readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: bert-base-cased-finetuned-filtered-0609
    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-cased-finetuned-filtered-0609
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2410
  - Accuracy: 0.9748
  - Precision: 0.9751
  - Recall: 0.9748
  - F1: 0.9749
  
  ## 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 | Precision | Recall | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.2028        | 1.0   | 3180  | 0.2405          | 0.9535   | 0.9561    | 0.9535 | 0.9538 |
  | 0.1632        | 2.0   | 6360  | 0.1686          | 0.9660   | 0.9664    | 0.9660 | 0.9661 |
  | 0.1203        | 3.0   | 9540  | 0.1625          | 0.9648   | 0.9655    | 0.9648 | 0.9648 |
  | 0.1233        | 4.0   | 12720 | 0.1510          | 0.9698   | 0.9702    | 0.9698 | 0.9699 |
  | 0.0823        | 5.0   | 15900 | 0.1600          | 0.9730   | 0.9732    | 0.9730 | 0.9730 |
  | 0.0453        | 6.0   | 19080 | 0.1953          | 0.9723   | 0.9724    | 0.9723 | 0.9723 |
  | 0.031         | 7.0   | 22260 | 0.1754          | 0.9755   | 0.9755    | 0.9755 | 0.9755 |
  | 0.0166        | 8.0   | 25440 | 0.2155          | 0.9739   | 0.9740    | 0.9739 | 0.9739 |
  | 0.0036        | 9.0   | 28620 | 0.2519          | 0.9730   | 0.9733    | 0.9730 | 0.9730 |
  | 0.0035        | 10.0  | 31800 | 0.2410          | 0.9748   | 0.9751    | 0.9748 | 0.9749 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.9.1+cu111
  - Datasets 1.16.1
  - Tokenizers 0.12.1
  