readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_2_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_2_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: 1.8941
  - F1: 0.7889
  
  ## 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   | 294  | 0.6025          | 0.7402 |
  | 0.5688        | 2.0   | 588  | 0.5025          | 0.7943 |
  | 0.5688        | 3.0   | 882  | 0.6102          | 0.7794 |
  | 0.2582        | 4.0   | 1176 | 0.8896          | 0.7835 |
  | 0.2582        | 5.0   | 1470 | 1.0392          | 0.7821 |
  | 0.1185        | 6.0   | 1764 | 1.0865          | 0.7848 |
  | 0.0461        | 7.0   | 2058 | 1.2951          | 0.7686 |
  | 0.0461        | 8.0   | 2352 | 1.3348          | 0.7821 |
  | 0.0313        | 9.0   | 2646 | 1.4267          | 0.7876 |
  | 0.0313        | 10.0  | 2940 | 1.4004          | 0.7957 |
  | 0.0142        | 11.0  | 3234 | 1.5501          | 0.7794 |
  | 0.0083        | 12.0  | 3528 | 1.5564          | 0.7903 |
  | 0.0083        | 13.0  | 3822 | 1.5699          | 0.7876 |
  | 0.0067        | 14.0  | 4116 | 1.7725          | 0.7794 |
  | 0.0067        | 15.0  | 4410 | 1.7642          | 0.7767 |
  | 0.0031        | 16.0  | 4704 | 1.7891          | 0.7848 |
  | 0.0031        | 17.0  | 4998 | 1.8528          | 0.7740 |
  | 0.0054        | 18.0  | 5292 | 1.8378          | 0.7781 |
  | 0.003         | 19.0  | 5586 | 1.8223          | 0.7862 |
  | 0.003         | 20.0  | 5880 | 1.7935          | 0.7930 |
  | 0.0021        | 21.0  | 6174 | 1.9117          | 0.7808 |
  | 0.0021        | 22.0  | 6468 | 1.8891          | 0.7930 |
  | 0.0015        | 23.0  | 6762 | 1.9167          | 0.7916 |
  | 0.0006        | 24.0  | 7056 | 1.9193          | 0.7862 |
  | 0.0006        | 25.0  | 7350 | 1.8941          | 0.7889 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  