readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: bert-base-uncased-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-uncased-finetuned-filtered-0609
  
  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: 0.1749
  - Accuracy: 0.9789
  - Precision: 0.9790
  - Recall: 0.9789
  - F1: 0.9789
  
  ## 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.1671        | 1.0   | 3180  | 0.1735          | 0.9632   | 0.9648    | 0.9632 | 0.9635 |
  | 0.1384        | 2.0   | 6360  | 0.1120          | 0.9736   | 0.9738    | 0.9736 | 0.9736 |
  | 0.1064        | 3.0   | 9540  | 0.1880          | 0.9635   | 0.9647    | 0.9635 | 0.9635 |
  | 0.0823        | 4.0   | 12720 | 0.1495          | 0.9758   | 0.9759    | 0.9758 | 0.9757 |
  | 0.0426        | 5.0   | 15900 | 0.1766          | 0.9742   | 0.9746    | 0.9742 | 0.9743 |
  | 0.0254        | 6.0   | 19080 | 0.1724          | 0.9777   | 0.9778    | 0.9777 | 0.9777 |
  | 0.0257        | 7.0   | 22260 | 0.1760          | 0.9764   | 0.9767    | 0.9764 | 0.9764 |
  | 0.0017        | 8.0   | 25440 | 0.1672          | 0.9786   | 0.9787    | 0.9786 | 0.9786 |
  | 0.0077        | 9.0   | 28620 | 0.1894          | 0.9789   | 0.9791    | 0.9789 | 0.9789 |
  | 0.0014        | 10.0  | 31800 | 0.1749          | 0.9789   | 0.9790    | 0.9789 | 0.9789 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.9.1+cu111
  - Datasets 1.16.1
  - Tokenizers 0.12.1
  