readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_1_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_1_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: 1.5992
  - F1: 0.7687
  
  ## 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  | 0.3960          | 0.7467 |
  | 0.3988        | 2.0   | 576  | 0.3947          | 0.7487 |
  | 0.3988        | 3.0   | 864  | 0.4511          | 0.7662 |
  | 0.1853        | 4.0   | 1152 | 0.7226          | 0.7285 |
  | 0.1853        | 5.0   | 1440 | 0.9398          | 0.7334 |
  | 0.0827        | 6.0   | 1728 | 1.0547          | 0.7427 |
  | 0.0287        | 7.0   | 2016 | 1.1602          | 0.7563 |
  | 0.0287        | 8.0   | 2304 | 1.3332          | 0.7171 |
  | 0.0219        | 9.0   | 2592 | 1.3429          | 0.7420 |
  | 0.0219        | 10.0  | 2880 | 1.2603          | 0.7648 |
  | 0.0139        | 11.0  | 3168 | 1.4126          | 0.7569 |
  | 0.0139        | 12.0  | 3456 | 1.3195          | 0.7483 |
  | 0.0115        | 13.0  | 3744 | 1.4356          | 0.7491 |
  | 0.0035        | 14.0  | 4032 | 1.5693          | 0.7636 |
  | 0.0035        | 15.0  | 4320 | 1.4071          | 0.7662 |
  | 0.0071        | 16.0  | 4608 | 1.4561          | 0.7579 |
  | 0.0071        | 17.0  | 4896 | 1.5405          | 0.7634 |
  | 0.0041        | 18.0  | 5184 | 1.5862          | 0.7589 |
  | 0.0041        | 19.0  | 5472 | 1.6782          | 0.76   |
  | 0.0024        | 20.0  | 5760 | 1.5699          | 0.7677 |
  | 0.0006        | 21.0  | 6048 | 1.5991          | 0.7467 |
  | 0.0006        | 22.0  | 6336 | 1.6205          | 0.7682 |
  | 0.0003        | 23.0  | 6624 | 1.6334          | 0.7643 |
  | 0.0003        | 24.0  | 6912 | 1.5992          | 0.7687 |
  | 0.0011        | 25.0  | 7200 | 1.6053          | 0.7624 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  