readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_12_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_12_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: 1.7046
  - F1: 0.8165
  
  ## 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   | 290  | 0.4165          | 0.7983 |
  | 0.4052        | 2.0   | 580  | 0.4005          | 0.8213 |
  | 0.4052        | 3.0   | 870  | 0.6003          | 0.8078 |
  | 0.1906        | 4.0   | 1160 | 0.8181          | 0.7945 |
  | 0.1906        | 5.0   | 1450 | 0.7775          | 0.7955 |
  | 0.0853        | 6.0   | 1740 | 1.0667          | 0.7912 |
  | 0.0407        | 7.0   | 2030 | 1.2061          | 0.7907 |
  | 0.0407        | 8.0   | 2320 | 1.2522          | 0.8011 |
  | 0.0145        | 9.0   | 2610 | 1.3073          | 0.8110 |
  | 0.0145        | 10.0  | 2900 | 1.4895          | 0.7994 |
  | 0.015         | 11.0  | 3190 | 1.4568          | 0.8082 |
  | 0.015         | 12.0  | 3480 | 1.4883          | 0.8058 |
  | 0.005         | 13.0  | 3770 | 1.4334          | 0.8217 |
  | 0.0026        | 14.0  | 4060 | 1.5032          | 0.8255 |
  | 0.0026        | 15.0  | 4350 | 1.5694          | 0.8193 |
  | 0.0062        | 16.0  | 4640 | 1.6058          | 0.8105 |
  | 0.0062        | 17.0  | 4930 | 1.7390          | 0.8058 |
  | 0.0051        | 18.0  | 5220 | 1.6942          | 0.8100 |
  | 0.0012        | 19.0  | 5510 | 1.6891          | 0.8151 |
  | 0.0012        | 20.0  | 5800 | 1.6961          | 0.8132 |
  | 0.0007        | 21.0  | 6090 | 1.6793          | 0.8168 |
  | 0.0007        | 22.0  | 6380 | 1.7542          | 0.8077 |
  | 0.0027        | 23.0  | 6670 | 1.6869          | 0.8203 |
  | 0.0027        | 24.0  | 6960 | 1.7006          | 0.8194 |
  | 0.0028        | 25.0  | 7250 | 1.7046          | 0.8165 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  