readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_1_ternary
    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_1_ternary
  
  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: 2.0582
  - F1: 0.7326
  
  ## 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  | 0.5524          | 0.6755 |
  | 0.5648        | 2.0   | 580  | 0.5654          | 0.7124 |
  | 0.5648        | 3.0   | 870  | 0.6547          | 0.6896 |
  | 0.2712        | 4.0   | 1160 | 0.8916          | 0.7263 |
  | 0.2712        | 5.0   | 1450 | 1.1187          | 0.7120 |
  | 0.1147        | 6.0   | 1740 | 1.2778          | 0.7114 |
  | 0.0476        | 7.0   | 2030 | 1.4441          | 0.7151 |
  | 0.0476        | 8.0   | 2320 | 1.5535          | 0.7133 |
  | 0.0187        | 9.0   | 2610 | 1.6439          | 0.7212 |
  | 0.0187        | 10.0  | 2900 | 1.7261          | 0.7313 |
  | 0.0138        | 11.0  | 3190 | 1.6806          | 0.7292 |
  | 0.0138        | 12.0  | 3480 | 1.8425          | 0.7111 |
  | 0.009         | 13.0  | 3770 | 1.9207          | 0.7213 |
  | 0.0045        | 14.0  | 4060 | 1.8900          | 0.7202 |
  | 0.0045        | 15.0  | 4350 | 1.9730          | 0.7216 |
  | 0.0042        | 16.0  | 4640 | 2.0775          | 0.7041 |
  | 0.0042        | 17.0  | 4930 | 2.0514          | 0.7106 |
  | 0.0019        | 18.0  | 5220 | 2.0582          | 0.7326 |
  | 0.0039        | 19.0  | 5510 | 2.1010          | 0.7081 |
  | 0.0039        | 20.0  | 5800 | 2.0487          | 0.7273 |
  | 0.0025        | 21.0  | 6090 | 2.0415          | 0.7254 |
  | 0.0025        | 22.0  | 6380 | 2.0753          | 0.7157 |
  | 0.0017        | 23.0  | 6670 | 2.0554          | 0.7246 |
  | 0.0017        | 24.0  | 6960 | 2.0644          | 0.7290 |
  | 0.0001        | 25.0  | 7250 | 2.0711          | 0.7310 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  