readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_9_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_9_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: 1.6965
  - F1: 0.8090
  
  ## 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   | 291  | 0.4193          | 0.7989 |
  | 0.3993        | 2.0   | 582  | 0.4039          | 0.8026 |
  | 0.3993        | 3.0   | 873  | 0.5227          | 0.7995 |
  | 0.2044        | 4.0   | 1164 | 0.7264          | 0.8011 |
  | 0.2044        | 5.0   | 1455 | 0.8497          | 0.8007 |
  | 0.0882        | 6.0   | 1746 | 0.9543          | 0.8055 |
  | 0.0374        | 7.0   | 2037 | 1.1349          | 0.7997 |
  | 0.0374        | 8.0   | 2328 | 1.3175          | 0.8009 |
  | 0.0151        | 9.0   | 2619 | 1.3585          | 0.8030 |
  | 0.0151        | 10.0  | 2910 | 1.4202          | 0.8067 |
  | 0.0068        | 11.0  | 3201 | 1.4364          | 0.8108 |
  | 0.0068        | 12.0  | 3492 | 1.4443          | 0.8088 |
  | 0.0096        | 13.0  | 3783 | 1.5308          | 0.8075 |
  | 0.0031        | 14.0  | 4074 | 1.5061          | 0.8020 |
  | 0.0031        | 15.0  | 4365 | 1.5769          | 0.7980 |
  | 0.0048        | 16.0  | 4656 | 1.5962          | 0.8038 |
  | 0.0048        | 17.0  | 4947 | 1.5383          | 0.8085 |
  | 0.0067        | 18.0  | 5238 | 1.5456          | 0.8158 |
  | 0.0062        | 19.0  | 5529 | 1.6325          | 0.8044 |
  | 0.0062        | 20.0  | 5820 | 1.5430          | 0.8141 |
  | 0.0029        | 21.0  | 6111 | 1.6590          | 0.8117 |
  | 0.0029        | 22.0  | 6402 | 1.6650          | 0.8112 |
  | 0.0017        | 23.0  | 6693 | 1.7016          | 0.8053 |
  | 0.0017        | 24.0  | 6984 | 1.6998          | 0.8090 |
  | 0.0011        | 25.0  | 7275 | 1.6965          | 0.8090 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  