readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-finetuned-requirements
    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-finetuned-requirements
  
  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: 0.0538
  - Precision: 0.9609
  - Recall: 0.9609
  - F1: 0.9609
  - Accuracy: 0.9822
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 33   | 0.1992          | 0.8903    | 0.8880 | 0.8892 | 0.9476   |
  | No log        | 2.0   | 66   | 0.1351          | 0.9039    | 0.9062 | 0.9051 | 0.9554   |
  | No log        | 3.0   | 99   | 0.0949          | 0.9368    | 0.9271 | 0.9319 | 0.9677   |
  | No log        | 4.0   | 132  | 0.0613          | 0.9556    | 0.9531 | 0.9544 | 0.9788   |
  | No log        | 5.0   | 165  | 0.0538          | 0.9609    | 0.9609 | 0.9609 | 0.9822   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  