readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_6_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_6_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: 1.9031
  - F1: 0.7910
  
  ## 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  | 0.5235          | 0.7769 |
  | 0.566         | 2.0   | 584  | 0.5268          | 0.7923 |
  | 0.566         | 3.0   | 876  | 0.6189          | 0.7756 |
  | 0.2514        | 4.0   | 1168 | 0.7777          | 0.8026 |
  | 0.2514        | 5.0   | 1460 | 0.9380          | 0.7936 |
  | 0.1175        | 6.0   | 1752 | 1.0957          | 0.7872 |
  | 0.0579        | 7.0   | 2044 | 1.2370          | 0.7923 |
  | 0.0579        | 8.0   | 2336 | 1.3739          | 0.7936 |
  | 0.0259        | 9.0   | 2628 | 1.3457          | 0.7846 |
  | 0.0259        | 10.0  | 2920 | 1.4938          | 0.7872 |
  | 0.0125        | 11.0  | 3212 | 1.5921          | 0.7885 |
  | 0.0108        | 12.0  | 3504 | 1.6504          | 0.7897 |
  | 0.0108        | 13.0  | 3796 | 1.7532          | 0.7756 |
  | 0.007         | 14.0  | 4088 | 1.7029          | 0.7821 |
  | 0.007         | 15.0  | 4380 | 1.7632          | 0.7987 |
  | 0.0067        | 16.0  | 4672 | 1.7084          | 0.7962 |
  | 0.0067        | 17.0  | 4964 | 1.7559          | 0.7962 |
  | 0.0072        | 18.0  | 5256 | 1.8431          | 0.7987 |
  | 0.0028        | 19.0  | 5548 | 1.8689          | 0.7846 |
  | 0.0028        | 20.0  | 5840 | 1.8641          | 0.7885 |
  | 0.0033        | 21.0  | 6132 | 1.8578          | 0.7923 |
  | 0.0033        | 22.0  | 6424 | 1.9071          | 0.7833 |
  | 0.003         | 23.0  | 6716 | 1.8959          | 0.7872 |
  | 0.0011        | 24.0  | 7008 | 1.9073          | 0.7987 |
  | 0.0011        | 25.0  | 7300 | 1.9031          | 0.7910 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  