readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_4_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_4_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: 1.5144
  - F1: 0.8245
  
  ## 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  | 0.3756          | 0.8175 |
  | 0.3977        | 2.0   | 578  | 0.3672          | 0.8336 |
  | 0.3977        | 3.0   | 867  | 0.4997          | 0.8276 |
  | 0.1972        | 4.0   | 1156 | 0.6597          | 0.8244 |
  | 0.1972        | 5.0   | 1445 | 0.8501          | 0.8195 |
  | 0.0824        | 6.0   | 1734 | 1.0074          | 0.8097 |
  | 0.037         | 7.0   | 2023 | 1.1122          | 0.8131 |
  | 0.037         | 8.0   | 2312 | 1.0963          | 0.8189 |
  | 0.0182        | 9.0   | 2601 | 1.2511          | 0.8125 |
  | 0.0182        | 10.0  | 2890 | 1.2255          | 0.8141 |
  | 0.0121        | 11.0  | 3179 | 1.3120          | 0.8187 |
  | 0.0121        | 12.0  | 3468 | 1.4182          | 0.8165 |
  | 0.0079        | 13.0  | 3757 | 1.4142          | 0.8218 |
  | 0.0081        | 14.0  | 4046 | 1.4765          | 0.8150 |
  | 0.0081        | 15.0  | 4335 | 1.3510          | 0.8187 |
  | 0.0109        | 16.0  | 4624 | 1.3455          | 0.8255 |
  | 0.0109        | 17.0  | 4913 | 1.4157          | 0.8234 |
  | 0.0022        | 18.0  | 5202 | 1.4651          | 0.8197 |
  | 0.0022        | 19.0  | 5491 | 1.4388          | 0.8267 |
  | 0.0017        | 20.0  | 5780 | 1.4552          | 0.8304 |
  | 0.0005        | 21.0  | 6069 | 1.5357          | 0.8248 |
  | 0.0005        | 22.0  | 6358 | 1.4924          | 0.8241 |
  | 0.0009        | 23.0  | 6647 | 1.4865          | 0.8248 |
  | 0.0009        | 24.0  | 6936 | 1.4697          | 0.8275 |
  | 0.0013        | 25.0  | 7225 | 1.5144          | 0.8245 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  