readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: distilbert-base-uncased-finetuned
    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-finetuned
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 7.2813
  
  ## 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: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 8.6309        | 1.0   | 76   | 7.4774          |
  | 7.0806        | 2.0   | 152  | 6.9937          |
  | 6.6842        | 3.0   | 228  | 6.9314          |
  | 6.4592        | 4.0   | 304  | 6.9088          |
  | 6.2936        | 5.0   | 380  | 6.9135          |
  | 6.1301        | 6.0   | 456  | 6.9018          |
  | 5.9878        | 7.0   | 532  | 6.8865          |
  | 5.8071        | 8.0   | 608  | 6.8926          |
  | 5.6372        | 9.0   | 684  | 6.8750          |
  | 5.4791        | 10.0  | 760  | 6.9394          |
  | 5.3365        | 11.0  | 836  | 6.9594          |
  | 5.2117        | 12.0  | 912  | 6.9962          |
  | 5.0887        | 13.0  | 988  | 7.0570          |
  | 4.9288        | 14.0  | 1064 | 7.0549          |
  | 4.8169        | 15.0  | 1140 | 7.0971          |
  | 4.7008        | 16.0  | 1216 | 7.1439          |
  | 4.6149        | 17.0  | 1292 | 7.1320          |
  | 4.487         | 18.0  | 1368 | 7.1577          |
  | 4.364         | 19.0  | 1444 | 7.1712          |
  | 4.3208        | 20.0  | 1520 | 7.1959          |
  | 4.2492        | 21.0  | 1596 | 7.2136          |
  | 4.1423        | 22.0  | 1672 | 7.2304          |
  | 4.0873        | 23.0  | 1748 | 7.2526          |
  | 4.0261        | 24.0  | 1824 | 7.2681          |
  | 3.9598        | 25.0  | 1900 | 7.2715          |
  | 3.9562        | 26.0  | 1976 | 7.2648          |
  | 3.8951        | 27.0  | 2052 | 7.2665          |
  | 3.8772        | 28.0  | 2128 | 7.2781          |
  | 3.8403        | 29.0  | 2204 | 7.2801          |
  | 3.8275        | 30.0  | 2280 | 7.2813          |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  