readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_5_binary_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_5_binary_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: 1.6980
  - F1: 0.8110
  
  ## 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   | 288  | 0.4412          | 0.7981 |
  | 0.396         | 2.0   | 576  | 0.4419          | 0.8078 |
  | 0.396         | 3.0   | 864  | 0.4955          | 0.8166 |
  | 0.2019        | 4.0   | 1152 | 0.6341          | 0.8075 |
  | 0.2019        | 5.0   | 1440 | 1.0351          | 0.7979 |
  | 0.0808        | 6.0   | 1728 | 1.1818          | 0.7844 |
  | 0.0315        | 7.0   | 2016 | 1.2530          | 0.8051 |
  | 0.0315        | 8.0   | 2304 | 1.3568          | 0.7937 |
  | 0.0143        | 9.0   | 2592 | 1.4009          | 0.8045 |
  | 0.0143        | 10.0  | 2880 | 1.5333          | 0.7941 |
  | 0.0066        | 11.0  | 3168 | 1.5242          | 0.7982 |
  | 0.0066        | 12.0  | 3456 | 1.5752          | 0.8050 |
  | 0.0091        | 13.0  | 3744 | 1.5199          | 0.8046 |
  | 0.0111        | 14.0  | 4032 | 1.5319          | 0.8117 |
  | 0.0111        | 15.0  | 4320 | 1.5333          | 0.8156 |
  | 0.0072        | 16.0  | 4608 | 1.5461          | 0.8192 |
  | 0.0072        | 17.0  | 4896 | 1.5288          | 0.8252 |
  | 0.0048        | 18.0  | 5184 | 1.5725          | 0.8078 |
  | 0.0048        | 19.0  | 5472 | 1.5896          | 0.8138 |
  | 0.0032        | 20.0  | 5760 | 1.6917          | 0.8071 |
  | 0.0028        | 21.0  | 6048 | 1.6608          | 0.8109 |
  | 0.0028        | 22.0  | 6336 | 1.7013          | 0.8122 |
  | 0.0029        | 23.0  | 6624 | 1.6769          | 0.8148 |
  | 0.0029        | 24.0  | 6912 | 1.6906          | 0.8100 |
  | 0.0006        | 25.0  | 7200 | 1.6980          | 0.8110 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  