readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlnet-base-cased_fold_6_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_6_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: 1.6214
  - F1: 0.8352
  
  ## 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  | 0.4174          | 0.7980 |
  | 0.4661        | 2.0   | 580  | 0.4118          | 0.8142 |
  | 0.4661        | 3.0   | 870  | 0.5152          | 0.8331 |
  | 0.2714        | 4.0   | 1160 | 0.6901          | 0.8242 |
  | 0.2714        | 5.0   | 1450 | 0.6853          | 0.8451 |
  | 0.1542        | 6.0   | 1740 | 0.8570          | 0.8399 |
  | 0.0935        | 7.0   | 2030 | 1.1342          | 0.8401 |
  | 0.0935        | 8.0   | 2320 | 1.1763          | 0.8397 |
  | 0.037         | 9.0   | 2610 | 1.3530          | 0.8215 |
  | 0.037         | 10.0  | 2900 | 1.3826          | 0.8402 |
  | 0.0351        | 11.0  | 3190 | 1.4057          | 0.8374 |
  | 0.0351        | 12.0  | 3480 | 1.4259          | 0.8455 |
  | 0.0159        | 13.0  | 3770 | 1.4270          | 0.8431 |
  | 0.0249        | 14.0  | 4060 | 1.4215          | 0.8442 |
  | 0.0249        | 15.0  | 4350 | 1.4245          | 0.8408 |
  | 0.0197        | 16.0  | 4640 | 1.4171          | 0.8353 |
  | 0.0197        | 17.0  | 4930 | 1.4537          | 0.8383 |
  | 0.0137        | 18.0  | 5220 | 1.4786          | 0.8430 |
  | 0.0068        | 19.0  | 5510 | 1.5635          | 0.8443 |
  | 0.0068        | 20.0  | 5800 | 1.5527          | 0.8378 |
  | 0.0062        | 21.0  | 6090 | 1.5917          | 0.8460 |
  | 0.0062        | 22.0  | 6380 | 1.6317          | 0.8318 |
  | 0.005         | 23.0  | 6670 | 1.6226          | 0.8340 |
  | 0.005         | 24.0  | 6960 | 1.6378          | 0.8310 |
  | 0.007         | 25.0  | 7250 | 1.6214          | 0.8352 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  