readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_4_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_4_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: 1.2977
  - F1: 0.8083
  
  ## 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  | 0.3701          | 0.7903 |
  | 0.4005        | 2.0   | 578  | 0.3669          | 0.7994 |
  | 0.4005        | 3.0   | 867  | 0.5038          | 0.7955 |
  | 0.1945        | 4.0   | 1156 | 0.6353          | 0.8006 |
  | 0.1945        | 5.0   | 1445 | 0.8974          | 0.7826 |
  | 0.0909        | 6.0   | 1734 | 0.8533          | 0.7764 |
  | 0.0389        | 7.0   | 2023 | 0.9969          | 0.7957 |
  | 0.0389        | 8.0   | 2312 | 1.0356          | 0.7952 |
  | 0.0231        | 9.0   | 2601 | 1.1538          | 0.7963 |
  | 0.0231        | 10.0  | 2890 | 1.2011          | 0.7968 |
  | 0.0051        | 11.0  | 3179 | 1.2329          | 0.7935 |
  | 0.0051        | 12.0  | 3468 | 1.2829          | 0.8056 |
  | 0.0066        | 13.0  | 3757 | 1.2946          | 0.7956 |
  | 0.004         | 14.0  | 4046 | 1.2977          | 0.8083 |
  | 0.004         | 15.0  | 4335 | 1.3970          | 0.7957 |
  | 0.0007        | 16.0  | 4624 | 1.3361          | 0.7917 |
  | 0.0007        | 17.0  | 4913 | 1.5782          | 0.7954 |
  | 0.0107        | 18.0  | 5202 | 1.4641          | 0.7900 |
  | 0.0107        | 19.0  | 5491 | 1.4490          | 0.7957 |
  | 0.0058        | 20.0  | 5780 | 1.4607          | 0.7932 |
  | 0.0016        | 21.0  | 6069 | 1.5048          | 0.7939 |
  | 0.0016        | 22.0  | 6358 | 1.5219          | 0.7945 |
  | 0.0027        | 23.0  | 6647 | 1.4783          | 0.7937 |
  | 0.0027        | 24.0  | 6936 | 1.4715          | 0.7981 |
  | 0.0004        | 25.0  | 7225 | 1.4989          | 0.7900 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  