readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_7_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_7_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: 2.0462
  - F1: 0.7836
  
  ## 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   | 291  | 0.5719          | 0.7490 |
  | 0.5541        | 2.0   | 582  | 0.5563          | 0.7836 |
  | 0.5541        | 3.0   | 873  | 0.7301          | 0.7849 |
  | 0.2509        | 4.0   | 1164 | 0.8073          | 0.7926 |
  | 0.2509        | 5.0   | 1455 | 1.0842          | 0.7823 |
  | 0.1182        | 6.0   | 1746 | 1.1721          | 0.7900 |
  | 0.0537        | 7.0   | 2037 | 1.4060          | 0.7785 |
  | 0.0537        | 8.0   | 2328 | 1.4497          | 0.7836 |
  | 0.0262        | 9.0   | 2619 | 1.4722          | 0.7708 |
  | 0.0262        | 10.0  | 2910 | 1.6529          | 0.7772 |
  | 0.0131        | 11.0  | 3201 | 1.6573          | 0.7862 |
  | 0.0131        | 12.0  | 3492 | 1.6986          | 0.7823 |
  | 0.0115        | 13.0  | 3783 | 1.7765          | 0.7810 |
  | 0.0098        | 14.0  | 4074 | 1.8036          | 0.7862 |
  | 0.0098        | 15.0  | 4365 | 1.7684          | 0.7926 |
  | 0.0028        | 16.0  | 4656 | 1.8385          | 0.7836 |
  | 0.0028        | 17.0  | 4947 | 1.7903          | 0.7887 |
  | 0.0054        | 18.0  | 5238 | 1.9065          | 0.7810 |
  | 0.0007        | 19.0  | 5529 | 1.9331          | 0.7875 |
  | 0.0007        | 20.0  | 5820 | 1.9384          | 0.7849 |
  | 0.0006        | 21.0  | 6111 | 1.8687          | 0.7887 |
  | 0.0006        | 22.0  | 6402 | 2.0603          | 0.7785 |
  | 0.0009        | 23.0  | 6693 | 2.0403          | 0.7836 |
  | 0.0009        | 24.0  | 6984 | 2.0348          | 0.7810 |
  | 0.0005        | 25.0  | 7275 | 2.0462          | 0.7836 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  