readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_6_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_6_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: 1.6625
  - F1: 0.7588
  
  ## 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  | 0.5117          | 0.7306 |
  | 0.5701        | 2.0   | 584  | 0.5273          | 0.7296 |
  | 0.5701        | 3.0   | 876  | 0.6037          | 0.7415 |
  | 0.2468        | 4.0   | 1168 | 0.7132          | 0.7318 |
  | 0.2468        | 5.0   | 1460 | 0.8980          | 0.7504 |
  | 0.12          | 6.0   | 1752 | 1.0343          | 0.7369 |
  | 0.0486        | 7.0   | 2044 | 1.1860          | 0.7333 |
  | 0.0486        | 8.0   | 2336 | 1.3348          | 0.7437 |
  | 0.019         | 9.0   | 2628 | 1.3040          | 0.7561 |
  | 0.019         | 10.0  | 2920 | 1.4649          | 0.7293 |
  | 0.0152        | 11.0  | 3212 | 1.4870          | 0.7431 |
  | 0.0078        | 12.0  | 3504 | 1.5668          | 0.7455 |
  | 0.0078        | 13.0  | 3796 | 1.5280          | 0.7378 |
  | 0.0091        | 14.0  | 4088 | 1.5672          | 0.7410 |
  | 0.0091        | 15.0  | 4380 | 1.5948          | 0.7491 |
  | 0.0052        | 16.0  | 4672 | 1.6625          | 0.7588 |
  | 0.0052        | 17.0  | 4964 | 1.6544          | 0.7411 |
  | 0.0048        | 18.0  | 5256 | 1.7124          | 0.7425 |
  | 0.0024        | 19.0  | 5548 | 1.7211          | 0.7477 |
  | 0.0024        | 20.0  | 5840 | 1.8216          | 0.7373 |
  | 0.001         | 21.0  | 6132 | 1.8325          | 0.7361 |
  | 0.001         | 22.0  | 6424 | 1.8089          | 0.7498 |
  | 0.0015        | 23.0  | 6716 | 1.8026          | 0.7506 |
  | 0.0005        | 24.0  | 7008 | 1.8026          | 0.7464 |
  | 0.0005        | 25.0  | 7300 | 1.8043          | 0.7464 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  