readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_3_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_3_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: 1.8310
  - F1: 0.7584
  
  ## 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  | 0.4560          | 0.7522 |
  | 0.4008        | 2.0   | 578  | 0.4790          | 0.7567 |
  | 0.4008        | 3.0   | 867  | 0.6368          | 0.7557 |
  | 0.1967        | 4.0   | 1156 | 0.6854          | 0.7534 |
  | 0.1967        | 5.0   | 1445 | 0.9823          | 0.7309 |
  | 0.0768        | 6.0   | 1734 | 1.2531          | 0.7511 |
  | 0.0202        | 7.0   | 2023 | 1.2906          | 0.7391 |
  | 0.0202        | 8.0   | 2312 | 1.4025          | 0.7460 |
  | 0.0087        | 9.0   | 2601 | 1.5713          | 0.7507 |
  | 0.0087        | 10.0  | 2890 | 1.4212          | 0.7528 |
  | 0.0162        | 11.0  | 3179 | 1.5775          | 0.7511 |
  | 0.0162        | 12.0  | 3468 | 1.6361          | 0.7377 |
  | 0.0048        | 13.0  | 3757 | 1.6972          | 0.7542 |
  | 0.0098        | 14.0  | 4046 | 1.6569          | 0.7565 |
  | 0.0098        | 15.0  | 4335 | 1.7547          | 0.7325 |
  | 0.0042        | 16.0  | 4624 | 1.8108          | 0.7544 |
  | 0.0042        | 17.0  | 4913 | 1.7593          | 0.7554 |
  | 0.0041        | 18.0  | 5202 | 1.7582          | 0.7551 |
  | 0.0041        | 19.0  | 5491 | 1.8200          | 0.7512 |
  | 0.0029        | 20.0  | 5780 | 1.8310          | 0.7584 |
  | 0.0018        | 21.0  | 6069 | 1.8146          | 0.7568 |
  | 0.0018        | 22.0  | 6358 | 1.7870          | 0.7558 |
  | 0.0029        | 23.0  | 6647 | 1.8508          | 0.7530 |
  | 0.0029        | 24.0  | 6936 | 1.8327          | 0.7543 |
  | 0.0001        | 25.0  | 7225 | 1.8546          | 0.7561 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  