readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_5_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_5_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: 1.8096
  - F1: 0.7352
  
  ## 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  | 0.6322          | 0.6742 |
  | 0.5533        | 2.0   | 582  | 0.5861          | 0.7285 |
  | 0.5533        | 3.0   | 873  | 0.6893          | 0.7117 |
  | 0.2576        | 4.0   | 1164 | 1.0393          | 0.7124 |
  | 0.2576        | 5.0   | 1455 | 1.1506          | 0.6988 |
  | 0.1097        | 6.0   | 1746 | 1.3005          | 0.7166 |
  | 0.0487        | 7.0   | 2037 | 1.5242          | 0.7124 |
  | 0.0487        | 8.0   | 2328 | 1.5705          | 0.7010 |
  | 0.0253        | 9.0   | 2619 | 1.5180          | 0.7194 |
  | 0.0253        | 10.0  | 2910 | 1.6251          | 0.7062 |
  | 0.022         | 11.0  | 3201 | 1.6299          | 0.7169 |
  | 0.022         | 12.0  | 3492 | 1.7322          | 0.7091 |
  | 0.0065        | 13.0  | 3783 | 1.8441          | 0.7044 |
  | 0.0093        | 14.0  | 4074 | 1.9063          | 0.7097 |
  | 0.0093        | 15.0  | 4365 | 1.8096          | 0.7352 |
  | 0.0037        | 16.0  | 4656 | 1.8589          | 0.7321 |
  | 0.0037        | 17.0  | 4947 | 1.9687          | 0.7211 |
  | 0.0036        | 18.0  | 5238 | 1.9244          | 0.7285 |
  | 0.0045        | 19.0  | 5529 | 1.9835          | 0.7299 |
  | 0.0045        | 20.0  | 5820 | 2.0766          | 0.7139 |
  | 0.0024        | 21.0  | 6111 | 2.1118          | 0.7144 |
  | 0.0024        | 22.0  | 6402 | 2.0544          | 0.7197 |
  | 0.0006        | 23.0  | 6693 | 2.0914          | 0.7217 |
  | 0.0006        | 24.0  | 6984 | 2.1028          | 0.7195 |
  | 0.0006        | 25.0  | 7275 | 2.1174          | 0.7224 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  