readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_11_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_11_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: 1.8389
  - F1: 0.8057
  
  ## 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  | 0.4534          | 0.8011 |
  | 0.4027        | 2.0   | 576  | 0.4299          | 0.8121 |
  | 0.4027        | 3.0   | 864  | 0.4840          | 0.8142 |
  | 0.1947        | 4.0   | 1152 | 0.7501          | 0.7992 |
  | 0.1947        | 5.0   | 1440 | 1.0307          | 0.7866 |
  | 0.0771        | 6.0   | 1728 | 1.1292          | 0.8034 |
  | 0.0253        | 7.0   | 2016 | 1.2620          | 0.8033 |
  | 0.0253        | 8.0   | 2304 | 1.4065          | 0.7954 |
  | 0.0137        | 9.0   | 2592 | 1.4922          | 0.7887 |
  | 0.0137        | 10.0  | 2880 | 1.4922          | 0.8050 |
  | 0.0046        | 11.0  | 3168 | 1.4883          | 0.8097 |
  | 0.0046        | 12.0  | 3456 | 1.5542          | 0.8133 |
  | 0.0066        | 13.0  | 3744 | 1.5180          | 0.8000 |
  | 0.0094        | 14.0  | 4032 | 1.6762          | 0.7919 |
  | 0.0094        | 15.0  | 4320 | 1.5808          | 0.8005 |
  | 0.0047        | 16.0  | 4608 | 1.7025          | 0.8012 |
  | 0.0047        | 17.0  | 4896 | 1.6494          | 0.7986 |
  | 0.0039        | 18.0  | 5184 | 1.7218          | 0.8010 |
  | 0.0039        | 19.0  | 5472 | 1.8293          | 0.7994 |
  | 0.0005        | 20.0  | 5760 | 1.8142          | 0.7980 |
  | 0.0033        | 21.0  | 6048 | 1.8350          | 0.8037 |
  | 0.0033        | 22.0  | 6336 | 1.8361          | 0.8042 |
  | 0.0023        | 23.0  | 6624 | 1.8715          | 0.7996 |
  | 0.0023        | 24.0  | 6912 | 1.8411          | 0.8057 |
  | 0.0019        | 25.0  | 7200 | 1.8389          | 0.8057 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  