readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: new-test-model
    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. -->
  
  # new-test-model
  
  This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0962
  - Precision: 0.9704
  - Recall: 0.9766
  - F1: 0.9735
  - Accuracy: 0.9791
  
  ## 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   | 151  | 0.1872          | 0.9295    | 0.9405 | 0.9349 | 0.9535   |
  | No log        | 2.0   | 302  | 0.1417          | 0.9574    | 0.9652 | 0.9613 | 0.9679   |
  | No log        | 3.0   | 453  | 0.1028          | 0.9676    | 0.9693 | 0.9684 | 0.9742   |
  | 0.3037        | 4.0   | 604  | 0.1063          | 0.9676    | 0.9696 | 0.9686 | 0.9743   |
  | 0.3037        | 5.0   | 755  | 0.0962          | 0.9704    | 0.9766 | 0.9735 | 0.9791   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  