readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-base-uncased-finetuned-filtered-0602
    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. -->
  
  # bert-base-uncased-finetuned-filtered-0602
  
  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: 0.1959
  - Accuracy: 0.9783
  - F1: 0.9783
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 0.1777        | 1.0   | 3180  | 0.2118          | 0.9563   | 0.9566 |
  | 0.1409        | 2.0   | 6360  | 0.1417          | 0.9736   | 0.9736 |
  | 0.1035        | 3.0   | 9540  | 0.1454          | 0.9739   | 0.9739 |
  | 0.0921        | 4.0   | 12720 | 0.1399          | 0.9755   | 0.9755 |
  | 0.0607        | 5.0   | 15900 | 0.1150          | 0.9792   | 0.9792 |
  | 0.0331        | 6.0   | 19080 | 0.1770          | 0.9758   | 0.9758 |
  | 0.0289        | 7.0   | 22260 | 0.1782          | 0.9767   | 0.9767 |
  | 0.0058        | 8.0   | 25440 | 0.1877          | 0.9796   | 0.9796 |
  | 0.008         | 9.0   | 28620 | 0.2034          | 0.9764   | 0.9764 |
  | 0.0017        | 10.0  | 31800 | 0.1959          | 0.9783   | 0.9783 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.9.0
  - Datasets 1.16.1
  - Tokenizers 0.12.1
  