readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: fine-tuned-arabert-random-negative
    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. -->
  
  # fine-tuned-arabert-random-negative
  
  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0080
  - Accuracy: 0.9989
  - Precision: 0.9990
  - Recall: 0.9988
  - F1: 0.9989
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.0105        | 1.0   | 62920  | 0.0061          | 0.9986   | 0.9993    | 0.9979 | 0.9986 |
  | 0.0069        | 2.0   | 125840 | 0.0096          | 0.9986   | 0.9993    | 0.9979 | 0.9986 |
  | 0.0058        | 3.0   | 188760 | 0.0084          | 0.9988   | 0.9988    | 0.9988 | 0.9988 |
  | 0.0047        | 4.0   | 251680 | 0.0080          | 0.9989   | 0.9990    | 0.9988 | 0.9989 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  