readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_3_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_3_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: 1.9405
  - F1: 0.7878
  
  ## 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  | 0.4630          | 0.7897 |
  | 0.3954        | 2.0   | 578  | 0.4549          | 0.7936 |
  | 0.3954        | 3.0   | 867  | 0.6527          | 0.7868 |
  | 0.1991        | 4.0   | 1156 | 0.7510          | 0.7951 |
  | 0.1991        | 5.0   | 1445 | 0.9327          | 0.8000 |
  | 0.095         | 6.0   | 1734 | 1.0974          | 0.7859 |
  | 0.0347        | 7.0   | 2023 | 1.2692          | 0.7919 |
  | 0.0347        | 8.0   | 2312 | 1.3718          | 0.7921 |
  | 0.0105        | 9.0   | 2601 | 1.4679          | 0.7999 |
  | 0.0105        | 10.0  | 2890 | 1.5033          | 0.8070 |
  | 0.0079        | 11.0  | 3179 | 1.6074          | 0.8008 |
  | 0.0079        | 12.0  | 3468 | 1.6921          | 0.7904 |
  | 0.0053        | 13.0  | 3757 | 1.7079          | 0.7945 |
  | 0.0054        | 14.0  | 4046 | 1.8361          | 0.7887 |
  | 0.0054        | 15.0  | 4335 | 1.7695          | 0.7873 |
  | 0.0046        | 16.0  | 4624 | 1.7934          | 0.7917 |
  | 0.0046        | 17.0  | 4913 | 1.8036          | 0.8008 |
  | 0.0064        | 18.0  | 5202 | 1.8780          | 0.7888 |
  | 0.0064        | 19.0  | 5491 | 1.8943          | 0.7923 |
  | 0.0032        | 20.0  | 5780 | 1.8694          | 0.7905 |
  | 0.002         | 21.0  | 6069 | 1.9348          | 0.7869 |
  | 0.002         | 22.0  | 6358 | 1.9578          | 0.7804 |
  | 0.0036        | 23.0  | 6647 | 1.9438          | 0.7827 |
  | 0.0036        | 24.0  | 6936 | 1.9386          | 0.7878 |
  | 0.0011        | 25.0  | 7225 | 1.9405          | 0.7878 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  