readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_9_ternary_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. -->
  
  # distilbert-base-uncased_fold_9_ternary_v1
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9406
  - F1: 0.7841
  
  ## 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   | 292  | 0.5684          | 0.7635 |
  | 0.5656        | 2.0   | 584  | 0.5753          | 0.7725 |
  | 0.5656        | 3.0   | 876  | 0.6159          | 0.7866 |
  | 0.2499        | 4.0   | 1168 | 0.7743          | 0.7828 |
  | 0.2499        | 5.0   | 1460 | 0.9820          | 0.7674 |
  | 0.1153        | 6.0   | 1752 | 1.2383          | 0.7738 |
  | 0.0547        | 7.0   | 2044 | 1.2468          | 0.7815 |
  | 0.0547        | 8.0   | 2336 | 1.3480          | 0.7622 |
  | 0.0233        | 9.0   | 2628 | 1.3791          | 0.7892 |
  | 0.0233        | 10.0  | 2920 | 1.4344          | 0.7841 |
  | 0.0142        | 11.0  | 3212 | 1.4958          | 0.7802 |
  | 0.0087        | 12.0  | 3504 | 1.5714          | 0.7674 |
  | 0.0087        | 13.0  | 3796 | 1.6129          | 0.7956 |
  | 0.0111        | 14.0  | 4088 | 1.7799          | 0.7751 |
  | 0.0111        | 15.0  | 4380 | 1.7272          | 0.7789 |
  | 0.0055        | 16.0  | 4672 | 1.7696          | 0.7866 |
  | 0.0055        | 17.0  | 4964 | 1.8622          | 0.7789 |
  | 0.003         | 18.0  | 5256 | 1.8563          | 0.7802 |
  | 0.0004        | 19.0  | 5548 | 1.8993          | 0.7815 |
  | 0.0004        | 20.0  | 5840 | 1.9199          | 0.7853 |
  | 0.0005        | 21.0  | 6132 | 1.9003          | 0.7879 |
  | 0.0005        | 22.0  | 6424 | 1.9161          | 0.7828 |
  | 0.0011        | 23.0  | 6716 | 1.9691          | 0.7815 |
  | 0.0017        | 24.0  | 7008 | 1.9492          | 0.7841 |
  | 0.0017        | 25.0  | 7300 | 1.9406          | 0.7841 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  