readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: new-test-model2
    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-model2
  
  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: 0.1040
  - Precision: 0.9722
  - Recall: 0.9757
  - F1: 0.9739
  - Accuracy: 0.9808
  
  ## 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 151  | 0.1819          | 0.9360    | 0.9405 | 0.9382 | 0.9540   |
  | No log        | 2.0   | 302  | 0.1196          | 0.9637    | 0.9639 | 0.9638 | 0.9703   |
  | No log        | 3.0   | 453  | 0.1322          | 0.9614    | 0.9682 | 0.9648 | 0.9711   |
  | 0.2764        | 4.0   | 604  | 0.1071          | 0.9677    | 0.9725 | 0.9701 | 0.9763   |
  | 0.2764        | 5.0   | 755  | 0.1084          | 0.9709    | 0.9766 | 0.9737 | 0.9790   |
  | 0.2764        | 6.0   | 906  | 0.1015          | 0.9717    | 0.9739 | 0.9728 | 0.9791   |
  | 0.0342        | 7.0   | 1057 | 0.1208          | 0.9686    | 0.9727 | 0.9706 | 0.9785   |
  | 0.0342        | 8.0   | 1208 | 0.1068          | 0.9680    | 0.9752 | 0.9716 | 0.9798   |
  | 0.0342        | 9.0   | 1359 | 0.1028          | 0.9719    | 0.9743 | 0.9731 | 0.9807   |
  | 0.0129        | 10.0  | 1510 | 0.1040          | 0.9722    | 0.9757 | 0.9739 | 0.9808   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  