  | 0.0306        | 12.0  | 3480 | 1.8446          | 0.7432 |
  | 0.0291        | 13.0  | 3770 | 1.7113          | 0.7639 |
  | 0.0207        | 14.0  | 4060 | 1.8073          | 0.7394 |
  | 0.0207        | 15.0  | 4350 | 1.7524          | 0.7585 |
  | 0.0171        | 16.0  | 4640 | 1.8751          | 0.7374 |
  | 0.0171        | 17.0  | 4930 | 1.7849          | 0.7561 |
  | 0.0084        | 18.0  | 5220 | 1.8618          | 0.7441 |
  | 0.0064        | 19.0  | 5510 | 1.9613          | 0.7437 |
  | 0.0064        | 20.0  | 5800 | 1.8898          | 0.7430 |
  | 0.006         | 21.0  | 6090 | 1.9889          | 0.7409 |
  | 0.006         | 22.0  | 6380 | 1.9949          | 0.7488 |
  | 0.0049        | 23.0  | 6670 | 1.9453          | 0.7488 |
  | 0.0049        | 24.0  | 6960 | 1.9754          | 0.7472 |
  | 0.002         | 25.0  | 7250 | 1.9946          | 0.7504 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  