readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlnet-base-cased_fold_2_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_2_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: 1.8748
  - F1: 0.8066
  
  ## 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  | 0.4803          | 0.7433 |
  | 0.434         | 2.0   | 580  | 0.4385          | 0.8099 |
  | 0.434         | 3.0   | 870  | 0.5382          | 0.8078 |
  | 0.254         | 4.0   | 1160 | 0.6944          | 0.7982 |
  | 0.254         | 5.0   | 1450 | 0.9908          | 0.8058 |
  | 0.1479        | 6.0   | 1740 | 1.1090          | 0.8062 |
  | 0.0874        | 7.0   | 2030 | 1.2405          | 0.8042 |
  | 0.0874        | 8.0   | 2320 | 1.3174          | 0.8012 |
  | 0.0505        | 9.0   | 2610 | 1.5211          | 0.7909 |
  | 0.0505        | 10.0  | 2900 | 1.4014          | 0.8126 |
  | 0.0301        | 11.0  | 3190 | 1.4798          | 0.8047 |
  | 0.0301        | 12.0  | 3480 | 1.4668          | 0.8091 |
  | 0.0279        | 13.0  | 3770 | 1.5286          | 0.8075 |
  | 0.0233        | 14.0  | 4060 | 1.6752          | 0.8006 |
  | 0.0233        | 15.0  | 4350 | 1.5265          | 0.8132 |
  | 0.019         | 16.0  | 4640 | 1.6440          | 0.7949 |
  | 0.019         | 17.0  | 4930 | 1.7471          | 0.8097 |
  | 0.0096        | 18.0  | 5220 | 1.7329          | 0.8121 |
  | 0.0075        | 19.0  | 5510 | 1.7472          | 0.8191 |
  | 0.0075        | 20.0  | 5800 | 1.8043          | 0.8161 |
  | 0.0052        | 21.0  | 6090 | 1.8102          | 0.8141 |
  | 0.0052        | 22.0  | 6380 | 1.7944          | 0.8116 |
  | 0.0044        | 23.0  | 6670 | 1.8211          | 0.8141 |
  | 0.0044        | 24.0  | 6960 | 1.8741          | 0.8066 |
  | 0.0046        | 25.0  | 7250 | 1.8748          | 0.8066 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  