readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_2_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_2_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: 0.4724
  - F1: 0.7604
  
  ## 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   | 290  | 0.4280          | 0.7515 |
  | 0.4018        | 2.0   | 580  | 0.4724          | 0.7604 |
  | 0.4018        | 3.0   | 870  | 0.5336          | 0.7428 |
  | 0.1995        | 4.0   | 1160 | 0.8367          | 0.7476 |
  | 0.1995        | 5.0   | 1450 | 0.9242          | 0.7412 |
  | 0.089         | 6.0   | 1740 | 1.0987          | 0.7410 |
  | 0.0318        | 7.0   | 2030 | 1.1853          | 0.7584 |
  | 0.0318        | 8.0   | 2320 | 1.2509          | 0.7500 |
  | 0.0189        | 9.0   | 2610 | 1.5060          | 0.7258 |
  | 0.0189        | 10.0  | 2900 | 1.5607          | 0.7534 |
  | 0.0084        | 11.0  | 3190 | 1.5871          | 0.7476 |
  | 0.0084        | 12.0  | 3480 | 1.7206          | 0.7338 |
  | 0.0047        | 13.0  | 3770 | 1.6776          | 0.7340 |
  | 0.0068        | 14.0  | 4060 | 1.7339          | 0.7546 |
  | 0.0068        | 15.0  | 4350 | 1.8279          | 0.7504 |
  | 0.0025        | 16.0  | 4640 | 1.7791          | 0.7411 |
  | 0.0025        | 17.0  | 4930 | 1.7917          | 0.7444 |
  | 0.003         | 18.0  | 5220 | 1.7781          | 0.7559 |
  | 0.0029        | 19.0  | 5510 | 1.8153          | 0.7559 |
  | 0.0029        | 20.0  | 5800 | 1.7757          | 0.7414 |
  | 0.0055        | 21.0  | 6090 | 1.8635          | 0.7454 |
  | 0.0055        | 22.0  | 6380 | 1.8483          | 0.7460 |
  | 0.001         | 23.0  | 6670 | 1.8620          | 0.7492 |
  | 0.001         | 24.0  | 6960 | 1.9058          | 0.7508 |
  | 0.0006        | 25.0  | 7250 | 1.8640          | 0.7504 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  