readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_3_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_3_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: 1.7987
  - F1: 0.7460
  
  ## 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   | 289  | 0.5903          | 0.6893 |
  | 0.5417        | 2.0   | 578  | 0.5822          | 0.7130 |
  | 0.5417        | 3.0   | 867  | 0.6471          | 0.7385 |
  | 0.2298        | 4.0   | 1156 | 0.8933          | 0.7322 |
  | 0.2298        | 5.0   | 1445 | 1.1002          | 0.7147 |
  | 0.1012        | 6.0   | 1734 | 1.2041          | 0.7249 |
  | 0.0508        | 7.0   | 2023 | 1.3575          | 0.7195 |
  | 0.0508        | 8.0   | 2312 | 1.3896          | 0.7385 |
  | 0.018         | 9.0   | 2601 | 1.5363          | 0.7238 |
  | 0.018         | 10.0  | 2890 | 1.5336          | 0.7364 |
  | 0.0142        | 11.0  | 3179 | 1.6335          | 0.7308 |
  | 0.0142        | 12.0  | 3468 | 1.6915          | 0.7295 |
  | 0.0047        | 13.0  | 3757 | 1.7087          | 0.7427 |
  | 0.0058        | 14.0  | 4046 | 1.7875          | 0.7378 |
  | 0.0058        | 15.0  | 4335 | 1.7649          | 0.7438 |
  | 0.0051        | 16.0  | 4624 | 1.7987          | 0.7460 |
  | 0.0051        | 17.0  | 4913 | 1.8435          | 0.7404 |
  | 0.0025        | 18.0  | 5202 | 1.9623          | 0.7257 |
  | 0.0025        | 19.0  | 5491 | 1.9005          | 0.7304 |
  | 0.0029        | 20.0  | 5780 | 1.9437          | 0.7374 |
  | 0.0011        | 21.0  | 6069 | 1.9840          | 0.7268 |
  | 0.0011        | 22.0  | 6358 | 1.9411          | 0.7346 |
  | 0.0025        | 23.0  | 6647 | 1.9233          | 0.7438 |
  | 0.0025        | 24.0  | 6936 | 1.9415          | 0.7395 |
  | 0.0015        | 25.0  | 7225 | 1.9481          | 0.7411 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  