readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_5_binary
    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
  
  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: 0.5093
  - F1: 0.7801
  
  ## 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  | 0.4760          | 0.7315 |
  | 0.3992        | 2.0   | 576  | 0.4428          | 0.7785 |
  | 0.3992        | 3.0   | 864  | 0.5093          | 0.7801 |
  | 0.2021        | 4.0   | 1152 | 0.6588          | 0.7634 |
  | 0.2021        | 5.0   | 1440 | 0.9174          | 0.7713 |
  | 0.0945        | 6.0   | 1728 | 0.9832          | 0.7726 |
  | 0.0321        | 7.0   | 2016 | 1.2103          | 0.7672 |
  | 0.0321        | 8.0   | 2304 | 1.3759          | 0.7616 |
  | 0.0134        | 9.0   | 2592 | 1.4405          | 0.7570 |
  | 0.0134        | 10.0  | 2880 | 1.4591          | 0.7710 |
  | 0.0117        | 11.0  | 3168 | 1.4947          | 0.7713 |
  | 0.0117        | 12.0  | 3456 | 1.6224          | 0.7419 |
  | 0.0081        | 13.0  | 3744 | 1.6462          | 0.7520 |
  | 0.0083        | 14.0  | 4032 | 1.6880          | 0.7637 |
  | 0.0083        | 15.0  | 4320 | 1.7080          | 0.7380 |
  | 0.0048        | 16.0  | 4608 | 1.7352          | 0.7551 |
  | 0.0048        | 17.0  | 4896 | 1.6761          | 0.7713 |
  | 0.0024        | 18.0  | 5184 | 1.7553          | 0.76   |
  | 0.0024        | 19.0  | 5472 | 1.7312          | 0.7673 |
  | 0.005         | 20.0  | 5760 | 1.7334          | 0.7713 |
  | 0.0032        | 21.0  | 6048 | 1.7963          | 0.7578 |
  | 0.0032        | 22.0  | 6336 | 1.7529          | 0.7679 |
  | 0.0025        | 23.0  | 6624 | 1.7741          | 0.7662 |
  | 0.0025        | 24.0  | 6912 | 1.7515          | 0.7679 |
  | 0.0004        | 25.0  | 7200 | 1.7370          | 0.7765 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  