readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_10_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_10_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: 1.9887
  - F1: 0.7797
  
  ## 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  | 0.5701          | 0.7463 |
  | 0.5651        | 2.0   | 580  | 0.5359          | 0.7748 |
  | 0.5651        | 3.0   | 870  | 0.6043          | 0.7847 |
  | 0.2605        | 4.0   | 1160 | 1.0124          | 0.7587 |
  | 0.2605        | 5.0   | 1450 | 1.1140          | 0.7599 |
  | 0.1223        | 6.0   | 1740 | 1.2713          | 0.7859 |
  | 0.0469        | 7.0   | 2030 | 1.3188          | 0.7822 |
  | 0.0469        | 8.0   | 2320 | 1.3819          | 0.7946 |
  | 0.0279        | 9.0   | 2610 | 1.5444          | 0.7847 |
  | 0.0279        | 10.0  | 2900 | 1.5851          | 0.7908 |
  | 0.0084        | 11.0  | 3190 | 1.7003          | 0.7822 |
  | 0.0084        | 12.0  | 3480 | 1.8148          | 0.7748 |
  | 0.007         | 13.0  | 3770 | 1.7651          | 0.7748 |
  | 0.008         | 14.0  | 4060 | 1.8423          | 0.7748 |
  | 0.008         | 15.0  | 4350 | 1.7871          | 0.7809 |
  | 0.0054        | 16.0  | 4640 | 1.9324          | 0.7748 |
  | 0.0054        | 17.0  | 4930 | 1.8685          | 0.7809 |
  | 0.0048        | 18.0  | 5220 | 1.9901          | 0.7797 |
  | 0.002         | 19.0  | 5510 | 1.9273          | 0.7785 |
  | 0.002         | 20.0  | 5800 | 1.9945          | 0.7809 |
  | 0.0018        | 21.0  | 6090 | 1.9250          | 0.7785 |
  | 0.0018        | 22.0  | 6380 | 1.9929          | 0.7822 |
  | 0.0032        | 23.0  | 6670 | 1.9306          | 0.7859 |
  | 0.0032        | 24.0  | 6960 | 1.9603          | 0.7847 |
  | 0.0029        | 25.0  | 7250 | 1.9887          | 0.7797 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  