readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlnet-base-cased_fold_3_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_3_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: 1.8649
  - F1: 0.8044
  
  ## 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  | 0.4483          | 0.8000 |
  | 0.4228        | 2.0   | 578  | 0.4264          | 0.8040 |
  | 0.4228        | 3.0   | 867  | 0.5341          | 0.8056 |
  | 0.2409        | 4.0   | 1156 | 0.9077          | 0.8103 |
  | 0.2409        | 5.0   | 1445 | 1.1069          | 0.7889 |
  | 0.1386        | 6.0   | 1734 | 1.0288          | 0.8093 |
  | 0.0817        | 7.0   | 2023 | 1.2477          | 0.8049 |
  | 0.0817        | 8.0   | 2312 | 1.5915          | 0.7872 |
  | 0.0465        | 9.0   | 2601 | 1.5323          | 0.8035 |
  | 0.0465        | 10.0  | 2890 | 1.4351          | 0.7989 |
  | 0.0376        | 11.0  | 3179 | 1.4639          | 0.7916 |
  | 0.0376        | 12.0  | 3468 | 1.6027          | 0.7956 |
  | 0.0234        | 13.0  | 3757 | 1.7860          | 0.7931 |
  | 0.0109        | 14.0  | 4046 | 1.8567          | 0.7934 |
  | 0.0109        | 15.0  | 4335 | 1.8294          | 0.8053 |
  | 0.0115        | 16.0  | 4624 | 1.7799          | 0.7971 |
  | 0.0115        | 17.0  | 4913 | 1.5935          | 0.8000 |
  | 0.0142        | 18.0  | 5202 | 1.8136          | 0.8066 |
  | 0.0142        | 19.0  | 5491 | 1.7718          | 0.8063 |
  | 0.0124        | 20.0  | 5780 | 1.8581          | 0.8053 |
  | 0.0083        | 21.0  | 6069 | 1.8523          | 0.8056 |
  | 0.0083        | 22.0  | 6358 | 1.8408          | 0.8035 |
  | 0.0045        | 23.0  | 6647 | 1.8347          | 0.8040 |
  | 0.0045        | 24.0  | 6936 | 1.8683          | 0.8067 |
  | 0.0005        | 25.0  | 7225 | 1.8649          | 0.8044 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  