readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_6_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_6_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: 1.7209
  - F1: 0.8156
  
  ## 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  | 0.4115          | 0.8048 |
  | 0.3976        | 2.0   | 580  | 0.3980          | 0.8156 |
  | 0.3976        | 3.0   | 870  | 0.5953          | 0.8142 |
  | 0.1965        | 4.0   | 1160 | 0.7940          | 0.8057 |
  | 0.1965        | 5.0   | 1450 | 0.8098          | 0.8069 |
  | 0.0847        | 6.0   | 1740 | 1.0293          | 0.7913 |
  | 0.03          | 7.0   | 2030 | 1.1649          | 0.8073 |
  | 0.03          | 8.0   | 2320 | 1.2876          | 0.7973 |
  | 0.0166        | 9.0   | 2610 | 1.3260          | 0.8038 |
  | 0.0166        | 10.0  | 2900 | 1.3523          | 0.8084 |
  | 0.0062        | 11.0  | 3190 | 1.3814          | 0.8097 |
  | 0.0062        | 12.0  | 3480 | 1.4134          | 0.8165 |
  | 0.0113        | 13.0  | 3770 | 1.5374          | 0.8068 |
  | 0.006         | 14.0  | 4060 | 1.5808          | 0.8100 |
  | 0.006         | 15.0  | 4350 | 1.6551          | 0.7972 |
  | 0.0088        | 16.0  | 4640 | 1.5793          | 0.8116 |
  | 0.0088        | 17.0  | 4930 | 1.6134          | 0.8143 |
  | 0.0021        | 18.0  | 5220 | 1.6204          | 0.8119 |
  | 0.0031        | 19.0  | 5510 | 1.7006          | 0.8029 |
  | 0.0031        | 20.0  | 5800 | 1.6777          | 0.8145 |
  | 0.0019        | 21.0  | 6090 | 1.7202          | 0.8079 |
  | 0.0019        | 22.0  | 6380 | 1.7539          | 0.8053 |
  | 0.0008        | 23.0  | 6670 | 1.7408          | 0.8119 |
  | 0.0008        | 24.0  | 6960 | 1.7388          | 0.8176 |
  | 0.0014        | 25.0  | 7250 | 1.7209          | 0.8156 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  