readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - emotone_ar
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-base-arabic-finetuned-emotion
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: emotone_ar
        type: emotone_ar
        config: default
        split: train[:90%]
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.7415506958250497
      - name: F1
        type: f1
        value: 0.7406006078114171
  ---
  
  <!-- 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-arabic-finetuned-emotion
  
  This model is a fine-tuned version of [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on the emotone_ar dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8965
  - Accuracy: 0.7416
  - F1: 0.7406
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.3476        | 1.0   | 142  | 0.8911          | 0.7008   | 0.6812 |
  | 0.8204        | 2.0   | 284  | 0.8175          | 0.7276   | 0.7212 |
  | 0.6227        | 3.0   | 426  | 0.8392          | 0.7376   | 0.7302 |
  | 0.4816        | 4.0   | 568  | 0.8531          | 0.7435   | 0.7404 |
  | 0.378         | 5.0   | 710  | 0.8817          | 0.7396   | 0.7388 |
  | 0.3134        | 6.0   | 852  | 0.8965          | 0.7416   | 0.7406 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  