readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlnet-base-cased_fold_7_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_7_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: 1.7774
  - F1: 0.8111
  
  ## 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  | 0.4189          | 0.7903 |
  | 0.432         | 2.0   | 576  | 0.3927          | 0.8045 |
  | 0.432         | 3.0   | 864  | 0.4868          | 0.8108 |
  | 0.2573        | 4.0   | 1152 | 0.6763          | 0.8019 |
  | 0.2573        | 5.0   | 1440 | 0.8132          | 0.8105 |
  | 0.1612        | 6.0   | 1728 | 0.8544          | 0.8086 |
  | 0.0972        | 7.0   | 2016 | 1.1274          | 0.8109 |
  | 0.0972        | 8.0   | 2304 | 1.2622          | 0.8056 |
  | 0.0515        | 9.0   | 2592 | 1.3398          | 0.8013 |
  | 0.0515        | 10.0  | 2880 | 1.5421          | 0.8082 |
  | 0.0244        | 11.0  | 3168 | 1.4931          | 0.8042 |
  | 0.0244        | 12.0  | 3456 | 1.5744          | 0.8045 |
  | 0.0287        | 13.0  | 3744 | 1.4169          | 0.8091 |
  | 0.0255        | 14.0  | 4032 | 1.5790          | 0.7999 |
  | 0.0255        | 15.0  | 4320 | 1.6094          | 0.7994 |
  | 0.0098        | 16.0  | 4608 | 1.5758          | 0.8006 |
  | 0.0098        | 17.0  | 4896 | 1.5326          | 0.8140 |
  | 0.0203        | 18.0  | 5184 | 1.6431          | 0.8114 |
  | 0.0203        | 19.0  | 5472 | 1.7105          | 0.8072 |
  | 0.0104        | 20.0  | 5760 | 1.6353          | 0.8139 |
  | 0.0062        | 21.0  | 6048 | 1.6762          | 0.8108 |
  | 0.0062        | 22.0  | 6336 | 1.7076          | 0.8106 |
  | 0.0088        | 23.0  | 6624 | 1.7887          | 0.8035 |
  | 0.0088        | 24.0  | 6912 | 1.7731          | 0.8099 |
  | 0.0026        | 25.0  | 7200 | 1.7774          | 0.8111 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  