readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: distilbert-base-uncased_fold_8_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_8_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: 1.6283
  - F1: 0.8178
  
  ## 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  | 0.4038          | 0.7981 |
  | 0.409         | 2.0   | 580  | 0.4023          | 0.8176 |
  | 0.409         | 3.0   | 870  | 0.5245          | 0.8169 |
  | 0.1938        | 4.0   | 1160 | 0.6242          | 0.8298 |
  | 0.1938        | 5.0   | 1450 | 0.8432          | 0.8159 |
  | 0.0848        | 6.0   | 1740 | 1.0887          | 0.8015 |
  | 0.038         | 7.0   | 2030 | 1.0700          | 0.8167 |
  | 0.038         | 8.0   | 2320 | 1.0970          | 0.8241 |
  | 0.0159        | 9.0   | 2610 | 1.2474          | 0.8142 |
  | 0.0159        | 10.0  | 2900 | 1.3453          | 0.8184 |
  | 0.01          | 11.0  | 3190 | 1.4412          | 0.8147 |
  | 0.01          | 12.0  | 3480 | 1.4263          | 0.8181 |
  | 0.007         | 13.0  | 3770 | 1.3859          | 0.8258 |
  | 0.0092        | 14.0  | 4060 | 1.4633          | 0.8128 |
  | 0.0092        | 15.0  | 4350 | 1.4304          | 0.8206 |
  | 0.0096        | 16.0  | 4640 | 1.5081          | 0.8149 |
  | 0.0096        | 17.0  | 4930 | 1.5239          | 0.8189 |
  | 0.0047        | 18.0  | 5220 | 1.5268          | 0.8151 |
  | 0.0053        | 19.0  | 5510 | 1.5445          | 0.8173 |
  | 0.0053        | 20.0  | 5800 | 1.6051          | 0.8180 |
  | 0.0014        | 21.0  | 6090 | 1.5981          | 0.8211 |
  | 0.0014        | 22.0  | 6380 | 1.5957          | 0.8225 |
  | 0.001         | 23.0  | 6670 | 1.5838          | 0.8189 |
  | 0.001         | 24.0  | 6960 | 1.6301          | 0.8178 |
  | 0.0018        | 25.0  | 7250 | 1.6283          | 0.8178 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  